Evaluating solar energy NWP forecasts during major dust aerosol events using MACC renalysis with WRF
In this study, Global and regional Earth system Monitoring using Satellite and in-situ data (GEMS) ECMWF Monitoring Atmospheric Composition and Climate (MACC) global reanalysis data of atmospheric composition is incorporated to simulate NCAR's Weather Research and Forecast (WRF) ARW model. The 3-hourly MACC reanalysis relies on MOZART chemical transport and 4D-Var data assimilation for aerosol prognosis. The MACC aerosol reanalysis atmospheric compositions biases are compared against AERONET ground observations. Combinations of multiphysics ensembles for regionally optimised radiation physics options in WRF are selected to simulate the dust storm event with MACC reanalysis data. Forecasts generated with MACC reanalysis are compared with gridded NCEP final analysis data and Global Forecast System (GFS) boundary conditions downscaled to perform WRF mesoscale simulations. The GFS case also utilises optimised multiphysics ensembles but with the Thompson aerosol-aware scheme that relies on a monthly climatology based on Goddard Chemistry Aerosol Radiation and Transport (GOCART). The forecast MACC reanalysis MOZART dust transport case and the GOCART monthly climatology case with surface solar radiation day ahead (6 to 48 hours) forecasts generated are both inter-compared to measure errors with solar pyrheliometer derived ground observation data from Bureau of Meteorology (BoM). The BoM sites selected are based on five key Köppen climate classification zones suitable for solar power. The bias errors in forecast direct normal irradiance (DNI) from MACC aerosol prognosis are reduced at most ground stations compared to the monthly GFS GOCART climatology case. For non-major aerosol event sites, the differences in DNI are less significant between the chemical transport 4D-Var and NCEP monthly climatology case.