Commenced in January 2007
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Edition: International
Paper Count: 33093
A Dynamic Equation for Downscaling Surface Air Temperature
Authors: Ch. Surawut, D. Sukawat
Abstract:
In order to utilize results from global climate models, dynamical and statistical downscaling techniques have been developed. For dynamical downscaling, usually a limited area numerical model is used, with associated high computational cost. This research proposes dynamic equation for specific space-time regional climate downscaling from the Educational Global Climate Model (EdGCM) for Southeast Asia. The equation is for surface air temperature. This equation provides downscaling values of surface air temperature at any specific location and time without running a regional climate model. In the proposed equations, surface air temperature is approximated from ground temperature, sensible heat flux and 2m wind speed. Results from the application of the equation show that the errors from the proposed equations are less than the errors for direct interpolation from EdGCM.Keywords: Dynamic Equation, Downscaling, Inverse distance weight interpolation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110515
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[1] Rockel, B., Castro, C.L., Pielke Sr, R.A., Storch, H.V. and Leoncini, G., 2008, “Dynamical Downscaling: Assessment of Model System Dependent Retained and Added Variability for Two Different Regional Climate Models”, Journal of Geophysical Research, Vol. 113, D21107, doi:10.1029/2007JD009461, pp. 1-9.
[2] Goncalves, M., Barrera-Escoda, A., Baldasano, J.M. and Cunillera, J., 2012, “High Resolution Climate Scenarios by Dynamic Downscaling Modelling Techniques over the Northwestern Mediterranean Basin”, EMS Annual Meeting Abstracts, Vol. 9, p. 297.
[3] Hoar, T. and Nychka, D., 2008, Statistical Downscaling of the Community Climate System Model (online), Available: http://gisclimatechange.ucar.edu/sites/default/files/users/Downscaling.pd f (2012, April 23).
[4] Kannan, S. and Ghosh, S., 2011, “Prediction of Daily Rainfall State in a River Basin Using Statistical Downscaling from GCM Output”, Stochastic Environmental Research and Risk Assessment, Vol. 25, doi: 10.1007/s00477-010-0415-y, pp. 457-474.
[5] Salvi, K., Kannan, S. and Ghosh, S., 2011, “Statistical Downscaling and Bias Correction for Projections of Indian Rainfall and Temperature in Climate Change Studies”, 2011 International Conference on Environmental and Computer Science (IPCBEE), Vol.19, IACSIT Press, Singapore, pp. 7-11.
[6] Chandler, M., Sohl, L. and Mankoff, K., 2001, NASA Climate Modeling and Data Applications Workshop, Goddard Institute for Space Studies, New York, pp. 7-12.
[7] Mohan, A. and Pecora, K., 2011, Modeling Climate Change and Testting EdGCM Effectiveness (online), Available: http://communities.earthportal.org/files/179401_179500/179472/mohan _pecora_thesis.pdf (2013, May 7).
[8] Stull, R.B., 1999, An Introduction to Boundary-Layer Meteorology, 6th ed., Kluwer Academic Publishers, Netherland, pp. 32 – 47.
[9] Stull, R.B., 2000, Meteorology for Scientists and Engineers, 2nd ed., Brooks Cole, Pacific Grove, CA, 2000, p. 109.
[10] Chiles, J.P. and Delfine, P., 1991, Geostatistics: Modeling Spatial Uncertainty, 2nd ed., John Wiley & Sons, New York, USA, p. 30.