Lena Merete Tallaksen

• Biagio, Amanda Johansen Di; Oen, Amy M P; Tallaksen, Lena M. & Capobianco, Vittoria (2026). Introducing a methodology to quantify the hydro-mechanical protective effects of forests on slope stability: application to a deciduous forest in Western Norway. CATENA. ISSN 0341-8162. 270. doi: 10.1016/j.catena.2026.110176. Full text in Research Archive Show summary

  Trees enhance slope stability through hydrological and mechanical processes, reducing the likelihood of shallow landslides. In this study, a methodology for quantifying the hydro-mechanical effects of forests on slope stability is developed and applied to a deciduous forest in Western Norway. The approach uses an infinite slope stability model for unsaturated conditions to estimate the factor of safety (), incorporating forest effects through suction stress and basal root cohesion. The “Forest Factor” () is introduced as the ratio between the minimum inside and outside a forest after a precipitation event, and its lower quartile () across all events is proposed as a design value for protection forest management. For the Norwegian case, hydrological data from May 2023 to September 2025 from a forest and a neighbouring hayfield, along with previously published estimations of root cohesion are used as inputs to the methodology. The resulting ranged between 1.18 and 2.27, depending on season and soil depth. The hydrological reinforcement effects of the forest were strongest in summer but present year-round, and generally exceeding the mechanical root reinforcement. Analysis of selected precipitation events highlights the importance of antecedent hydraulic conditions in soil response to rainfall. These results emphasize the need to account for both hydrological and mechanical vegetation effects in landslide risk assessments. The methodology application represents the first attempt to quantify the hydro-mechanical effects of forests based on long-term monitoring in Scandinavia, and the estimated provide practical guidance for managing and planning protection forests in similar geo-climatological settings.

• Biagio, Amanda Johansen Di; Schwarz, Massimiliano; Borrajo-Pelaez, Rafael; Ngo, Ha My; Cohen, Denis & Oen, Amy M P [Show all 8 contributors for this article] (2026). Quantifying the spatio-temporal mechanical root reinforcement of the pioneer species Betula pendula: experimental investigations and modelling for a case study in Western Norway. Ecological Engineering: The Journal of Ecotechnology. ISSN 0925-8574. 228. doi: 10.1016/j.ecoleng.2026.107984. Full text in Research Archive
• Hassanyar, Mohammad Hassan; Gelati, Emiliano & Tallaksen, Lena Merete (2025). Farmer perception of climate change and adaptation strategies in Bamyan province, Afghanistan. Mitigation and Adaptation Strategies for Global Change. ISSN 1381-2386. 30(8). doi: 10.1007/s11027-025-10255-4. Full text in Research Archive Show summary

  Agriculture is the most important economic sector in Afghanistan. Most people rely on agriculture and livestock for their livelihoods. This study aimed to investigate perception of climate change, its impacts and adaptation measures taken by households in their farming activities. A structured questionnaire was used to collect data from 194 farmers in four districts of Bamyan Province, Afghanistan, during the years 2016–2017. The province is located in the central highland of Afghanistan where farmers practice a traditional agriculture adapted to a climate with cold winters and dry summers. A binary logistic regression model was used to assess correlations between socio-demographic factors (age, education, family size, land size and income) and farmer decisions to adapt farming practices. Findings revealed that over 70% of households perceived an increase in air temperature and a decrease in precipitation, subsequently leading to drought and reduced crop yield. Further, the survey showed that farmers utilised several adaptation strategies to minimise the negative impacts of climate change on their farming. Still, adverse climatic conditions forced some families to sell their livestock and take loans. The analysis showed that family size was the most influential factor significantly and favourably influencing farmers’ decision to implement adaptation strategies, including planting early maturing crops, new varieties, water conservation, irrigation canal improvement and selling livestock. Education level, land size and income were factors affecting the farmers’ decision to advance the sowing date, whereas family size, land size and income all affected the introduction of water conservation measures. On the other hand, poverty and lack of official guidance and support were key constraints limiting the ability to implement coping strategies. Therefore, it is key that the government addresses these challenges in agriculture and help farmers increase their resilience toward climate change.

• Biagio, Amanda Johansen Di; Oen, Amy M P; Capobianco, Vittoria & Tallaksen, Lena M. (2025). Navigating Divergent Perspectives: Assessing Landslide Risk Perception In Western Norway. In Liu, Zhongqiang; Dai, Jian & Robinson, Kate (Ed.), Proceedings of the 9th International Symposium for Geotechnical Safety and Risk (ISGSR). Research Publishing Services. ISSN 9789819440757. p. 516–520. doi: 10.3850/GRF-25280825_isgsr-110-P044-cd. Full text in Research Archive Show summary

  The subjective perception of landslide risk among the local population can deviate from scientifically assessed risk maps, as it is often shaped by personal experience, cultural beliefs, and immediate concerns. In this study, we explore the perception of landslide risk among different groups, consisting of inhabitants from three landslideprone villages located in Aurland municipality in western Norway. The goal is to provide a basis for developing risk management strategies aligned with local priorities. Based on preliminary scoping activities in the area and the outcomes of two engagement workshops in one of the villages,a survey was sent out to the inhabitants in allthree villages to systematically collect relevant risk perception data. The main outcome of this study is that most of the respondents are quite concerned about landslides; however, reducing the current landslide risk is not highly prioritized.

• Bekken, Michael Andrew; Vatne, Astrid; Larsen, Poul; Ibrom, Andreas; Larsen, Klaus Steenberg & Elberling, Bo [Show all 14 contributors for this article] (2025). Carbon dynamics of a controlled peatland rewetting experiment in the Norwegian boreal zone. Scientific Reports. 16(1). doi: 10.1038/s41598-025-30836-2. Full text in Research Archive Show summary

  A controlled peatland rewetting experiment was conducted on two adjacent drained peatland sites in southeastern Norway. Eddy covariance monitoring of CO 2 and CH 4 fluxes at both sites began in 2019. In 2021, the Treatment Site was rewetted while the Control Site remained drained. Using nine environmental variables and the processed flux data as training data, Bayesian Additive Regression Tree (BART) models were used to generate annual flux balances for CO 2 and CH 4 . The 4-year mean annual flux at the Control Site was 17.3 ± 10 g CO 2 -C m − 2 yr − 1 and 4.6 ± 0.1 g CH 4 -C m − 2 yr − 1 . At the Treatment Site, the 2-year mean annual flux before the rewetting was 12.2  ±  3.8 g CO 2 -C m − 2 yr − 1 and 1.8  ±  0.04 g CH 4 -C m − 2 yr − 1 . In the first year after rewetting the annual flux was 53.3  ±  13 g CO 2 -C m − 2 yr − 1 and 3.8  ±  0.3 g CH 4 -C m − 2 yr − 1 , and in the second year after rewetting the annual flux was 41.2  ±  18 g CO 2 -C m − 2 yr − 1 and 3.4  ±  0.4 g CH 4 -C m − 2 yr − 1 . BART counterfactual modeling was able to estimate the effect of the rewetting on CO 2 and CH 4 fluxes. Two years after the rewetting, the BART counterfactual modeling estimated that the cumulative fluxes had increased by 80.3 ± 49 g CO 2 -C m − 2 and 3.4 ± 0.47 g CH 4 -C m − 2 because of the rewetting. Carbon flux monitoring of both sites is ongoing as the Control Site remains drained and the soil and vegetation at the Treatment Site continues to adjust to the altered hydrological regime after rewetting.

• Biagio, Amanda Johansen Di; Capobianco, Vittoria; Oen, Amy M P & Tallaksen, Lena M. (2025). Hydro-mechanical effects of deciduous forest on slope stability: first results from a case study in Western Norway. E3S Web of Conferences. 642. doi: 10.1051/e3sconf/202564201011. Full text in Research Archive Show summary

  The use of vegetation as a nature-based solution for shallow landslide risk reduction is receiving increased attention in the scientific community, as plants can provide hydro-mechanical reinforcement of slopes. Although numerous studies on this topic are well-documented in the literature, the hydro-mechanical effects of vegetation on partially saturated slopes under Nordic conditions remain unexplored. In this study, the first results from a newly established case study site located in Western Norway are presented. The study site is situated on a natural slope partially used as hayfield and partially covered by deciduous forest. The study includes an assessment of both the hydrological and mechanical reinforcement effects of the forest, as compared with the control scenario represented by the hayfield. Reinforcement effects analysed include changes in soil suction and volumetric water content induced by the forest and mechanical root reinforcement acting on the basal plane of a potential slip surface. The preliminary results show that the deciduous forest significantly contribute to slope stability through both hydrological and mechanical reinforcement. Despite the short monitoring period, these results provide valuable insights into the role of deciduous forest in mitigating shallow landslides in Western Norway.

• Nkhoma, Lusungu; Gelati, Emiliano; Xu, Chong-Yu & Tallaksen, Lena M. (2025). Evaluation of the performance of high-resolution global climate datasets over Malawi. Physics and Chemistry of the Earth. ISSN 1474-7065. 142. doi: 10.1016/j.pce.2025.104221. Full text in Research Archive
• Finne, Eirik Aasmo; Bjerke, Jarle W.; Stordal, Frode & Tallaksen, Lena M. (2025). Lichens are more tolerant against winter warming stress than vascular and non-vascular plants: Insights from an alpine field experiment. Journal of Ecology. ISSN 0022-0477. 113(3), p. 518–530. doi: 10.1111/1365-2745.14482. Full text in Research Archive Show summary

  Extreme weather events influence carbon cycling and lead to pervasive changes in ecosystem structure and function. Vegetation at high latitudes and in alpine bioclimatic zones can be particularly sensitive to winter warming events, which are short-lived climatic events where temperatures are unusually high and often include rainfall. With climate change the frequency and severity of winter warming events are increasing. We report here from a field experiment on a lichen-dominated ridge at a high mountain plateau in central Norway. This is a common vegetation type at high latitudes and altitudes, yet little is known about ecophysiological responses to winter warming events in lichens, and how it may differ from responses in bryophytes and vascular plants. We ran a week-long simulation of vegetation stress from winter warming events through thaw–freeze and ice encasement, during late winter in 2021 and 2022. The thaw–freeze treatment had minor effects on summer ecophysiology in lichens (Cladonia mitis, Cetraria islandica and Nephromopsis nivalis), while the species N. nivalis and to a lesser extent, C. mitis had reduced vitality after the ice encasement treatment. Contrastingly, the bryophyte Polytrichum juniperinum, and vascular plant Empetrum nigrum had reduced photosynthetic efficiency and seasonal growth in both thaw–freeze and ice encasement treatments. The ice encasement treatment was overall more lethal and led to reduced NDVI (Normalised Difference Vegetation Index). However, reduction in vitality of vascular and non-vascular plants was not enough to impact overall ecosystem carbon flux. Synthesis: The lichen's stronger tolerance against thaw–freeze and ice encasement than co-existing plants oppose the general effects of summer climate warming, where lichens may succumb under greater plant-growth and warmer soils. This study advocates for the importance of year-round ecology to understand vegetation change under climate change.

