Terje Koren Berntsen

• Shetty, Shobitha; Hassani, Amirhossein; Hamer, Paul David; Stebel, Kerstin; Salamalikis, Vasileios & Berntsen, Terje Koren [Show all 8 contributors for this article] (2026). Evaluating the role of low-cost sensors in machine learning based European PM2.5 monitoring. Environmental Research. ISSN 0013-9351. 291. doi: 10.1016/j.envres.2025.123558. Full text in Research Archive Show summary

  We evaluate the added value of integrating validated Low-Cost Sensor (LCS) data into a Machine Learning (ML) framework for providing surface PM2.5 estimates over Central Europe at 1 km spatial resolution. The synergistic ML-based S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) approach is extended, to incorporate LCS data through two strategies: using validated LCS data as a target variable (LCST) and as an input feature via an inverse distance weighted spatial convolution layer (LCSI). Both strategies are implemented within a stacked XGBoost model that ingests satellite-derived aerosol optical depth, meteorological variables, and CAMS (Copernicus Atmospheric Monitoring Service) regional forecasts. Model performance for 2021–2022 is evaluated against a baseline trained on air quality monitoring stations without any form of LCS integration. Our results indicate that the LCSI approach consistently outperforms both the baseline and LCST models, particularly in urban areas, with RMSE reductions of up to 15–20 %. It also exhibits higher accuracy than the CAMS regional interim reanalysis with a lower annual mean absolute error (MAE) of 2.68 μg/m3 compared to 3.32 μg/m3. SHapley Additive exPlanations based analysis indicates that LCSI information improves both spatial and temporal representativeness, with the LCSI strategy better capturing localized pollution dynamics. However, the LCSI's dependency on the spatial LCS layer limits its ability to capture inter-urban pollution transport in regions with sparse or no LCS data. These findings highlight the value of large-scale sensor networks in addressing spatial coverage gaps in official air quality monitoring stations and advancing high-resolution air quality modeling.

• Mužić, Iris; Hodnebrog, Øivind; Yilmaz, Yeliz A.; Berntsen, Terje Koren; Sillmann, Jana & Lawrence, David M. [Show all 7 contributors for this article] (2025). Soil moisture-Temperature coupling during extreme warm conditions in 2018 in Sweden: a case study with WRF-CTSM. Advances in Statistical Climatology, Meteorology and Oceanography (ASCMO). ISSN 2364-3579. 11(2), p. 273–292. doi: 10.5194/ascmo-11-273-2025. Full text in Research Archive Show summary

  Abstract. Soil moisture–temperature coupling (SM–T) significantly influences the frequency and amplitude of heat extremes. It describes how variations in soil moisture affect surface air temperature conditions and vice versa. This study aims to determine the spatial extent and duration of SM–T in southern and central Sweden, an area increasingly recognized as a coupling hot spot, during the extreme warm conditions between May and August 2018 (MJJA 2018). The assessment of coupling is based on a multi-correlation overlay analysis of key coupling variables: surface soil moisture, evaporative fraction, and daily maximum 2 m temperature from four different simulations of the coupled regional climate model WRF-CTSM, along with a merged gridded GLEAM-E-OBS observational–reanalysis dataset. These datasets demonstrate robust precision in representing the magnitude and variability of the key coupling variables during the MJJA 2018 compared to in situ observations, though the precise timing and duration of the coupling are challenging to reproduce at the local scale. WRF-CTSM provides a more realistic depiction of the key coupling variables and their interactions when recent CTSM advancements are incorporated. On average, across the study region and all five datasets, SM–T persisted for 22 d throughout the MJJA period. The atmospheric leg alone (involving daily evaporative fraction and maximum 2 m temperature), averaged across datasets, contributed 92 % to the regional coupling duration.

• Mužić, Iris; Hodnebrog, Øivind; Yilmaz, Yeliz A.; Berntsen, Terje Koren; Lawrence, David M. & Sobhani, Negin (2025). The Evaluation of Hydroclimatic Variables Over Nordic Fennoscandia Using WRF-CTSM. Journal of Geophysical Research (JGR): Atmospheres. ISSN 2169-897X. 130(9). doi: 10.1029/2024JD043103. Full text in Research Archive Show summary

  This study is the first to evaluate the state-of-the-art coupled land-atmosphere regional climate model WRF-CTSM. It comprises the Weather Research and Forecasting model, WRF, and the Community Terrestrial Systems Model, CTSM (using a configuration that is the same as the Community Land Model Version 5, CLM5). The evaluation is conducted over Nordic Fennoscandia (Norway, Sweden, and Finland) since there is uncertainty in climate models' representation of key hydroclimatic variables in high-latitude regions as they experience accelerated transformation in a changing climate. A 13-year WRF-CTSM simulation (2010–2022) is performed using a 10.5 km horizontal grid spacing to assess the model biases in simulating mean, minimum, and maximum 2 m temperature, precipitation, snow cover (snow depth, snow water equivalent, fractional snow-covered duration), and surface energy balance components. The analysis is based on annual, seasonal, monthly, and daily mean comparisons against openly available observational data sets, comprising regional scale gridded station-based and satellite-based data sets, as well as point scale observations from ground stations. The model shows robust agreement with the evaluation data sets across all considered variables. Furthermore, in situ scale conditions in 2 m temperature, precipitation, snow cover variables, and latent heat are captured with considerable precision. WRF-CTSM is thus considered a powerful research tool for the assessment of land-atmosphere interactions over Nordic Fennoscandia.

• Aas, Elin Cecilie Ristorp; Althuizen, Inge; Tang, Hui; Geange, Sonya Rita; Lieungh, Eva & Vandvik, Vigdis [Show all 7 contributors for this article] (2024). Implications of climate and litter quality for simulations of litterbag decomposition at high latitudes. Biogeosciences. ISSN 1726-4170. 21(16), p. 3789–3817. doi: 10.5194/bg-21-3789-2024. Full text in Research Archive Show summary

  Litter decomposition is a vital part of the carbon cycle and is thoroughly studied both in the field and with models. Although temporally and spatially limited, litterbag decomposition experiments are often used to calibrate and evaluate soil models, coupled to land models, that are intended for use on large scales. We used the microbially explicit soil decomposition model MIMICS+ to replicate two high-latitude litterbag decomposition experiments of different spatial and temporal scales. We investigated how well the model represented observed mass loss in terms of the controlling factors of climate and litter quality and their relative importance with time. In addition to default model forcing, we used measured and site-specific model-derived microclimatic variables (soil moisture and temperature), hypothesizing that this would improve model results. We found that MIMICS+ represented mass loss after 1, 3, and 6 years well across a climatic gradient of Canadian sites but had more variable results for 1-year mass loss across a climate grid in southern Norway. In terms of litter quality, the litter metabolic fraction had more influence on modeled mass loss than the carbon-to-nitrogen ratio of the litter. Using alternative microclimate sources led to up to 23 % more mass remaining and down to 22 % less mass remaining compared to the simulations using default model inputs. None of the input alternatives significantly improved results compared to using the default model setup. We discuss possible causes for our findings and suggest measures to better utilize short-term field experiments to inform microbially explicit decomposition models.

• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Hamer, Paul David; Kylling, Arve & Berntsen, Terje Koren (2024). Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning. Remote Sensing of Environment. ISSN 0034-4257. 312. doi: 10.1016/j.rse.2024.114321. Full text in Research Archive Show summary

  Satellite observations from instruments such as the TROPOspheric Monitoring Instrument (TROPOMI) show significant potential for monitoring the spatiotemporal variability of NO2, however they typically provide vertically integrated measurements over the tropospheric column. In this study, we introduce a machine learning approach entitled ‘S-MESH’ (Satellite and ML-based Estimation of Surface air quality at High resolution) that allows for estimating daily surface NO2 concentrations over Europe at 1 km spatial resolution based on eXtreme gradient boost (XGBoost) model using primarily observation-based datasets over the period 2019–2021. Spatiotemporal datasets used by the model include TROPOMI NO2 tropospheric vertical column density, night light radiance from the Visible Infrared Imaging Radiometer Suite (VIIRS), Normalized Difference Vegetation Index from the Moderate Resolution Imaging Spectroradiometer (MODIS), observations of air quality monitoring stations from the European Environment Agency database and

• Shetty, Shobitha; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve; Hassani, Amirhossein & Berntsen, Terje Koren [Show all 7 contributors for this article] (2024). Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast. Environmental Research. ISSN 0013-9351. 264. doi: 10.1016/j.envres.2024.120363. Full text in Research Archive Show summary

  Fine particulate matter (PM2.5) is a key air quality indicator due to its adverse health impacts. Accurate PM2.5 assessment requires high-resolution (e.g., atleast 1 km) daily data, yet current methods face challenges in balancing accuracy, coverage, and resolution. Chemical transport models such as those from the Copernicus Atmosphere Monitoring Service (CAMS) offer continuous data but their relatively coarse resolution can introduce uncertainties. Here we present a synergistic Machine Learning (ML)-based approach called S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) for estimating daily surface PM2.5 over Europe at 1 km spatial resolution and demonstrate its performance for the years 2021 and 2022. The approach enhances and downscales the CAMS regional ensemble 24 h PM2.5 forecast by training a stacked XGBoost model against station observations, effectively integrating satellite-derived data and modeled meteorological variables. Overall, against station observations, S-MESH (mean absolute error (MAE) of 3.54 μg/m3) shows higher accuracy than the CAMS forecast (MAE of 4.18 μg/m3) and is approaching the accuracy of the CAMS regional interim reanalysis (MAE of 3.21 μg/m3), while exhibiting a significantly reduced mean bias (MB of −0.3 μg/m3 vs. −1.5 μg/m3 for the reanalysis). At the same time, S-MESH requires substantially less computational resources and processing time. At concentrations >20 μg/m3, S-MESH outperforms the reanalysis (MB of −7.3 μg/m3 and -10.3 μg/m3 respectively), and reliably captures high pollution events in both space and time. In the eastern study area, where the reanalysis often underestimates, S-MESH better captures high levels of PM2.5 mostly from residential heating. S-MESH effectively tracks day-to-day variability, with a temporal relative absolute error of 5% (reanalysis 10%). Exhibiting good performance at high pollution events coupled with its high spatial resolution and rapid estimation speed, S-MESH can be highly relevant for air quality assessments where both resolution and timeliness are critical.

• Skeie, Ragnhild Bieltvedt; Aldrin, Magne Tommy; Berntsen, Terje Koren; Holden, Marit; Huseby, Ragnar Bang & Myhre, Gunnar [Show all 7 contributors for this article] (2024). The aerosol pathway is crucial for observationally constraining climate sensitivity and anthropogenic forcing. Earth System Dynamics (ESD). ISSN 2190-4979. 15(6), p. 1435–1458. doi: 10.5194/esd-15-1435-2024. Full text in Research Archive Show summary

  Climate sensitivity and aerosol forcing are two of the most central, but uncertain, quantities in climate science that are crucial for assessing historical climate as well as future climate projections. Here, we use a Bayesian approach to estimate inferred climate sensitivity and aerosol forcing using observations of temperature and global ocean heat content as well as prior knowledge of effective radiative forcing (ERF) over the industrial period. Due to limited information on uncertainties related to the time evolution of aerosol forcing, we perform a range of sensitivity analyses with idealized aerosol time evolution. The estimates are sensitive to the aerosol forcing pathway, with the mean estimate of inferred effective climate sensitivity ranging from 2.0 to 2.4 K, present-day (2019 relative to 1750) aerosol ERF ranging from −0.7 to −1.1 W m−2, and anthropogenic ERF ranging from 2.6 to 3.1 W m−2. Using observations and forcing up to and including 2022, the inferred effective climate sensitivity is 2.2 K with a 1.6 to 3.0 K 90 % uncertainty range. Analysis with more freely evolving aerosol forcing between 1950 and 2014 shows that a strong negative aerosol forcing trend in the latter part of the 20th century is not consistent with observations. Although we test our estimation method with strongly idealized aerosol ERF pathways, our posteriori estimates of the climate sensitivity consistently end up in the weaker end of the range assessed in the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). As our method only includes climate feedbacks that have occurred over the historical period, it does not include the pattern effect, i.e., where climate feedbacks are dependent on the pattern of warming which will likely change into the future. Adding the best estimate of the pattern effect from IPCC AR6, our climate sensitivity estimate is almost identical to the IPCC AR6 best estimate and very likely range.

