Jiquan Chen, Cheyenne Lei, Housen Chu, Xianglan Li, Margaret Susan Torn, Yingping Wang, P. Sciusco, G. P. Robertson
{"title":"Overlooked cooling effects of albedo in terrestrial ecosystems","authors":"Jiquan Chen, Cheyenne Lei, Housen Chu, Xianglan Li, Margaret Susan Torn, Yingping Wang, P. Sciusco, G. P. Robertson","doi":"10.1088/1748-9326/ad661d","DOIUrl":null,"url":null,"abstract":"\n Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by IPCC assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced radiative forcing (RF¬) and the consequent global warming impact (GWI∆α). We then highlight the shortcomings of available current databases and methodologies for calculating GWI∆α at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from Earth System Models suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI∆α is substantial, exceeding the RF∆α values of IPCC reports. Inclusion of GWIΔα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI∆α component into future Earth System Models.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Research Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1748-9326/ad661d","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by IPCC assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced radiative forcing (RF¬) and the consequent global warming impact (GWI∆α). We then highlight the shortcomings of available current databases and methodologies for calculating GWI∆α at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from Earth System Models suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI∆α is substantial, exceeding the RF∆α values of IPCC reports. Inclusion of GWIΔα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI∆α component into future Earth System Models.