P3.2
Verification of the North American Land Data Assimilation System (NLDAS) using data from Oklahoma Mesonet OASIS sites
Kodi L. Nemunaitis, Oklahoma Climatological Survey, University of Oklahoma, Norman, OK; and J. B. Basara, B. A. Cosgrove, D. Lohmann, and K. E. Mitchell
The Oklahoma Mesonet is an automated network of 116 remote, hydrometeorological stations across Oklahoma. Each station measures ten core parameters which include: air temperature and relative humidity at 1.5 m, wind speed and direction at 10 m, barometric pressure, rainfall, incoming solar radiation, bare and vegetated soil temperatures at 5, 10, and 30 cm below ground level, and soil moisture at 5, 25, 60, and 75 cm.
In 1999, the Oklahoma Atmospheric Surface-layer Instrumentation System (OASIS) Project upgraded 89 sites with a suite of instruments capable of estimating the surface energy balance. In addition, a subset of 10 OASIS sites, designated OASIS Super Sites, were instrumented to measure the components of the surface energy balance with enhanced accuracy.
A team of federal agencies and universities which includes the NCEP Environmental Modeling Center, NASA Goddard Space Flight Center, NWS/OHD, NESDIS/ORA, Princeton University, Rutgers University, the University of Washington, University of Maryland, and the University of Oklahoma is developing a Land Data Assimilation System (LDAS) for use at both North American (NLDAS) and global scales (GLDAS). The NLDAS infrastructure consists of uncoupled land surface models forced with precipitation observations, output from the Eta model data assimilation system (EDAS), solar radiation from the GOES satellites, and radar precipitation estimates. It is being developed to initialize and improve the simulation of land surface states and energy fluxes in coupled and uncoupled land model components of numerical forecast models. The NLDAS system is expected to reduce forecast errors by providing better initial condition for the land surface component in NWP and climate models.
It has been shown that biases exist in the NLDAS forcing data and resulting surface energy fluxes from the Mosaic and Noah land surface models. To gauge the impact of biased forcing data on the performance of the Mosaic and Noah land surface models, forcing experiments are being conducted. A three-year dataset of locally observed forcing was created from Oklahoma Mesonet data for January 1999 - July 2003 at the Norman and Marena OASIS Super Sites. Two sets of retrospective simulations are being conducted with the Mosaic and Noah land surface models during June and July 2003 – one set using NLDAS forcing data, and one set using Mesonet-based forcing data. In this research presentation, the model-simulated energy fluxes from these simulations will be compared with validation data from the corresponding OASIS surface flux data sets.
Poster Session 3, Land Atmosphere Interactions Posters
Wednesday, 12 January 2005, 2:30 PM-4:00 PM
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