• Aas, Elin Cecilie Ristorp; Wit, Heleen de & Berntsen, Terje Koren (2024). Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0). Geoscientific Model Development. ISSN 1991-959X. 17(7), p. 2929–2959. doi: 10.5194/gmd-17-2929-2024. Full text in Research Archive Show summary

  Understanding carbon exchange processes between land reservoirs and the atmosphere is essential for predicting carbon–climate feedbacks. Still, considerable uncertainty remains in the representation of the terrestrial carbon cycle in Earth system models. An emerging strategy to constrain these uncertainties is to include the role of different microbial groups explicitly. Following this approach, we extend the framework of the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with additional mycorrhizal groups and a nitrogen cycle that includes a novel representation of inorganic nitrogen sorption to particles via a Langmuir isotherm. MIMICS+ v1.0 is designed to capture and quantify relationships between soil microorganisms and their environment, with a particular emphasis on boreal ecosystems. We evaluated MIMICS+ against podzolic soil profiles in Norwegian forests as well as the conventional Community Land Model (CLM). MIMICS+ matched observed carbon stocks better than CLM and gave a broader range of C:N

• Mack, Laura; Berntsen, Terje Koren; Vercauteren, Nikki & Pirk, Norbert (2024). Transfer Efficiency and Organization in Turbulent Transport over Alpine Tundra. Boundary-Layer Meteorology. ISSN 0006-8314. 190. doi: 10.1007/s10546-024-00879-5. Full text in Research Archive Show summary

  The exchange of momentum, heat and trace gases between atmosphere and surface is mainly controlled by turbulent fluxes. Turbulent mixing is usually parametrized using Monin–Obukhov similarity theory (MOST), which was derived for steady turbulence over homogeneous and flat surfaces, but is nevertheless routinely applied to unsteady turbulence over non-homogeneous surfaces. We study four years of eddy-covariance measurements at a highly heterogeneous alpine valley site in Finse, Norway, to gain insights into the validity of MOST, the turbulent transport mechanisms and the contributing coherent structures. The site exhibits a bimodal topography-following flux footprint, with the two dominant wind sectors characterized by organized and strongly negative momentum flux, but different anisotropy and contributions of submeso-scale motions, leading to a failure of eddy-diffusivity closures and different transfer efficiencies for different scalars. The quadrant analysis of the momentum flux reveals that under stable conditions sweeps transport more momentum than the more frequently occurring ejections, while the opposite is observed under unstable stratification. From quadrant analysis, we derive the ratio of the amount of disorganized to organized structures, that we refer to as organization ratio (OR). We find an invertible relation between transfer efficiency and corresponding organization ratio with an algebraic sigmoid function. The organization ratio further explains the scatter around scaling functions used in MOST and thus indicates that coherent structures modify MOST. Our results highlight the critical role of coherent structures in turbulent transport in heterogeneous tundra environments and may help to find new parametrizations for numerical weather prediction or climate models.

• Tang, Hui; Haugvaldstad, Ove Westermoen; Stordal, Frode; Bi, Jianrong; Zwaaftink, Christine Groot & Grythe, Henrik [Show all 11 contributors for this article] (2023). Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations. Frontiers in Environmental Science. 10. doi: 10.3389/fenvs.2022.1013875. Full text in Research Archive Show summary

  The 2021 East Asia sandstorm began from the Eastern Gobi desert steppe in Mongolia on March 14, and later spread to northern China and the Korean Peninsula. It was the biggest sandstorm to hit China in a decade, causing severe air pollution and a significant threat to human health. Capturing and predicting such extreme events is critical for society. The Lagrangian particle dispersion model FLEXPART and the associated dust emission model FLEXDUST have been recently developed and applied to simulate global dust cycles. However, how well the model captures Asian dust storm events remains to be explored. In this study, we applied FLEXPART to simulate the recent 2021 East Asia sandstorm, and evaluated its performance comparing with observation and observation-constrained reanalysis datasets, such as the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and CAMS global atmospheric composition forecasts (CAMS-F). We found that the default setting of FLEXDUST substantially underestimates the strength of dust emission and FLEXPART modelled dust concentration in this storm compared to that in MERRA-2 and CAMS-F. An improvement of the parametrization of bare soil fraction, topographical scaling, threshold friction velocity and vertical dust flux scheme based on Kok et al. (Atmospheric Chemistry and Physics, 2014, 14, 13023–13041) in FLEXDUST can reproduce the strength and spatio-temporal pattern of the dust storm comparable to MERRA-2 and CAMS-F. However, it still underestimates the observed spike of dust concentration during the dust storm event over northern China, and requires further improvement in the future. The improved FLEXDUST and FLEXPART perform better than MERRA-2 and CAMS-F in capturing the observed particle size distribution of dust aerosols, highlighting the importance of using more dust size bins and size-dependent parameterization for dust emission, and dry and wet deposition schemes for modelling the Asian dust cycle and its climatic feedbacks.

• Pirk, Norbert; Aalstad, Kristoffer; Yilmaz, Yeliz A.; Vatne, Astrid; Popp, Andrea & Horvath, Peter [Show all 12 contributors for this article] (2023). Snow-vegetation-atmosphere interactions in alpine tundra. Biogeosciences. ISSN 1726-4170. 20(11), p. 2031–2047. doi: 10.5194/bg-20-2031-2023. Full text in Research Archive Show summary

  The interannual variability of snow cover in alpine areas is increasing, which may affect the tightly coupled cycles of carbon and water through snow–vegetation–atmosphere interactions across a range of spatio-temporal scales. To explore the role of snow cover for the land–atmosphere exchange of CO2 and water vapor in alpine tundra ecosystems, we combined 3 years (2019–2021) of continuous eddy covariance flux measurements of the net ecosystem exchange of CO2 (NEE) and evapotranspiration (ET) from the Finse site in alpine Norway (1210 m a.s.l.) with a ground-based ecosystem-type classification and satellite imagery from Sentinel-2, Landsat 8, and MODIS. While the snow conditions in 2019 and 2021 can be described as site typical, 2020 features an extreme snow accumulation associated with a strong negative phase of the Scandinavian pattern of the synoptic atmospheric circulation during spring. This extreme snow accumulation caused a 1-month delay in melt-out date, which falls in the 92nd percentile in the distribution of yearly melt-out dates in the period 2001–2021. The melt-out dates follow a consistent fine-scale spatial relationship with ecosystem types across years. Mountain and lichen heathlands melt out more heterogeneously than fens and flood plains, while late snowbeds melt out up to 1 month later than the other ecosystem types. While the summertime average normalized difference vegetation index (NDVI) was reduced considerably during the extreme-snow year 2020, it reached the same maximum as in the other years for all but one of the ecosystem types (late snowbeds), indicating that the delayed onset of vegetation growth is compensated to the same maximum productivity. Eddy covariance estimates of NEE and ET are gap-filled separately for two wind sectors using a random forest regression model to account for complex and nonlinear ecohydrological interactions. While the two wind sectors differ markedly in vegetation composition and flux magnitudes, their flux response is controlled by the same drivers as estimated by the predictor importance of the random forest model, as well as by the high correlation of flux magnitudes (correlation coefficient r=0.92 for NEE and r=0.89 for ET) between both areas. The 1-month delay of the start of the snow-free season in 2020 reduced the total annual ET by 50 % compared to 2019 and 2021 and reduced the growing-season carbon assimilation to turn the ecosystem from a moderate annual carbon sink (−31 to −6 gC m−2 yr−1) to a source (34 to 20 gC m−2 yr−1). These results underpin the strong dependence of ecosystem structure and functioning on snow dynamics, whose anomalies can result in important ecological extreme events for alpine ecosystems.

• Falk, Stefanie; Vollsnes, Ane V.; Eriksen, Aud Else Berglen; Stordal, Frode & Berntsen, Terje Koren (2021). Technical note: Quality assessment of ozone reanalysis products and gap-filling over subarctic Europe for vegetation risk mapping. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 21(20), p. 15647–15661. doi: 10.5194/acp-21-15647-2021. Full text in Research Archive
• Szopa, Sophie; Naik, Vaishali; Adhikary, Bhupesh; Artaxo, Paulo; Berntsen, Terje Koren & Collins, William D [Show all 15 contributors for this article] (2021). Short-lived Climate Forcers. In Masson-Delmotte, Valérie; Zhai, Panmao; Pirani, Anna; Connors, Sarah L.; Péan, Clotilde; Chen, Yang; Goldfarb, Leah; Gomis, Melissa I.; Matthews, J. B. Robin; Berger, Sophie; Huang, Mengtian; Yelekçi, Ozge; Yu, Rong & Zhou, Baiquan (Ed.), Climate Change 2021. The Physical Science Basis. Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.. Cambridge University Press. p. 817–922. Full text in Research Archive
• Horvath, Peter; Tang, Hui; Halvorsen, Rune; Stordal, Frode; Tallaksen, Lena M. & Berntsen, Terje Koren [Show all 7 contributors for this article] (2021). Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models. Biogeosciences. ISSN 1726-4170. 18(1), p. 95–112. doi: 10.5194/bg-18-95-2021. Full text in Research Archive Show summary

  Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

• Blichner, Sara Marie; Sporre, Moa Kristina & Berntsen, Terje Koren (2021). Reduced effective radiative forcing from cloud–aerosol interactions (ERFaci) with improved treatment of early aerosol growth in an Earth system model. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 21(23), p. 17243–17265. doi: 10.5194/acp-21-17243-2021. Full text in Research Archive Show summary

  Historically, aerosols of anthropogenic origin have offset some of the warming from increased atmospheric greenhouse gas concentrations. The strength of this negative aerosol forcing, however, is highly uncertain – especially the part originating from cloud–aerosol interactions. An important part of this uncertainty originates from our lack of knowledge about pre-industrial aerosols and how many of these would have acted as cloud condensation nuclei (CCN). In order to simulate CCN concentrations in models, we must adequately model secondary aerosols, including new particle formation (NPF) and early growth, which contributes a large part of atmospheric CCN. In this study, we investigate the effective radiative forcing (ERF) from cloud–aerosol interactions (ERFaci) with an improved treatment of early particle growth, as presented in Blichner et al. (2021). We compare the improved scheme to the default scheme, OsloAero, which are both embedded in the atmospheric component of the Norwegian Earth System Model v2 (NorESM2). The improved scheme, OsloAeroSec, includes a sectional scheme that treats the growth of particles from 5–39.6 nm in diameter, which thereafter inputs the particles to the smallest mode in the pre-existing modal aerosol scheme. The default scheme parameterizes the growth of particles from nucleation up to the smallest mode, a process that can take several hours. The explicit treatment of early growth in OsloAeroSec, on the other hand, captures the changes in atmospheric conditions during this growth time in terms of air mass mixing, transport, and condensation and coagulation. We find that the ERFaci with the sectional scheme is −1.16 W m−2, which is 0.13 W m−2 weaker compared to the default scheme. This reduction originates from OsloAeroSec producing more particles than the default scheme in pristine, low-aerosol-concentration areas and fewer NPF particles in high-aerosol areas. We find, perhaps surprisingly, that NPF inhibits cloud droplet activation in polluted and/or high-aerosol-concentration regions because the NPF particles increase the condensation sink and reduce the growth of the larger particles which may otherwise activate. This means that in these high-aerosol regions, the model with the lowest NPF – OsloAeroSec – will have the highest cloud droplet activation and thus more reflective clouds. In pristine and/or low-aerosol regions, however, NPF enhances cloud droplet activation because the NPF particles themselves tend to activate. Lastly, we find that sulfate emissions in the present-day simulations increase the hygroscopicity of secondary aerosols compared to pre-industrial simulations. This makes NPF particles more relevant for cloud droplet activation in the present day than the pre-industrial atmosphere because increased hygroscopicity means they can activate at smaller sizes.

