Evaluation of topographical and geographical effects on some climatic parameters in the Central Anatolia Region of Turkey

被引:35
|
作者
Apaydin, Halit [1 ]
Anli, Alper S. [1 ]
Ozturk, Fazli [1 ]
机构
[1] Ankara Univ, Dept Farm Struct & Irrigat, TR-06110 Ankara, Turkey
关键词
spatial interpolation; kriging; climate parameters; GIS; regression analysis; BLUE-RIDGE MOUNTAINS; SPATIAL INTERPOLATION; PRECIPITATION; RAINFALL; VARIABLES; BASIN;
D O I
10.1002/joc.2154
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A two-phase research was implemented to determine the effect of topography on climate parameters by using spatial interpolation and conventional statistical procedures in non-homogeneous topography. The primary set of climate data for the Central Anatolia Region includes monthly mean global solar radiation, sunshine duration, surface air temperature, relative humidity, wind speed and rainfall, recorded from 1976 to 2005. In the first phase, the effect of elevation on climate parameters was evaluated. For this purpose, kriging and co-kriging geostatistical interpolation techniques were compared to determine which one of the two techniques was more successful in determining the spatial distribution of climate parameters in variable topography. The inclusion of elevation as a covariate resulted in reduction of errors on sunshine duration, temperature and wind speed. On the basis of these error values, there is a relationship between elevation and sunshine duration, temperature and wind speed. In the second phase, multiple regression equations were developed to determine the effect of topography on annual mean values of climate factors. The highest correlation (-0.76) was found between solar radiation and latitude. The most effective factors were latitude and elevation. They alone explain 57% of the variability for sunshine duration and 56% for temperature, respectively. The multiple regression results were more significant than were the individual, pairwise correlation relationships. The mostly explained factor was temperature. Its variability was explained by latitude, elevation, aspect and slope as a ratio of 81.7%. Separate regression models for each data set and both response variables varied in their ability to explain variability in the response, with R-2 values between 0.125 and 0.817. Copyright (C) 2010 Royal Meteorological Society
引用
收藏
页码:1264 / 1279
页数:16
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