ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011, Vol. 8, No. 3, pp. 283-289

Regionalization and regression analysis of air temperature and precipitation in global Data Base on climate

V.G. Konovalov , V.V. Matskovskiy 
Institute of Geography RAS, 29, Staromonetny per., 119017, Moscow
Estimates of informative capacity were obtained for the climatic factors of river runoff (precipitation, air temperature) at different levels of spatial resolution. The local level is presented by long-term observations at meteorological stations, regional one - by series of meteorological characteristics in the global DB on climate CRU TS 3.0 ( Series of meteorological data in this global data base refers to the period of 1901-2006 years. Spatial interval between the nodes of a regular grid is equal to 0,5 degrees in longitude and latitude. Data are distributed along altitude from 0 to 5,734 m above sea level. The scale of spatial integration of fields of meteorological data in the database CRU TS 3.0 is roughly equivalent to the swath area of satellites of medium resolution such as LANDSAT 7 and TERRA. Given the possibility of direct use data from these satellites to seasonal and annual hydrological forecasts, the comparative analysis was performed for the quality of multiple linear regression equation Run = f(A1 ... AN) and R = f(B1 ... BN) on an example of the Amu Darya and Syr Darya rivers - the main sources of water supply in Aral Sea Basin. Here: Run - runoff or water flow, A1 ... AN - direct measurements of precipitation and air temperature, B1 ... BN - the same characteristics, selected from a database CRU TS 3.0. Determining the most informative composition of the climatic factors of runoff is performed by the method of exhaustive search 2 ... N combinations of independent variables in the training sample. Information capacity of the average annual air temperature at the regional level offers an opportunity to apply the method of statistical downscaling to the output results of models of global circulation of atmosphere and ocean.
Keywords: air temperature and precipitation, global database, regionalization, runoff of the Amu Darya and Syr Darya rivers, multiple linear regression
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