• Biagio, Amanda Johansen Di; Capobianco, Vittoria; Oen, Amy M P & Tallaksen, Lena M. (2024). State-of-the-art: parametrization of hydrological and mechanical reinforcement effects of vegetation in slope stability models for shallow landslides. Landslides. Journal of the International Consortium on Landslides. ISSN 1612-510X. 21, p. 2417–2446. doi: 10.1007/s10346-024-02300-1. Full text in Research Archive Show summary

  The use of vegetation as a Nature-based Solution (NbS) for shallow landslide risk reduction is receiving increased attention in the scientific community. Vegetation can contribute to slope stability through both hydrological and mechanical processes. Slope stability models are valuable tools to quantify the performance of vegetation management as a slope stabilizing measure. The aim of this study is to provide a comprehensive overview of how both the mechanical and hydrological effects of vegetation are parametrized in existing slope stability models. To this end, a systematic review of the peer-reviewed literature published between January 2000 and June 2023 is conducted. The review has shown that existing slope stability models that include effects of vegetation, do so with various degrees of complexity with regard to how accurately they attempt to mimic the physical processes present in nature. There is a need for further validation of existing models, especially extended to areas in the global south and in colder regions. Moreover, studies of time dependency in vegetation reinforcement capabilities are lacking, an aspect which is especially important in the light of climate change. This review provides valuable guidance for researchers and practitioners in their choice of appropriate slope stability models for their studies.

• Biagio, Amanda Johansen Di; Capobianco, Vittoria; Oen, Amy M P & Tallaksen, Lena Merete (2024). Monitoring the hydro-mechanical effects of vegetation cover on shallow landslide triggering: Preliminary results from a case study in western Norway. In Guerra, Nuno; Fernandes, Manuel Matos; Ferreira, Cristiana; Correia, Antonio Gomes; Pinto, Alexandre & Pinto, Pedro Seco e (Ed.), Proceedings of the XVIII ECSMGE 2024 - Geotechnical Engineering Challenges to Meet Current and Emerging Needs of Society. CRC Press. ISSN 9781003431749. p. 1090–1093. doi: 10.1201/9781003431749-192. Full text in Research Archive Show summary

  Rainfall-induced shallow landslides are amongst the most common gravitational mass movements on slopes in steep terrain. The use of vegetation as a nature-based solution for shallow landslide risk reduction is receiving increased attention in the scientific community. Until now, no studies on the effects of vegetation on slope stability have been conducted for Nordic conditions. Additionally, direct comparison between the hydrological conditions in a forest and a neighbouring open field has never previously been carried out in this region. To contribute to filling this knowledge gap, a monitoring program is installed, and field investigations are conducted in a natural slope in the Flåm valley, located in western Norway. The case study site is situated on a slope partially used as hayfield, and partially covered by deciduous forest. Both the hayfield and the forest are assessed to compare the effects of the presence of vegetation on slope stability. Herein, preliminary results are presented. A detailed analysis of the monitored variables and the laboratory test results must be carried out before to conclude on the effectiveness of the existing forest as a shallow landslide mitigation measure at the case study site.

• Keetz, Lasse Torben; Lieungh, Eva; Karimi-Asli, Kaveh; Geange, Sonya Rita; Gelati, Emiliano & Tang, Hui [Show all 24 contributors for this article] (2023). Climate–ecosystem modelling made easy: The Land Sites Platform. Global Change Biology. ISSN 1354-1013. 29(15), p. 4440–4452. doi: 10.1111/gcb.16808. Full text in Research Archive Show summary

  Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.

• Finne, Eirik Aasmo; Bjerke, Jarle W.; Erlandsson, Rasmus; Tømmervik, Hans; Stordal, Frode & Tallaksen, Lena M. (2023). Variation in albedo and other vegetation characteristics in non-forested northern ecosystems: the role of lichens and mosses. Environmental Research Letters. 18(7). doi: 10.1088/1748-9326/ace06d. Full text in Research Archive Show summary

  Vegetation has a profound impact on climate through complex interactions and feedback loops, where especially regulation of albedo, the ratio of reflected to incoming solar radiation, is important at high latitudes. How vegetation albedo varies along environmental gradients in tundra ecosystems is still not well understood, particularly for ecosystems dominated by nonvascular vegetation. We studied broadband shortwave albedo of open boreal, arctic, and alpine ecosystems over a 2000 km long latitudinal gradient (60◦ N–79◦ N) and contrasted this against species composition, vegetation greenness (normalised difference vegetation index—NDVI), momentary ecosystem CO2 fluxes and reindeer (Rangifer tarandus) grazing pressure. High cover of pale terricolous fruticose lichens was the single most important predictor for vegetation albedo, which had a maximum value of 0.389 under clear sky conditions and solar zenith angle 60◦. To our knowledge, this is the highest broadband albedo recorded for a vegetated surface. NDVI was negatively correlated to lichen biomass (rs = −0.56), and albedo (rs = −0.19). Gross primary production and ecosystem respiration varied considerably less between plots and vegetation types than albedo. While it is well-known that Rangifer affects climate-relevant aboveground biomass, we here show that its regulation of surface albedo in northern ecosystems may also be of high importance for land-atmosphere interactions. The data presented here thus advocate for an increased understanding of the important and complex role of herbivores and lichen cover in climate-vegetation interactions.

• Bakke, Sigrid Jørgensen; Ionita, Monica & Tallaksen, Lena M. (2023). Recent European drying and its link to prevailing large-scale atmospheric patterns. Scientific Reports. 13. doi: 10.1038/s41598-023-48861-4. Full text in Research Archive Show summary

  Abstract The extreme 2018 and 2022 droughts pose as recent examples of a series of drought events that have hit Europe over the last decades with wide ranging social, environmental and economic impacts. Although the link between atmospheric circulation and meteorological drought is clear and often highlighted during major drought events, there is a lack of in-depth studies linking historical changes in meteorological drought indices and prevailing large-scale atmospheric patterns in Europe. To meet this shortfall, we investigated the relation between changes in large-scale atmospheric patterns and meteorological drought, as indicated by the geopotential height at 500mb (Z500) and the Standardised Precipitation-Evapotranspiration Index (SPEI), respectively. Calculations were done separately for four climate regions (North, West, Central-East and Mediterranean) over the growing season (March–September). Coherent patterns of significant changes towards higher pressure (increasing Z500) and drier conditions (decreasing SPEI) over 1979–2021 are found over West in spring and Central-East in summer. Z500 and SPEI are strongly linked, reflected by both significant (1979–2021) correlations and high co-occurrences (69-96%) between meteorological drought and high-pressure anomaly occurrences since 1900. North shows the most heterogeneous trend patterns and weakest links, but constitutes a hotspot of significantly increasing Z500 in September. Finally, we performed an ensemble-based, European wide analysis of future Z500, based on CMIP6 low-end (SSP126) and high-end (SSP585) 21st century emission scenarios. According to the projected changes, anomalously high-pressure systems will be the new normal regardless of scenario, and well exceeding the 2018 and 2022 levels in the case of the high-end emission scenario. However, due to the limitations of the model ensemble to represent the spatial heterogeneity in historical Z500 variability and trends (1979–2014), projected changes in large-scale circulation, and associated meteorological droughts, are highly uncertain. This paper provides new insight into significant trends in atmospheric circulation over Europe, their strong links to the observed drying trends, and the inability of a CMIP6 ensemble to reproduce the spatial heterogeneity of the circulation changes.

• Bakke, Sigrid Jørgensen; Wanders, Niko; Wiel, Karin Van Der & Tallaksen, Lena M. (2023). A data-driven model for Fennoscandian wildfire danger. Natural Hazards and Earth System Sciences. ISSN 1561-8633. 23(1), p. 65–89. doi: 10.5194/nhess-23-65-2023. Full text in Research Archive Show summary

  Wildfires are recurrent natural hazards that affect terrestrial ecosystems, the carbon cycle, climate and society. They are typically hard to predict, as their exact location and occurrence are driven by a variety of factors. Identifying a selection of dominant controls can ultimately improve predictions and projections of wildfires in both the current and a future climate. Data-driven models are suitable for identification of dominant factors of complex and partly unknown processes and can both help improve process-based models and work as independent models. In this study, we applied a data-driven machine learning approach to identify dominant hydrometeorological factors determining fire occurrence over Fennoscandia and produced spatiotemporally resolved fire danger probability maps. A random forest learner was applied to predict fire danger probabilities over space and time, using a monthly (2001–2019) satellite-based fire occurrence dataset at a 0.25∘ spatial grid as the target variable. The final data-driven model slightly outperformed the established Canadian Forest Fire Weather Index (FWI) used for comparison. Half of the 30 potential predictors included in the study were automatically selected for the model. Shallow volumetric soil water anomaly stood out as the dominant predictor, followed by predictors related to temperature and deep volumetric soil water. Using a local fire occurrence record for Norway as target data in a separate analysis, the test set performance increased considerably. This demonstrates the potential of developing reliable data-driven models for regions with a high-quality fire occurrence record and the limitation of using satellite-based fire occurrence data in regions subject to small fires not identified by satellites. We conclude that data-driven fire danger probability models are promising, both as a tool to identify the dominant predictors and for fire danger probability mapping. The derived relationships between wildfires and the selected predictors can further be used to assess potential changes in fire danger probability under different (future) climate scenarios.

• 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.

• Blauhut, Veit; Stoelzle, Michael; Ahopelto, Lauri; Brunner, Manuela I.; Teutschbein, Claudia & Wendt, Doris E. [Show all 45 contributors for this article] (2022). Lessons from the 2018-2019 European droughts: a collective need for unifying drought risk management. Natural Hazards and Earth System Sciences. ISSN 1561-8633. 22(6), p. 2201–2217. doi: 10.5194/nhess-22-2201-2022. Full text in Research Archive Show summary

  Abstract. Drought events and their impacts vary spatially and temporally due to diverse pedo-climatic and hydrologic conditions, as well as variations in exposure and vulnerability, such as demographics and response actions. While hazard severity and frequency of past drought events have been studied in detail, little is known about the effect of drought management strategies on the actual impacts and how the hazard is perceived by relevant stakeholders. In a continental study, we characterised and assessed the impacts and the perceptions of two recent drought events (2018 and 2019) in Europe and examined the relationship between management strategies and drought perception, hazard, and impact. The study was based on a pan-European survey involving national representatives from 28 countries and relevant stakeholders responding to a standard questionnaire. The survey focused on collecting information on stakeholders' perceptions of drought, impacts on water resources and beyond, water availability, and current drought management strategies on national and regional scales. The survey results were compared with the actual drought hazard information registered by the European Drought Observatory (EDO) for 2018 and 2019. The results highlighted high diversity in drought perception across different countries and in values of the implemented drought management strategies to alleviate impacts by increasing national and sub-national awareness and resilience. The study identifies an urgent need to further reduce drought impacts by constructing and implementing a European macro-level drought governance approach, such as a directive, which would strengthen national drought management and mitigate damage to human and natural assets.

• Pirk, Norbert; Aalstad, Kristoffer; Westermann, Sebastian; Vatne, Astrid; Hove, Alouette van & Tallaksen, Lena Merete [Show all 8 contributors for this article] (2022). Inferring surface energy fluxes using drone data assimilation in large eddy simulations. Atmospheric Measurement Techniques. ISSN 1867-1381. 15(24), p. 7293–7314. doi: 10.5194/amt-15-7293-2022. Full text in Research Archive Show summary

  Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.

• Marttila, Hannu; Laudon, Hjalmar; Tallaksen, Lena M.; Jaramillo, Fernando; Alfredsen, Knut & Ronkanen, Anna-Kaisa [Show all 14 contributors for this article] (2022). Nordic hydrological frontier in the 21st century. Hydrology Research. ISSN 1998-9563. 53(5), p. 700–715. doi: 10.2166/nh.2022.120. Full text in Research Archive Show summary

  The 21st century has brought new challenges and opportunities and has also increased demands on the Nordic hydrological community. Our hydrological science focus and approaches need rethinking and adaptation to the changing requirements of society in response to climate change and human interventions, in search of more comprehensive and cross-disciplinary solutions. This commentary highlights new possibilities and suggests vital steps forward for the scientific discipline within Nordic hydrological research. By providing a common direction, we hope to increase awareness, accelerate progress in the hydrological community, and emphasize the importance of hydrological knowledge for serving other fields of science and society at large. We hope that our vision and the opportunities we identify will raise awareness of the scientific discipline and assist in the long-term development of the Nordic hydrological frontier in the 21st century.

