WRF-Solar is a specific configuration and augmentation of the Weather Research and Forecasting (WRF) model designed for solar energy applications. Recent upgrades to the WRF model contribute to making the model appropriate for solar power forecasting, and comprise 1) developments to diagnose internally relevant atmospheric parameters required by the solar industry, 2) improved representation of aerosol-radiation feedback, 3) incorporation of cloud-aerosol interactions, and 4) improved cloudradiation feedback.
The Multi-sensor Advection Diffusion nowCast (MADCast) model (MADCast) assimilates infrared pro files using the Multivariate Minimum Residual (MMR) scheme to infer the presence of clouds. MMR has been implemented in the Gridpoint Statistical Interpolation system (GSI). Once GSI has generated the three dimensional cloud fields, the clouds are advected and diffused by a modified version of the Weather Research and Forecasting (WRF) model.
WRF-Solar are augmentations to WRF in support of solar energy applications (Jimenez et. al 2016). The model developments focus on the representation of the cloud-aerosol-radiation system. Main developments include:
A parameterization of the aerosol direct effect (Ruiz-Arias et al. 2014; Lee et al. 2016)
Implementaiton of the cloud-aerosol representation that accounts for the aerosol indirect effects (Thompson and Eidhammer, 2014; Thompson et al. 2015) as well as the aerosol direct effect.
A shallow cumulus parameterization that accounts for the effects of unresolved clouds in the shortwave irradiance (Deng et la. 2014; Jimenez et al. 2016; Lee et al. 2016).
MADCast is a nowcasting system to predict cloudiness and surface irradaince (Auligne 2014a; 2014b; Descombes et al. 2014).
WRF and thus WRF-Solar integrate the Euler equations to perform a forecast. A detailed description of the method used by WRF to integrate the Euler equations is described in Skamarock et al. (2008). The method uses a time-split integration scheme wherein meteorologically significant modes are integrated using a longer time step than the high-frequency acoustic modes that are integrated over smaller time steps to maintain numerical stability.
MMR is the mathematical core of MADCast. A complete description of the MMR scheme can be found in Auligne (2014a; 2014b). MMR is inspired by the minimum residual technique by Eyre and Menzel (1989) and is especially suitable for exploiting the large number of channels from hyperspectral infrared sounders.
MADCast installation step by step:
Create a ~/Code directory in your home directory.
Untar the GSI GSI_cldfra.tar.gz and the WRF WRFV3.6_cldfra.tar.gz tarballs in your ~/Code directory, compile according to the README.cldfra and the GSI and WRF user guides. Also see GSI_MMR_notes.pptx.
Untar the test case data cldfra_case.tar.gz in your project directory and run the test case according to the README.cldfra.
Set-up the post-processing (Verif_cldfra.tar.gz). Also see Post-processing_MADCast.pptx.