Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018JD029021 |
Observation-Based Radiative Kernels From CloudSat/CALIPSO | |
Kramer, Ryan J.1; 39;Ecuyer, Tristan S.2 | |
2019-05-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2019 |
卷号 | 124期号:10页码:5431-5444 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Radiative kernels describe the differential response of radiative fluxes to small perturbations in state variables and are widely used to quantify radiative feedbacks on the climate system. Radiative kernels have traditionally been generated using simulated data from a global climate model, typically sourced from the model's base climate. Consequently, these radiative kernels are subject to model bias from the climatological fields used to produce them. Here, we introduce the first observation-based temperature, water vapor, and surface albedo radiative kernels, developed from CloudSat's fluxes and heating rates data set, 2B-FLXHR-LIDAR, which is supplemented with cloud information from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). We compare the radiative kernels to a previously published set generated from the Geophysical Fluid Dynamics Laboratory (GFDL) model and find general agreement in magnitude and structure. However, several key differences illustrate the sensitivity of radiative kernels to the distribution of clouds. The radiative kernels are used to quantify top-of-atmosphere and surface cloud feedbacks in an ensemble of global climate models from the Climate Model Intercomparison Project Phase 5, showing that biases in the GFDL low clouds likely cause the GFDL kernel to underestimate longwave surface cloud feedback. Since the CloudSat kernels are free of model bias in the base state, they will be ideal for future analysis of radiative feedbacks and forcing in both models and observations and for evaluating biases in model-derived radiative kernels. |
英文关键词 | radiative kernel cloud feedback cloud masking remote sensing cloud distribution |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000471237200017 |
WOS关键词 | CLIMATE FEEDBACKS ; ATMOSPHERE ; PERSPECTIVE ; SURFACE ; CLOUDS |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/183350 |
专题 | 气候变化 |
作者单位 | 1.Univ Miami, Rosenstiel Sch Marine & Atmospher Sci, 4600 Rickenbacker Causeway, Miami, FL 33149 USA; 2.Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI USA |
推荐引用方式 GB/T 7714 | Kramer, Ryan J.,39;Ecuyer, Tristan S.. Observation-Based Radiative Kernels From CloudSat/CALIPSO[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(10):5431-5444. |
APA | Kramer, Ryan J.,&39;Ecuyer, Tristan S..(2019).Observation-Based Radiative Kernels From CloudSat/CALIPSO.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(10),5431-5444. |
MLA | Kramer, Ryan J.,et al."Observation-Based Radiative Kernels From CloudSat/CALIPSO".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.10(2019):5431-5444. |
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