Articles | Volume 26, issue 5
https://doi.org/10.5194/acp-26-3653-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-3653-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Past, present, and future arctic radiative states simulated by Polar-WRF
Cameron Bertossa
CORRESPONDING AUTHOR
Dept. Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
Tristan L'Ecuyer
Dept. Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
Cooperative Institute for Meteorological Satellite Studies, Madison, Wisconsin, USA
David Henderson
Dept. Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo
EGUsphere, https://doi.org/10.5194/egusphere-2023-2463, https://doi.org/10.5194/egusphere-2023-2463, 2023
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A cloud detection mask algorithm is developed for the upcoming Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) satellite mission to be launched by NASA in May 2024. The cloud mask is compared to "truth" and is capable of detecting over 90 % of all clouds globally tested with simulated data, and about 87 % of all clouds in the Arctic region.
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This study addresses the long-standing challenge of quantifying the impact of aerosol–cloud interactions. Using satellite observations, reanalysis data, and a "perfect-model" cross-validation, we show that explicitly accounting for aerosol–cloud droplet activation rates is key to accurately estimating ERFaci (effective radiative forcing due to aerosol–cloud interactions). Our results indicate a smaller and less uncertain ERFaci than previously assessed, implying the reduced role of aerosol–cloud interactions in shaping climate sensitivity.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2040, https://doi.org/10.5194/egusphere-2024-2040, 2024
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PREFIRE uses two CubeSats to make novel measurements of outgoing energy. The CubeSats will frequently resample regions, forming orbit “intersections” that reveal how polar processes impact thermal emissions. This study develops new methods to characterize orbit intersections and applies them to simulated PREFIRE orbits to assess the hypothetical resampling distribution. Generalizing our results informs future missions that two CubeSats at different altitudes greatly enhance resampling coverage.
Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo
EGUsphere, https://doi.org/10.5194/egusphere-2023-2463, https://doi.org/10.5194/egusphere-2023-2463, 2023
Preprint archived
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A cloud detection mask algorithm is developed for the upcoming Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) satellite mission to be launched by NASA in May 2024. The cloud mask is compared to "truth" and is capable of detecting over 90 % of all clouds globally tested with simulated data, and about 87 % of all clouds in the Arctic region.
R. Bradley Pierce, Monica Harkey, Allen Lenzen, Lee M. Cronce, Jason A. Otkin, Jonathan L. Case, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 9613–9635, https://doi.org/10.5194/acp-23-9613-2023, https://doi.org/10.5194/acp-23-9613-2023, 2023
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We evaluate two high-resolution model simulations with different meteorological inputs but identical chemistry and anthropogenic emissions, with the goal of identifying a model configuration best suited for characterizing air quality in locations where lake breezes commonly affect local air quality along the Lake Michigan shoreline. This analysis complements other studies in evaluating the impact of meteorological inputs and parameterizations on air quality in a complex environment.
Jason A. Otkin, Lee M. Cronce, Jonathan L. Case, R. Bradley Pierce, Monica Harkey, Allen Lenzen, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 7935–7954, https://doi.org/10.5194/acp-23-7935-2023, https://doi.org/10.5194/acp-23-7935-2023, 2023
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We performed model simulations to assess the impact of different parameterization schemes, surface initialization datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were run with high-resolution, real-time datasets depicting lake surface temperatures, green vegetation fraction, and soil moisture. The most accurate results were obtained when using high-resolution sea surface temperature and soil datasets to constrain the model simulations.
Alyson Rose Douglas and Tristan L'Ecuyer
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-688, https://doi.org/10.5194/acp-2022-688, 2022
Revised manuscript not accepted
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Aerosol, or small particles released by human activities, enter the atmosphere and eventually interact with clouds in what we term aerosol-cloud interactions. As more aerosol enter a cloud, they act as cloud droplet nuclei, increasing the number of cloud droplets in a cloud and delaying rain formation, leading to a larger cloud. We use machine learning and found that these interactions lead to 1.27 % more cloudiness on Earth and offset ~1/4 of the warming due to CO2.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
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We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
Michael R. Gallagher, Matthew D. Shupe, Hélène Chepfer, and Tristan L'Ecuyer
The Cryosphere, 16, 435–450, https://doi.org/10.5194/tc-16-435-2022, https://doi.org/10.5194/tc-16-435-2022, 2022
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By using direct observations of snowfall and mass changes, the variability of daily snowfall mass input to the Greenland ice sheet is quantified for the first time. With new methods we conclude that cyclones west of Greenland in summer contribute the most snowfall, with 1.66 Gt per occurrence. These cyclones are contextualized in the broader Greenland climate, and snowfall is validated against mass changes to verify the results. Snowfall and mass change observations are shown to agree well.
Alyson Douglas and Tristan L'Ecuyer
Atmos. Chem. Phys., 21, 15103–15114, https://doi.org/10.5194/acp-21-15103-2021, https://doi.org/10.5194/acp-21-15103-2021, 2021
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When aerosols enter the atmosphere, they interact with the clouds above in what we term aerosol–cloud interactions and lead to a series of reactions which delay the onset of rain. This delay may lead to increased rain rates, or invigoration, when the cloud eventually rains. We show that aerosol leads to invigoration in certain environments. The strength of the invigoration depends on how large the cloud is, which suggests that it is highly tied to the organization of the cloud system.
Erik Johansson, Abhay Devasthale, Michael Tjernström, Annica M. L. Ekman, Klaus Wyser, and Tristan L'Ecuyer
Geosci. Model Dev., 14, 4087–4101, https://doi.org/10.5194/gmd-14-4087-2021, https://doi.org/10.5194/gmd-14-4087-2021, 2021
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Understanding the coupling of clouds to large-scale circulation is a grand challenge for the climate community. Cloud radiative heating (CRH) is a key parameter in this coupling and is therefore essential to model realistically. We, therefore, evaluate a climate model against satellite observations. Our findings indicate good agreement in the seasonal pattern of CRH even if the magnitude differs. We also find that increasing the horizontal resolution in the model has little effect on the CRH.
Andrew M. Dzambo, Tristan L'Ecuyer, Kenneth Sinclair, Bastiaan van Diedenhoven, Siddhant Gupta, Greg McFarquhar, Joseph R. O'Brien, Brian Cairns, Andrzej P. Wasilewski, and Mikhail Alexandrov
Atmos. Chem. Phys., 21, 5513–5532, https://doi.org/10.5194/acp-21-5513-2021, https://doi.org/10.5194/acp-21-5513-2021, 2021
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This work highlights a new algorithm using data collected from the 2016–2018 NASA ORACLES field campaign. This algorithm synthesizes cloud and rain measurements to attain estimates of cloud and precipitation properties over the southeast Atlantic Ocean. Estimates produced by this algorithm compare well against in situ estimates. Increased rain fractions and rain rates are found in regions of atmospheric instability. This dataset can be used to explore aerosol–cloud–precipitation interactions.
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Short summary
This study evaluates how well an Arctic-specific model can capture two key cloud states that control how the region traps surface radiation. The model reproduces these states better than others but still produces too many thick, low clouds. With further improvements, it could offer valuable insight into how Arctic cloud behavior and surface heat balance may evolve under future climate change.
This study evaluates how well an Arctic-specific model can capture two key cloud states that...
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