• Blichner, Sara Marie; Sporre, Moa Kristina; Makkonen, Risto & Berntsen, Terje Koren (2021). Implementing a sectional scheme for early aerosol growth from new particle formation in the Norwegian Earth System Model v2: comparison to observations and climate impacts. Geoscientific Model Development. ISSN 1991-959X. 14(6), p. 3335–3359. doi: 10.5194/gmd-14-3335-2021. Full text in Research Archive Show summary

  Aerosol–cloud interactions contribute to a large portion of the spread in estimates of climate forcing, climate sensitivity and future projections. An important part of this uncertainty is how much new particle formation (NPF) contributes to cloud condensation nuclei (CCN) and, furthermore, how this changes with changes in anthropogenic emissions. Incorporating NPF and early growth in Earth system models (ESMs) is, however, challenging due to uncertain parameters (e.g. participating vapours), structural issues (numerical description of growth from ∼1 to ∼100 nm) and the large scale of an ESM grid compared to the NPF scale. A common approach in ESMs is to represent the particle size distribution by a certain number of log-normal modes. Sectional schemes, on the other hand, in which the size distribution is represented by bins, are considered closer to first principles because they do not make an a priori assumption about the size distribution. In order to improve the representation of early growth, we have implemented a sectional scheme for the smallest particles (5–39.6 nm diameter) in the Norwegian Earth System Model (NorESM), feeding particles into the original aerosol scheme. This is, to our knowledge, the first time such an approach has been tried. We find that including the sectional scheme for early growth improves the aerosol number concentration in the model when comparing against observations, particularly in the 50–100 nm diameter range. Furthermore, we find that the model with the sectional scheme produces much fewer particles than the original scheme in polluted regions, while it produces more in remote regions and the free troposphere, indicating a potential impact on the estimated aerosol forcing. Finally, we analyse the effect on cloud–aerosol interactions and find that the effect of changes in NPF efficiency on clouds is highly heterogeneous in space. While in remote regions, more efficient NPF leads to higher cloud droplet number concentration (CDNC), in polluted regions the opposite is in fact the case.

• Karset, Inger Helene H.; Gettelman, Andrew; Storelvmo, Trude; Alterskjær, Kari & Berntsen, Terje Koren (2020). Exploring Impacts of Size-Dependent Evaporation and Entrainment in a Global Model. Journal of Geophysical Research (JGR): Space Physics. ISSN 2169-9380. 125(4). doi: 10.1029/2019JD031817. Full text in Research Archive Show summary

  Aerosol radiative forcing can influence climate both locally and far outside the emission region. Here we investigate black carbon (BC) aerosols emitted in four major emission areas and evaluate the importance of emission location and magnitude as well as the concept of the absolute regional temperature-change potentials (ARTP). We perform simulations with a climate model (NorESM) with a fully coupled ocean and with fixed sea surface temperatures. BC emissions for year 2000 are increased by factors of 10 and 20 in South Asia, North America, and Europe, respectively, and by 5 and 10 in East Asia (due to higher emissions there). The perturbed simulations and a reference simulation are run for 100 years with three ensemble members each. We find strikingly similar regional surface temperature responses and geographical patterns per unit BC emission in Europe and North America but somewhat lower temperature sensitivities for East Asian emissions. BC emitted in South Asia shows a different geographical pattern in surface temperatures, by changing the Indian monsoon and cooling the surface. We find that the ARTP approach rather accurately reproduces the fully coupled temperature response of NorESM. Choosing the highest emission rate results in lower surface temperature change per emission unit compared to the lowest rate, but the difference is generally not statistically significant except for the Arctic. An advantage of high-perturbation simulations is the clearer emergence of regional signals. Our results show that the linearity of normalized temperature effects of BC is fairly well preserved despite the relatively large perturbations but that regional temperature coefficients calculated from high perturbations may be a conservative estimate. Regardless of emission region, BC causes a northward shift of the ITCZ, and this shift is apparent both with a fully coupled ocean and with fixed sea surface temperatures. For these regional BC emission perturbations, we find that the effective radiative forcing is not a good measure of the climate response. A limitation of this study is the uncertainties in BC–cloud interactions and the amount of BC absorption, both of which are model dependent.

• Sand, Maria; Berntsen, Terje Koren; Ekman, Annica M.L.; Lewinschal, Anna & Hansson, Hans-Christen (2020). Surface temperature response to regional black carbon emissions: do location and magnitude matter? Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 20(5), p. 3079–3089. doi: 10.5194/acp-20-3079-2020. Full text in Research Archive Show summary

  Aerosol radiative forcing can influence climate both locally and far outside the emission region. Here we investigate black carbon (BC) aerosols emitted in four major emission areas and evaluate the importance of emission location and magnitude as well as the concept of the absolute regional temperature-change potentials (ARTP). We perform simulations with a climate model (NorESM) with a fully coupled ocean and with fixed sea surface temperatures. BC emissions for year 2000 are increased by factors of 10 and 20 in South Asia, North America, and Europe, respectively, and by 5 and 10 in East Asia (due to higher emissions there). The perturbed simulations and a reference simulation are run for 100 years with three ensemble members each. We find strikingly similar regional surface temperature responses and geographical patterns per unit BC emission in Europe and North America but somewhat lower temperature sensitivities for East Asian emissions. BC emitted in South Asia shows a different geographical pattern in surface temperatures, by changing the Indian monsoon and cooling the surface. We find that the ARTP approach rather accurately reproduces the fully coupled temperature response of NorESM. Choosing the highest emission rate results in lower surface temperature change per emission unit compared to the lowest rate, but the difference is generally not statistically significant except for the Arctic. An advantage of high-perturbation simulations is the clearer emergence of regional signals. Our results show that the linearity of normalized temperature effects of BC is fairly well preserved despite the relatively large perturbations but that regional temperature coefficients calculated from high perturbations may be a conservative estimate. Regardless of emission region, BC causes a northward shift of the ITCZ, and this shift is apparent both with a fully coupled ocean and with fixed sea surface temperatures. For these regional BC emission perturbations, we find that the effective radiative forcing is not a good measure of the climate response. A limitation of this study is the uncertainties in BC–cloud interactions and the amount of BC absorption, both of which are model dependent.

• Sporre, Moa Kristina; Blichner, Sara Marie; Schrödner, Roland; Karset, Inger Helene H.; Berntsen, Terje Koren & Noije, Twan Van [Show all 9 contributors for this article] (2020). Large difference in aerosol radiative effects from BVOC-SOA treatment in three Earth system models. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 20(14), p. 8953–8973. doi: 10.5194/acp-20-8953-2020. Full text in Research Archive Show summary

  Biogenic volatile organic compounds (BVOCs) emitted from vegetation are oxidised in the atmosphere and can form aerosol particles either by contributing to new particle formation or by condensing onto existing aerosol particles. As the understanding of the importance of BVOCs for aerosol formation has increased over the years, these processes have made their way into Earth system models (ESMs). In this study, sensitivity experiments are run with three different ESMs (the Norwegian Earth System Model (NorESM), EC-Earth and ECHAM) to investigate how the direct and indirect aerosol radiative effects are affected by changes in the formation of secondary organic aerosol (SOA) from BVOCs. In the first two sensitivity model experiments, the yields of SOA precursors from oxidation of BVOCs are changed by ±50 %. For the third sensitivity test, the formed oxidation products do not participate in the formation of new particles but are only allowed to condense onto existing aerosols. In the last two sensitivity experiments, the emissions of BVOC compounds (isoprene and monoterpenes) are turned off, one at a time. The goal of the study is to investigate whether it is of importance to treat SOA formation processes correctly in the models rather than to evaluate the correctness of the current treatment in the models. The results show that the impact on the direct radiative effect (DRE) is linked to the changes in the SOA production in the models, where more SOA leads to a stronger DRE and vice versa. However, the magnitude by which the DRE changes (maximally 0.15 W m−2 globally averaged) in response to the SOA changes varies between the models, with EC-Earth displaying the largest changes. The results for the cloud radiative effects (CREs) are more complicated than for the DRE. The changes in CRE differ more among the ESMs, and for some sensitivity experiments they even have different signs. The most sensitive models are NorESM and EC-Earth, which have CRE changes of up to 0.82 W m−2. The varying responses in the different models are connected to where in the aerosol size distributions the changes in mass and number due to SOA formation occur, in combination with the aerosol number concentration levels in the models. We also find that interactive gas-phase chemistry as well as the new particle formation parameterisation has important implications for the DRE and CRE in some of the sensitivity experiments. The results from this study indicate that BVOC-SOA treatment in ESMs can have a substantial impact on the modelled climate but that the sensitivity varies greatly between the models. Since BVOC emissions have changed historically and will continue to change in the future, the spread in model results found in this study implies uncertainty into ESM estimates of aerosol forcing from land-use change and BVOC feedback strengths.

• Lund, Marianne Tronstad; Aamaas, Borgar; Stjern, Camilla Weum; Klimont, Zbigniew; Berntsen, Terje Koren & Samset, Bjørn Hallvard (2020). A continued role of short-lived climate forcers under the Shared Socioeconomic Pathways. Earth System Dynamics (ESD). ISSN 2190-4979. 11(4), p. 977–993. doi: 10.5194/esd-11-977-2020. Full text in Research Archive Show summary

  Mitigation of non-CO2 emissions plays a key role in meeting the Paris Agreement ambitions and sustainable development goals. Implementation of respective policies addressing these targets mainly occur at sectoral and regional levels, and designing efficient mitigation strategies therefore relies on detailed knowledge about the mix of emissions from individual sources and their subsequent climate impact. Here we present a comprehensive dataset of near- and long-term global temperature responses to emissions of CO2 and individual short-lived climate forcers (SLCFs) from 7 sectors and 13 regions – for both present-day emissions and their continued evolution as projected under the Shared Socioeconomic Pathways (SSPs). We demonstrate the key role of CO2 in driving both near- and long-term warming and highlight the importance of mitigating methane emissions from agriculture, waste management, and energy production as the primary strategy to further limit near-term warming. Due to high current emissions of cooling SLCFs, policies targeting end-of-pipe energy sector emissions may result in net added warming unless accompanied by simultaneous methane and/or CO2 reductions. We find that SLCFs are projected to play a continued role in many regions, particularly those including low- to medium-income countries, under most of the SSPs considered here. East Asia, North America, and Europe will remain the largest contributors to total net warming until 2100, regardless of scenario, while South Asia and Africa south of the Sahara overtake Europe by the end of the century in SSP3-7.0 and SSP5-8.5. Our dataset is made available in an accessible format, aimed also at decision makers, to support further assessment of the implications of policy implementation at the sectoral and regional scales.

• Aamaas, Borgar; Berntsen, Terje Koren & Samset, Bjørn Hallvard (2019). The regional temperature implications of strong air quality measures. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 19(24), p. 15235–15245. doi: 10.5194/acp-19-15235-2019. Full text in Research Archive Show summary

  Abstract. Anthropogenic emissions of short-lived climate forcers (SLCFs) affect both air quality and climate. How much regional temperatures are affected by ambitious SLCF emission mitigation policies is, however, still uncertain. We investigate the potential temperature implications of stringent air quality policies by applying matrices of regional temperature responses to new pathways for future anthropogenic emissions of aerosols, methane (CH4), and other short-lived gases. These measures have only a minor impact on CO2 emissions. Two main options are explored, one with climate optimal reductions (i.e., constructed to yield a maximum global cooling) and one with the maximum technically feasible reductions. The temperature response is calculated for four latitude response bands (90–28∘ S, 28∘ S–28∘ N, 28–60∘ N, and 60–90∘ N) by using existing absolute regional temperature change potential (ARTP) values for four emission regions: Europe, East Asia, shipping, and the rest of the world. By 2050, we find that global surface temperature can be reduced by -0.3±0.08 ∘C with climate-optimal mitigation of SLCFs relative to a baseline scenario and as much as −0.7 ∘C in the Arctic. Cutting CH4 and black carbon (BC) emissions contributes the most. The net global cooling could offset warming equal to approximately 15 years of current global CO2 emissions. On the other hand, mitigation of other SLCFs (e.g., SO2) leads to warming. If SLCFs are mitigated heavily, we find a net warming of about 0.1 ∘C, but when uncertainties are included a slight cooling is also possible. In the climate optimal scenario, the largest contributions to cooling come from the energy, domestic, waste, and transportation sectors. In the maximum technically feasible mitigation scenario, emission changes from the industry, energy, and shipping sectors will cause warming. Some measures, such as those in the agriculture waste burning, domestic, transport, and industry sectors, have large impacts on the Arctic, especially by cutting BC emissions in winter in areas near the Arctic.

