HR: 1340h
AN: A53A-0855    [Abstracts]
TI: Evaluation of a Regional Climate Hindcast for East Asia
AU: * Jung, H
EM: hsjung@atmos.ucla.edu
AF: UCLA Dept. Atmospheric Sciences, 405 Hilgard Avenue, Los Angeles, CA 90095-1565 United States
AU: Kim, J
EM: jkim@atmos.ucla.edu
AF: UCLA Dept. Atmospheric Sciences, 405 Hilgard Avenue, Los Angeles, CA 90095-1565 United States
AU: Mechoso, C R
EM: mechoso@atmos.ucla.edu
AF: UCLA Dept. Atmospheric Sciences, 405 Hilgard Avenue, Los Angeles, CA 90095-1565 United States
AB: As a preliminary step in a climate change and impact assessment study for East Asia, which is among the most vulnerable regions to climate change, we have analyzed a long-term simulation by a regional model in hindcast mode. Socio-economical developments and accompanying urbanization in East Asia are placing ever increasing demands on natural resources that are already far stretched in many parts of the region, such as water and food. Shifts in the water cycle due to the climate change induced by anthropogenic emissions of greenhouse gases will inevitably affect human sectors in the region. Hence, assessing the regional climate change and its impacts on the water cycle is a crucial step for planning long-term sustainable development. Climate change projections for impact assessment studies are usually generated by dynamical models. Uncertainties originating from model errors remain an important concern in the interpretation of the results. As it is impossible to avoid model errors, the close examination of model results and errors is an important task in projections of future climates. In this study we use the Mesoscale Atmospheric Simulation (MAS) model driven by the NCEP R2 for the 22-yr period 1979-2000. The model simulation was successful in reproducing, at least qualitatively several important features of the regional climate, such as the spatial distributions of precipitation and temperature. The spatial anomaly correlations between the upper-air wind fields from the simulation and the R2 remained well above 0.95 throughout the 22-yr period, suggesting that the simulated structures are consistent with the large-scale forcing that drove the simulation. The simulation also reproduced extreme hydrologic events as measured by their recurrence periods. The model results showed significant local biases, however. An examination of the simulated standard deviations and coefficient of variations suggested that the simulated variables scaled by the model climatology can compare more closely with the similarly scaled data constructed from observations than the raw model data. For example, the precipitation data scaled with its own climatology agreed more closely with observations than the raw model data.
DE: 3329 Mesoscale meteorology
DE: 3337 Numerical modeling and data assimilation
DE: 3354 Precipitation (1854)
DE: 3319 General circulation
DE: 1620 Climate dynamics (3309)
SC: Atmospheric Sciences [A]
MN: 2004 AGU Fall Meeting