• 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.

• Brunner, Manuela I; Slater, Louise; Tallaksen, Lena M. & Clark, Martyn (2021). Challenges in modeling and predicting floods and droughts: A review. WIREs Water. 8(3). doi: 10.1002/wat2.1520. Full text in Research Archive Show summary

  Predictions of floods, droughts, and fast drought-flood transitions are required at different time scales to develop management strategies targeted at minimizing negative societal and economic impacts. Forecasts at daily and seasonal scale are vital for early warning, estimation of event frequency for hydraulic design, and long-term projections for developing adaptation strategies to future conditions. All three types of predictions—forecasts, frequency estimates, and projections—typically treat droughts and floods independently, even though both types of extremes can be studied using related approaches and have similar challenges. In this review, we (a) identify challenges common to drought and flood prediction and their joint assessment and (b) discuss tractable approaches to tackle these challenges. We group challenges related to flood and drought prediction into four interrelated categories: data, process understanding, modeling and prediction, and human–water interactions. Data-related challenges include data availability and event definition. Process-related challenges include the multivariate and spatial characteristics of extremes, non-stationarities, and future changes in extremes. Modeling challenges arise in frequency analysis, stochastic, hydrological, earth system, and hydraulic modeling. Challenges with respect to human–water interactions lie in establishing links to impacts, representing human–water interactions, and science communication. We discuss potential ways of tackling these challenges including exploiting new data sources, studying droughts and floods in a joint framework, studying societal influences and compounding drivers, developing continuous stochastic models or non-stationary models, and obtaining stakeholder feedback. Tackling one or several of these challenges will improve flood and drought predictions and help to minimize the negative impacts of extreme events.

• Erlandsen, Helene Birkelund; Beldring, Stein; Eisner, Stephanie; Hisdal, Hege; Huang, Shaochun & Tallaksen, Lena Merete (2021). Constraining the HBV model for robust water balance assessments in a cold climate. Nordic Hydrology. ISSN 0029-1277. 52(2), p. 356–372. doi: 10.2166/nh.2021.132. Full text in Research Archive Show summary

  Robust projections of changes in the hydrological cycle in a non-stationary climate rely on trustworthy estimates of the water balance elements. Additional drivers than precipitation and temperature, namely wind, radiation, and humidity are known to have a significant influence on processes such as evaporation, snow accumulation, and snow-melt. A gridded version of the rainfall-runoff HBV model is run at a 1 × 1 km scale for mainland Norway for the period 1980–2014, with the following alterations: (i) the implementation of a physically based evaporation scheme; (ii) a net radiation-restricted degree-day factor for snow-melt, and (iii) a diagnostic precipitation phase threshold based on temperature and humidity. The combination of improved forcing data and model alterations allowed for a regional calibration with fewer calibrated parameters. Concurrently, modeled discharge showed equally good or better validation results than previous gridded model versions constructed for the same domain; and discharge trend patterns, snow water equivalent, and potential evaporation compared fairly to observations. Compared with previous studies, lower precipitation and evaporation values for mainland Norway were found. The results suggest that a more robust and more physically based model for climate change studies has been obtained, although additional studies will be needed to further constrain evaporation estimates.

• Tijdeman, E.; Stahl, K & Tallaksen, Lena M. (2020). Drought Characteristics Derived Based on the Standardized Streamflow Index: A Large Sample Comparison for Parametric and Nonparametric Methods. Water Resources Research. ISSN 0043-1397. 56(10). doi: 10.1029/2019WR026315. Full text in Research Archive Show summary

  The streamflow drought hazard can be characterized in a variety of ways, including using different indices. Traditionally, percentile‐based indices, such as Q95 (the flow exceeded 95% of time), have been used by the hydrological community. Recently, the use of anomaly indices such as the Standardized Streamflow Index (SSI), a probability index‐based approach adopted from the climatological community, has increased in popularity. The SSI can be calculated based on various (non)parametric methods. Up to now, there is no consensus which method to use. This study aims to raise awareness how the inherent sensitivity of the SSI to the used method influences derived drought characteristics. We compared SSI time series computed with seven different probability distributions and two fitting methods as well as with different nonparametric methods for 369 rivers across Europe. Results showed that SSI time series and associated drought characteristics are indeed sensitive to the method of choice. A resampling experiment demonstrated the sensitivity of the parametric SSI to properties of both the low and high end of the sample. Such sensitivities might hinder a fair comparison of drought in space and time and highlight the need for a clear recommendation which method to use. We could recommend overall suitable methods, for example, from the parametric approaches, the Tweedie distribution has several advantageous properties such as a low rejection rate (2%) and a lower bound at zero. However, the most suitable method depends on the used evaluation criteria. Rather, we stress that shown approach‐specific sensitivities and uncertainties should be carefully considered.

• Stoelzle, Michael; Schuetz, Tobias; Weiler, Markus; Stahl, Kerstin & Tallaksen, Lena M. (2020). Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 24(2), p. 849–867. doi: 10.5194/hess-24-849-2020. Full text in Research Archive Show summary

  Abstract. Understanding components of the total streamflow is important to assess the ecological functioning of rivers. Binary or two-component separation of streamflow into a quick and a slow (often referred to as baseflow) component are often based on arbitrary choices of separation parameters and also merge different delayed components into one baseflow component and one baseflow index (BFI). As streamflow generation during dry weather often results from drainage of multiple sources, we propose to extend the BFI by a delayed-flow index (DFI) considering the dynamics of multiple delayed contributions to streamflow. The DFI is based on characteristic delay curves (CDCs) where the identification of breakpoint (BP) estimates helps to avoid rather subjective separation parameters and allows for distinguishing four types of delayed streamflow contributions. The methodology is demonstrated using streamflow records from a set of 60 mesoscale catchments in Germany and Switzerland covering a pronounced elevation gradient of roughly 3000 m. We found that the quickflow signal often diminishes earlier than assumed by two-component BFI analyses and distinguished a variety of additional flow contributions with delays shorter than 60 d. For streamflow contributions with delays longer than 60 d, we show that the method can be used to assess catchments' water sustainability during dry spells. Colwell's predictability (PT), a measure of streamflow periodicity and sustainability, was applied to attribute the identified delay patterns to dynamic catchment storage. The smallest dynamic storages were consistently found for catchments between approx. 800 and 1800 m a.s.l. Above an elevation of 1800 m the DFI suggests that seasonal snowpack provides the primary contribution, whereas below 800 m groundwater resources are most likely the major streamflow contributions. Our analysis also indicates that dynamic storage in high alpine catchments might be large and is overall not smaller than in lowland catchments. We conclude that the DFI can be used to assess the range of sources forming catchments' storages and to judge the long-term sustainability of streamflow.

• Bhattarai, Bikas Chandra; Burkhart, John; Tallaksen, Lena M.; Xu, Chong-Yu & Matt, Felix Nikolaus (2020). Evaluation of global forcing datasets for hydropower inflow simulation in Nepal. Hydrology Research. ISSN 1998-9563. 51(2), p. 202–225. doi: 10.2166/nh.2020.079. Full text in Research Archive Show summary

  Abstract Discharge over the Narayani river catchment of Nepal was simulated using Statkraft's Hydrologic Forecasting Toolbox (Shyft) forced with observations and three global forcing datasets: (i) ERA-Interim (ERA-I), (ii) Water and Global Change (WATCH) Forcing Data ERA-I (WFDEI), and (iii) Coordinated Regional Climate Downscaling Experiment with the contributing institute Rossy Centre, Swedish Meteorological and Hydrological Institute (CORDEX-SMHI). Not only does this provide an opportunity to evaluate discharge variability and uncertainty resulting from different forcing data but also it demonstrates the capability and potential of using these global datasets in data-sparse regions. The fidelity of discharge simulation is the greatest when using observations combined with the WFDEI forcing dataset (hybrid datasets). These results demonstrate the successful application of global forcing datasets for regional catchment-scale modeling in remote regions. The results were also promising to provide insight of the interannual variability in discharge. This study showed that while large biases in precipitation can be reduced by applying a precipitation correction factor (p_corr_factor), the best result is obtained using bias-corrected forcing data as input, i.e. the WFDEI outperformed other forcing datasets. Accordingly, the WFDEI forcing dataset holds great potential for improving our understanding of the hydrology of data-sparse Himalayan regions and providing the potential for prediction. The use of CORDEX-SMHI- and ERA-I-derived data requires further validation and bias correction, particularly over the high mountain regions.

• Bakke, Sigrid Jørgensen; Ionita, Monica & Tallaksen, Lena M. (2020). The 2018 northern European hydrological drought and itsdrivers in a historical perspective. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 24, p. 5621–5653. doi: 10.5194/hess-24-5621-2020. Full text in Research Archive Show summary

  Abstract. In 2018, large parts of northern Europe were affected by an extreme drought. A better understanding of the characteristics and the large-scale atmospheric circulation driving such events is of high importance to enhance drought forecasting and mitigation. This paper examines the historical extremeness of the May–August 2018 meteorological situation and the accompanying meteorological and hydrological (streamflow and groundwater) drought. Further, it investigates the relation between the large-scale atmospheric circulation and summer streamflow in the Nordic region. In May and July 2018, record-breaking temperatures were observed in large parts of northern Europe associated with blocking systems centred over Fennoscandia and sea surface temperature anomalies of more than 3 ∘C in the Baltic Sea. Extreme meteorological drought, as indicated by the 3-month Standardized Precipitation Index (SPI3) and Standardized Precipitation Evapotranspiration Index (SPEI3), was observed in May and covered large parts of northern Europe by July. Streamflow drought in the Nordic region started to develop in June, and in July 68 % of the stations had record-low or near-record-low streamflow. Extreme streamflow conditions persisted in the southeastern part of the region throughout 2018. Many groundwater wells had record-low or near-record-low levels in July and August. However, extremeness in groundwater levels and (to a lesser degree) streamflow showed a diverse spatial pattern. This points to the role of local terrestrial processes in controlling the hydrological response to meteorological conditions. Composite analysis of low summer streamflow and 500 mbar geopotential height anomalies revealed two distinct patterns of summer streamflow variability: one in western and northern Norway and one in the rest of the region. Low summer streamflow in western and northern Norway was related to high-pressure systems centred over the Norwegian Sea. In the rest of the Nordic region, low summer streamflow was associated with a high-pressure system over the North Sea and a low-pressure system over Greenland and Russia, resembling the pattern of 2018. This study provides new insight into hydrometeorological aspects of the 2018 northern European drought and identifies large-scale atmospheric circulation patterns associated with summer streamflow drought in the Nordic region.

• Pall, Pardeep; Tallaksen, Lena M. & Stordal, Frode (2019). A Climatology of Rain-on-Snow Events for Norway. Journal of Climate. ISSN 0894-8755. 32(20), p. 6995–7016. doi: 10.1175/JCLI-D-18-0529.1. Full text in Research Archive Show summary

  Rain-on-snow (ROS) events are multivariate hydrometeorological phenomena that require a combination of rain and snowpack, with complex processes occurring on and within the snowpack. Impacts include floods and landslides, and rain may freeze within the snowpack or on bare ground, potentially affecting vegetation, wildlife, and permafrost. ROS events occur mainly in high-latitude and mountainous areas, where sparse observational networks hinder accurate quantification—as does a scale mismatch between coarse-resolution (50–100 km) reanalysis products and localized events. Variability in the rain–snow temperature threshold and temperature sensitivity of snowmelt adds additional uncertainty. Here the high-resolution (1 km) seNorge hydrometeorological dataset, capturing complex topography and drainage networks, is utilized to produce the first large-scale climatology of ROS events for mainland Norway. For daily data spanning 1957–2016, suitable rain and snowpack thresholds for defining ROS events are applied to construct ROS climatologies for 1961–90 and 1981–2010 and to investigate trends. Differing ROS characteristics are found, reflecting Norway’s diverse climates. Relative to 1961–90, events in the 1981–2010 period decrease most in the southwest low elevations in winter, southeast in spring, and north in summer (consistent with less snow cover in a warming climate) and increase most in the southwest high elevations, central mountains, and north in winter–spring (consistent with increased precipitation and/or more snow falling as rain in a warming climate). Winter–spring events also broadly correlate with the North Atlantic Oscillation, and the Scandinavia pattern—and more so with the Arctic Oscillation, particularly in the southern mountain region where long-term ROS trends are significant (+0.50 and +0.33 daily ROS counts per kilometer squared per decade for winter and spring).