• Sporre, Moa Kristina; Blichner, Sara Marie; Karset, Inger Helene H.; Makkonen, Risto & Berntsen, Terje Koren (2019). BVOC-aerosol-climate feedbacks investigated using NorESM. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 19(7), p. 4763–4782. doi: 10.5194/acp-19-4763-2019. Full text in Research Archive Show summary

  Both higher temperatures and increased CO2 concentrations are (separately) expected to increase the emissions of biogenic volatile organic compounds (BVOCs). This has been proposed to initiate negative climate feedback mechanisms through increased formation of secondary organic aerosol (SOA). More SOA can make the clouds more reflective, which can provide a cooling. Furthermore, the increase in SOA formation has also been proposed to lead to increased aerosol scattering, resulting in an increase in diffuse radiation. This could boost gross primary production (GPP) and further increase BVOC emissions. In this study, we have used the Norwegian Earth System Model (NorESM) to investigate both these feedback mechanisms. Three sets of experiments were set up to quantify the feedback with respect to (1) doubling the CO2, (2) increasing temperatures corresponding to a doubling of CO2 and (3) the combined effect of both doubling CO2 and a warmer climate. For each of these experiments, we ran two simulations, with identical setups, except for the BVOC emissions. One simulation was run with interactive BVOC emissions, allowing the BVOC emissions to respond to changes in CO2 and/or climate. In the other simulation, the BVOC emissions were fixed at present-day conditions, essentially turning the feedback off. The comparison of these two simulations enables us to investigate each step along the feedback as well as estimate their overall relevance for the future climate. We find that the BVOC feedback can have a significant impact on the climate. The annual global BVOC emissions are up to 63 % higher when the feedback is turned on compared to when the feedback is turned off, with the largest response when both CO2 and climate are changed. The higher BVOC levels lead to the formation of more SOA mass (max 53 %) and result in more particles through increased new particle formation as well as larger particles through increased condensation. The corresponding changes in the cloud properties lead to a −0.43 W m−2 stronger net cloud forcing. This effect becomes about 50 % stronger when the model is run with reduced anthropogenic aerosol emissions, indicating that the feedback will become even more important as we decrease aerosol and precursor emissions. We do not find a boost in GPP due to increased aerosol scattering on a global scale. Instead, the fate of the GPP seems to be controlled by the BVOC effects on the clouds. However, the higher aerosol scattering associated with the higher BVOC emissions is found to also contribute with a potentially important enhanced negative direct forcing (−0.06 W m−2). The global total aerosol forcing associated with the feedback is −0.49 W m−2, indicating that it has the potential to offset about 13 % of the forcing associated with a doubling of CO2.

• Lewinschal, Anna; Ekman, Annica M. L.; Hansson, Hans-Christen; Sand, Maria; Berntsen, Terje Koren & Langner, Joakim (2019). Local and remote temperature response of regional SO2 emissions. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 19(4), p. 2385–2403. doi: 10.5194/acp-19-2385-2019. Full text in Research Archive Show summary

  Short-lived anthropogenic climate forcers (SLCFs), such as sulfate aerosols, affect both climate and air quality. Despite being short-lived, these forcers do not affect temperatures only locally; regions far away from the emission sources are also affected. Climate metrics are often used in a policy context to compare the climate impact of different anthropogenic forcing agents. These metrics typically relate a forcing change in a certain region with a temperature change in another region and thus often require a separate model to convert emission changes to radiative forcing (RF) changes. In this study, we used a coupled Earth system model, NorESM (Norwegian Earth System Model), to calculate emission-to-temperature-response metrics for sulfur dioxide (SO2) emission changes in four different policy-relevant regions: Europe (EU), North America (NA), East Asia (EA) and South Asia (SA). We first increased the SO2 emissions in each individual region by an amount giving approximately the same global average radiative forcing change (−0.45 Wm−2). The global mean temperature change per unit sulfur emission compared to the control experiment was independent of emission region and equal to ∼0.006 K(TgSyr−1)−1. On a regional scale, the Arctic showed the largest temperature response in all experiments. The second largest temperature change occurred in the region of the imposed emission increase, except when South Asian emissions were changed; in this experiment, the temperature response was approximately the same in South Asia and East Asia. We also examined the non-linearity of the temperature response by removing all anthropogenic SO2 emissions over Europe in one experiment. In this case, the temperature response (both global and regional) was twice that in the corresponding experiment with a European emission increase. This non-linearity in the temperature response is one of many uncertainties associated with the use of simplified climate metrics.

• Aas, Kjetil Schanke; Martin, Leo Celestin Paul; Nitzbon, Jan; Langer, Moritz; Boike, Julia & Lee, Hanna [Show all 8 contributors for this article] (2019). Thaw processes in ice-rich permafrost landscapes represented with laterally coupled tiles in a land surface model. The Cryosphere. ISSN 1994-0416. 13(2), p. 591–609. doi: 10.5194/tc-13-591-2019. Full text in Research Archive Show summary

  Earth system models (ESMs) are our primary tool for projecting future climate change, but their ability to represent small-scale land surface processes is currently limited. This is especially true for permafrost landscapes in which melting of excess ground ice and subsequent subsidence affect lateral processes which can substantially alter soil conditions and fluxes of heat, water, and carbon to the atmosphere. Here we demonstrate that dynamically changing microtopography and related lateral fluxes of snow, water, and heat can be represented through a tiling approach suitable for implementation in large-scale models, and we investigate which of these lateral processes are important to reproduce observed landscape evolution. Combining existing methods for representing excess ground ice, snow redistribution, and lateral water and energy fluxes in two coupled tiles, we show that the model approach can simulate observed degradation processes in two very different permafrost landscapes. We are able to simulate the transition from low-centered to high-centered polygons, when applied to polygonal tundra in the cold, continuous permafrost zone, which results in (i) a more realistic representation of soil conditions through drying of elevated features and wetting of lowered features with related changes in energy fluxes, (ii) up to 2 ∘C reduced average permafrost temperatures in the current (2000–2009) climate, (iii) delayed permafrost degradation in the future RCP4.5 scenario by several decades, and (iv) more rapid degradation through snow and soil water feedback mechanisms once subsidence starts. Applied to peat plateaus in the sporadic permafrost zone, the same two-tile system can represent an elevated peat plateau underlain by permafrost in a surrounding permafrost-free fen and its degradation in the future following a moderate warming scenario. These results demonstrate the importance of representing lateral fluxes to realistically simulate both the current permafrost state and its degradation trajectories as the climate continues to warm. Implementing laterally coupled tiles in ESMs could improve the representation of a range of permafrost processes, which is likely to impact the simulated magnitude and timing of the permafrost–carbon feedback.

• Karset, Inger Helene H.; Berntsen, Terje Koren; Storelvmo, Trude; Alterskjær, Kari; Grini, Alf & Oliviè, Dirk Jan Leo [Show all 10 contributors for this article] (2018). Strong impacts on aerosol indirect effects from historical oxidant changes. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 18(10), p. 7669–7690. doi: 10.5194/acp-18-7669-2018. Full text in Research Archive Show summary

  Uncertainties in effective radiative forcings through aerosol–cloud interactions (ERFaci, also called aerosol indirect effects) contribute strongly to the uncertainty in the total preindustrial-to-present-day anthropogenic forcing. Some forcing estimates of the total aerosol indirect effect are so negative that they even offset the greenhouse gas forcing. This study highlights the role of oxidants in modeling of preindustrial-to-present-day aerosol indirect effects. We argue that the aerosol precursor gases should be exposed to oxidants of its era to get a more correct representation of secondary aerosol formation. Our model simulations show that the total aerosol indirect effect changes from −1.32 to −1.07 W m−2 when the precursor gases in the preindustrial simulation are exposed to preindustrial instead of present-day oxidants. This happens because of a brightening of the clouds in the preindustrial simulation, mainly due to large changes in the nitrate radical (NO3). The weaker oxidative power of the preindustrial atmosphere extends the lifetime of the precursor gases, enabling them to be transported higher up in the atmosphere and towards more remote areas where the susceptibility of the cloud albedo to aerosol changes is high. The oxidation changes also shift the importance of different chemical reactions and produce more condensate, thus increasing the size of the aerosols and making it easier for them to activate as cloud condensation nuclei.

• Skeie, Ragnhild Bieltvedt; Berntsen, Terje Koren; Aldrin, Magne Tommy; Holden, Marit & Myhre, Gunnar (2018). Climate sensitivity estimates - Sensitivity to radiative forcing time series and observational data. Earth System Dynamics (ESD). ISSN 2190-4979. 9(2), p. 879–894. doi: 10.5194/esd-9-879-2018. Full text in Research Archive Show summary

  Inferred effective climate sensitivity (ECSinf) is estimated using a method combining radiative forcing (RF) time series and several series of observed ocean heat content (OHC) and near-surface temperature change in a Bayesian framework using a simple energy balance model and a stochastic model. The model is updated compared to our previous analysis by using recent forcing estimates from IPCC, including OHC data for the deep ocean, and extending the time series to 2014. In our main analysis, the mean value of the estimated ECSinf is 2.0 ∘C, with a median value of 1.9 ∘C and a 90 % credible interval (CI) of 1.2–3.1 ∘C. The mean estimate has recently been shown to be consistent with the higher values for the equilibrium climate sensitivity estimated by climate models. The transient climate response (TCR) is estimated to have a mean value of 1.4 ∘C (90 % CI 0.9–2.0 ∘C), and in our main analysis the posterior aerosol effective radiative forcing is similar to the range provided by the IPCC. We show a strong sensitivity of the estimated ECSinf to the choice of a priori RF time series, excluding pre-1950 data and the treatment of OHC data. Sensitivity analysis performed by merging the upper (0–700 m) and the deep-ocean OHC or using only one OHC dataset (instead of four in the main analysis) both give an enhancement of the mean ECSinf by about 50 % from our best estimate.

• Tanaka, Katsumasa; Lund, Marianne Tronstad; Aamaas, Borgar & Berntsen, Terje Koren (2018). Climate effects of non-compliant Volkswagen diesel cars. Environmental Research Letters. 13(4). doi: 10.1088/1748-9326/aab18c. Full text in Research Archive Show summary

  On-road operations of Volkswagen light-duty diesel vehicles equipped with defeat devices cause emissions of NOx up to 40 times above emission standards. Higher on-road NOx emissions are a widespread problem not limited to Volkswagen vehicles, but the Volkswagen violations brought this issue under the spotlight. While several studies investigated the health impacts of high NOx emissions, the climatic impacts have not been quantified. Here we show that such diesel cars generate a larger warming on the time scale of several years but a smaller warming on the decadal time scale during actual on-road operations than in vehicle certification tests. The difference in longer-term warming levels, however, depends on underlying driving conditions. Furthermore, in the presence of defeat devices, the climatic advantage of 'clean diesel' cars over gasoline cars, in terms of global-mean temperature change, is in our view not necessarily the case.

• Aas, Kjetil Schanke; Gisnås, Kjersti; Westermann, Sebastian & Berntsen, Terje Koren (2017). A Tiling Approach to Represent Subgrid Snow Variability in Coupled Land Surface–Atmosphere Models. Journal of Hydrometeorology. ISSN 1525-755X. 18(1), p. 49–63. doi: 10.1175/JHM-D-16-0026.1. Full text in Research Archive Show summary

  A mosaic approach to represent subgrid snow variation in a coupled atmosphere–land surface model (WRF–Noah) is introduced and tested. Solid precipitation is scaled in 10 subgrid tiles based on precalculated snow distributions, giving a consistent, explicit representation of variable snow cover and snow depth on subgrid scales. The method is tested in the Weather Research and Forecasting (WRF) Model for southern Norway at 3-km grid spacing, using the subgrid tiling for areas above the tree line. At a validation site in Finse, the modeled transition time from full snow cover to snow-free ground is increased from a few days with the default snow cover fraction formulation to more than 2 months with the tiling approach, which agrees with in situ observations from both digital camera images and surface temperature loggers. This in turn reduces a cold bias at this site by more than 2°C during the first half of July, with the noontime bias reduced from −5° to −1°C. The improved representation of subgrid snow variation also reduces a cold bias found in the reference simulation on regional scales by up to 0.8°C and increases surface energy fluxes (in particular the latent heat flux), and it resulted in up to 50% increase in monthly (June) precipitation in some of the most affected areas. By simulating individual soil properties for each tile, this approach also accounts for a number of secondary effects of uneven snow distribution resulting in different energy and moisture fluxes in different tiles also after the snow has disappeared. This research was originally published in Journal of Hydrometeorology. © 2017 American Meteorological Society

• Skeie, Ragnhild Bieltvedt; Fuglestvedt, Jan S.; Berntsen, Terje Koren; Peters, Glen Philip; Andrew, Robbie & Allen, Myles [Show all 7 contributors for this article] (2017). Perspective has a strong effect on the calculation of historical contributions to global warming. Environmental Research Letters. 12(2). doi: 10.1088/1748-9326/aa5b0a. Full text in Research Archive Show summary

  The politically contentious issue of calculating countries' contributions to climate change is strongly dependent on methodological choices. Different principles can be applied for distributing efforts for reducing human-induced global warming. According to the 'Brazilian Proposal', industrialized countries would reduce emissions proportional to their historical contributions to warming. This proposal was based on the assumption that the political process would lead to a global top-down agreement. The Paris Agreement changed the role of historical responsibilities. Whereas the agreement refers to equity principles, differentiation of mitigation efforts is delegated to each country, as countries will submit new national contributions every five years without any international negotiation. It is likely that considerations of historical contributions and distributive fairness will continue to play a key role, but increasingly so in a national setting. Contributions to warming can be used as a background for negotiations to inform and justify positions, and may also be useful for countries' own assessment of what constitutes reasonable and fair contributions to limiting warming. Despite the fact that the decision from COP21 explicitly rules out compensation in the context of loss and damage, it is likely that considerations of historical responsibility will also play a role in future discussions. However, methodological choices have substantial impacts on calculated contributions to warming, including rank-ordering of contributions, and thus support the view that there is no single correct answer to the question of how much each country has contributed. There are fundamental value-related and ethical questions that cannot be answered through a single set of calculated contributions. Thus, analyses of historical contributions should not present just one set of results, but rather present a spectrum of results showing how the calculated contributions vary with a broad set of choices. Our results clearly expose some of the core issues related to climate responsibility.

