The objective of this proposal is to transition and infuse the recent developments of the Noah land surface model into NCEP operation to improve the skill and reliability of NCEP seasonal climate predictions of precipitation, temperature and land-surface hydrological variables, such as soil moisture, runoff and snowpack. The improvement in prediction skill is to be accomplished by means of improved representation of land surface processes and land-atmosphere interactions in the NCEP operational global and regional climate prediction systems, including their companion land data assimilation systems.
The scientific basis for this objective is that climate predictability on intraseasonal to interannual time scales is largely determined by slow variations of the ocean and land surface states. This proposal aims to improve the understanding and modeling of land surface processes through a focus on better understanding of land-atmosphere interactions and related hydrometeorological physics. Upgrades in the Noah land surface model, coupled to the NCEP Climate Forecast System, will be the parameterizations for cold season snow processes, surface thermal roughness, groundwater and runoff, vegetation canopy layer, and dynamic vegetation.
To achieve the above objective, this proposal will establish explicit interfaces between internal NCEP operational climate prediction model developers and external academic researchers, in particular those who received funding from the NOAA Climate Program Office, to facilitate the transition from research to operation. Specifically, to transition those tested, proven, CPO funded research projects to NOAA operations.