• Horvath, Peter; Halvorsen, Rune; Stordal, Frode; Tallaksen, Lena Merete; Tang, Hui & Bryn, Anders (2019). Distribution modelling of vegetation types based on area frame survey data. Applied Vegetation Science. ISSN 1402-2001. 22(4), p. 547–560. doi: 10.1111/avsc.12451. Full text in Research Archive Show summary

  Aim: Many countries lack informative, high‐resolution, wall‐to‐wall vegetation or land cover maps. Such maps are useful for land use and nature management, and for input to regional climate and hydrological models. Land cover maps based on remote sensing data typically lack the required ecological information, whereas traditional field‐based mapping is too expensive to be carried out over large areas. In this study, we therefore explore the extent to which distribution modelling (DM) methods are useful for predicting the current distribution of vegetation types (VT) on a national scale. Location: Mainland Norway, covering ca. 324,000 km2. Methods: We used presence/absence data for 31 different VTs, mapped wall‐to‐wall in an area frame survey with 1081 rectangular plots of 0.9 km2. Distribution models for each VT were obtained by logistic generalised linear modelling, using stepwise forward selection with an F‐ratio test. A total of 116 explanatory variables, recorded in 100 m × 100 m grid cells, were used. The 31 models were evaluated by applying the AUC criterion to an independent evaluation dataset. Results: Twenty‐one of the 31 models had AUC values higher than 0.8. The highest AUC value (0.989) was obtained for Poor/rich broadleaf deciduous forest, whereas the lowest AUC (0.671) was obtained for Lichen and heather spruce forest. Overall, we found that rare VTs are predicted better than common ones, and coastal VTs are predicted better than inland ones. Conclusions: Our study establishes DM as a viable tool for spatial prediction of aggregated species‐based entities such as VTs on a regional scale and at a fine (100 m) spatial resolution, provided relevant predictor variables are available. We discuss the potential uses of distribution models in utilizing large‐scale international vegetation surveys. We also argue that predictions from such models may improve parameterisation of vegetation distribution in earth system models.

• Brunner, Manuela I & Tallaksen, Lena M. (2019). Proneness of European Catchments to Multiyear Streamflow Droughts. Water Resources Research. ISSN 0043-1397. 55(11), p. 8881–8894. doi: 10.1029/2019WR025903. Full text in Research Archive
• Hegdahl, Trine Jahr; Engeland, Kolbjørn; Steinsland, Ingelin & Tallaksen, Lena M. (2019). Streamflow forecast sensitivity to air temperature forecast calibration for 139 Norwegian catchments. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 23(2), p. 723–739. doi: 10.5194/hess-23-723-2019. Full text in Research Archive Show summary

  In this study, we used meteorological ensemble forecasts as input to hydrological models to quantify the uncertainty in forecasted streamflow, with a particular focus on the effect of temperature forecast calibration on the streamflow ensemble forecast skill. In catchments with seasonal snow cover, snowmelt is an important flood-generating process. Hence, high-quality air temperature data are important to accurately forecast streamflows. The sensitivity of streamflow ensemble forecasts to the calibration of temperature ensemble forecasts was investigated using ensemble forecasts of temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) covering a period of nearly 3 years, from 1 March 2013 to 31 December 2015. To improve the skill and reduce biases of the temperature ensembles, the Norwegian Meteorological Institute (MET Norway) provided parameters for ensemble calibration, derived using a standard quantile mapping method where HIRLAM, a high-resolution regional weather prediction model, was used as reference. A lumped HBV (Hydrologiska Byråns Vattenbalansavdelning) model, distributed on 10 elevation zones, was used to estimate the streamflow. The results show that temperature ensemble calibration affected both temperature and streamflow forecast skill, but differently depending on season and region. We found a close to 1:1 relationship between temperature and streamflow skill change for the spring season, whereas for autumn and winter large temperature skill improvements were not reflected in the streamflow forecasts to the same degree. This can be explained by streamflow being less affected by subzero temperature improvements, which accounted for the biggest temperature biases and corrections during autumn and winter. The skill differs between regions. In particular, there is a cold bias in the forecasted temperature during autumn and winter along the coast, enabling a large improvement by calibration. The forecast skill was partly related to elevation differences and catchment area. Overall, it is evident that temperature forecasts are important for streamflow forecasts in climates with seasonal snow cover.

• Erlandsen, Helene B.; Tallaksen, Lena M. & Kristiansen, Jørn (2019). Merits of novel high-resolution estimates and existing long-term estimates of humidity and incident radiation in a complex domain. Earth System Science Data. ISSN 1866-3508. 11(2), p. 797–821. doi: 10.5194/essd-11-797-2019. Full text in Research Archive Show summary

  To provide better and more robust estimates of evaporation and snowmelt in a changing climate, hydrological and ecological modeling practices are shifting towards solving the surface energy balance. In addition to precipitation and near-surface temperature (T2), which often are available at high resolution from national providers, high-quality estimates of 2 m humidity and surface incident shortwave (SW↓) and longwave (LW↓) radiation are also required. Novel, gridded estimates of humidity and incident radiation are constructed using a methodology similar to that used in the development of the WATCH forcing data; however, national 1 km×1 km gridded, observation-based T2 data are consulted in the downscaling rather than the 0.5∘×0.5∘ Climatic Research Unit (CRU) T2 data. The novel data set, HySN, covering 1979 to 2017, is archived in Zenodo (https://doi.org/10.5281/zenodo.1970170). The HySN estimates, existing estimates from reanalysis data, post-processed reanalysis data, and Variable Infiltration Capacity (VIC) type forcing data are compared with observations from the Norwegian mainland from 1982 through 1999. Humidity measurements from 84 stations are used, and, by employing quality control routines and including agricultural stations, SW↓ observations from 10 stations are made available. Meanwhile, only two stations have observations of LW↓. Vertical gradients, differences when compared at common altitudes, daily correlations, sensitivities to air mass type, and, where possible, trends and geographical gradients in seasonal means are assessed. At individual stations, differences in seasonal means from the observations are as large as 7 ∘C for dew point temperature, 62 W m−2 for SW↓, and 24 W m−2 for LW↓. Most models overestimate SW↓ and underestimate LW↓. Horizontal resolution is not a predictor of the model's efficiency. Daily correlation is better captured in the products based on newer reanalysis data. Certain model estimates show different dependencies on geographical features, diverging trends, or a different sensitivity to air mass type than the observations.

• Rizzi, Jonathan; Nilsen, Irene Brox; Stagge, James Howard; Gisnås, Kjersti Gleditsch & Tallaksen, Lena M. (2018). Five decades of warming: impacts on snow cover in Norway. Hydrology Research. ISSN 1998-9563. 49(3), p. 670–688. doi: 10.2166/nh.2017.051. Full text in Research Archive Show summary

  Northern latitudes are experiencing faster warming than other regions in the world, which is partly explained by the snow albedo feedback. In Norway, mean temperatures have been increasing since the 1990s, with 2014 being the warmest year on record, 2.2 °C above normal (1961–1990). At the same time, a concurrent reduction in the land area covered by snow has been reported. In this study, we present a detailed spatial and temporal (monthly and seasonal) analysis of trends and changes in snow indices based on a high resolution (1 km) gridded hydro-meteorological dataset for Norway (seNorge). During the period 1961–2010, snow cover extent (SCE) was found to decrease, notably at the end of the snow season, with a corresponding decrease in snow water equivalent except at high elevations. SCE for all Norway decreased by more than 20,000 km2 (6% of the land area) between the periods 1961–1990 and 1981–2010, mainly north of 63° N. Overall, air temperature increased in all seasons, with the highest increase in spring (particularly in April) and winter. Mean monthly air temperatures were significantly correlated with the monthly SCE, suggesting a positive land–atmosphere feedback enhancing warming in winter and spring.

• Laaha, Gregor; Gauster, Tobias; Tallaksen, Lena M.; Vidal, Jean-Philippe; Stahl, Kerstin & Prudhomme, Christel [Show all 24 contributors for this article] (2017). The European 2015 drought from a hydrological perspective. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 21(6), p. 3001–3024. doi: 10.5194/hess-21-3001-2017. Full text in Research Archive Show summary

  In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.

• Stagge, James Howard; Kingston, Daniel G.; Tallaksen, Lena M. & Hannah, David M. (2017). Observed drought indices show increasing divergence across Europe. Scientific Reports. 7(1). doi: 10.1038/s41598-017-14283-2. Full text in Research Archive Show summary

  Recent severe European droughts raise the vital question: are we already experiencing measurable changes in drought likelihood that agree with climate change projections? The plethora of drought definitions compounds this question, requiring instead that we ask: how have various types of drought changed, how do these changes compare with climate projections, and what are the causes of observed differences? To our knowledge, this study is the first to reveal a regional divergence in drought likelihood as measured by the two most prominent meteorological drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) across Europe over the period 1958–2014. This divergence is driven primarily by an increase in temperature from 1970–2014, which in turn increased reference evapotranspiration (ET0) and thereby drought area measured by the SPEI. For both indices, Europe-wide analysis shows increasing drought frequencies in southern Europe and decreasing frequencies in northern Europe. Notably, increases in temperature and ET0 have enhanced droughts in southern Europe while counteracting increased precipitation in northern Europe. This is consistent with projections under climate change, indicating that climate change impacts on European drought may already be observable and highlighting the potential for discrepancies among standardized drought indices in a non-stationary climate.

