Improved weather predictions through data assimilation for GFDL SHiELD

The DA system is useful in identifying and understanding model errors. The most noticeable model error detected by the DA system originates from the turbulent kinetic energy (TKE)‐based moist eddy‐diffusivity mass‐flux vertical turbulent mixing (TKE‐EDMF) scheme. The model error leads to insufficient ensemble spread.

Including two versions of the TKE‐EDMF scheme in the ensemble helps increase ensemble spread, further improves forecast skills and alleviate the systematic errors in marine stratocumulus regions. Applying interchannel correlated observation errors for Infrared Atmospheric Sounding Interferometer (IASI) and Cross‐track Infrared Sounder (CrIS) also reduces the systematic errors and improves the forecast skill up to day 5.

Further investigation of the forecast errors reveals that the ensemble spread is largely affected by the parameterization of eddy diffusivity through its impact on the gradient of the model state. The systematic forecast errors in marine stratocumulus regions are associated with the vertical location of the stratocumulus cloud, which is sensitive to model vertical resolution within the cloud layer. Enhancing eddy diffusion within the cloud or near cloud top elevates cloud top but reduces cloud amount.