• Aamaas, Borgar; Berntsen, Terje Koren; Fuglestvedt, Jan S.; Shine, Keith P & Collins, William J (2017). Regional temperature change potentials for short-lived climate forcers based on radiative forcing from multiple models. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 17(17), p. 10795–10809. doi: 10.5194/acp-17-10795-2017. Full text in Research Archive Show summary

  We calculate the absolute regional temperature change potential (ARTP) of various short-lived climate forcers (SLCFs) based on detailed radiative forcing (RF) calculations from four different models. The temperature response has been estimated for four latitude bands (90–28° S, 28° S–28° N, 28–60° N, and 60–90° N). The regional pattern in climate response not only depends on the relationship between RF and surface temperature, but also on where and when emissions occurred and atmospheric transport, chemistry, interaction with clouds, and deposition. We present four emissions cases covering Europe, East Asia, the global shipping sector, and the entire globe. Our study is the first to estimate ARTP values for emissions during Northern Hemisphere summer (May–October) and winter season (November–April). The species studied are aerosols and aerosol precursors (black carbon, organic carbon, SO2, NH3), ozone precursors (NOx, CO, volatile organic compound), and methane (CH4). For the response to BC in the Arctic, we take into account the vertical structure of the RF in the atmosphere, and an enhanced climate efficacy for BC deposition on snow. Of all SLCFs, BC is the most sensitive to where and when the emissions occur, as well as giving the largest difference in response between the latitude bands. The temperature response in the Arctic per unit BC emission is almost four times larger and more than two times larger than the global average for Northern Hemisphere winter emissions for Europe and East Asia, respectively. The latitudinal breakdown likely gives a better estimate of the global temperature response as it accounts for varying efficacies with latitude. An annual pulse of non-methane SLCF emissions globally (representative of 2008) lead to a global cooling. In contrast, winter emissions in Europe and East Asia give a net warming in the Arctic due to significant warming from BC deposition on snow.

• Lund, Marianne Tronstad; Aamaas, Borgar; Berntsen, Terje Koren; Bock, Lisa; Burkhardt, Ulrike & Fuglestvedt, Jan S. [Show all 7 contributors for this article] (2017). Emission metrics for quantifying regional climate impacts of aviation. Earth System Dynamics (ESD). ISSN 2190-4979. 8(3), p. 547–563. doi: 10.5194/esd-8-547-2017. Full text in Research Archive Show summary

  This study examines the impacts of emissions from aviation in six source regions on global and regional temperatures. We consider the NOx-induced impacts on ozone and methane, aerosols and contrail-cirrus formation and calculate the global and regional emission metrics global warming potential (GWP), global temperature change potential (GTP) and absolute regional temperature change potential (ARTP). The GWPs and GTPs vary by a factor of 2–4 between source regions. We find the highest aviation aerosol metric values for South Asian emissions, while contrail-cirrus metrics are higher for Europe and North America, where contrail formation is prevalent, and South America plus Africa, where the optical depth is large once contrails form. The ARTP illustrate important differences in the latitudinal patterns of radiative forcing (RF) and temperature response: the temperature response in a given latitude band can be considerably stronger than suggested by the RF in that band, also emphasizing the importance of large-scale circulation impacts. To place our metrics in context, we quantify temperature change in four broad latitude bands following 1 year of emissions from present-day aviation, including CO2. Aviation over North America and Europe causes the largest net warming impact in all latitude bands, reflecting the higher air traffic activity in these regions. Contrail cirrus gives the largest warming contribution in the short term, but remain important at about 15 % of the CO2 impact in several regions even after 100 years. Our results also illustrate both the short- and long-term impacts of CO2: while CO2 becomes dominant on longer timescales, it also gives a notable warming contribution already 20 years after the emission. Our emission metrics can be further used to estimate regional temperature change under alternative aviation emission scenarios. A first evaluation of the ARTP in the context of aviation suggests that further work to account for vertical sensitivities in the relationship between RF and temperature response would be valuable for further use of the concept.

• Sand, Maria; Samset, Bjørn Hallvard; Balkanski, Yves; Bauer, Susanne; Bellouin, Nicolas & Berntsen, Terje Koren [Show all 29 contributors for this article] (2017). Aerosols at the poles: an AeroCom Phase II multi-model evaluation. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 17(19), p. 12197–12218. doi: 10.5194/acp-17-12197-2017. Full text in Research Archive Show summary

  Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes. The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60°N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70°S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (−0.12W m−2), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33% increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39% increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.

• Lund, Marianne Tronstad; Berntsen, Terje Koren & Samset, Bjørn Hallvard (2017). Sensitivity of black carbon concentrations and climate impact to aging and scavenging in OsloCTM2-M7. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 17(9), p. 6003–6022. doi: 10.5194/acp-17-6003-2017. Full text in Research Archive Show summary

  Accurate representation of black carbon (BC) concentrations in climate models is a key prerequisite for understanding its net climate impact. BC aging and scavenging are treated very differently in current models. Here, we examine the sensitivity of three-dimensional (3-D), temporally resolved BC concentrations to perturbations to individual model processes in the chemistry transport model OsloCTM2–M7. The main goals are to identify processes related to aerosol aging and scavenging where additional observational constraints may most effectively improve model performance, in particular for BC vertical profiles, and to give an indication of how model uncertainties in the BC life cycle propagate into uncertainties in climate impacts. Coupling OsloCTM2 with the microphysical aerosol module M7 allows us to investigate aging processes in more detail than possible with a simpler bulk parameterization. Here we include, for the first time in this model, a treatment of condensation of nitric acid on BC. Using kernels, we also estimate the range of radiative forcing and global surface temperature responses that may result from perturbations to key tunable parameters in the model. We find that BC concentrations in OsloCTM2–M7 are particularly sensitive to convective scavenging and the inclusion of condensation by nitric acid. The largest changes are found at higher altitudes around the Equator and at low altitudes over the Arctic. Convective scavenging of hydrophobic BC, and the amount of sulfate required for BC aging, are found to be key parameters, potentially reducing bias against HIAPER Pole-to-Pole Observations (HIPPO) flight-based measurements by 60 to 90  %. Even for extensive tuning, however, the total impact on global-mean surface temperature is estimated to less than 0.04 K. Similar results are found when nitric acid is allowed to condense on the BC aerosols. We conclude, in line with previous studies, that a shorter atmospheric BC lifetime broadly improves the comparison with measurements over the Pacific. However, we also find that the model–measurement discrepancies can not be uniquely attributed to uncertainties in a single process or parameter. Model development therefore needs to be focused on improvements to individual processes, supported by a broad range of observational and experimental data, rather than tuning of individual, effective parameters such as the global BC lifetime.

• Koffi, Brigitte; Schulz, Michael; Bréon, François-Marie; Dentener, Frank; Steensen, Birthe Marie Rødssæteren & Griesfeller, Jan [Show all 33 contributors for this article] (2016). Evaluation of the aerosol vertical distribution in global aerosol models through comparison against CALIOP measurements: AeroCom phase II results. Journal of Geophysical Research (JGR): Atmospheres. ISSN 2169-897X. 121(12), p. 7254–7283. doi: 10.1002/2015JD024639. Full text in Research Archive Show summary

  The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.

• Aamaas, Borgar; Berntsen, Terje Koren; Fuglestvedt, Jan S.; Shine, Keith P & Bellouin, Nicolas (2016). Regional emission metrics for short-lived climate forcers from multiple models. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 16(11), p. 7451–7468. doi: 10.5194/acp-16-7451-2016. Full text in Research Archive Show summary

  For short-lived climate forcers (SLCFs), the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF) values calculated in four different (chemical-transport or coupled chemistry–climate) models. We distinguish between emissions during summer (May–October) and winter (November–April) for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3), as well as ozone precursors (NOx, CO, VOCs), which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP) and global temperature change potential (GTP), based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies. For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation policy package is robust even when accounting for the fact that the magnitude of emission metrics for different species in a given model is correlated. For the ramping emission metrics, the values are generally larger than for pulse or sustained emissions, which holds for all SLCFs. For SLCFs mitigation policies, the dependency of metric values on the region and season of emission should be considered.

• Aas, Kjetil Schanke; Dunse, Thorben; Collier, E.; Schuler, Thomas; Berntsen, Terje Koren & Kohler, Jack [Show all 7 contributors for this article] (2016). The climatic mass balance of Svalbard glaciers: A 10-year simulation with a coupled atmosphere-glacier mass balance model. The Cryosphere. ISSN 1994-0416. 10(3), p. 1089–1104. doi: 10.5194/tc-10-1089-2016. Full text in Research Archive Show summary

  In this study we simulate the climatic mass balance of Svalbard glaciers with a coupled atmosphere–glacier model with 3 km grid spacing, from September 2003 to September 2013. We find a mean specific net mass balance of −257 mm w.e. yr−1, corresponding to a mean annual mass loss of about 8.7 Gt, with large interannual variability. Our results are compared with a comprehensive set of mass balance, meteorological, and satellite measurements. Model temperature biases of 0.19 and −1.9 °C are found at two glacier automatic weather station sites. Simulated climatic mass balance is mostly within about 100 mm w.e. yr−1 of stake measurements, and simulated winter accumulation at the Austfonna ice cap shows mean absolute errors of 47 and 67 mm w.e. yr−1 when compared to radar-derived values for the selected years 2004 and 2006. Comparison of modeled surface height changes from 2003 to 2008, and satellite altimetry reveals good agreement in both mean values and regional differences. The largest deviations from observations are found for winter accumulation at Hansbreen (up to around 1000 mm w.e. yr−1), a site where sub-grid topography and wind redistribution of snow are important factors. Comparison with simulations using 9 km grid spacing reveal considerable differences on regional and local scales. In addition, 3 km grid spacing allows for a much more detailed comparison with observations than what is possible with 9 km grid spacing. Further decreasing the grid spacing to 1 km appears to be less significant, although in general precipitation amounts increase with resolution. Altogether, the model compares well with observations and offers possibilities for studying glacier climatic mass balance on Svalbard both historically as well as based on climate projections.

