Reconstruction of Historical Atmospheric Data by a Hydroclimate Model for the Mekong River Basin
Publication: Journal of Hydrologic Engineering
Volume 16, Issue 12
Abstract
It is necessary to have historical atmospheric data at fine time and spatial grid resolutions as input to watershed-scale models of the Mekong River Basin to perform water balance studies over the basin. However, such historical atmospheric data are not available at the desired fine time-space scales for various reasons in this region. Therefore, it is necessary to reconstruct the atmospheric data over the Mekong River Basin at a fine spatial resolution (approximately 20 km) by means of a regional coupled atmospheric-hydrologic model from the available historical global atmospheric data that have a very coarse resolution (approximately 285 km). The coarse resolution (approximately 285 km) reanalysis of atmospheric data for 1956–2006 from the U.S. National Center for Atmospheric Research (NCAR) and the U.S. National Center for Environmental Prediction (NCEP) were used for the reconstruction of the fine resolution (approximately 20 km) historical atmospheric data over the basin. To incorporate the complex topographical and land surface features of this basin, a regional, fully coupled atmospheric-hydrologic hydro-climate model of the Mekong River Basin, called “RegHCM-Mekong,” was developed for the dynamic downscaling. The coarse time-space resolution NCEP-NCAR historical atmospheric data were then downscaled by RegHCM-Mekong to produce meteorological information on rainfall, air temperature, specific humidity, wind velocity, solar radiation, and net radiation at 0.2 degrees spatial resolution (approximately 20 km) and at hourly intervals over the whole Mekong River Basin during a historical period. After a bias correction of the RegHCM-Mekong-downscaled data (by means of Global Precipitation Climatology Project (GPCP) data), the RegHCM-Mekong-reconstructed historical rainfall fields were successfully validated through comparisons against available point-location observations. The comparisons against the interpolated spatial maps of historical precipitation showed satisfactory results.
Get full access to this article
View all available purchase options and get full access to this article.
References
Adler, R. F., et al. (2003). “The Version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-Present).” J. Hydrometeorol., 4(6), 1147–1167.
Anthes, R. A. (1977). “A cumulous parameterization scheme utilizing a one-dimensional cloud model.” Mon. Weather Rev., 105(3), 270–286.
Anthes, R. A., and Warner, T. T. (1978). “Development of hydrodynamic models suitable for air pollution and other mesometeorological studies.” Mon. Weather Rev., 106(8), 1045–1078.
Brooks, R. H., and Corey, A. T. (1964). “Hydraulic properties of porous media.” Hydrol. Pap. 3, Colorado State Univ., Fort Collins, CO.
Chen, Z. Q., Govindaraju, R. S., and Kavvas, M. L. (1994a). “Spatial averaging of unsaturated flow equations under infiltration conditions over areally heterogeneous fields: 1. Development of models.” Water Resour. Res., 30(2), 523–533.
Chen, Z. Q., Govindaraju, R. S., and Kavvas, M. L. (1994b). “Spatial averaging of unsaturated flow equations under infiltration conditions over areally heterogeneous fields: 2. Numerical simulations.” Water Resour. Res., 30(2), 535–548.
Deardorff, J. W. (1978). “Efficient prediction of ground surface temperature and moisture, with inclusion of layer of vegetation.” J. Geophys. Res., 83(C4), 1889–1903.
Dunne, T. (1978). “Field studies of hillslope flow processes.” Chapter 7, Hillslope Hydrology, M. J. Kirkby, ed., Wiley, New York.
Grell, G., Dudhia, J., and Stauffer, D. (1994). “A description of the fifth-generation Penn State/NCAR mesoscale model (MM5).” NCAR Technical Note NCAR/TN-398+STR, National Center for Atmospheric Research, Boulder, CO.
Hall, D. K., Riggs, G. A., and Salomonson, V. V. (1995). “Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer (MODIS) data.” Remote Sens. Environ., 54, 127–140.
Kain, J. S., and Fritsch, J. M. (1990). “A one-dimensional entraining/detraining plume model and its application in convective parameterization.” J. Atmos. Sci., 47(23), 2784–2802.
Kavvas, M. L., et al. (1998). “A regional-scale land surface parameterization based on areally-averaged hydrologic conservation equations.” Hydrol. Sci. J., 43(4), 611–631.
Kuo, H. L. (1974). “Further studies of the parameterization of the influence of cumulous convection on large-scale flow.” J. Atmos. Sci., 31(5), 1232–1240.
McCuen, R. H., Rawls, W. J., and Brakensiek, D. L. (1981). “Statistical analysis of the Brooks-Corey and the Green-Ampt parameters across soil textures.” Water Resour. Res., 17(4), 1005–1013.
Nash, J. E., and Sutcliffe, J. V. (1970). “River flow forecasting through conceptual models part I—A discussion of principles.” J. Hydrol. (Amsterdam), 10(3), 282–290, .
Noilhan, J., and Planton, S. (1989). “A simple parameterization of land surface processes for meteorological models.” Mon. Weather Rev., 117(3), 536–549.
Pielke, R. A. (2002). Mesoscale Meteorological Modeling, Academic Press, San Diego.
Willmott, C. J. et al. (1985). “Statistics for evaluation and comparison of models.” J. Geophysical Research, 90(C5), 8995–9005.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 16 • Issue 12 • December 2011
Pages: 1030 - 1039
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Jul 22, 2009
Accepted: Dec 8, 2010
Published online: Dec 10, 2010
Published in print: Dec 1, 2011
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.