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Journal of Arid Land
Journal of Arid Land  2025, Vol. 17 Issue (6): 772-790    DOI: 10.1007/s40333-025-0081-z     CSTR: 32276.14.JAL.0250081z
Review article     
Spatiotemporal distribution characteristics of clear-sky downward surface shortwave radiation in Xinjiang
HUANG Guan1, CHEN Yonghang2, WANG Pengtao1,*(), FAN Ting1, HE Qing3, SHAO Weiling4, SUN Linlin2
1College of Tourism, Xi'an International Studies University, Xi'an 710128, China
2College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
3Taklimakan Desert Meteorology Field Experiment Station of CMA, Institute of Desert Meteorology, China Meteorological Administration (CMA), Urumqi 830002, China
4Xinjiang Climate Center, Urumqi 830002, China
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Abstract  

Given that Xinjiang Uygur Autonomous Region of China possesses exceptionally abundant solar radiation resources that can be harnessed to develop clean energy, accurately characterizing their spatiotemporal distribution is crucial. This study investigated the applicability of the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product downward surface shortwave radiation dataset (DSSRCER) under clear-sky conditions in Xinjiang. By integrating multi-source data and utilizing techniques like multivariate fitting and model simulation, we established a two-layer aerosol model and developed a clear-sky downward surface shortwave radiation (DSSR) retrieval model specific to Xinjiang using the Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART) model. We further explored the spatiotemporal distribution characteristics of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019 based on the localized DSSR retrieval model. Our findings revealed a significant discrepancy in DSSRCER under clear-sky conditions at the Xiaotang station in Xinjiang. By comparing, screening, and correcting core input parameters while incorporating the two-layer aerosol model, we achieved a more accurate SBDART simulated DSSR (DSSRSBD) compared to DSSRCER. The annual mean DSSR exhibited a distinct distribution pattern with high values in mountainous regions such as the Altay Mountains, Kunlun Mountains, and Tianshan Mountains and significantly lower values in adjacent lowland areas, including the Tarim River Basin and Junggar Basin. In the four typical administrative regions in northern Xinjiang, the annual mean DSSR (ranging from 551.60 to 586.09 W/m2) was lower than that in the five typical administrative regions in southern Xinjiang (ranging from 522.10 to 623.62 W/m2). These spatial variations stem from a complex interplay of factors, including latitude, altitude, solar altitude angle, and sunshine duration. The variations in seasonal average DSSR aligned closely with variations in the solar altitude angle, with summer (774.76 W/m2) exhibiting the highest values, followed by spring (684.86 W/m2), autumn (544.76 W/m2), and winter (422.74 W/m2). The monthly average DSSR showed a unimodal distribution, peaking in June (792.94 W/m2) and reaching its lowest level in December (363.06 W/m2). Overall, our study findings enhance the current understanding of the spatiotemporal distribution characteristics of DSSR in Xinjiang and provide certain references for the management of clean energy development in this region.

Key words： downward surface shortwave radiation (DSSR)      clear-sky condition      two-layer aerosol model      Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART)      Clouds and the Earth's Radiant Energy System (CERES)     
Received: 04 January 2025      Published: 30 June 2025
Corresponding Authors: *WANG Pengtao (E-mail: wnpengtao@126.com)
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HUANG Guan
CHEN Yonghang
WANG Pengtao
FAN Ting
HE Qing
SHAO Weiling
SUN Linlin
Cite this article:

HUANG Guan, CHEN Yonghang, WANG Pengtao, FAN Ting, HE Qing, SHAO Weiling, SUN Linlin. Spatiotemporal distribution characteristics of clear-sky downward surface shortwave radiation in Xinjiang. Journal of Arid Land, 2025, 17(6): 772-790.

URL:

http://jal.xjegi.com/10.1007/s40333-025-0081-z     OR     http://jal.xjegi.com/Y2025/V17/I6/772