• Stohl, Andreas; Aamaas, Borgar; Amann, M; Baker, LH; Bellouin, N & Berntsen, Terje Koren [Show all 40 contributors for this article] (2015). Evaluating the climate and air quality impacts of short-lived pollutants. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 15(18), p. 10529–10566. doi: 10.5194/acp-15-10529-2015. Full text in Research Archive Show summary

  This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80%, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22±0.09K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22% to this response and CH4 78%. This could not be fully confirmed by the transient simulations, which attributed about 90% of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted spec

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• Wit, Heleen de; Worner, Elisabeth-Christina; Lu, Xiang; Balkoni, Areti; Jackson-Blake, Leah Amber & Berntsen, Terje Koren [Show all 8 contributors for this article] (2026). Integration of terrestrial and aquatic carbon fluxes in a boreal headwater catchment. Full text in Research Archive
• Shetty, Shobitha; Stebel, Kerstin; Hamer, Paul David; Hassani, Amirhossein; Salamalikis, Vasileios & Chen, Jiayao [Show all 9 contributors for this article] (2026). Machine-learning data fusion of model, satellite and low-cost sensor observations for 1-km PM2.5 mapping across Europe. Full text in Research Archive
• Zaini, Adele; Blichner, Sara Marie; Tang, Jing; Fisher, Rosie; Lund, Marianne T. & Oliviè, Dirk Jan Leo [Show all 7 contributors for this article] (2026). Beyond carbon, from Arctic forest migration to climate mitigation: can biogeochemical effects challenge albedo-driven warming? European Geosciences Union General Assembly Abstracts. doi: 10.5194/egusphere-egu26-20671. Full text in Research Archive Show summary

  Rising global temperatures are expected to drive a northward expansion of boreal forests into Arctic regions, triggering multiple and interacting climate feedbacks. This land cover change is also relevant as a parallel to mitigation strategies such as afforestation, which are often evaluated solely for their carbon benefits, while other biogeophysical and biogeochemical effects may substantially offset the intended carbon uptake. Reduced surface albedo from forests replacing snow-covered, treeless areas is widely recognised as a strong warming mechanism. Chemical emissions, specifically biogenic volatile organic compounds (BVOCs), in these regions may also play a substantial role, potentially counteracting albedo-driven warming. In this study, we aim to provide new insights into the climate impacts of Arctic land cover change by assessing both biogeophysical and biogeochemical pathways beyond carbon uptake.BVOCs influence climate through multiple, partly opposing pathways. Their oxidation products contribute directly to secondary organic aerosol formation and modify indirectly cloud optical properties, potentially leading to a cooling effect. At the same time, BVOCs affect atmospheric chemistry by altering the concentrations and lifetimes of key climate forcers such as ozone and methane, which can introduce a positive radiative forcing. The combined effect of these processes, and their relative importance compared to albedo changes, remains uncertain.Here, we use the Norwegian Earth System Model version 2.3 (NorESM2.3), including a newly implemented comprehensive atmospheric chemistry scheme, to investigate the radiative impacts of projected boreal forest expansion. We perform targeted simulations under present-day and warmer climate scenarios, allowing us to isolate the contributions from surface albedo changes, BVOC-driven direct aerosol effects, cloud interactions, and chemistry-related impacts on ozone and methane.By comparing these pathways within a single modelling framework, this work evaluates whether BVOC-related processes can significantly offset albedo-driven warming and how their relative importance evolves under climate warming. The results provide a comprehensive understanding of how land use and land cover changes influence the Arctic climate via interacting biogeophysical and biogeochemical mechanisms.

• Walsh-Vilander, Anna; Vollsnes, Ane; Berntsen, Terje Koren; Fisher, Rosie & Parmentier, Frans-Jan W. (2026). Quantifying Cold Hardening in Arctic-Boreal Vegetation using Differential Thermal Analysis. Full text in Research Archive
• Yilmaz, Yeliz A.; Pirk, Norbert; Tallaksen, Lena M.; Stordal, Frode; Berntsen, Terje Koren & Bryn, Anders (2026). Cold region land-atmosphere interactions. doi: https:/www.gewexevents.org/meetings/glass2026/program/abstracts/#Y. Full text in Research Archive Show summary

  Environmental change in high latitudes is progressing faster and more intensely than in many other regions of the Earth. A warmer climate has already triggered unprecedented changes in the terrestrial cryosphere, hydrosphere and ecosphere, which feed back to the atmosphere and the hydrologic cycle. Yet, many studies still rely on one-way coupling between the atmosphere and the land surface, thereby neglecting important interactions and feedback mechanisms. To advance our knowledge on climate change in northern environments, LATICE (Land–ATmosphere Interactions in Cold Environments) was established as a strategic research initiative at the University of Oslo in 2015. Since then, it has developed into a collaborative network of researchers from atmospheric and terrestrial research groups. We combine novel observations, process-based model development, and integrated Earth observation frameworks to improve our understanding of high latitude environmental processes and their representation in Earth System Models - particularly the Norwegian Earth System Model (NorESM). The current LATICE infrastructure including flux towers, drone-based measurements, and a cold climate container contributes to expanding our observational data records in cold environments complemented by regionally calibrated satellite products tailored to boreal and Arctic conditions. These coordinated in-situ, airborne, and spaceborne datasets provide important constraints on surface fluxes, snow dynamics, and vegetation processes. On the modelling side, LATICE researchers have been contributing to land surface and hydrological models to better represent cold region processes by including process parameterizations, new plant functional types, and vegetation demography. The integration of observations and models through data assimilation methods, and further exploration of hybrid approaches with machine learning algorithms support improved understanding of land-atmosphere coupling and uncertainty quantification. This presentation highlights key activities and scientific advances within the LATICE community, presents example studies, and discusses future directions for scientific collaboration with the Pan-GLASS community.

• Schneider, Philipp; Shetty, Shobitha; Stebel, Kerstin; Hamer, Paul David; Hassani, Amirhossein & Salamalikis, Vasileios [Show all 8 contributors for this article] (2026). ML-based data fusion of model, satellite, and ground observations for 1-km PM2.5 mapping over Europe. Full text in Research Archive
• Schneider, Philipp; Shetty, Shobitha; Hassani, Amirhossein; Salamalikis, Vasileios; Stebel, Kerstin & Hamer, Paul David [Show all 8 contributors for this article] (2026). Integrating validated large-scale sensor observations into ML-based PM2.5 mapping: lessons from Europe with global relevance. doi: 10.5194/egusphere-egu26-7366. Full text in Research Archive Show summary

  Low-cost sensor (LCS) networks can complement sparse regulatory monitoring, but their value depends on robust integration strategies that preserve data quality while exploiting dense spatial sampling. Here we assess the added value of incorporating validated LCS PM2.5 observations into the S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) machine learning framework (Shetty et al., 2024, 2025) to generate continental-scale, 1 km resolution surface PM2.5 fields across Central Europe. Two integration strategies are evaluated for 2021–2022 within a stacked XGBoost architecture driven by satellite aerosol optical depth, meteorological predictors, and CAMS regional forecasts: a) using LCS data as an additional training target (LCST), and b) using LCS information as a model input feature (LCSI) via an inverse-distance-weighted spatial convolution layer that encodes local sensor influence. Relative to a baseline trained only on official monitoring stations, LCSI yields consistent performance gains, with RMSE reductions of ~15–20% in urban areas, whereas LCST provides less consistent improvement. The resulting high-resolution mapping product achieves skill comparable to the CAMS regional reanalysis, often considered as a modelling “gold standard” for European air-quality assessment, and in some evaluations surpasses it, with lower annual mean absolute error (2.68 vs 3.32 µg m⁻³) (Shetty et al., 2026). This demonstrates that a data-fusion ML approach including LCS information can deliver reanalysis-level performance at 1 km resolution while requiring only modest computational resources compared with running full chemical transport model reanalyses, enabling rapid updates and scalable deployment. SHAP-based attribution further suggests that LCSI improves the model’s ability to capture localized pollution variability, while performance degrades where sensor density is low, limiting representation of inter-urban transport.Although demonstrated in Europe, the underlying methodology, namely combining globally available satellite products and meteorology with quality-controlled LCS networks in a computationally efficient ML framework, has potential to strengthen air-quality assessment also in resource-limited settings where regulatory infrastructure is scarce. A requirement for this is that appropriate sensor calibration/validation workflows are in place and equitable partnerships support sustainable sensor deployment and data stewardship. Shetty, S., Schneider, P., Stebel, K., Hamer, P. D., Kylling, A., and Koren Berntsen, T.: Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning, Remote Sens. Environ., 312, 114321, https://doi.org/10.1016/j.rse.2024.114321, 2024.Shetty, S., Hamer, P. D., Stebel, K., Kylling, A., Hassani, A., Berntsen, T. K., and Schneider, P.: Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast, Environ. Res., 264, 120363, https://doi.org/10.1016/j.envres.2024.120363, 2025.Shetty, S., Hassani, A., Hamer, P. D., Stebel, K., Salamalikis, V., Berntsen, T. K., Castell, N., and Schneider, P.: Evaluating the role of low-cost sensors in machine learning based European PM2.5 monitoring, Environ. Res., 291, 123558, https://doi.org/10.1016/j.envres.2025.123558, 2026.

• Schneider, Philipp; Shetty, Shobitha; Stebel, Kerstin; Hamer, Paul David; Hassani, Amirhossein & Salamalikis, Vasileios [Show all 8 contributors for this article] (2026). Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast. Full text in Research Archive
• Berntsen, Terje Koren (2025). How can we model soil carbon in a warmer climate? Full text in Research Archive Show summary

  Land surface models used in Earth system models are used to simulate changes in carbon stocks in soils due to changes in litter input from vegetation and changes in decomposition rates of soil organic matter by microbes. In the lecture we present a new module for these processes applied in CLM module of the Norwegian Earth Syetem model NorESM.

• Berntsen, Terje Koren (2025). How can we model soil carbon in a warmer climate? Full text in Research Archive
• Muzic, Iris; Hodnebrog, Øivind; Yilmaz, Yeliz A.; Berntsen, Terje Koren; Sillmann, Jana & Lawrence, David M. [Show all 8 contributors for this article] (2025). Evaluating Land-Atmosphere Interactions in the coupled WRF-CTSM model over Nordic Fennoscandia. Full text in Research Archive Show summary

  High latitude regions are experiencing rapid changes under evolving climate conditions. Advanced research tools are essential for understanding these dynamics and their associated feedback mechanisms. Here we present 1) a comprehensive evaluation of the state-of-the-art coupled regional climate model WRF–CTSM in simulating hydroclimatic variables and 2) soil moisture–temperature coupling analysis during the extreme 2018 heatwave. The WRF–CTSM model couples the Weather Research and Forecasting (WRF) model with the Community Terrestrial Systems Model (CTSM) which enables a more detailed representation of land surface processes and their interactions with the atmosphere. We conducted a high-resolution (10.5 km) 13-year simulation (2010–2022) over Nordic Fennoscandia (Norway, Sweden, and Finland) to assess the model’s performance in capturing key hydroclimatic variables such as mean, minimum, and maximum 2 m temperatures, precipitation, snow variables (snow depth, snow water equivalent, fractional snow‐covered duration), and surface energy balance components. A multi-source comparison using gridded, satellite-based, and in situ observations indicates that the WRF–CTSM model effectively captures high latitude climate conditions at different timescales. In addition, we used WRF–CTSM to investigate soil moisture–temperature coupling during the 2018 heatwave with a focus on southern and central Sweden that is considered as a coupling hotspot. A multi-correlation overlay analysis was performed using four different WRF–CTSM configurations. We employed a gridded observational dataset as a reference after validating against in situ measurements to assess the magnitude and variability of the key coupling variables. Our results show that soil moisture–temperature coupling persisted for an average of 40 days. The atmospheric leg contributes on average 88% of the coupling duration with considerable variability across datasets. Our findings highlight the capability of the WRF–CTSM model to simulate complex land–atmosphere interactions in high latitude environments

