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SPATIO-TEMPORAL ANALYSIS OF PRECIPITATION AND TEMPERATURE DISTRIBUTION OVER TURKEY

机译:土耳其降水量分析的时空分析

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摘要

In this study, mean annual precipitation and temperature values observed at 225 meteorological observations over Turkey are used to disclose spatial distribution of mean annual precipitation and temperature values. Data components were obtained from the Turkish State Meteorological Service for 34 years period (1970-2003) The basic objectives of the study are: to in fer the nature of spatial variation of precipitation and temperature over Turkey based on meteorological observations and to model the pattem of variability of these data components by using secondary variables extracted from SRTM and river network. Modeling the spatial distribution of data sets is implemented with Co-kriging (COK), Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) techniques with using secondary variables such as elevation, aspect, distance to river, roughness, drop (elevation differences between station and grid), sd-grid (standard deviation of 5*5 km grid), and plan-profile curvature. Correlations among the listed variables were analyzed and highly correlated ones were removed from the analysis The study found a presence of high spatial non-stationary in the strength of relationships and regression parameters. The co-kriging interpolation method gave strong relationship for temperature (r~2=0.823) but comparatively weak relationship for precipitation (r~2=0.542). OLS method resulted with lower relationships for temperature (r~2= 0.68) and for precipitation (r~2= 0.3). The highest adjusted r~2 values were obtained with GWR method; 0.96 for temperature and 0.66 for precipitation.
机译:在这项研究中,使用土耳其225个气象观测观察到的平均年降水和温度值用于公开平均年降水量和温度值的空间分布。从土耳其国家气象服务获得数据组件34年(1970-2003)该研究的基本目标是:根据气象观测,在土耳其的降水和温度的空间变化性质的性质,并模拟Pattem使用从SRTM和River网络中提取的次要变量使用次要变量的这些数据组件的可变性。模拟数据集的空间分布是用Co-Kriging(COK),普通最小二乘(OLS)和地理加权回归(GWR)技术实现,所述次要变量如高程,方面,距离到河流,粗糙度,下降(高度站和网格之间的差异),SD-GRID(标准偏差为5千米克网格)和平面轮廓曲率。分析了列出的变量之间的相关性,并从分析中除去高度相关的变量,研究发现在关系和回归参数的强度中发现了高空间非静止的存在。 Co-Kriging插值方法对温度(R〜2 = 0.823)产生了强烈的关系,但对沉淀的关系相对较弱(R〜2 = 0.542)。 OLS方法导致温度(R〜2 = 0.68)的关系较低(R〜2 = 0.3)。用GWR法获得最高调整的R〜2值;温度为0.96和0.66沉淀。

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