Fig. 1 Overview of Xinjiang Uygur Autonomous Region of China based on the digital elevation model (DEM) and geographical locations of ground observation stations. Noted that the figure is based on the standard map (No. 新S(2021)023) of the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services (https://xinjiang.tianditu.gov.cn/bzdt_code/bzdt.html#) marked by the Department of Natural Resources of Xinjiang Uygur Autonomous Region, and the boundary of the base map has not been modified. MPL, Micro Pulse Lidar; BSRN, Baseline Surface Radiation Network.
Type Product Scientific dataset Spatial resolution Temporal resolution
In situ observation
data		 - Measured DSSR from the Xiaotang
station		 - 30 min
- MPL data acquired from Urumqi
and Pamir stations		 - 60 min
Satellite remote
sensing data		 CER_SSF_Aqua-FM3-
MODIS_Edition4A		 CERES downward SW surface
flux-Model B		 20 km -
Clear area percent coverage at subpixel
resolution		 - -
CER_SYN1deg-1Hour_
Terra-Aqua-MODIS_Edition4A		 Observed clear-sky TOA Albedo 1.000°×1.000° Hourly
C6.1 MYD04_L2 Deep_Blue_Aerosol_Optical_
Depth_550_Land_Best_Estimate		 10 km -
Reanalysis data MERRA-2 tavg1_2d_aer_Nx TOTSCATAU; TOTEXTTAU 0.500°×0.625° Hourly
MERRA-2 tavg1_2d_slv_Nx TCWV 0.500°×0.625° Hourly
ERA5 hourly data on single
levels from 1979 to present		 Mean surface downward shortwave
radiation flux		 0.250°×0.250° Hourly
Boundary layer height 0.125°×0.125° Hourly
ERA5 hourly data on pressure levels from 1979 to present z; T; RH; u, v; w 0.125°×0.125° Hourly
Table 1 Summary of data used in this study
Parameter Meaning Unit Parameter Meaning Unit
iday Day of the year - wlbaer Wavelength (550 nm) nm
time UTC time in decimal hours - tbaer AOD (from MODIS) -
alat Latitude ° wbaer SSA (0.92 or calculated from MERRA-2) -
alon East longitude ° gbaer ASY (0.60 or 0.59) -
albcon Surface albedo (calculated using TOA albedo from CERES) - pbl PBLH (from ERA5) km
uw TCWV g/cm2 zbaer ALH (calculated from ERA5) km
iaer Aerosol model (user-defined) -
Table 2 Key input parameters of SBDART
Fig. 2 Automatic flow chart algorithm for ALH retrieval based on ERA5 meteorological parameters. ALH, aerosol layer height; ERA5, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5; MPL, Micro Pulse Lidar; PBLH, planetary boundary layer height; PBL, planetary boundary layer; z, geopotential energy; T, temperature; RH, relative humidity; u, v, horizontal wind speed; w, vertical velocity; RH(s), the relative humidity of the lowest layer near the ground at the corresponding time and grid point; a1-an, the atmospheric layers at which the vertical temperature change intensity exceeds -1 (1-n are arranged in ascending order of altitude, the subsequent parameters adopt the same numbering pattern); b1-bn, the atmospheric layers between a1 and the top of the PBL, which meets temperature variation conditions and the judgment condition of RH; c1-cn, the atmospheric layers that with w=0 although the RH condition is not met; f1-fn, the atmospheric layers between e1 and the top of the PBL, which meets the judgment condition of RH; g1-gn, the atmospheric layers above the top of the PBL that with w=0.
Fig. 3 Linear fitting results of DSSRCER (a) and DSSRSBD with initial parameter combination (b) under clear-sky conditions against DSSRBSRN at the Xiaotang station in 2017. DSSRCER, downward surface shortwave radiation (DSSR) retrieval using the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) Langley Parameterized Shortwave Algorithm (LPSA); DSSRSBD, DSSR retrieval in the Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART); DSSRBSRN, ground-based observational DSSR; r, correlation coefficient, MAE, mean absolute error; RMB, relative mean bias; RMSE, root mean square error.
Input r k b MAE (W/m2) RMB RMSE (W/m2)
Initial combination 0.995 1.029 -9.900 14.572 1.013 15.575
SSA after substitution and correction 0.995 1.028 -9.600 14.382 1.012 15.443
ASY after correction 0.995 1.027 -9.238 14.477 1.012 15.767
AOD after correction 0.995 1.026 -8.981 14.451 1.011 15.931
TCWV after substitution 0.995 1.041 -16.923 16.018 1.013 16.699
AS after substitution 0.995 1.032 -12.781 14.237 1.010 15.988
Table 3 Fitting results of DSSRSBD and DSSRBSRN under different inputs at the Xiaotang station
Fig. 4 Linear fitting results of MPL_PBLH and ERA5_PBLH at the Urumqi (a) and Pamir (b) stations
Fig. 5 Linear fitting results of MPL_ALH and ERA5_ALH at the Urumqi station
Parameter Optimum dataset Parameter Optimum dataset
SSA MERRA-2 SSA after substitution and correction AS AS (same as the dataset used by CERES SSF LPSA)
ASY 0.590 (fixed value) PBLH ERA5_PBLH
AOD MODIS AOD after correction ALH ERA5_ALH (based on ERA5 meteorological parameters)
TCWV TCWV (same as the dataset used by CERES SSF LPSA)
Table 4 Optimal combination of SBDART inputs
DSSR source r k b MAE (W/m2) RMB RMSE (W/m2)
DSSRCER 0.987 1.121 -60.470 24.611 1.021 32.076
DSSRSBD 0.995 1.029 -9.900 14.572 1.013 15.575
DSSRSBD_optimal 0.996 1.023 -8.190 12.413 1.009 13.351
Table 5 Linear fitting results of DSSRCER, DSSRSBD, and DSSRSBD_optimal with DSSRBSRN under clear-sky conditions at the Xiaotang station
Fig. 6 Linear fitting results of DSSRSBD_optimal (a) and DSSRERA5 (b) with DSSRBSRN under clear-sky conditions at the Xiaotang station in 2017. DSSRSBD_optimal, DSSR retrieval based on the optimized SBDART model (namely the localized DSSR retrieval model); DSSRERA5, ERA5-derived DSSR.
Fig. 7 Seasonal distribution of DSSR under clear-sky conditions in Xinjiang during 2017-2019. (a), spring; (b), summer; (c), autumn; (d), winter.
Fig. 8 Monthly variation of DSSR in Xinjiang
Fig. 9 Monthly DSSR variations of typical administrative regions in northern Xinjiang (a) and southern Xinjiang (b) during 2017-2019
Region Administrative region Annual average DSSR (W/m2) Maximum monthly
average DSSR (W/m2)		 Minimum monthly average DSSR (W/m2) Range of monthly
average DSSR (W/m2)
Xinjiang - 606.78 792.94 363.06 429.88
Northern Xinjiang Urumqi City 559.21 767.66 321.72 445.94
Turpan City 551.60 749.87 292.43 457.44
Qinghe County 586.09 828.17 288.32 539.85
Hami City 581.20 772.91 321.85 451.06
Southern Xinjiang Kashgar City 618.64 798.88 393.99 404.89
Hotan City 623.62 830.66 431.17 399.49
Ruoqiang County 522.10 740.13 342.06 398.07
Aksu City 581.11 792.07 348.04 444.03
Tazhong Town 591.59 799.68 367.59 432.09
Table 6 Statistics of DSSR of typical administrative regions in Xinjiang
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