• Erlandsen, Helene B.; Haddeland, Ingjerd; Tallaksen, Lena M. & Kristiansen, Jørn (2017). The sensitivity of the terrestrial surface energy and water balance estimates in the WRF model to lower surface boundary representations: a South Norway case study. Journal of Hydrometeorology. ISSN 1525-755X. 18(1), p. 265–284. doi: 10.1175/JHM-D-15-0146.1. Full text in Research Archive Show summary

  A seasonal snow cover, expansive forests, a long coast line, and a mountainous terrain are features of Norway’s geography. Forests, ground snow, and sea surface temperature (SST) vary on time scales relevant for weather forecasting and climate projections. The mapping and model parameterization of these features vary in novelty, accuracy, and complexity. This paper investigates how increasing the influence of each of these features affects southern Norway’s surface energy and water balance in a regional climate model (WRF). High-resolution (3.7 km) experimental runs have been conducted over two consecutive hydrological years, including 1) heightening the boreal forest line (the Veg experiment), 2) increasing ground snow by altering the snow/rain criterion (the Snow experiment), or 3) increasing the SST (the SST experiment). The Veg experiment led to an increase in annual net radiation in the study area (by 3 W m−2), largely balanced out by an increase in latent heat flux. Moisture recycling increased, leaving only a negligible decrease in annual runoff. Surface temperature increased by 0.1°C, and its seasonal variability was dampened. Significant changes were also found outside the area of vegetation change. Snow decreased by 1.5 W m−2, despite slight increases in downward shortwave and longwave radiation. Both sensible heat flux and surface temperature decreased (by 1.3 W m−2 and 0.2°C, respectively), but the annual water balance remained mostly unchanged. The SST experiment led to increased downward and upward longwave radiation. Surface temperature was raised by 0.2°C. Advected oceanic moisture and thus both precipitation and runoff increased (by 2.5% and 2.8%, respectively). This research was originally published in the Journal of Hydrometeorology. © 2017 American Meteorological Society

• Rydsaa, Johanne Hope; Stordal, Frode; Bryn, Anders & Tallaksen, Lena M. (2017). Effects of shrub and tree cover increase on the near-surface atmosphere in northern Fennoscandia. Biogeosciences. ISSN 1726-4170. 14(18), p. 4209–4227. doi: 10.5194/bg-14-4209-2017. Full text in Research Archive
• Devoli, Graziella; Jørandli, L.; Engeland, Kolbjørn & Tallaksen, Lena M. (2017). Large-Scale Synoptic Weather Types and Precipitation Responsible for Landslides in Southern Norway. In Mikoš, Matjaž; Casagli, Nicola; Yin, Yueping & Sassa, Kyoji (Ed.), Advancing Culture of Living with Landslides: Volume 4 Diversity of Landslide Forms. Springer Publishing Company. ISSN 9783319534855. p. 159–167. doi: 10.1007/978-3-319-53485-5_17. Full text in Research Archive Show summary

  This volume contains peer-reviewed papers from the Fourth World Landslide Forum organized by the International Consortium on Landslides (ICL), the Global Promotion Committee of the International Programme on Landslides (IPL), University of Ljubljana (UL) and Geological Survey of Slovenia in Ljubljana, Slovenia from May 29 to June 2, 2017. The complete collection of papers from the Forum is published in five full-color volumes.

• Ionita, Monica; Tallaksen, Lena M.; Kingston, Daniel; Stagge, James Howard; Laaha, Gregor & Lanen, Henny, A.J. van [Show all 9 contributors for this article] (2017). The European 2015 drought from a climatological perspective. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 21(3), p. 1397–1419. doi: 10.5194/hess-21-1397-2017. Full text in Research Archive
• Loon, Anne F. Van; Stahl, Kerstin; Baldassarre, Giuliano Di; Clark, Julian; Rangecroft, Sally & Wanders, Niko [Show all 18 contributors for this article] (2016). Drought in a human-modified world: Reframing drought definitions, understanding, and analysis approaches. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 20(9), p. 3631–3650. doi: 10.5194/hess-20-3631-2016. Full text in Research Archive
• Lanen, Henny, A.J. van; Laaha, Gregor; Kingston, Daniel; Gauster, Tobias; Ionita, Monica & Vidal, Jean-Philippe [Show all 31 contributors for this article] (2016). Hydrology needed to manage droughts: the 2015 European case. Hydrological Processes. ISSN 0885-6087. 30(17), p. 3097–3104. doi: 10.1002/hyp.10838. Full text in Research Archive Show summary

  It is generally accepted that drought is one of the most costly weather‐related natural hazards. In 2015, a long‐lasting drought hit Europe, particularly affecting central and eastern Europe. In some regions it was the driest (North Slovakia) and in others (Czech Republic and Poland) it was the second driest summer of the last 50 years (following 2003). Key questions are: (i) how extreme are these events, not only in terms of hydro‐meteorological characteristics but also impacts? and (ii) how are these impacts managed?

• Hegdahl, Trine Jahr; Tallaksen, Lena M.; Engeland, Kolbjørn; Burkhart, John & Xu, Chong-Yu (2016). Discharge sensitivity to snowmelt parameterization: A case study for Upper Beas basin in Himachal Pradesh, India. Hydrology Research. ISSN 1998-9563. 47(4), p. 683–700. doi: 10.2166/nh.2016.047. Full text in Research Archive
• Stahl, Kerstin; Kohn, Irene; Blauhut, Veit; Urquijo, Julia; Stefano, Lucia De & Acacio, Vanda [Show all 19 contributors for this article] (2016). Impacts of European drought events: Insights from an international database of text-based reports. Natural Hazards and Earth System Sciences. ISSN 1561-8633. 16(3), p. 801–819. doi: 10.5194/nhess-16-801-2016. Full text in Research Archive
• Loon, Anne F. Van; Gleeson, Tom; Clark, Julian; Dijk, Albert I. J. M. Van; Stahl, Kerstin & Hannaford, Jamie [Show all 18 contributors for this article] (2016). Drought in the Antropocene. Nature Geoscience. ISSN 1752-0894. 9(2), p. 89–91. doi: 10.1038/ngeo2646. Full text in Research Archive
• Nilsen, Irene Brox; Stagge, James Howard & Tallaksen, Lena M. (2016). A probabilistic approach for attributing temperature changes to synoptic type frequency. International Journal of Climatology. ISSN 0899-8418. 37(6), p. 2990–3002. doi: 10.1002/joc.4894. Full text in Research Archive Show summary

  To understand the cause of regional temperature change, it is common to separate the temperature change signal into changes in atmospheric synoptic circulation and other factors, so-called within-type changes. In this study, we suggest a novel probabilistic approach that allows detection of months and regions where temperature changes can mainly be attributed to changes in synoptic circulation and where within-type changes also play a role. By combining resampling with a Monte Carlo test, we assess the likelihood that the observed warming can be explained by synoptic circulation changes alone. This method is applicable for any variable, and in any region of the world. We applied it to an example case using gridded WATCH Forcing Data ERA-Interim (WFDEI) temperature data and synoptic types derived from the SynopVis Grosswetterlagen catalogue (1981–2010). For this European example, the most widespread warming was found in summer, with up to 60% of the land area experiencing signicant warming during August, notably in Eastern and Northern Europe. In spring and autumn, this area was reduced to 10–30%. In December and January, only about 5% of the land area experienced signicant warming, most pronounced in northern Scandinavia. The probabilistic approach revealed that changes in synoptic circulation c ould not account for all the observed (WFDEI) warming, with the exception of regions in southeastern Europe in February and Western Europe in May. Signicant warming in other months and regions, such as the large-scale warming in April, June, July, August, and November, must also be caused by other factors. Within-type changes were conrmed for the Black Sea region in November, where the magnitude of a widespread temperature trend was strongest. This European example contributes to an improved understanding of the causes of recent temperature change by assessing the relative role of synoptic circulation changes and within-type changes on regional-scale warming.

• Stagge, James Howard; Tallaksen, Lena M.; Gudmundsson, Lukas; Loon, Anne F. Van & Stahl, Kerstin (2016). Response to comment on 'Candidate Distributions for Climatological Drought Indices (SPI and SPEI)'. International Journal of Climatology. ISSN 0899-8418. 36(4), p. 2132–2138. doi: 10.1002/joc.4564. Full text in Research Archive
• Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; Stefano, Lucia De & Vogt, Jürgen V. (2016). Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 20(7), p. 2779–2800. doi: 10.5194/hess-20-2779-2016. Full text in Research Archive
• Lanen, Henny, A.J. van; Tallaksen, Lena M.; Assimacopoulos, Dionysis; Stahl, Kerstin; Wolters, Wouter & Andreu, Joaquin [Show all 12 contributors for this article] (2015). Fostering Drought Research and Science-Policy Interfacing: Achievements of the DROUGHT-R&SPI project. In Alvarez, Joaquin Andreu; Solera, Abel; Paredes-Arquiola, Javier; Haro-Monteagudo, David & Lanen, Henny van (Ed.), Drought: research and science-policy interfacing. CRC Press. ISSN 9781138027794. p. 3–12. doi: 10.1201/b18077-3. Full text in Research Archive
• Stagge, James Howard; Kohn, Irene; Tallaksen, Lena M. & Stahl, Kerstin (2015). Modeling drought impact occurrence based on meteorological drought indices in Europe. Journal of Hydrology. ISSN 0022-1694. 530, p. 37–50. doi: 10.1016/j.jhydrol.2015.09.039. Full text in Research Archive
• Kingston, Daniel; Stagge, James Howard; Tallaksen, Lena M. & Hannah, David M. (2015). European-scale drought: Understanding connections between atmospheric circulation and meteorological drought indices. Journal of Climate. ISSN 0894-8755. 28(2), p. 505–516. doi: 10.1175/JCLI-D-14-00001.1. Full text in Research Archive
• Ngongondo, Cosmo; Xu, Chong-Yu; Tallaksen, Lena M. & Alemaw, B. (2015). Observed and simulated changes in the water balance components over Malawi, during 1971-2000. Quaternary International. ISSN 1040-6182. 369, p. 7–16. doi: 10.1016/j.quaint.2014.06.028. Full text in Research Archive
• Fleig, Anne Kristina; Tallaksen, Lena M.; James, Philip; Hisdal, Hege & Stahl, Kerstin (2015). Attribution of European precipitation and temperature trends to changes in synoptic circulation. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 19(7), p. 3093–3107. doi: 10.5194/hess-19-3093-2015. Full text in Research Archive
• Tallaksen, Lena M.; Stagge, James Howard; Stahl, Kerstin; Gudmundsson, Lukas; Orth, Rene & Seneviratne, Sonia I. [Show all 8 contributors for this article] (2015). Characteristics and drivers of drought in Europe—a summary of the DROUGHT-R&SPI project. In Alvarez, Joaquin Andreu; Solera, Abel; Paredes-Arquiola, Javier; Haro-Monteagudo, David & Lanen, Henny van (Ed.), Drought: research and science-policy interfacing. CRC Press. ISSN 9781138027794. p. 15–21. doi: 10.1201/b18077-5. Full text in Research Archive
• Stahl, Kerstin; Kohn, I.; Stefano, L. De; Tallaksen, Lena M.; Rego, F.C. & Seneviratne, S.I. [Show all 8 contributors for this article] (2015). An impact perspective on pan-European drought sensitivity. In Alvarez, Joaquin Andreu; Solera, Abel; Paredes-Arquiola, Javier; Haro-Monteagudo, David & Lanen, Henny van (Ed.), Drought: research and science-policy interfacing. CRC Press. ISSN 9781138027794. p. 329–334. doi: 10.1201/b18077-56. Full text in Research Archive

View all works in NVA

• 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.

• Ahlbäck, Malin; Pirk, Norbert; Tallaksen, Lena M. & Silantyeva, Olga (2025). Temporal Dynamics and Hydrological Impacts of Snow-Atmosphere Vapor Exchanges in a High-Altitude Catchment. doi: https:/www.hydrologiraadet.no/wp-content/uploads/2025/08/AbstractsLillehammer2025_210825.pdf. Full text in Research Archive Show summary

  The evolution of the snowpack is strongly influenced by turbulent fluxes, where latent heat transfer alters the snowpack water equivalent through processes such as snow sublimation and deposition, in addition to changing the cold content and structure of the snow. In alpine regions, the contribution of sublimation to the water balance varies widely, with results indicating only a negligible part of snowfall is sublimated, to up to 90% locally at wind-exposed ridges and crests. To improve our understanding of these dynamics, this study integrates small-scale micrometeorological observations with catchment-scale modelling, enabling a multi-scale analysis of snow-atmosphere water vapour exchanges and their impacts on the snowpack water balance in a high-altitude catchment in southern Norway. We will outline preliminary insights into the temporal scales governing water vapour fluxes and its linkage to environmental drivers, using micrometeorological site data and wavelet analysis. Compared to the commonly used eddy covariance method, processing the high-frequency site data using wavelet analysis allowed for resolving fluxes over small (<1 min) time scales, and offer a detailed analysis of the eddy distribution over time, and as such, new insights into the dynamics governing sublimation. In addition, the wavelet analysis method handled non-stationary time periods where the eddy covariance method fails, indicating the potential for using wavelet analysis over eddy covariance for processing complex micrometeorological data where traditional methods are not possible. To evaluate the broader hydrological impacts of sublimation and deposition fluxes, we also plan to present results from a snow model framework over the whole catchment and contrast the annual variability between dry and wet winters. Our findings are expected to contribute to a deeper understanding of sublimation and deposition processes in Nordic regions, and how they may change in a future climate. By combining field measurements and modelling approaches, these insights can be used for advancing the parametrisation of winter vapour fluxes for applications in snow hydrology.

