IGSNRR OpenIR
Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky
Wang, Chunlei1,2; Tang, Bo-Hui1,2; Wu, Hua1,2; Tang, Ronglin1,2; Li, Zhao-Liang1,2,3
2017-03-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume9Issue:3Pages:19
Corresponding AuthorTang, Bo-Hui(tangbh@igsnrr.ac.cn)
AbstractThe variation of aerosols, especially dust aerosol, in time and space plays an important role in climate forcing studies. Aerosols can effectively reduce land surface longwave emission and re-emit energy at a colder temperature, which makes it difficult to estimate downwelling surface longwave radiation (DSLR) with satellite data. Using the latest atmospheric radiative transfer code (MODTRAN 5.0), we have simulated the outgoing longwave radiation (OLR) and DSLR under different land surface types and atmospheric profile conditions. The results show that dust aerosol has an obvious warming effect to longwave radiation compared with other aerosols; that aerosol longwave radiative forcing (ALRF) increased with the increasing of aerosol optical depth (AOD); and that the atmospheric water vapor content (WVC) is critical to the understanding of ALRF. A method is proposed to improve the accuracy of DSLR estimation from satellite data for the skies under heavy dust aerosols. The AOD and atmospheric WVC under cloud-free conditions with a relatively simple satellite-based radiation model yielding the high accurate DSLR under heavy dust aerosol are used explicitly as model input to reduce the effects of dust aerosol on the estimation of DSLR. Validations of the proposed model with satellites data and field measurements show that it can estimate the DSLR accurately under heavy dust aerosol skies. The root mean square errors (RMSEs) are 20.4 W/m(2) and 24.2 W/m(2) for Terra and Aqua satellites, respectively, at the Yingke site, and the biases are 2.7 W/m(2) and 9.6 W/m(2), respectively. For the Arvaikheer site, the RMSEs are 23.2 W/m(2) and 19.8 W/m(2) for Terra and Aqua, respectively, and the biases are 7.8 W/m(2) and 10.5 W/m(2), respectively. The proposed method is especially applicable to acquire relatively high accurate DSLR under heavy dust aerosol using MODIS data with available WVC and AOD data.
Keyworddownwelling surface longwave radiation (DSLR) dust aerosol aerosol optical depth (AOD) MODIS
DOI10.3390/rs9030207
WOS KeywordURBAN COASTAL SITE ; MINERAL DUST ; SAHARAN DUST ; CERES OBSERVATIONS ; OPTICAL-PROPERTIES ; IBERIAN PENINSULA ; CLOUDY SKIES ; MODIS DATA ; DESERT ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFA0600103] ; National Natural Science Foundation of China[41571353] ; National Natural Science Foundation of China[41231170] ; Innovation Project of LREIS[O88RA801YA]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China ; Innovation Project of LREIS
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000398720100021
PublisherMDPI AG
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64636
Collection中国科学院地理科学与资源研究所
Corresponding AuthorTang, Bo-Hui
Affiliation1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Agr Sci, Key Lab Agriinformat, Minist Agr, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
Recommended Citation
GB/T 7714
Wang, Chunlei,Tang, Bo-Hui,Wu, Hua,et al. Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky[J]. REMOTE SENSING,2017,9(3):19.
APA Wang, Chunlei,Tang, Bo-Hui,Wu, Hua,Tang, Ronglin,&Li, Zhao-Liang.(2017).Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky.REMOTE SENSING,9(3),19.
MLA Wang, Chunlei,et al."Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky".REMOTE SENSING 9.3(2017):19.
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