Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF)

被引:13
作者
Fibbi, Luca [1 ,2 ]
Maselli, Fabio [1 ]
Pieri, Maurizio [1 ]
机构
[1] Natl Res Council IBE CNR, Inst BioEcon, Via Madonna Piano 10, I-50019 Sesto Fiorentino, Italy
[2] LaMMA Consortium, Sesto Fiorentino, Italy
关键词
DEM; disaggregation; global solar radiation; topographic correction; IRRADIANCE; VALIDATION; TEMPERATURE; ALGORITHM; HUMIDITY; NETWORK; MODELS;
D O I
10.1002/met.1940
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper presents a new method to predict global solar radiation over irregular terrain, named Estimation of global solar RADiation (ERAD). The method is based on the disaggregation of Satellite Applications Facility on Land Surface Analysis (LSA SAF) data using a digital elevation model and is applied in Italy with a time step of 1 min and a spatial resolution of 200 m. A quantitative assessment of ERAD is performed in comparison with three other standard methods (Mountain Microclimate Simulation Model [MTCLIM], LSA SAF and Copernicus Atmosphere Monitoring Service [CAMS]) using measurements taken in 43 stations located in Italy or in the surrounding countries, in the years 2005-2016. Such assessment concerns the irradiance incoming on a horizontal surface, which is measured by ground radiation sensors and is summarized by means of four accuracy statistics (i.e. mean absolute error [MAE], root mean square error [RMSE], coefficient of determination [R-2] and mean bias error [MBE]). Overall, the average daily global solar radiation estimates obtained by ERAD have RMSE andR(2)about 25 W center dot m(-2)and 0.943, respectively. These statistics are similar to those of LSA SAF and better than those of CAMS and, above all, MTCLIM. The bias analysis by elevation ranges shows a slight ERAD overestimation over plains and hills and a slight underestimation over mountains. An additional qualitative assessment shows how the ERAD radiation estimates are more spatially detailed than those of the other methods and are redistributed on inclined surfaces consistently with expectations.
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页数:18
相关论文
共 52 条
[1]   Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale [J].
Aguilar, C. ;
Herrero, J. ;
Polo, M. J. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2010, 14 (12) :2479-2494
[2]  
[Anonymous], 1983, INTRO SOLAR RAD
[3]  
[Anonymous], 2009, P ISRSE 33 STRES IT
[4]   Evaluation of decomposition models of various complexity to estimate the direct solar irradiance over Belgium [J].
Bertrand, Cedric ;
Vanderveken, Gilles ;
Journee, Michel .
RENEWABLE ENERGY, 2015, 74 :618-626
[5]   Modifications of the Heliosat procedure for irradiance estimates from satellite images [J].
Beyer, HG ;
Costanzo, C ;
Heinemann, D .
SOLAR ENERGY, 1996, 56 (03) :207-212
[6]   Global evaluation of MTCLIM and related algorithms for forcing of ecological and hydrological models [J].
Bohn, Theodore J. ;
Livneh, Ben ;
Oyler, Jared W. ;
Running, Steve W. ;
Nijssen, Bart ;
Lettenmaier, Dennis P. .
AGRICULTURAL AND FOREST METEOROLOGY, 2013, 176 :38-49
[7]  
CAMS, 2019, US GUID CAMS RAD SER
[8]   A METHOD FOR THE DETERMINATION OF THE GLOBAL SOLAR-RADIATION FROM METEOROLOGICAL SATELLITE DATA [J].
CANO, D ;
MONGET, JM ;
ALBUISSON, M ;
GUILLARD, H ;
REGAS, N ;
WALD, L .
SOLAR ENERGY, 1986, 37 (01) :31-39
[9]   Satellite Retrieval of Downwelling Shortwave Surface Flux and Diffuse Fraction under All Sky Conditions in the Framework of the LSA SAF Program (Part 1: Methodology) [J].
Carrer, Dominique ;
Ceamanos, Xavier ;
Moparthy, Suman ;
Vincent, Chloe ;
Freitas, Sandra C. ;
Trigo, Isabel F. .
REMOTE SENSING, 2019, 11 (21)
[10]   Satellite Retrieval of Downwelling Shortwave Surface Flux and Diffuse Fraction under All Sky Conditions in the Framework of the LSA SAF Program (Part 2: Evaluation) [J].
Carrer, Dominique ;
Moparthy, Suman ;
Vincent, Chloe ;
Ceamanos, Xavier ;
Freitas, Sandra C. ;
Trigo, Isabel F. .
REMOTE SENSING, 2019, 11 (22)