• Huang, Shaochun; Silantyeva, Olga; Gelati, Emiliano; Yilmaz, Yeliz A.; Engeland, Kolbjørn & Tallaksen, Lena M. (2025). Quantifying the uncertainty of evapotranspiration estimates for unregulated Norwegian catchments using multiple hydrological models and remote sensing products. doi: 10.5194/egusphere-egu25-14913. Full text in Research Archive Show summary

  Previous studies show high uncertainty of evapotranspiration (ET) estimates for Norway, ranging from about 200 to more than 500 mm/year. It is partly due to sparce ET measurements in Norway to constrain the ET process in the hydrological modelling, and partly due to the uncertainty of precipitation (P) observations, especially in high mountainous regions with complex topography. In this study, we aim to quantify the uncertainty of ET estimates for 66 Norwegian catchments based on three hydrological models and four global remote sensing products. All the selected catchments are small (< 1000 km2), non-regulated and non-glacierized, with long-term discharge (Q) observations and runoff coefficient less than one (i.e. P>Q). These catchments differ substantially in climatic and hydrological characteristics and span the five hydrological regimes commonly used in Norway (Atlantic, Mountain, Inland, Baltic, and Transition). The three hydrological models (HBV, LISFLOOD and Shyft) are calibrated against daily discharge between 1981 and 2000 using three objective functions (KGE, KGE+LKGE, and KGE+BoxcoxKGE) and validated between 2001 and 2020 using six criteria (KGE, LKGE, BoxcoxKGE, percent Bias (PBias), and KGE &#160;and PBias in the snow free period). The latter two criteria are specifically selected to evaluate the model performance in simulating ET given the absence of direct ET measurements. The snow free period is identified for each catchment and year based on a daily fractional snow-covered area data at 500 m spatial resolution produced from a combined MODIS dataset (MOD10A1 and MYD10A1). The four global remote sensing estimates of ET are obtained from BESSV2, ETMonitor, PML_V2 and SSEBop_V2 datasets and they are available at fine spatial resolution (&#8804;0.05&#176;) and monthly time steps. The calibration and validation results show that the three hydrological models perform best using different objective functions for each hydrological regime and target variable (discharge and ET). The uncertainty ranges of annual mean ET are up to 177 mm based on all hydrological model results and remote sensing products. Using the best performing hydrological model results as the benchmark, all remote sensing products overestimate ET for the mountain regime and PML_V2 gives the best estimate for the other four hydrological regimes.

• Nair, Akhilesh S.; Tallaksen, Lena M.; Bjørbæk, Torkel A. & Collenteur, Raoul (2025). Gap-filling groundwater level time series of irregular temporal resolution using physical modeling (Pastas) and simple statistical scaling. doi: 10.5194/egusphere-egu25-10107. Full text in Research Archive Show summary

  Groundwater level (GWL) monitoring datasets are essential for effective groundwater resource management and understanding the potential impacts of climate change. However, these datasets frequently contain gaps and irregular measurement intervals, posing challenges for time series analyses that depend on consistent sampling. As a result, GWL datasets with substantial gaps are frequently excluded from further analysis, leading to a loss of temporal and spatial coverage, regional representativity, and potentially valuable insights. Addressing this issue requires effective and interpretable imputation techniques to fill missing values while preserving the physical realism of the reconstructed data. Traditional statistical imputation methods and advanced machine learning algorithms, such as missForest, have been used to address data gaps. While these approaches often yield effective imputations, they lack physical interpretability, particularly for extreme events, which is crucial for understanding the variability and resilience of groundwater systems under changing environmental conditions. This study proposes a novel hybrid imputation approach that combines physical modeling with statistical adjustments. First, GWL data are simulated using Pastas, an open-source framework that leverages hydrometeorological variables and impulse response functions to model GWL time series. These simulations serve as a physically consistent basis for imputing missing values. In the second step, a linear scaling approach is applied to scale the simulated GWL to match the observed start and end point of each gap, ensuring consistency with observations. The hybrid method was tested on data from 213 monitoring wells across Sweden, encompassing diverse temporal resolution and gap characteristics. This process generated continuous daily time series spanning 34 years (1990&#8211;2023), enabling the evaluation of long-term groundwater dynamics across Sweden (future work). Validation focused on the ability to capture extreme GWL events. While Pastas-only simulations performed well in reproducing seasonal GWL variability, they failed to accurately capture extremes. The hybrid technique demonstrated significant improvements in representing extreme variability, offering a robust solution for handling irregular and incomplete datasets. Additionally, the study provides insights into regional data characteristics, such as variations in gap patterns and hydrometeorological drivers, offering valuable information for groundwater modeling and analysis. The proposed method not only enhances the reliability of GWL datasets but also supports better decision-making in groundwater resource management. The work is a contribution to the Water4All GroundedExtremes project.

• Silantyeva, Olga; Ahlbäck, Malin; Yilmaz, Yeliz A.; Tallaksen, Lena M.; Lappegard, Gaute & Erlandsen, Helene B. [Show all 11 contributors for this article] (2024). SnowSub: Assessing snow sublimation for hydropower production in Norway. Project results at Snow Bridges workshop. Full text in Research Archive
• Erlandsson, Rasmus; Finne, Eirik Aasmo; Tømmervik, Hans; Stordal, Frode & Tallaksen, Lena M. (2024). Pan-arctic lichen estimation indicates a shift from herbivory to climate change driven declines in lichen biomass. Full text in Research Archive
• Tallaksen, Lena M. (2024). For vått og for tørt - om fravær av vann og hvordan tørke har blitt en stadig større utfordring i Europa. Full text in Research Archive
• Tallaksen, Lena M. (2024). State of the art & new developments in drought research. Full text in Research Archive
• Nkhoma, Lusungu Wezzie; Ngongondo, Cosmo; Xu, Chong-Yu; Gelati, Emiliano & Tallaksen, Lena M. (2024). Evaluation of the performance of high-resolution global climate datasets over Malawi. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke [Show all 9 contributors for this article] (2024). Leveraging Earth observations to model snow cover dynamics over Scandinavia. Full text in Research Archive
• Tallaksen, Lena M.; Stordal, Frode; Pirk, Norbert & Yilmaz, Yeliz A. (2024). Land-Atmosphere Interactions at High Northern Latitudes. Full text in Research Archive
• Tallaksen, Lena M. (2024). A world of drought - lessons learnt and future perspective. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke [Show all 9 contributors for this article] (2024). Using Earth observations to model snow cover over Scandinavia. Full text in Research Archive
• Ahlbäck, Malin; Pirk, Norbert; Tallaksen, Lena M. & Silantyeva, Olga (2024). Assessing the impact of sublimation for hydrological forecasting. Full text in Research Archive
• Gelati, Emiliano; Bakke, Sigrid Jørgensen; Engeland, Kolbjørn & Tallaksen, Lena Merete (2023). River discharge extremes in Norwegian regulated catchments: hydrologic model simulations including human interventions. Full text in Research Archive Show summary

  Slides: https://www.hydrologiraadet.no/wp-content/uploads/2023/10/1_Gelati.pdf In the coming years and decades, Norway will likely be affected by more frequent and severe extreme weather events, including both intense precipitation and drought. Predicting how these hazards will result in extreme high and low river discharge in a changing climate requires robust hydrologic models representing all relevant physical and human processes. While hydrologic modelling in catchments affected by human activities is more challenging than in pristine environments, it is mainly in the former that water-related natural hazards have the largest societal impacts. Therefore it is crucial to test and refine hydrologic predictions in human influenced catchments. We apply the spatially distributed hydrologic and water resources model LISFLOOD to regulated Norwegian catchments, aiming to evaluate, and possibly improve, the simulation of high and low discharge conditions under the influence of human interventions. LISFLOOD simulates hydrologic processes on several sub-grid land use and cover classes, routing discharge along river networks. It can also simulate lakes and reservoir regulation, as well as human water abstractions, consumption and return flows. We focus primarily on the Drammen catchment, which is heavily regulated and serves several water users, with the possibility to extend the analysis to other catchments in Norway. Land use, vegetation, soil and river data are derived from the LISFLOOD setup at 5 km resolution used in the European Flood Awareness System. The model is forced with daily SeNorge_2018 and European Meteorological Observations atmospheric data at, respectively, 1 km and 1 arcminute spatial resolution. Detailed information for the Drammen catchment, in particular regarding human water use and regulation, is available through collaboration with the STARS4Water research project, which focuses on how climate change affects water resources availability at catchment scale and the potential impacts on ecosystems and society. Model evaluation is based on observed river discharge and reservoir water storage time series obtained from the Norwegian Water Resources and Energy Directorate. We aim to assess the ability of the model to reproduce extreme high and low discharge conditions, and whether representing human interventions improves model performance.

• Engeland, Kolbjørn; Erlandsen, Helene B.; Gelati, Emiliano; Huang, Shaochun; Narayanappa, Devaraju & Pirk, Norbert [Show all 10 contributors for this article] (2023). Intercomparison of local evapotranspiration estimates at high latitudes. Full text in Research Archive
• Bjerke, Jarle W.; Tallaksen, Lena M.; Stordal, Frode & Yilmaz, Yeliz A. (2023). EMERALD Open Science Day - Summary of Group Discussions. Full text in Research Archive Show summary

  Group discussions, key questions: How to move from single discipline to multidisciplinary studies? Which processes are missing in terms of plant-climate interactions for improving models?

• Vatne, Astrid; Vollsnes, Ane Victoria; Pirk, Norbert & Tallaksen, Lena M. (2023). Drought effects on dwarf birch leaves. Full text in Research Archive
• Engeland, Kolbjørn; Aas, Kjetil Schanke; Erlandsen, Helene Birkelund; Gelati, Emiliano; Huang, Shaochun & Narayanappa, Devaraju [Show all 11 contributors for this article] (2022). LATICE MIP evapotranspiration – A model intercomparison project for evapotranspiration estimates at high latitudes. 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
• Finne, Eirik Aasmo; Tallaksen, Lena M.; Stordal, Frode & Bjerke, Jarle W. (2022). Effects of winter warming events on vegetation ecophysiology on a low-alpine ridge. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke [Show all 8 contributors for this article] (2022). Evaluating modeled snow cover dynamics over Fennoscandia using Earth observations and reanalyses. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Pirk, Norbert & Remmers, Janneke [Show all 8 contributors for this article] (2022). Evaluating modeled snow cover dynamics over Fennoscandia using Earth observations. Full text in Research Archive Show summary

  The snow cover is an essential part of the climate system in cold regions through its effects on the terrestrial water, energy, and carbon balance. Due to the high spatiotemporal variability of snow, it is challenging to resolve snow cover dynamics in models. Thus, our ability to improve the representation of these dynamics in Earth System Models (ESMs) leans heavily on the accuracy and representativeness of the observational data sets used for model evaluation. The big picture provided by the long-term climate data record from satellites helps us to monitor changes in land cover over large areas. At the same time, rapidly developing drone and terrestrial imaging technology provides higher resolution information over specific areas. This complimentary information from spaceborne, airborne, and terrestrial Earth observations is invaluable for better understanding the complex processes in the climate system. In our work, we are currently exploiting estimates of snow-covered area from different optical sensors onboard polar orbiting satellites that are imaging the Nordic region. Drone and terrestrial images are being explored as a source of validation and calibration data for the satellite products.  Having representative snow cover maps enables us to better evaluate the terrestrial component of the Norwegian Earth System Model (NorESM), namely the Community Land Model (CLM5). With a focus on snow processes, we are conducting an analysis using satellite-based estimates of snow-covered area (MODIS, Sentinel-2, and Landsat 8), snow simulations from CLM5, snow variables from several climate reanalyses (ERA5, ERA5-Land, and MERRA-2), and in-situ data from eddy covariance stations (LATICE flux sites). Two offline CLM5 simulations are conducted with different atmospheric forcing, namely the default data set (GSWP3) and ERA5. We are investigating trends in the snow cover phenology, which we characterize using snow cover duration, first and last days of the snow cover, and consecutive snow cover days for each snow season over the last two decades. This work illuminates a path to integrate Earth observations with Earth system modeling in cold environments to both identify and constrain sources of uncertainty. Acknowledgement: This ongoing study is supported by the LATICE (Land-ATmosphere Interactions in Cold Environments) strategic research initiative funded by the University of Oslo, and the project EMERALD (294948) funded by the Research Council of Norway.

