Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

Abstract The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Overall, this work provides a unique analysis of cloud and radiation properties based on high‐resolution shipborne observations, which can be used to assist future model evaluation and development.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-11-21
DOI
https://doi.org/10.1029/2025jd044239
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
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article

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

Neel Desai, Yang Shi, Xiaohong Liu, Jagdev Singh et al.
Journal of Geophysical Research Atmospheres
Atmospheric aerosols and clouds
article

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

Neel Desai, Yang Shi, Xiaohong Liu, Jagdev Singh, Minghui Diao
article en

Abstract

Abstract The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Overall, this work provides a unique analysis of cloud and radiation properties based on high‐resolution shipborne observations, which can be used to assist future model evaluation and development.

Journal of Geophysical Research AtmospheresVol. 130(22)
Pacific Northwest National Laboratory (US), San Jose State University (US), Massachusetts Institute of Technology (US), Texas A&M University (US)
Openalex Percentile: Top 67%
Atmospheric aerosols and clouds
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