Santanello, Joseph A. Jr., National Aeronautics and
Space Administration/GSFC, Sujay V. Kumar, NASA-GSFC, Ken Harrison, NASA-GSFC,
and Christa D. Peters-Lidard, NASA-GSFC
Land-atmosphere (L-A)
interactions play a critical role in determining the diurnal evolution of both
planetary boundary layer (PBL) and land surface temperature and moisture
budgets, as well as controlling feedbacks with clouds and precipitation that
lead to the persistence of dry and wet regimes. Recent efforts to quantify the
strength of L-A coupling in prediction models have produced diagnostics that
integrate across both the land and PBL components of the system. In this study,
we examine the impact of improved specification of land surface states,
anomalies, and fluxes on coupled WRF forecasts during the summers of extreme
dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The
improved land initialization and surface flux parameterizations are obtained
through the use of a new optimization and uncertainty estimation module in
NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated
in the Noah land surface model and classified according to the land cover and
soil type mapping of the observations and the full domain. The impact of the
calibrated parameters on the a) spinup of land surface states used as initial
conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF)
simulations are then assessed in terms of ambient weather, PBL budgets, and
precipitation along with measures of uncertainty propagation into the
forecasts. In addition, the sensitivity of this approach to the period of
calibration (dry, wet, normal) is investigated. Finally, tradeoffs of
computational tractability and scientific validity (e.g.,. relating to the
representation of the spatial dependence of parameters) and the feasibility of
calibrating to multiple observational datasets are also discussed.