A Quality Control Method Based on an Improved Random Forest Algorithm for Surface Air Temperature Observations

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/amete/volume-2017/8601296/figures/8601296.fig.0012a.svgz" name="8601296.fig.0012a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Edge stations of GZ</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/amete/volume-2017/8601296/figures/8601296.fig.0012b.svgz" name="8601296.fig.0012b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Edge stations of MY</td></tr></table>

<div>Comparisons of performance between the ARF and SRT methods for different edge stations: (a) Guangzhou and (b) Miyun.</div>

Advances in Meteorology

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Figure 12

Figure 12: A Quality Control Method Based on an Improved Random Forest Algorithm for Surface Air Temperature Observations 