• Gelati, Emiliano; Yilmaz, Yeliz A.; Bakke, Sigrid Jørgensen & Tallaksen, Lena M. (2021). Community Land Model v5 runoff evaluation in small near-natural catchments in Fennoscandia. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Stordal, Frode & Tallaksen, Lena M. (2021). Fennoscandian snow cover dynamics in the MODIS era. Full text in Research Archive
• Gelati, Emiliano; Yilmaz, Yeliz; Bakke, Sigrid Jørgensen & Tallaksen, Lena Merete (2021). Community Land Model v5 runoff evaluation in small near-natural catchments in Fennoscandia. Full text in Research Archive
• Keetz, Lasse Torben; Bryn, Anders; Horvath, Peter; Skarpaas, Olav; Tallaksen, Lena M. & Zliobaite, Indre (2021). Using machine learning to model the distribution of Vegetation Types across Norway. Full text in Research Archive
• Silantyeva, Olga; Bhattarai, Bikas Chandra; Tallaksen, Lena M.; Burkhart, John Faulkner; Skavhaug, Ola & Helset, Sigbjørn (2021). Modeling Sensitivity To Mesh Size And Shape: A Case Study At Central Himalayan Catchment Revealing Importance Of Regional Dataset. Full text in Research Archive Show summary

  The complex terrain, high seasonal variability, complexity in precipitation patterns and cold region hydrology at Budhi-Gandaki catchment in central Himalaya, Nepal, presents a challenge for hydrological modeling. Regional or local forcing data, especially with high spatial resolution is preferred over coarser global dataset. However, such data is not always available. The Budhi-Gandaki catchment is subject to significant hydropower development, so accurate discharge simulation is important. Shyft is a novel hydrologic modeling software for streamflow forecasting targeted for use in hydropower production environments and research (Burkhart et al, 2021). It allows easy manipulation with configurations, which is a great tool in decision-making processes in the power production chain. The new functionality of Shyft.hydrology allows capturing of detailed terrain topography using triangular irregular networks (tin) and “on the fly” slope and aspect correction of radiation forcing. We compare discharge simulations using two different forcing datasets: WFDEI global dataset (0.5o x 0.5o) and HI-AWARE regional dataset (5x5 km precipitation and temperature) in both a grid and tin-based configurations. Simulated discharge is compared to observed discharge for ten-year period (2000-2010) using two performance measures, Nash- Sutcliffe efficiency (NSE) and Kling-Gupta efficiency (KGE). We show that the regional dataset combined with a tin configuration performs better than using a rectangular grid resolution, both in terms of NSE and KGE. Furthermore, correcting radiation for slope and aspect at each cell improves the resultant NSE and KGE even more. However, for the global dataset a configuration based on tin performs worse than grid, which is partly attributed to the complexity of the precipitation distribution over the catchment area. One WFDEI grid cell covers the whole catchment, so it is only represented by one precipitation value, which does not allow the interpolation routines in the Shyft.hydrology to separate between windward and leeward areas. However, for less complex terrain and precipitation patterns, like in the Marsyangdi catchment, studied previously (Bhattarai et all, 2020), good results obtained even with the coarse resolution WFDEI dataset. Here introducing a tin configurations improved agreement between simulated and observed discharge as compared to using a rectangular grid. We conclude on the advantages of using a tin-based configurations for water planning in hydropower production in the region. This work contributes to LATICE (Land Atmosphere Interactions in Cold Environments) project at the University of Oslo Keywords: Central Himalaya; Budhi-Gandaki; Hi-AWARE; Shyft; TIN; Discharge simulation; References 1. Burkhart, J. F., Matt, F. N., Helset, S., Sultan Abdella, Y., Skavhaug, O., and Silantyeva, O.: Shyft v4.8: a framework for uncertainty assessment and distributed hydrologic modeling for operational hydrology, Geosci. Model Dev., 14, 821–842, https://doi.org/10.5194/gmd-14-821-2021, 2021. 2. Bhattarai, B. C., Silantyeva, O., Teweldebrhan, A. T., Helset, S., Skavhaug, O., and Burkhart, J. F.: Impact of Catchment Discretization and Imputed Radiation on Model Response: A Case Study from Central Himalayan Catchment, Water, 12, 2020.

• Tallaksen, Lena M. (2021). Tallaksen, L. M.: Drought in a changing climate – a pan-European view. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Stordal, Frode & Tallaksen, Lena M. (2021). Probing Fennoscandian Snow Cover Dynamics in the Community Land Model and Climate Reanalyses during the Satellite Era. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon; Gascoin, Simon; Stordal, Frode & Tallaksen, Lena M. (2021). Benchmarking CLM5 snow cover dynamics with MODIS and reanalyses over Fennoscandia. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon Vincent P; Stordal, Frode & Tallaksen, Lena M. (2020). Fennoscandian snow cover phenology from MODIS, CLM5, and climate reanalyses. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon Vincent P; Stordal, Frode & Tallaksen, Lena M. (2020). Scandinavian snow cover phenology from MODIS, CLM, and reanalyses. Full text in Research Archive
• Yilmaz, Yeliz A.; Aalstad, Kristoffer; Filhol, Simon Vincent P; Stordal, Frode & Tallaksen, Lena M. (2020). The Representation of the Fennoscandian Snow Cover Phenology in Reanalyses and CLM5 during the MODIS-era. Full text in Research Archive Show summary

  Snow plays an important role in cold regions through its effect on the terrestrial exchange of energy, water, and carbon. Accurately simulating snow processes is therefore important in capturing various climate feedbacks in Earth system models. The representation of the subgrid heterogeneity of snow properties (e.g. coverage, depth, density, albedo) are, in addition to accumulation and snowmelt, major sources of uncertainty in the snow modules of land surface schemes. Using multiple data sources is essential to address these uncertainties and to evaluate overall model performance. Unlike in-situ observations, satellite remote sensing products provide unique representative information at the scale of Earth system models. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua and Terra satellites provide a continuous long-term climate record for the last two decades. In this study, two daily snow cover data sets from MODIS (MOD10A1 and MYD10A1) were used to retrieve fractional snow-covered area (fSCA) and several snow cover metrics (e.g. snow cover duration, first and last day of snow) over Fennoscandia for the 2001-2020 water years. We use these retrievals to evaluate the fSCA outputs from multiple reanalyses (ERA5-Land, ERA5, and MERRA-2) and the latest version of the Community Land Model (CLM5) which is the land component of the Community Earth System Model (CESM) and the Norwegian Earth System Model (NorESM). In order to test the accuracy of the MODIS data, we employed Sentinel-2 and Landsat 8 satellite retrievals as well as local‐scale measurements around the Finse Eco-Hydrological Observatory (Finse EcHO), a low-alpine site in central Norway. Lastly, we compared the trends in snow cover metrics with terrestrial water storage anomalies obtained from the Gravity Recovery and Climate Experiment (GRACE) to better understand the regional water cycle dynamics over this region. This study provides a useful starting point for integrating Earth observations into Earth system modeling in cold regions to help identify and constrain sources of uncertainty. Acknowledgement : This study is conducted under the LATICE strategic research initiative funded by the Faculty of Mathematics and Natural Sciences at the University of Oslo, and the EMERALD (project #294948) funded by the Research Council of Norway.

• Yilmaz, Yeliz; Tallaksen, Lena M. & Stordal, Frode (2020). Hydroclimatological evaluation of CLM5 simulations using multiple data sources for land-atmosphere interaction studies over Scandinavia. Full text in Research Archive Show summary

  Arctic amplification leads to rapid changes in the terrestrial water and energy balances at high northern latitudes. Advances in Earth System Models (ESMs) is improving our understanding of the underlying feedback mechanisms leading to these changes. The representation of the land surface in ESMs is essential to simulate and understand changes at the global and regional scales. The latest version of the land component of the Norwegian Earth System Model (NorESM), namely the Community Land Model (CLM5), has received substantial new implementations to help simulate the land surface processes in cold environments. At the same time, the behaviour of offline CLM5 simulations and new observational data sets have not been systematically compared over Scandinavian regions. In this study, we run the CLM5 model at relatively high resolution (0.25 degrees) over Scandinavia (including Svalbard) for 15 years between 2002 and 2016. We evaluate the water and energy budget components of CLM5 using several reanalyses and satellite-based observational data sets. In particular, we use monthly model outputs and compare with the satellite retrievals from GRACE, MODIS, AMSR2, and AMSR-E, and reanalysis data sets from ERA5, GLDAS, and MERRA-2. As an additional data source, we use the local‐scale measurements obtained from the Finse Eco-Hydrological Observatory (Finse EcHO) at 1200 m a.s.l, and the high-Arctic research site at Bayelva near Ny-Ålesund, Svalbard. Our investigation is focused on several variables including terrestrial water storage, snow water equivalent, turbulent fluxes, net radiation, and skin temperature. The results indicate that the perceived performance of the land surface model (CLM5) depends strongly on the reference observational data set. Regional discrepancies between data sets, particularly for Svalbard, prompts further investigation of the underlying sources of uncertainty. The results of this evaluation provide a valuable source of information for future studies in the region, particularly in the Land-ATmosphere Interactions in Cold Environments (LATICE) project, which focuses on cold region land surface dynamics, integrating across observational systems, laboratory experiments, field, and modeling efforts. Acknowledgement : This study is conducted under the LATICE strategic research initiative funded by the Faculty of Mathematics and Natural Sciences at the University of Oslo, and the project EMERALD (294948) funded by the Research Council of Norway.

• Pirk, Norbert; Ramtvedt, Eirik Næsset; Decker, Sven; Cassiani, Massimo; Burkhart, John & Stordal, Frode [Show all 7 contributors for this article] (2019). Causes of surface energy imbalances of eddy covariance measurements in mountainous terrain. Full text in Research Archive
• Silantyeva, Olga; Tallaksen, Lena M. & Burkhart, John (2019). Understanding terrain topography impact on snowmelt at catchment scale. Full text in Research Archive Show summary

  The work by [Fan et.al., 2019] calls for model experiments to evaluate the major hypothesis that energy or water-limited regions are largely controlled by hillslopes. However, the meteorological data in mountainous areas lacks accuracy due to sparse station network and coarse re-analysis grids (for example, high-resolution senorge data is only 1km). Simulation tools that model hydrologic processes at local scales require ways to overcome the lack of accuracy in the observational data, particular at high elevations. SHyFT is a tool for distributed hydrologic modeling, which has demonstrated a high potential in the ability to model stream flow in complex and data sparse regions [Burkhart et al., 2016]. Steps are also taken to further account for hillslope-scale terrain structures carefully. This new functionality allows downscaling and translating radiation measurements or re-analysis data onto inclined surfaces improving the predictive power of the model. Based on the SHyFT framework we are analyzing the importance of topographic details such as slope/aspect and shading on predicting snowmelt and vegetation in northern latitudes, which are characterized by energy-limited complex terrain. Observations inform us that slope/aspect and shading effects in mountainous regions impact snowmelt: sunny slopes melt earlier while shady ones store snow for longer periods. Our framework provides a unique capability to directly incorporate these effects online within the hydrologic computation, and we will further evaluate whether the aforementioned hypothesis is accurately characterized with this new functionality for operational cases. Further, we will assess whether there is a direct benefit to hydrologic simulation. This project contributes to LATICE (Land Atmosphere Interaction in Cold Environments) initiative at the University of Oslo. References J. F. Burkhart, S. Helset, Y. S. Abdella, and G. Lappegard. Operational research:evaluating multi- model implementations for 24/7 runtime environment. American Geophysical Union, Fall General Assembly 2016, Abstract Id. H51F-1541, 2016. Y. Fan et al. Hillslope hydrology in global change research and earth system modeling. Water- Resources Research, 55(2), 2019.