• Schneider, Philipp; Hassani, Amirhossein; Salamalikis, Vasileios; Castell, Nuria; Shetty, Shobitha & Stebel, Kerstin [Show all 8 contributors for this article] (2025). Quality control of PM2.5 sensor networks and their use in mapping air quality. Full text in Research Archive
• Schneider, Philipp; Shetty, Shobitha; Stebel, Kerstin; Hamer, Paul David; Hassani, Amirhossein & Salamalikis, Vasileios [Show all 8 contributors for this article] (2025). Daily high-resolution PM2.5 estimation in Europe via ML-based downscaling of CAMS. Full text in Research Archive
• Wit, Heleen de; Berntsen, Terje Koren; Worner, Elisabeth-Christina; Jackson-Blake, Leah Amber; Clayer, Francois & lu, xiang (2025). Integration of terrestrial and aquatic C fluxes. Full text in Research Archive
• Wit, Heleen de; Jackson-Blake, Leah Amber; Berntsen, Terje Koren; Worner, Elisabeth-Christina; Lange, Holger & Clayer, Francois [Show all 7 contributors for this article] (2025). Integration of terrestrial and aquatic C fluxes. Case study Langtjern. Full text in Research Archive
• Tjessem, Ingrid Vesterdal; Bryn, Anders; Horvath, Peter; Naas, Adam Eindride; Halvorsen, Rune & Berntsen, Terje Koren [Show all 10 contributors for this article] (2025). Tales from the past: remapping rising tree- and forest lines in response to changing climate and land use regimes. Full text in Research Archive
• Schneider, Philipp; Shetty, Shobitha; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve & Hassani, Amirhossein [Show all 12 contributors for this article] (2025). EO-based Downscaling for Urban-Scale Air Quality Applications. Full text in Research Archive
• Zaini, Adele; Blichner, Sara Marie; Tang, Jing; Fisher, Rosie; Lund, Marianne Tronstad & Berntsen, Terje Koren (2024). Exploring the biogeophysical and biogeochemical impacts of an Arctic poleward expansion of the boreal forest. Full text in Research Archive
• Zaini, Adele; Blichner, Sara Marie; Tang, Jing; Fisher, Rosie; Lund, Marianne Tronstad & Berntsen, Terje Koren (2024). Exploring the biogeophysical and biogeochemical impacts of an Arctic poleward expansion of the boreal forest. Full text in Research Archive
• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Hamer, Paul David; Kylling, Arve & Berntsen, Terje Koren (2024). Estimating high resolution surface air pollutants using machine learning and satellites. Full text in Research Archive
• Shetty, Shobitha; Schneider, Philipp; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve & Berntsen, Terje Koren (2024). Estimating high resolution daily surface PM2.5 over Europe using CAMS PM forecast, satellite AOD, and a Machine Learning Model. Full text in Research Archive
• Berntsen, Terje Koren (2023). Klimafølsomheten: Det store spørsmålet i klimaforskningen. Full text in Research Archive
• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Hamer, Paul David; Kylling, Arve & Berntsen, Terje Koren (2023). Estimating High Resolution Surface PM2.5 Over Europe Using Satellite AOD Datasets, CAMS Forecast and Machine Learning. Full text in Research Archive
• Falk, Stefanie; Vollsnes, Ane Victoria; Eriksen, Aud Berglen; Emberson, Lisa D.; O’Neill, Connie & Stordal, Frode [Show all 7 contributors for this article] (2023). Modelling the effects of ozone pollution on coniferous and deciduous forests. Full text in Research Archive
• Mužić, Iris; Hodnebrog, Øivind; Berntsen, Terje Koren; Yilmaz, Yeliz A.; Sillmann, Jana & Lawrence, David [Show all 8 contributors for this article] (2023). The relevance of coupled climate model WRF-CTSM for land-atmosphere interactions analysis. Full text in Research Archive
• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Kylling, Arve; Berntsen, Terje Koren & Hamer, Paul David (2023). Evaluation of TROPOMI observations for estimating surface NO2 concentrations over Europe using XGBoost Model. Full text in Research Archive
• Berntsen, Terje Koren & Aas, Elin Cecilie Ristorp (2023). Modelling soil carbon in the Norwegian Earth System Model. Full text in Research Archive
• Tang, Hui; Aas, Kjetil Schanke; Althuizen, Inge; Geange, Sonya Rita; Berntsen, Terje Koren & Vandvik, Vigdis (2022). Update on the implementation of moss in CTSM-FATES. Full text in Research Archive
• Aas, Kjetil Schanke; Lambert, Marius; Tang, Hui; Althuizen, Inge; Berntsen, Terje Koren & Fisher, Rosie [Show all 11 contributors for this article] (2022). Recent high-latitude vegetation developments in CLM-FATES. Full text in Research Archive
• Vollsnes, Ane Victoria; Eriksen, Aud Berglen; Falk, Stefanie; Stordal, Frode & Berntsen, Terje Koren (2022). Ozone-induced early senescence studied in Trifolium repens genotypes from subarctic grasslands. Full text in Research Archive Show summary

  Previous experiments have shown that several European clovers may develop more visible injuries due to ozone when the night is not dark. At high latitudes, the summer nights are bright, giving the background for the question whether plants adapted to midnight sun also have this response of being more easily injured by ozone when the night is not dark. The plants included in the present experiment are expected to be adapted to light exposure during night, since there is midnight sun from the time they melt out of the snow cover in spring until the end of July, in the sites where they were collected. This constitutes about 50 % of the growing season for grassland species in these areas. Cuttings of two genotypes of white clover (Trifolium repens) collected in two sites in subarctic Norway were cultivated under controlled environment conditions. Using a factorial design, the plants were exposed to two different night-time light conditions and two different ozone exposure levels. We studied the development of visible injuries, foliar chlorophyll concentrations and N concentration as signs of premature senescence due to ozone.

• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Hamer, Paul David; Kylling, Arve & Berntsen, Terje Koren (2022). Synergy of Sentinel 5P and ground measurements to estimate surface NO2 concentration using Machine Learning models. Full text in Research Archive
• Bryn, Anders; Horvath, Peter; Torma, Michal; Naas, Adam Eindride; Volden, Inger Kristine & Liahjell, Gunnar Thorsen [Show all 10 contributors for this article] (2022). Treeline research at Natural history museum (UiO). Full text in Research Archive
• Tang, Hui; Aas, Kjetil Schanke; Finne, Eirik Aasmo; Althuizen, Inge; Fisher, Rosie A. & Tømmervik, Hans [Show all 14 contributors for this article] (2021). The impact of moss and lichen on hydrological cycle at surface: a study using CLM-FATES. Full text in Research Archive
• Vollsnes, Ane Victoria; Stordal, Frode; Falk, Stefanie; Eriksen, Aud Berglen; Kauserud, Håvard & Berntsen, Terje Koren (2021). Field and lab experiments, plant ecophysiology starting from The double punch. Full text in Research Archive
• Vollsnes, Ane Victoria; Falk, Stefanie; eriksen, Aud Berglen; Emberson, Lisa D.; O’Neill, Connie & Stordal, Frode [Show all 7 contributors for this article] (2021). Model parameterisation of subarctic vegetation in climate models, an example from an ozone effect study. Full text in Research Archive
• Mužić, Iris; Vestin, Patrik; Lindroth, Anders; Mölder, Meelis; Biermann, Tobias & Heliasz, Michal [Show all 11 contributors for this article] (2021). MSc: Changes in radiative forcing due to clear-cutting in Sweden; PhD: The role of land-atmosphere interactions on temperature variability and extremes in Fennoscandia. Full text in Research Archive
• Vollsnes, Ane Victoria; Falk, Stefanie; Eriksen, Aud Else Berglen; Stordal, Frode; Kauserud, Håvard & Berntsen, Terje Koren (2021). Luftforurensning og klimaendringer gir dobbelt stress for vegetasjonen. Naturen. ISSN 0028-0887. 5, p. 265–271. doi: 10.18261/issn.1504-3118-2021-05-10. Full text in Research Archive
• Narayanappa, Devaraju; Berntsen, Terje Koren & Stordal, Frode (2021). Simulated runoff and river discharge in CTSM version 5.1: Evaluation over Scandinavia. Full text in Research Archive Show summary

  Reliable representation of terrestrial water and energy balance in global climate models is crucial to better understand the response of the hydrological cycle to climate change. Though the current generation of global climate models have improved substantially, they still fail to represent all terrestrial processes adequately. Specifically simulating runoff and river discharge are important for many applications such as water resources management and future water availability projections. In this study, we use the land surface model component of the Norwegian Earth System Model which is Community Land Model version 5 (CLM5) to evaluate against observation-based estimates of runoff and river discharge data of selected catchments data. For the latest three decades (1985-2015), we compare the CLM5 simulated grid-scale runoff with observation-based gridded runoff estimates (E-RUN version 1.1) and with data from the Global Runoff Data Centre (GRDC). CLM5 is also capable of simulating river discharge to the oceans through the Model for Scale Adaptive River Transport (MOSART) and is applicable across local, regional, and global scales. The 3-hourly 0.5o meteorological forcing for CLM5 was provided by the Global Soil Wetness Project version 3v1, an international land surface modeling project. We also compare the simulated river discharge data with selected station discharge data in Norway and Sweden. I will present the detailed evaluation results at the conference. Briefly, the evaluation analysis suggests the further calibration to hydrologic parameters is needed to improve simulations of runoff and river discharge, especially subsurface runoff.

• Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Kylling, Arve; Hamer, Paul David & Berntsen, Terje Koren (2021). Combining Sentinel-5P and Ground Measurements to estimate surface NO2 Concentrations over Europe Using Machine Learning Models. Full text in Research Archive
• Falk, Stefanie; Lombardozzi, Danica; Vollsnes, Ane Victoria; Stordal, Frode; Berntsen, Terje Koren & Eriksen, Aud Else Berglen (2021). OzoneLUNA: Ozone damage in CLM revisited. Full text in Research Archive
• Falk, Stefanie; Vollsnes, Ane Victoria; Eriksen, Aud E Berglen; Emberson, Lisa D.; O'Neill, Connie & Stordal, Frode [Show all 7 contributors for this article] (2021). Charakterisierung der subarktischen Ökozone hinsichtlich der Modellierung von Ozonverschmutzung und Klimarisiken. Full text in Research Archive Show summary

  https://www.dpg-verhandlungen.de/year/2021/conference/smuk/part/up/session/5/contribution/2?lang=en

• Falk, Stefanie; Vollsnes, Ane Victoria; Emberson, Lisa D.; O'Neill, Connie; Eriksen, Aud E Berglen & Stordal, Frode [Show all 7 contributors for this article] (2021). Characterizing subarctic biomes for land surface modeling of pollution and climate risk. Full text in Research Archive Show summary

  Here we assess the importance of characterization of key meteorological variables and air pollution profiles on the modeled susceptibility of subarctic vegetation to ozone. Changes in climate (e.g. temperature, water availability) will manifest in both direct and indirect effects influencing the species' sensitivity to air pollution. A likely increase in frequency of persistent heatwaves in the future, will inflict heat related stress while generating favorable conditions for the formation of ambient air ozone, e.g. due to wildfires. We have monitored ambient air ozone concentrations at the Norwegian Institute of Bioeconomy Research (NIBIO) Environment Centre Svanhovd in Northern Norway in the vegetation period 2018/19. Due to data acquisition problems, ozone concentrations for two weeks in July 2018 were missing from our record. We present a reconstruction based on probability density function with respect to the Swedish and Finnish atmospheric monitoring sites and compare with available surface ozone products for the region. Over all, ozone concentrations did not differ significantly between the two years. While temperatures and global irradiance diverged substantially from the multi annual mean precipitation varied only to some extend. We investigate the difference in uptake of ozone using the DO3SE model, for typical vegetation at the location. We find that bespoke parameterization for subarctic vegetation is essential for an accurate estimation of Phototoxic Ozone Dose (POD) and an assessment of damage risk. Accurate estimates of the start and length of growing season are also crucial. We find that temperature and its derivative vapor pressure deficit are likely the most important climate variables while the variability of ozone concentration within climatologically reasonable limits plays a minor role. The use of subarctic parameterization suggests an improvement in risk assessment as POD values are increased in 2018; corroborated by evidence of visible injury in the Svanhovd ozone garden.

• Bryn, Anders; Dalen, Thea Grobstok; Finne, Eirik Aasmo; Heiberg, Hanne; Nilsen, Irene Brox & Parmentier, Frans-Jan W. [Show all 22 contributors for this article] (2020). Natur i endring - en vandreutstilling. Full text in Research Archive
• Vollsnes, Ane Victoria; Falk, Stefanie; Eriksen, Aud Berglen; Kapperud, Åshild Fandango; Kauserud, Håvard & Stordal, Frode [Show all 7 contributors for this article] (2020). Responses to experimental ozone exposure in some native plant species from Northern Scandinavia. Full text in Research Archive
• Falk, Stefanie; Vollsnes, Ane Victoria; Stordal, Frode; Eriksen, Aud Else Berglen & Berntsen, Terje Koren (2020). Surface Ozone in Northern Scandinavia and Implications on Local Vegetation - A Case Study. Full text in Research Archive Show summary

  The Arctic biosphere is subject to comprehensive changes induced by climate change. The highly specialized subartic vegetation will be challenged by both, changing environmental conditions as well as further interference through human activity. Permission of exploitation of natural resources in the Artic is likely to increase the levels of air pollutants which are precursors to ozone. n the course of our project (OzoNorClim: The Double Punch), we had an ozone monitor installed at the Norwegian Institute for Bioeconomic Research (NIBIO) Svanhovd Research Station operated by the Norwegian Institute for Air Research (NILU). In 2018, a long-lasting heatwave accompanied by extensive forest fires across Europe and Scandinavia enhanced surface ozone concentrations by about 2 ppt above the climatological mean in Northern Scandinavia. Ozone sensitive glover species in the ozone garden at Svanhovd showed clear signs of ozone damage in 2018 but not in 2019. We study these two years as example for probable future scenarios in which both heat stress and ozone stress affect vegetation negatively. We look at the corresponding surface ozone concentrations, accumulated ozone dose, and implications on natural and semi-natural vegetation especially in the Pasvik valley in Northern Norway, put these in a larger regional context, and give an outlook on further modelling work.

