Enhancing Hydrologic Processes in the Noah-MP Land Surface Model to Improve Seasonal Forecast Skill

Communication between the land surface and atmosphere via fluxes of water and energy involve many complex non-linear processes. In this study, the Noah-MP land surface model is enhanced with several physical processes that may be necessary to improve seasonal to sub-seasonal forecasts. These processes include interaction of shallow soil with groundwater, the application of irrigation water, and dynamic growth of crops. The focus here is on how the land surface with a shallow two-meter soil interacts (1) with the atmosphere at short time scales through latent heat flux and subsequent feedbacks via precipitation and vegetation dynamics, and (2) with the groundwater below shallow soil at longer time scales to modulate surface fluxes later in numerical simulations. These processes are analyzed using six-month regional climate simulations in the central United States during three contrasting years, 2012 (dry), 2013 (normal) and 2014 (wet). The results are verified using observational 2-meter temperature and Stage IV radar precipitation and show that these hydrologic processes are crucial for seasonal forecasting especially in summer.