Remote Sensing (Oct 2022)

Improving Clear-Sky Solar Power Prediction over China by Assimilating Himawari-8 Aerosol Optical Depth with WRF-Chem-Solar

  • Su Wang,
  • Tie Dai,
  • Cuina Li,
  • Yueming Cheng,
  • Gang Huang,
  • Guangyu Shi

DOI
https://doi.org/10.3390/rs14194990
Journal volume & issue
Vol. 14, no. 19
p. 4990

Abstract

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Although the Weather Research and Forecasting model with solar extensions (WRF-Solar) is tailed for solar energy applications, its official version lacks the consideration of the online aerosol-radiation process. To overcome this limitation, we have coupled the aerosol module online with the radiation module, then assimilated the high-resolution aerosol optical depth (AOD) from the Himawari-8 next-generation geostationary satellite using a three-dimensional variational (3DVAR) AOD data assimilation system to optimize the irradiance predictions with the better aerosol–radiation interaction. The results show that data assimilation can significantly eliminate the AOD underestimations and reasonably reproduce the AOD temporal distributions, improving 51.63% for biases and 61.29% for correlation coefficients. Compared with the original WRF-Solar version, coupled online with an advanced aerosol module minifies the bias value of global horizontal irradiance (GHI) up to 44.52%, and AOD data assimilation contributes to a further reduction of 17.43%.

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