Haochi Che

• Che, Haochi; Zhang, Lu; Segal-Rozenhaimer, Michal; Dang, Caroline; Zuidema, Paquita & III, Arthur J. Sedlacek (2025). Aerosol hygroscopicity over the South-East Atlantic Ocean during the biomass burning season – Part 2: Influence of sea salt and burning conditions on CCN hygroscopicity. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 25(18), p. 10987–11002. doi: 10.5194/acp-25-10987-2025. Full text in Research Archive Show summary

  Biomass burning (BB) significantly influences cloud condensation nuclei (CCN) concentrations over the southeastern Atlantic; however, aerosol hygroscopicity (κ) – a key factor for CCN activation – remains poorly constrained during the BB season. This study investigates κ variability using in situ measurements from Ascension Island during the 2016 and 2017 BB seasons. Results show substantial monthly variability, with κ values lowest in August and increasing through October. On average, κ was significantly higher in 2017 (∼ 0.55) than in 2016 (∼ 0.33), suggesting that the aerosols in 2017 were more hygroscopic and more easily activated as CCN. Sulfate and sea salt were the two dominant contributors to κ and the primary drivers of its interannual variability. During the 2017 BB season, sulfate – the major inorganic component – accounted for ∼ 34 % of the submicron aerosol mass, while sea salt, estimated via κ-closure analysis, contributed ∼ 17 %. The higher κ in 2017 was largely attributed to increased sea salt, likely driven by stronger marine winds. Approximately 67 % of sulfate was linked to BB emissions. Variations in BB combustion efficiency, modulated by regional meteorology, influenced sulfate fraction and thus κ values. Specifically, higher relative humidity and lower wind speeds over BB source regions in 2017 favored smoldering combustion, explaining the higher sulfate fraction. Overall, the observed interannual differences in aerosol hygroscopicity reflect the combined impacts of BB combustion characteristics and sea salt emissions, underscoring the critical roles of both BB and marine aerosol sources in regulating aerosol-cloud interactions over the southeastern Atlantic.

• Hellmuth, Franziska; Carlsen, Tim; Daloz, Anne Sophie; David, Robert Oscar; Che, Haochi & Storelvmo, Trude (2025). Evaluation of biases in mid-to-high-latitude surface snowfall and cloud phase in ERA5 and CMIP6 using satellite observations. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 25(2), p. 1353–1383. doi: 10.5194/acp-25-1353-2025. Full text in Research Archive Show summary

  Supercooled liquid-containing clouds (sLCCs) play a significant role in Earth's radiative budget and the hydrological cycle, especially through surface snowfall production. Evaluating state-of-the-art climate models with respect to their ability to simulate the frequency of occurrence of sLCCs and the frequency with which they produce snow is, therefore, critically important. Here, we compare these quantities as derived from satellite observations, reanalysis datasets, and Earth system models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and find significant discrepancies between the datasets for mid- and high latitudes in both hemispheres. Specifically, we find that the ERA5 reanalysis and 10 CMIP6 models consistently overestimate the frequency of sLCCs and snowfall frequencies from sLCCs compared to CloudSat–CALIPSO satellite observations. The biases are very similar for ERA5 and the CMIP6 models, which indicates that the discrepancies in cloud phase and snowfall stem from differences in the representation of cloud microphysics rather than the representation of meteorological conditions. This, in turn, highlights the need for refinements in the models’ parameterizations of cloud microphysics in order for them to represent cloud phase and snowfall accurately. The thermodynamic phase of clouds and precipitation has a strong influence on simulated climate feedbacks and, thus, projections of future climate. Understanding the origin(s) of the biases identified here is, therefore, crucial for improving the overall reliability of climate models.

• Zhang, Lu; Segal-Rozenhaimer, Michal; Che, Haochi; Dang, Caroline; Sun, Junying & Kuang, Ye [Show all 8 contributors for this article] (2024). Aerosol hygroscopicity over the southeast Atlantic Ocean during the biomass burning season - Part 1: From the perspective of scattering enhancement. Atmospheric Chemistry and Physics (ACP). ISSN 1680-7316. 24(23), p. 13849–13864. doi: 10.5194/acp-24-13849-2024. Full text in Research Archive Show summary

  Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f(RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f(80 %) from ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the southeast Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f(80 %) of 1.40 ± 0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f(80 %) of 1.51 ± 0.22, consistent with higher values of BB aerosol hygroscopicity found in the literature. The hygroscopicity parameter of OA (κOA) is retrieved from the Mie model with a mean value of 0.11 ± 0.08, which is in the middle to upper range compared to the literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced biomass burning aerosol (BBA) hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulfate fraction, and greater κOA at lower altitudes. We propose a parameterization that quantifies f(RH) with chemical composition and κOA based on Mie simulation of internally mixed OA–(NH4)2SO4–BC mixtures. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA–(NH4)2SO4–BC internal mixture with respect to the f(RH) prediction. The sensitivity of f(RH) to κOA indicates that applying a constant κOA is only suitable when the OA fraction is low and κOA shows limited variation. However, in situations deviating these two criteria, κOA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κOA variability is recommended.

• Rozenhaimer, Michal Segal; Nukrai, David; Che, Haochi; Wood, Robert & Zhang, Zhibo (2023). Cloud Mesoscale Cellular Classification and Diurnal Cycle Using a Convolutional Neural Network (CNN). Remote Sensing. 15(6). doi: 10.3390/rs15061607. Full text in Research Archive Show summary

  Marine stratocumulus (MSC) clouds are important to the climate as they cover vast areas of the ocean’s surface, greatly affecting radiation balance of the Earth. Satellite imagery shows that MSC clouds exhibit different morphologies of closed or open mesoscale cellular convection (MCC) but many limitations still exist in studying MCC dynamics. Here, we present a convolutional neural network algorithm to classify pixel-level closed and open MCC cloud types, trained by either visible or infrared channels from a geostationary SEVIRI satellite to allow, for the first time, their diurnal detection, with a 30 min. temporal resolution. Our probability of detection was 91% and 92% for closed and open MCC, respectively, which is in line with day-only detection schemes. We focused on the South-East Atlantic Ocean during months of biomass burning season, between 2016 and 2018. Our resulting MCC type area coverage, cloud effective radii, and cloud optical depth probability distributions over the research domain compare well with monthly and daily averages from MODIS. We further applied our algorithm on GOES-16 imagery over the South-East Pacific (SEP), another semi-permanent MCC domain, and were able to show good prediction skills, thereby representing the SEP diurnal cycle and the feasibility of our method to be applied globally on different satellite platforms.

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• Zhang, Lu; Skov, Henrik; Massling, Andreas; Dall’Osto, Manuel; Evangeliou, Nikolaos & Che, Haochi [Show all 8 contributors for this article] (2026). Long-term trend of elemental carbon in the high Arctic and its potential drivers. doi: 10.5194/egusphere-egu26-17708. Full text in Research Archive Show summary

  The Arctic is warming at more than twice the global average rate, a phenomenon known as Arctic amplification (Rantanen et al., 2022). In addition to greenhouse gases, short-lived climate forcers play a critical role in modulating Arctic climate through their impacts on radiation, cloud properties, and the surface energy balance (e.g. AMAP, 2015, 2021). Among these forcers, elemental carbon (EC) is of particular importance due to its strong light-absorbing properties and its ability to reduce surface albedo when deposited on snow and ice. Furthermore, aged EC particles transported to the Arctic can act as cloud condensation nuclei, influencing cloud microphysical processes and thereby modifying Arctic radiative forcing and climate feedbacks.In this study, we investigate long-term trends in EC concentrations and their potential drivers in the high Arctic using 16 years of continuous EC measurements from the Villum Research Station in northeast Greenland. We combine in situ observations with Lagrangian transport modelling and back-trajectory analyses to assess the relative contributions of changes in source-region emissions, transport pathway variability, and wet scavenging processes to the observed EC trends. Robust non-parametric statistical methods are applied to assess monotonic trends over the full observational period and before 2020, enabling a systematic comparison between the declining and stagnating phases. This integrated observational–modelling framework provides new constraints on the processes controlling EC variability in the Arctic and advances our understanding of how anthropogenic emission reductions are reflected in Arctic atmospheric composition under a rapidly evolving climate.

• Zhang, Lu; Skov, Henrik; Massling, Andreas; Dall’Osto, Manuel; Evangeliou, Nikolaos & Che, Haochi [Show all 8 contributors for this article] (2026). Evolving Anthropogenic and Natural Aerosol Sources in the High Arctic. Full text in Research Archive

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