David Painemal, William L. Smith Jr., Siddhant Gupta, Richard Moore, Brian Cairns, Greg M. McFarquhar, Joseph O’Brien
{"title":"局部多云场景中边界层云能否依靠卫星可见光/红外微物理反演?对气候研究的影响","authors":"David Painemal, William L. Smith Jr., Siddhant Gupta, Richard Moore, Brian Cairns, Greg M. McFarquhar, Joseph O’Brien","doi":"10.1029/2024GL113825","DOIUrl":null,"url":null,"abstract":"<p>This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (<i>τ</i>) and droplet effective radius (<i>r</i><sub><i>e</i></sub>) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP <i>r</i><sub><i>e</i></sub> substantially improves when the retrievals are averaged after removing pixels with <i>τ</i> < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of <i>r</i><sub><i>e</i></sub>, and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.</p>","PeriodicalId":12523,"journal":{"name":"Geophysical Research Letters","volume":"52 8","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024GL113825","citationCount":"0","resultStr":"{\"title\":\"Can We Rely on Satellite Visible/Infrared Microphysical Retrievals of Boundary Layer Clouds in Partially Cloudy Scenes? Implications for Climate Research\",\"authors\":\"David Painemal, William L. Smith Jr., Siddhant Gupta, Richard Moore, Brian Cairns, Greg M. McFarquhar, Joseph O’Brien\",\"doi\":\"10.1029/2024GL113825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (<i>τ</i>) and droplet effective radius (<i>r</i><sub><i>e</i></sub>) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP <i>r</i><sub><i>e</i></sub> substantially improves when the retrievals are averaged after removing pixels with <i>τ</i> < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of <i>r</i><sub><i>e</i></sub>, and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.</p>\",\"PeriodicalId\":12523,\"journal\":{\"name\":\"Geophysical Research Letters\",\"volume\":\"52 8\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024GL113825\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geophysical Research Letters\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2024GL113825\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Research Letters","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024GL113825","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Can We Rely on Satellite Visible/Infrared Microphysical Retrievals of Boundary Layer Clouds in Partially Cloudy Scenes? Implications for Climate Research
This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (τ) and droplet effective radius (re) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP re substantially improves when the retrievals are averaged after removing pixels with τ < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of re, and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.
期刊介绍:
Geophysical Research Letters (GRL) publishes high-impact, innovative, and timely research on major scientific advances in all the major geoscience disciplines. Papers are communications-length articles and should have broad and immediate implications in their discipline or across the geosciences. GRLmaintains the fastest turn-around of all high-impact publications in the geosciences and works closely with authors to ensure broad visibility of top papers.