## 2 Data and Methods
### Datasets
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**No** & **Abbreviation** & **Sources** & **Full Name** & **Spatial** & **Temporal** & **Coverage** & **References** \\ \hline
1 & CRU & G & \
\begin{tabular}{c} Climatic Research Unit (CRU) \\ Time-Series (CRUST4.01) \\ \end{tabular} &
\begin{tabular}{c} 0.5\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1901–2016 & [13] \\ \hline
2 & CPCGlobal & G & \
\begin{tabular}{c} Climate Prediction Center \\ (CPC) Unified \\ \end{tabular} &
\begin{tabular}{c} 0.5\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1979–present & [38] \\ \hline
3 & PRECL & G & \
\begin{tabular}{c} PRECIPitation REconstruction \\ over Land (PREC/L) \\ \end{tabular} &
\begin{tabular}{c} 0.5\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1948–present & [39] \\ \hline
4 & GPCC05 & G & \
\begin{tabular}{c} Global Precipitation \\ climatology Centre (GPCC) \\ Full Data Reanalysis \\ \end{tabular} &
\begin{tabular}{c} 0.5\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1891–2016 & [40] \\ \hline
5 & GPCC025 & G & \
\begin{tabular}{c} Global Precipitation \\ climatology Centre (GPCC) \\ Full Data Reanalysis \\ \end{tabular} &
\begin{tabular}{c} 0.25\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1891–2016 & [40] \\ \hline
6 & HERRAULT & G & \
\begin{tabular}{c} High resolution Regional \\ statistical GOFCC v7 \\ for the Caribbean \\ \end{tabular} &
\begin{tabular}{c} 0.033\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1950–2017 & [32] \\ \hline
7 & CHIRPS & G,S & \
\begin{tabular}{c} Climate Hazards group \\ Infrared Precipitation with \\ Stations (CHIRPS) \\ \end{tabular} &
\begin{tabular}{c} 0.05\({}^{\circ}\) \\ (land) \\ \end{tabular} & 1981–present & [17] \\ \hline
8 & PERISANNCD & G,S &
\begin{tabular}{c} Precipitation Estimation from \\ Remotely Sensed Information \\ using Artificial Neural \\ Networks (PERISANN) \\ Climate Data Record (CDR) \\ PERISANN-CDR \\ \end{tabular} & 0.25\({}^{\circ}\) & 1983–present & [16] \\ \hline
9 & TERACLIMATE & G,R &
\begin{tabular}{c} High-resolution global dataset \\ of monthly climate and climatic \\ water balance from 1958–2015 \\ \end{tabular} & 0.0416\({}^{\circ}\) & 1958–2015 & [41] \\ \hline
10 & CHELSA & G,R &
\begin{tabular}{c} Climatologies at high \\ resolution for the earth’s land \\ surface areas \\ \end{tabular} & 0.0083\({}^{\circ}\) & 1979–2013 & [42] \\ \hline
11 & CFSR & R &
\begin{tabular}{c} National Centers for \\ Environmental Prediction \\ (NCEP) Climate Forecast \\ System Reanalysis (CFSR) \\ \end{tabular} & 0.3125\({}^{\circ}\) & 1979–2010 & [43] \\ \hline
12 & ERAi & R &
\begin{tabular}{c} European Center for \\ Medium-range Forecast \\ Reanalysis Interim \\ (ERA-Interim) \\ \end{tabular} & 0.25\({}^{\circ}\) & 1979–present & [44] \\ \hline
13 & ERA5 & R &
\begin{tabular}{c} European Center for \\ Medium-range Forecast \\ Reanalysis \\ \end{tabular} & 0.25\({}^{\circ}\) & 1979–present & [45] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Information on GPP used in this study. The abbreviations in column 3 are defined as follow: G, gauges; S, satellite; and R, reanalysis. The term land in the column 5 means the dataset is limited to land areas only. A detailed description of each GPP is provided as Supplementary Information.