Evaluation of CMPA precipitation estimate in the evolution of typhoon-related storm
rainfall in Guangdong, China
1
Dashan Wang, 1Xianwei Wang, 1,2 Lin Liu, 1Dagang Wang, 1Huabing Huang, and 1Cuilin
Pan
1
Center of Integrated Geographic Information Analysis, School of Geography and Planning,
And Guangdong Key Laboratory for Urbanization and Geo-simulation
Sun Yat-sen University, Guangzhou, China
2
Department of Geography, University of Cincinnati, Cincinnati, OH, USA
AUXILIARY MATERIAL
Introduction
This auxiliary file contains six figures named from A.Figure 1 to A.Figure 6. These figures
are similar to Figure 2–7 in the main manuscript, but for the other four typhoon-related
rainfall events to provide better understanding about the performance of CMPA.
A.Figure 1. Total precipitation for the auxiliary four typhoon events (Mujigae, Kalmaegi,
Rammasun and Rumbia) detected by rain gauges (a–d) and by CMPA (e–h), and the densitycolor scatter plots of CMPA versus gauge data (i–l). Density is the number of grids within a
rain depth interval of 5 mm. The black lines in A.Figure 1a–h outline the tracks of the four
typhoon events.
A.Figure 2. Spatial distributions of the Correlation Coefficient (a–d), Relative Bias (e–h),
Root Mean Squared Difference (i–l) and the density scatter plots (m–p) of the hourly CMPA
estimates against rain gauge observations for the auxiliary four typhoon rain events. All are
computed using the gauge-CMPA pairs at each grid during the events. The black lines outline
the tracks of typhoon events.
A.Figure 3. (a–d) Probability distribution functions by occurrence (PDFc) and (e–h) by
volume (PDFv) within different rain depth intervals for the hit pairs of the auxiliary four
typhoon rain events.
A.Figure 4. Gauge-based relative bias of CMPA within different rain depth intervals of three
typhoon events. The box represents the 25% and 75% quartiles, and the line and dot within
the box represent the median and mean values, respectively. The whiskers indicate the 5%
and 95% percentile.
A.Figure 5. Probability distribution functions by occurrence (PDFc) for the false and miss
counts.
A.Figure 6. (a1–a4) Spatial distribution of the three rain types obtained by the K-means
cluster analysis from gauge observations for the Mujigae, Kalmaegi, Rammasun and Rumbia
events; (b1–d4) hourly (stairs, left-hand vertical axis) and accumulated (lines, right-hand
vertical axis) rain series from gauge and CMPA at the three clustered types of the four events.