HR: 1340h
AN: H33C-0477    [Abstracts]
TI: Improving Temporal and Spatial Variability of Hydrological and Energy Parameters in Global Analysis through Precipitation Assimilation
AU: * Hou, A Y
EM: arthur.y.hou@nasa.gov
AF: NASA Goddard Space Flight Center, code 900.3, Greenbelt, MD 20771 United States
AU: Wu, M
EM: mwu@gmao.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, code 900.3, Greenbelt, MD 20771 United States
AU: Schubert, S D
EM: sschubert@gmao.gafc.nasa.gov
AF: NASA Goddard Space Flight Center, code 900.3, Greenbelt, MD 20771 United States
AB: Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. At the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Yet, for many hydrological and climate applications it is essential that analyses can accurately reproduce the observed rainfall intensity and variability. Analyses of the tropics have long been shown to be sensitive to the treatment of cloud/precipitation processes, which remains a major source of uncertainty in current generation of atmospheric models. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a 1o x 1o "TRMM re-analysis" that assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using the GEOS-3 global data assimilation system. The goal is to provide a multi-year global analysis that is dynamically consistent with available tropical precipitation observations. A distinct feature of the GEOS-3/TRMM re-analysis is that its precipitation analysis is not derived from a short-term forecast (as for most operational systems) but given by a time-continuous model integration directly constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields adjust to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, we show that precipitation assimilation leads to significant improvements in the intensity and variability of hydrological and climate parameters in the GEOS-3/TRMM re-analysis and compare results against other operational and reanalysis products.
DE: 3337 Numerical modeling and data assimilation
DE: 3314 Convective processes
DE: 1854 Precipitation (3354)
DE: 1878 Water/energy interactions
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting