The Use of Geographically Weighted Regression for the Relationship among Extreme Climate Indices in China

<table>Geographic distributions of the estimated GWR coefficient functions ((a) <svg height="21.200001" id="M174" style="vertical-align:-4.24515pt" version="1.1" viewbox="0 0 52.112499 21.200001" width="52.112499" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg>, (b) <svg height="21.200001" id="M175" style="vertical-align:-4.24515pt" version="1.1" viewbox="0 0 52.112499 21.200001" width="52.112499" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg>, and (d) <svg height="21.200001" id="M177" style="vertical-align:-4.24515pt" version="1.1" viewbox="0 0 52.112499 21.200001" width="52.112499" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g transform="matrix(.017,-0,0,-.017,16.275,15.85)"><use xlink:href="#x28"></use></g><g transform="matrix(.017,-0,0,-.017,22.157,15.85)"><use xlink:href="#x1D462"></use></g><g transform="matrix(.017,-0,0,-.017,31.302,15.85)"><use xlink:href="#x2C"></use></g><g transform="matrix(.017,-0,0,-.017,37.999,15.85)"><use xlink:href="#x1D463"></use></g><g transform="matrix(.017,-0,0,-.017,46.159,15.85)"><use xlink:href="#x29"></use></g>
</svg>) over the 504 stations in China.</table>

Mathematical Problems in Engineering

fig4

Figure 4

Figure 4: The Use of Geographically Weighted Regression for the Relationship among Extreme Climate Indices in China 