TY  - JOUR
AU  - Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
PY  - 2020
DA  - 2020//
TI  - A framework for estimating cloudy sky surface downward longwave radiation from the derived active and passive cloud property parameters
JO  - Remote Sensing of Environment
VL  - 248 %KSurface downward longwave radiation;Cloud-base temperature;Cloud-top temperature;Cloud thickness;Single-layer cloud model;Remote sensing
CY  - State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China;;Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
AB  - Abstract(#br)The cloud-base temperature (CBT) is one of the parameters that dominates the cloudy sky surface downward longwave radiation (SDLR). However, CBT is rarely available at regional and global scales, and its application in estimating cloud sky SDLR is limited. In this study, a framework to globally estimate cloud sky SDLR during both daytime and nighttime is proposed. This framework is composed of three parts. First, a global cloudy property database was constructed by combing the extracted cloud vertical structure (CVS) parameters from the active CloudSat data and cloud properties from passive MODIS data. Second, the empirical methods for estimating cloud thickness (CT) under ISCCP cloud classification system and MODIS cloud classification system were developed. Additionally, the coefficients of CERES CT estimate models were refitted using the constructed cloud property database. With the estimated CT and reanalysis data, calculating the CBT is straightforward. The accuracy of the estimated CT for I...
SN  - 0034-4257
UR  - https://kns.cnki.net/kcms2/article/abstract?v=FruxrO_GJXLvQA8UIi-QKQNqV8fOwQ66a-4ZnCEYnCWvxpfBZgSwGBVPRRZVgljQyWOav6yUqK6JCeErYK3_JGdDxfbkVSBSfT8BMC3nFi18gP5vHGyB7GL4Qvq2ibTCU-FCAPEJnDVsnlXv5tY-WDCeUulLM4N66hv97vbvC5c=&uniplatform=NZKPT&language=CHS
ID  - InstituteofRemoteSensingScienceandEngineering2020
ER  -