Improving the Prediction of DNI with Physics-Based Representation of All-Sky Circumsolar Radiation

Yu Xie, Jaemo Yang, Manajit Sengupta, Yangang Liu, Xin Zhou

Research output: Contribution to journalArticlepeer-review

5 Scopus Citations

Abstract

Direct normal irradiance (DNI) is often interpreted differently in ground measurements and forecasts using numerical weather prediction (NWP) models, leading to substantial bias in DNI forecasting especially under cloudy-sky conditions. To mitigate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to conduct physics-based simulations of solar radiation in the circumsolar region. The DNI is quantified using the sum of the radiation along the sun direction and the scattered radiation within the circumsolar region. FARMS-DNI is coupled with the Weather Research and Forecasting model with solar extensions (WRF-Solar) to predict day-ahead DNI in 9-km pixels over an extended domain covering the contiguous United States. The DNI forecasts for the entire year of 2018 are validated using surface-based observations at the Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) sites and a satellite-based solar radiation product developed by the procedure of the National Solar Radiation Data Base (NSRDB). The results show that the WRF-Solar coupled with the conventional Beer-Bouguer-Lambert law underestimes the overall DNI forecasts by 30%-60%, which is a joint effect of the uncertainties in computing the circumsolar radiation and forecasting cloud properties. This bias is significantly reduced by using FARMS-DNI.

Original languageAmerican English
Pages (from-to)758-766
Number of pages9
JournalSolar Energy
Volume231
DOIs
StatePublished - 1 Jan 2022

Bibliographical note

Publisher Copyright:
© 2021 International Solar Energy Society

NREL Publication Number

  • NREL/JA-5D00-80201

Keywords

  • Circumsolar radiation
  • Direct normal irradiance
  • NWP
  • Solar forecasting
  • Solar radiation

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