An Evaluation of Satellite Estimates of Solar Surface Irradiance Using Ground Observations in San Antonio, Texas, USA

Abstract

Abstract:Estimates of solar irradiance at the earth's surface from satellite observations are useful for planning both the deployment of distributed photovoltaic systems and their integration into electricity grids. In order to use surface solar irradiance from satellites for these purposes, validation of its accuracy against ground observations is needed. In this study, satellite estimates of surface solar irradiance from Geostationary Operational Environmental Satellite (GOES) are compared with ground observations at two sites, namely the main campus of the University of Texas at San Antonio (UTSA) and the Alamo Solar Farm of San Antonio (ASF). The comparisons are done mostly on an hourly timescale, under different cloud conditions classified by cloud types and cloud layers, and at different solar zenith angle intervals. It is found that satellite estimates and ground observations of surface solar irradiance are significantly correlated (p < 0.05) under all sky conditions (r: 0.80 and 0.87 on an hourly timescale and 0.94 and 0.91 on a daily timescale, respectively for the UTSA and ASF sites); on the hourly timescale, the correlations are 0.77 and 0.86 under clear-sky conditions, and 0.74 and 0.84 under cloudy conditions, respectively for the UTSA and ASF sites, and mostly >0.60 under different cloud types and layers for both sites. The correlations under cloudy-sky conditions are mostly stronger than those under clear-sky conditions at different solar zenith angles. The correlation coefficients are mostly the smallest with solar zenith angle in the range of 75-90 • under all sky, clear-sky and cloudy-sky conditions. At the ASF site, the overall bias of GOES surface solar irradiance is small (+1.77 Wm −2 ) under all sky while relatively larger under clear-sky (−22.29 Wm −2 ) and cloudy-sky (+40.31 Wm −2 ) conditions. The overall good agreement of the satellite estimates with the ground observations underscores the usefulness of the GOES surface solar irradiance estimates for solar energy studies in the San Antonio area.

Validation of Hourly Global Horizontal Irradiance for Two Satellite-Derived Datasets in Northeast Iraq

“…Recently, GHI data from the MFG and MSG have been evaluated over India, which show an overestimation bias of 10-20% of daily mean [33]. Some other studies have evaluated SDDs over the United States in different climate regions against several ground-based measurements [34][35][36][37].…”

Improvement in Surface Solar Irradiance Estimation Using HRV/MSG Data

“…In the evaluation of the performances under different sky conditions, the statistical scores were also compared to those given by the validation of 4 different papers cited in the introduction. The first and the second [11,22] were selected because they report the statistics for different weather conditions and different satellite platforms; the third [42] was considered because it uses the HRV channel, whereas the fourth [2] is based on MSG/SEVIRI and reports on the validation against some alpine stations. The statistical scores reported in [11] In the HelioMont model, correction methods are also implemented to account for the effects of topography, such as shadowing, reflection, local horizon elevation angle and sky view factor.…”

“…The first and the second [11,22] were selected because they report the statistics for different weather conditions and different satellite platforms; the third [42] was considered because it uses the HRV channel, whereas the fourth [2] is based on MSG/SEVIRI and reports on the validation against some alpine stations. The statistical scores reported in [11] In the HelioMont model, correction methods are also implemented to account for the effects of topography, such as shadowing, reflection, local horizon elevation angle and sky view factor. All these statistical scores, compared with those obtained using AMESIS model (Table 4), suggest that our proposed method can successfully estimate surface solar irradiance and yields similar or sometimes better performances.…”

“…During the second step, i.e., the final estimation of SSI, the HRV processing takes longer than the VIS processing by a factor of five, due to the greater number of pixels to consider. To evaluate the AMESIS performance, our statistical scores were compared against those obtained in [2,11,22,42]; this comparison suggests that our proposed AMESIS model (SSI_HRV) can successfully estimate surface solar irradiance and yields similar or sometimes better performances. This confirms that the HRV channel, or more generally, a higher-resolution sensor, can improve the estimation of solar irradiance over partially cloudy sky.…”

Validation of All-Sky Imager Technology and Solar Irradiance Forecasting at Three Locations: NREL, San Antonio, Texas, and the Canary Islands, Spain

“…The temporal sampling of the data is still insufficient to support optical flow predictions 15-min ahead. Continued improvements in GOES-R (geostationary satellite with high spatial and temporal resolution) may well make the satellite approach to minutes-ahead irradiance prediction more attractive in the future [17][18][19][20]. Statistical methods based on historical time-series data and climatology are also useful for day-ahead PV forecasting.…”