作者:Zhou, YJ (Zhou, Yingji)[ 1,2,3 ] ; Yan, GJ (Yan, Guangjian)[ 1,2,3 ] ; Zhao, J (Zhao, Jing)[ 4 ] ; Chu, Q (Chu, Qing)[ 1,2,3 ] ; Liu, YN (Liu, Yanan)[ 1,2,3 ] ; Yan, K (Yan, Kai)[ 1,2,3 ] ; Tong, YY (Tong, Yiyi)[ 1,2,3 ] ; Mu, XH (Mu, Xihan)[ 1,2,3 ] ; Xie, DH (Xie, Donghui)[ 1,2,3 ] ; Zhang, WM (Zhang, Wuming)[ 1,2,3 ]

REMOTE SENSING

卷: 10  期: 3

文献号: 422

DOI: 10.3390/rs10030422

出版年: MAR 2018

文献类型:Article

摘要

Surface shortwave (SW) irradiation is the primary driving force of energy exchange in the atmosphere and land interface. The global climate is profoundly influenced by irradiation changes due to the special climatic condition in Antarctica. Remote-sensing retrieval can offer only the instantaneous values in an area, whilst daily cycle and average values are necessary for further studies and applications, including climate change, ecology, and land surface process. When considering the large values of and small diurnal changes of solar zenith angle and cloud coverage, we develop two methods for the temporal extension of remotely sensed downward SW irradiance over Antarctica. The first one is an improved sinusoidal method, and the second one is an interpolation method based on cloud fraction change. The instantaneous irradiance data and cloud products are used in both methods to extend the diurnal cycle, and obtain the daily average value. Data from South Pole and Georg von Neumayer stations are used to validate the estimated value. The coefficient of determination (R-2) between the estimated daily averages and the measured values based on the first method is 0.93, and the root mean square error (RMSE) is 32.21 W/m(2) (8.52%). As for the traditional sinusoidal method, the R-2 and RMSE are 0.68 and 70.32 W/m(2) (18.59%), respectively The R-2 and RMSE of the second method are 0.96 and 25.27 W/m(2) (6.98%), respectively. These values are better than those of the traditional linear interpolation (0.79 and 57.40 W/m(2) (15.87%)).

通讯作者地址: Yan, GJ (通讯作者)

Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

通讯作者地址: Yan, GJ (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100875, Peoples R China.

通讯作者地址: Yan, GJ (通讯作者)

Beijing Normal Univ, Beijing Engn Res Ctr Global Land Remote Sensing P, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100875, Peoples R China

[ 3 ] Beijing Normal Univ, Beijing Engn Res Ctr Global Land Remote Sensing P, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing 100875, Peoples R China

[ 4 ] Harbin Inst Technol, Shenzhen Grad Sch, Shenzhen 518000, Peoples R China