• Silantyeva, Olga; Tallaksen, Lena M.; Burkhart, John; Skavhaug, Ola & Helset, Sigbjørn (2019). Analysis on the added value of accounting for slope/aspect and shading effects in hydrologic simulations. Full text in Research Archive Show summary

  Radiation flux is a major component of earth’s energy balance. It is the driving factor for various processes withing the earth’s atmosphere and surface. However, the precise measurement of insolation is still subject to errors due to number of effects such as clouds and terrain shading. At regional scale the main issues is the existence and quality of radiation measurements in mountainous areas. The observational errors typically propagate through simulations leading to less accurate predictions of events such as snowmelt. We further develop SHyFT framework (https://github.com/statkraft/shyft), which is an opera- tional tool for distributed hydrologic modeling. Our current progress accounts for terrain topography. The new part of the tool allows detailed capture of topography and simulates slope/aspect and shad- ing effects. The radiation flux is translated onto inclined surfaces based on the method developed by [Allen et al., 2006]. The shading effects are added as a part of new triangulation tool (https://github.com/expertanalytics/rasputin). We expect that new functionality will help us investigate the hypothesis formulated in [Fan et al., 2019] that in energy-limited areas insolation contrast between sunny and shady slopes impacts water and vegetation. In order to conclude about the added value of the new methods at regional scale we are going to simulate number of local cases to asses impact on snowmelt and vegetation. The formulated results will be interesting for water planning in hydropower production as well as for weather predicting specialists. This work is a part of LATICE (Land Atmosphere Interaction in Cold Environments) project at the University of Oslo. References Richard G. Allen, Ricardo Trezza, and Masahiro Tasumi. Analytical integrated functions for daily solar radiation on slopes. Agricultural and Forest Meteorology, 139:55–73, 2006. Y. Fan et al. Hillslope hydrology in global change research and earth system modeling. Water Resources Research, 55(2), 2019.

• Silantyeva, Olga; Burkhart, John; Tallaksen, Lena M.; Helset, Sigbjørn & Skavhaug, Ola (2019). Shyft - Hydrologic Forecasting Toolbox: current state and future work. Full text in Research Archive
• Yilmaz, Yeliz; Tallaksen, Lena M. & Stordal, Frode (2019). Assessment of the water and energy balance simulations of CTSM using satellite-based observations over Scandinavia. Full text in Research Archive
• Haugnes, Gunhild M.; Tallaksen, Lena M.; Vogt, Rolf David; Storelvmo, Trude; Hessen, Dag Olav & Stordal, Frode [Show all 9 contributors for this article] (2018). Klimaforskerne tar temperaturen på tropesommeren. [Journal]. Titan.uio.no. Full text in Research Archive
• Rydsaa, Johanne Hope; Stordal, Frode; Bryn, Anders & Tallaksen, Lena M. (2017). Effects of shrub cover changes on the near surface atmosphere in northern Fennoscandia: A model study. Full text in Research Archive
• Burkhart, John; Decker, Sven; Filhol, Simon; Hulth, John; Nesje, Atle & Schuler, Thomas [Show all 8 contributors for this article] (2017). Development of the Finse Alpine Research Station towards a platform for multi-disciplinary research on Land-Atmosphere Interaction in Cold Environments (LATICE). Full text in Research Archive
• Nilsen, Irene Brox; Tallaksen, Lena M. & Stordal, Frode (2017). Potential feedbacks between snow cover, soil moisture and surface energy fluxes in Southern Norway. Full text in Research Archive Show summary

  At high latitudes, the snow season has become shorter during the past decades because snowmelt is highly sensitive to a warmer climate. Snowmelt influences the energy balance by changing the albedo and the partitioning between latent and sensible heat fluxes. It further influences the water balance by changing the runoff and soil moisture. In a previous study, we identified southern Norway as a region where significant temperature changes in summer could potentially be explained by land-atmosphere interactions. In this study we hypothesise that changes in snow cover would influence the summer surface fluxes in the succeeding weeks or months. The exceptionally warm summer of 2014 was chosen as a test bed. In Norway, evapotranspiration is not soil moisture limited, but energy limited, under normal conditions. During warm summers, however, such as in 2014, evapotranspiration can be restricted by the available soil moisture. Using the Weather Research and Forecasting (WRF) model we replace the initial ground conditions for 2014 with conditions representative of a snow-poor spring and a snow-rich spring. WRF was coupled to Noah-MP at 3 km horizontal resolution in the inner domain, and the simulations covered mid-May through September 2014. Boundary conditions used to force WRF were taken from the Era-Interim reanalysis. Snow, runoff, soil moisture and soil temperature observational data were provided by the Norwegian Water Resources and Energy Directorate for validation. The validation shows generally good agreement with observations. Preliminary results show that the reduced snowpack, hereafter “sim1” increased the air temperature by up to 5 K and the surface temperature by up to 10 K in areas affected by snow changes. The increased snowpack, hereafter “sim2”, decreased the air and surface temperature by the same amount. These are weekly mean values for the first eight simulation weeks from mid May. Because of the higher net energy available (∼ 100 Wm-2) in sim 1, both the evapotranspiration and sensible heat fluxes increased. In sim 2, they decreased because of lower net energy. The ground heat flux decreased in sim1 (and increased in sim2). Large increases were seen in runoff, both surface and underground runoff, during the first weeks of sim2 (from mid May), but the timing of snowmelt was only slightly affected. This study contributes to a greater understanding of land-atmosphere interactions in a wet, temperate climate, in particular the role of snow cover (and snowmelt) and its feedback to the atmosphere.

• Holter, Øystein Gullvåg; Liestøl, Knut; Tallaksen, Lena M. & Kristensen, Solveig (2016). Universitetene er sterkt konkurransedrevet. I dette løpet taper kvinnene. Kronikk Aftenposten 7.3.2016 http://www.aftenposten.no/meninger/kronikker/Kronikk-Universitetene-er-sterk t-konkurransedrevet-I-dette-lopet-taper-kvinnene-8380246.html. Full text in Research Archive
• Burkhart, John; Schuler, Thomas; Tallaksen, Lena M.; Filhol, Simon; Hulth, John & Decker, Sven (2016). Snow model validation in Norway at the Land Atmosphere Interaction in Cold Environments (LATICE) Finse site. Full text in Research Archive
• Nilsen, Irene Brox; Stagge, James Howard & Tallaksen, Lena M. (2016). A probabilistic approach to attribute warming to changes in atmospheric circulation. Full text in Research Archive Show summary

  Europe has been warming over the past decades, especially in southern Europe in summer and northern Europe in winter. To understand the causes of regional warming, it is common to separate the temperature change signal into changes in atmospheric circulation (or dynamic causes) and other factors, so-called within-type changes (or thermodynamic causes). For example, increasing temperatures due to greenhouse gases may alter the position and strength of the polar jet stream, thus causing a change in the atmospheric circulation signal. On the other hand, warming may be entirely independent of circulation, occurring as a general increase in surface temperature. With the aim to detect regions and time of the year in Europe in which recent warming can either be explained by changes in atmospheric circulation or by within-type changes, we suggest a novel probabilistic approach to calculate the circulation-induced trend, the part of the temperature trend that is induced by changes in atmospheric circulation. Through the use of resampling, in combination with a Monte Carlo test, we assessed the likelihood that the observed temperature trend can be explained entirely by changes in atmospheric circulation frequency. The temperature data originate from the gridded 0.5◦ Watch Forcing Data Era-Interim (WFDEI), and cover the period 1981–2010. The SynopVis Grosswetterlagen catalogue of circulation types was used to detect circulation-induced trends in the same time period. We analysed trends on the monthly time scale to reveal short-term responses, such as those related to snow or greening. The most wide-spread observed warming was found in summer, with up to 60% of the European land area experiencing a significant warming trend during August, most notable in eastern and northern Europe. In spring and autumn, the percent area with significant temperature increases reduced to 10–30%. In December and January, only 5% of the land area experienced significant warming, most pronounced in northern Scandinavia. The probabilistic approach revealed that changes in atmospheric circulation could not account for all the observed warming. Regions where the observed trend likely can be explained entirely by changes in atmospheric circulation include western Europe in May, eastern Europe in August and Scandinavia in September. In most of the regions and months experiencing significant trends, however, warming must be caused by other factors as well; such within-type changes potentially driven by feedbacks between the land surface and atmosphere. For two cases where the magnitude of the temperature trend was strongest, northern Scandinavia in December and in the Black Sea region in November, circulation types warmed over time. This confirms the role of within-type change, i.e., that circulation types changed their properties over time. This study provides an important contribution toward improved understanding of the causes of synoptic-scale temperature change in Europe, more specifically, the relative role of circulation-induced changes and within-type changes.

• Nilsen, Irene Brox; Tallaksen, Lena M. & Stagge, James Howard (2015). A probabilistic method of calculating circulation-induced trends. Full text in Research Archive Show summary

  The water cycle in Europe has changed substantially over the past three decades. Increasing runoff is observed during winter and at northern latitudes in particular. Spring and summer months, as well as southern latitudes, are facing drier conditions. To understand what is driving large-scale changes in runoff, we look into changes in precipitation and temperature and link these to changes in atmospheric circulation. Previous studies have used the method of trend ratios (Cahynová and Huth, 2009) to attribute precipitation and temperature trends to changes in the frequency of circulation types. A trend ratio is the ratio of hypothetical trend, i.e., the trend that would result due to changes in circulation type frequency only, to the observed trend. However, the method of trend ratios has two drawbacks. First, if the observed trend is small, division by a very low value results in a meaningless trend ratio and thus requires a cut-off value to keep the trend ratio within meaningful boundaries. Second, the method does not allow a comparison of the observed trend to the spread of possible outcomes, because the method of hypothetical trends is based on a deterministic model. We propose a new, more robust method for detecting the importance of circulation-induced changes in explaining the observed trends, which has the benefit of being a non-parametric statistical test that assesses the entire range of hypothetical trends. Instead of creating a hypothetical series by replacing the observation on a given day with the long-term climatic mean of a certain month and circulation type (as in the existing trend ratio method), the new approach replaces the observation on a given day with a random sample from the distribution of the variable for the given month and circulation type. The method introduces the possibility to assign a rejection rate, thus allowing statistical significance to be assessed. We apply the method on time series of precipitation and temperature from the gridded 0.5 degree WFDEI dataset, covering Europe (40-65N, 10W-30E). The SynopVis Grosswetterlagen catalogue of circulation types for the time period 1981-2010, the same period as the climatic data, is used. The new approach is used to map in which regions and months changes in atmospheric circulation is the dominating factor controlling changes in precipitation and temperature in Europe.

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