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Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018

State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
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Academic Editor: Steven Dewitte
Remote Sens. 2021, 13(9), 1848; https://doi.org/10.3390/rs13091848
Received: 28 March 2021 / Revised: 23 April 2021 / Accepted: 3 May 2021 / Published: 9 May 2021
(This article belongs to the Special Issue Advances on Land–Ocean Heat Fluxes Using Remote Sensing)
It is of great importance for climate change studies to construct a worldwide, long-term surface downward longwave radiation (Ld, 4–100 μm) dataset. Although a number of global Ld datasets are available, their low accuracies and coarse spatial resolutions limit their applications. This study generated a daily Ld dataset with a 5-km spatial resolution over the global land surface from 2000 to 2018 using atmospheric parameters, which include 2-m air temperature (Ta), relative humidity (RH) at 1000 hPa, total column water vapor (TCWV), surface downward shortwave radiation (Sd), and elevation, based on the gradient boosting regression tree (GBRT) method. The generated Ld dataset was evaluated using ground measurements collected from AmeriFlux, AsiaFlux, baseline surface radiation network (BSRN), surface radiation budget network (SURFRAD), and FLUXNET networks. The validation results showed that the root mean square error (RMSE), mean bias error (MBE), and correlation coefficient (R) values of the generated daily Ld dataset were 17.78 W m−2, 0.99 W m−2, and 0.96 (p < 0.01). Comparisons with other global land surface radiation products indicated that the generated Ld dataset performed better than the clouds and earth’s radiant energy system synoptic (CERES-SYN) edition 4.1 dataset and ERA5 reanalysis product at the selected sites. In addition, the analysis of the spatiotemporal characteristics for the generated Ld dataset showed an increasing trend of 1.8 W m−2 per decade (p < 0.01) from 2003 to 2018, which was closely related to Ta and water vapor pressure. In general, the generated Ld dataset has a higher spatial resolution and accuracy, which can contribute to perfect the existing radiation products. View Full-Text
Keywords: surface downward longwave radiation; air temperature; relative humidity; surface downward shortwave radiation; total column water vapor; gradient boosting regression tree surface downward longwave radiation; air temperature; relative humidity; surface downward shortwave radiation; total column water vapor; gradient boosting regression tree
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MDPI and ACS Style

Feng, C.; Zhang, X.; Wei, Y.; Zhang, W.; Hou, N.; Xu, J.; Yang, S.; Xie, X.; Jiang, B. Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018. Remote Sens. 2021, 13, 1848. https://doi.org/10.3390/rs13091848

AMA Style

Feng C, Zhang X, Wei Y, Zhang W, Hou N, Xu J, Yang S, Xie X, Jiang B. Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018. Remote Sensing. 2021; 13(9):1848. https://doi.org/10.3390/rs13091848

Chicago/Turabian Style

Feng, Chunjie, Xiaotong Zhang, Yu Wei, Weiyu Zhang, Ning Hou, Jiawen Xu, Shuyue Yang, Xianhong Xie, and Bo Jiang. 2021. "Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018" Remote Sensing 13, no. 9: 1848. https://doi.org/10.3390/rs13091848

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