• Vollsnes, Ane Victoria; Falk, Stefanie; Eriksen, Aud Else Berglen; Stordal, Frode; Kauserud, Håvard & Berntsen, Terje Koren [Show all 9 contributors for this article] (2020). The double punch: ozone and climate stresses on vegetation. Full text in Research Archive
• Byre, Hanne Eline; Falk, Stefanie; Stordal, Frode & Berntsen, Terje Koren (2019). An Investigation of Source Regions Contributing to the Deposition of Reactive Nitrogen in Arctic and Boreal Areas. Full text in Research Archive Show summary

  Long range atmospheric transport is an important source of reactive nitrogen (Nr) to Boreal and Artic ecosystems. The combined effect of climate change and deposition of reactive nitrogen which is an important nutriant for these systems, have the potential to change the carbon storage in high latitude reservoirs. Furthermore a change in vegetation, will lead to changes in the exchange of energy and humidity between the land surface and the atmosphere. We have conducted several model studies to investigate and quantify the importance and contribution of distinguished source regions to Nr deposition in polar and sub-polar regions in the northern hemisphere. Using a global chemistry transport model, we will assess the following questions: To what extent are emissions from agriculture in South-Asia affecting NOx deposition in the Arctic? What would happen if we shut down the automotive sector in Germany, do we see a reduction in the amount of NOx deposited in Norway?

• Vollsnes, Ane Victoria; Eriksen, Aud Berglen; Berntsen, Terje Koren; Kauserud, Håvard; Büker, Patrick & Emberson, Lisa D. [Show all 7 contributors for this article] (2018). The double punch: ozone and climate stresses to sub-Arctic vegetation. Full text in Research Archive
• Vollsnes, Ane Victoria; Eriksen, Aud Berglen; Falk, Stefanie; Berntsen, Terje Koren; Kauserud, Håvard & Emberson, Lisa D. [Show all 7 contributors for this article] (2018). Project The double punch: ozone and climate stresses on vegetation. Full text in Research Archive
• Stordal, Frode; Berntsen, Terje Koren; Büker, Patrick; Falk, Stefanie; Rydsaa, Johanne Hope & Gillies, David [Show all 7 contributors for this article] (2018). Ozone and climate stresses on sub-ARctic tundra vegetation: Modelling of stomatal fluxes in midnight sun. Full text in Research Archive
• Bryn, Anders; Stordal, Frode; Berntsen, Terje Koren & Tang, Hui (2017). Vegetation dynamics - distribution, modelling and feedbacks. Full text in Research Archive
• Tang, Hui; Stordal, Frode; Berntsen, Terje Koren & Bryn, Anders (2017). Improve dynamic vegetation model of community land model in simulating Arctic vegetation and its interaction with climate. Full text in Research Archive
• Bryn, Anders; Potthoff, Kerstin; Horvath, Peter; Volden, Inger Kristine; Tang, Hui & Berntsen, Terje Koren [Show all 7 contributors for this article] (2017). Greening and browning: 100 years of tree- and forest line dynamics. Full text in Research Archive
• Aas, Kjetil Schanke; Westermann, Sebastian; Martin, Leo Celestin Paul & Berntsen, Terje Koren (2017). Degrading Palsa Mires in Northern Norway Simulated with a Regional Climate Model with a Subgrid Snow Scheme. Full text in Research Archive
• Stordal, Frode; Tang, Hui; Berntsen, Terje Koren; Büker, Patrick; Vollsnes, Ane Victoria & Eriksen, Aud Berglen [Show all 7 contributors for this article] (2017). Modelling combined effects of ozone and climate stresses on Arctic and boreal species. Full text in Research Archive
• Jeanette, Viken; Vollsnes, Ane Victoria; Eriksen, Aud Else Berglen; Berntsen, Terje Koren & Stordal, Frode (2017). DO3SEiNORD. Full text in Research Archive
• Lund, Marianne Tronstad; Berntsen, Terje Koren & Fuglestvedt, Jan S. (2017). Climate response to ozone perturbations at different altitudes and latitudes. Full text in Research Archive
• Tang, Hui; Stordal, Frode; Berntsen, Terje Koren & Bryn, Anders (2016). Dynamical vegetation-atmosphere modelling of the boreal zone. Full text in Research Archive
• Shetty, Shobitha; Schneider, Philipp; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve & Berntsen, Terje Koren (2025). Synergy of Earth Observation and Machine Learning for Air Quality Monitoring in Europe. Universitetet i Oslo. Full text in Research Archive Show summary

  Air pollution is a major environmental and public health challenge, particularly in urban areas where nitrogen dioxide (NO2) and fine particulate matter (PM2.5) contribute significantly to adverse health effects. Accurate, high-resolution estimates of surface air pollution are essential for exposure assessments and relevant policy interventions. While regulatory air quality monitoring networks provide reliable measurements, their spatial coverage and density is limited, necessitating alternative data sources such as satellite retrievals, chemical transport models (CTMs), and low-cost sensors (LCS). However, these sources have inherent limitations in terms of spatial resolution, columnar measurements, data quality, and computational constraints when used individually. This thesis develops a synergistic approach under the “Satellite and Machine Learning (ML)-based Estimation of Surface air quality at High resolution” (S-MESH) framework, applying machine learning to integrate multiple data sources for improved NO2 and PM2.5 surface estimations across Europe at both urban and continental scales. For NO2, the thesis explores the fusion of satellite observations, range of reanalysis meteorological variables, and ground-based measurements to generate daily 1 km resolution surface NO2 estimates over Europe, for the periods 2019-2021. Key satellite-derived inputs include tropospheric vertical column density (VCD) of NO2 from Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI), nightlight radiance from the Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, and vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS), while meteorological variables are obtained from ERA5 and ERA5-Land. In addition, NO2 observations from reference-grade air quality monitoring stations serve as the ground-truth data for model training and evaluation. The ML modeling is conducted using an eXtreme Gradient Boosting (XGBoost) model within the S-MESH framework. The model achieves a median bias of 6%, with the most reliable NO2 predictions in the medium pollution range (10-40 μg/m3). A comprehensive Shapley Additive exPlanations (SHAP) analysis reveals the strong influence of TROPOMI NO2 column and VIIRS nightlight data in capturing both the spatial and temporal pollution variations, while also quantifying their impact on model uncertainty. The findings highlight the critical role of TROPOMI NO2 in high-resolution surface air quality mapping and in unexpected events, particularly when complemented by ground-based and ancillary datasets. For PM2.5, the thesis investigates the downscaling of the Copernicus Atmosphere Monitoring Service (CAMS) regional (0.1×0.1 resolution) forecasts to 1 km resolution hindcasts through a synergy with satellite aerosol optical depth (AOD), meteorological data, and other variables. PM2.5 is estimated over the period 2021-2022 as daily means, which makes it relevant within the EU’s monitoring and regulatory framework. Unlike for the NO2 model, where TROPOMI NO2 tropospheric VCD was by far the most important predictor variable, satellite-based AOD exhibits lower predictive importance but remains essential for capturing episodic events such as dust transport. This downscaling approach improves CAMS forecast-based estimates, particularly over Poland and Eastern Europe. In these regions, it effectively corrects the known underestimations of winter months from the CAMS European interim reanalysis. For concentrations exceeding 20 μg/m³, S-MESH outperforms the interim reanalysis, achieving a lower median bias (-7.3 μg/m3 vs -10.3 μg/m3 for the reanalysis) while effectively capturing high pollution events with improved spatial and temporal accuracy. These findings demonstrate S-MESH’s utility as a timely alternative to the CAMS interim reanalysis, which otherwise becomes available with a significant delay of up to 15 months. A key innovation in this study is the use of stacked XGBoost models, which enable spatially continuous PM2.5 predictions even in the presence of satellite AOD retrieval spatiotemporal gaps. The third component of this thesis evaluates the possible role of low(er) cost sensor data particularly from citizen science initiatives for PM2.5 estimation, focusing on Central Europe, where LCS networks are densest. Two integration strategies are studied: (i) training an ML model with LCS as a substitute for regulatory stations (LCST model), and (ii) incorporating LCS data as an additional feature via a convolutional layer approach (LCSI model). These are compared against a Baseline model trained without LCS data. Results show that the convolution-based LCSI model achieves the highest accuracy, outperforming the Baseline model, particularly in urban areas where LCS density is highest. The Baseline model, while not as locally accurate, demonstrates strong generalization across diverse settings. In contrast, the LCST model tends to underestimate absolute concentration but captures temporal pollution dynamics effectively at daily mean scales. The inclusion of LCS data as an input feature plays a crucial role in resolving small-scale and localized variations of PM2.5 that are often missed by satellites or coarser models. With advancements in sensor technology and growing adoption of LCS for PM2.5 monitoring, these networks provide increasingly dense observations that can further complement traditional monitoring approaches. This thesis highlights the added value of multi-source synergies in ML-based monitoring of air pollution. By systematically exploring data fusion methodologies and integration strategies, it demonstrates the computational efficiency and scalability of ML-based approaches, particularly the suitability of XGBoost for large-scale applications. The findings provide new insights into the spatial representativity and applicability of diverse data sources for air quality assessment, supporting the development of enhanced monitoring strategies and data-driven policy frameworks across Europe and beyond.

• Aamaas, Borgar & Berntsen, Terje Koren (2021). Metodikk for framstilling av klimaeffekt på kort og lang sikt. CICERO Senter for Klimaforskning. Full text in Research Archive Show summary

  CICERO Senter for klimaforskning har på oppdrag fra Miljødirektoratet utviklet og illustrert metodikk for framstilling av klimaeffekt på kort og lang sikt. Vi har vurdert klimaeffekt på to forskjellige måter, med vektfaktorer og med en veldig enkel klimamodell for å estimere temperaturbaner av utslippsbaner og utslippstiltak. Analysen bygger på tidligere arbeid CICERO har gjort for Miljødirektoratet. Mandatet CICERO fikk var analysearbeid på disse fire temaene: 1) Vurdering av behovet for å oppdatere GTP(10)-faktoren Miljødirektoratet i dag benytter. 2) Beregne norske utslipp med GTP(10), AGTP, GWP* og eventuelt andre vektfaktorer for ulike tidshorisonter. 3) Metodikk for framstilling av klimaeffekt på kort og lang sikt av ulike utslipp/utslippsreduksjoner i samme figur. 4) Metodikk for kostnadsberegninger.

• Aamaas, Borgar & Berntsen, Terje Koren (2019). Vurdering av ulike vektfaktorer. CICERO. Full text in Research Archive
• Lund, Marianne Tronstad; Aamaas, Borgar; Berntsen, Terje Koren & Fuglestvedt, Jan S. (2016). Luftfart og klima - En oppdatert oversikt over status for forskning på klimaeffekter av utslipp fra fly. CICERO Senter for Klimaforskning. Full text in Research Archive Show summary

  Denne rapporten gir en oppdatert oversikt over hvordan og i hvilken grad de ulike utslippene fra flytrafikk påvirker klima basert på den nyeste forskningen. For å forstå den totale klimaeffekten av luftfart er det viktig å inkludere alle mekanismene som bidrar til klimapåvirkning, samt hvordan disse kan vektes og sammenlignes på tvers av ulike skalaer i tid og rom. Dette er hovedfokus i denne rapporten. Rapporten er en oppdatering av Lund m.fl. (2011) og fokuserer på forskningsresultater siden da. Arbeidet er finansiert av Avinor

• Aamaas, Borgar; Hodnebrog, Øivind; Samset, Bjørn Hallvard; Fuglestvedt, Jan S.; Myhre, Gunnar & Berntsen, Terje Koren (2015). Oppdaterte vektfaktorer for BC og OC. CICERO. Full text in Research Archive

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