# Multi-Sensor Precipitation Estimation from Space: Data Sources, Methods and Validation
## 6 Validation
### Uncertainties and Recommendations for SPPs
\begin{table}
\begin{tabular}{l l l l l l l} \hline
**SPP** & **Region** & **Scale** & **Main Results** & **Reference** & **Remarks** \\ \hline IMERG V03 & U.S. & Daily & IMERG: 8-30\% & [205] & Uncalibrated SPPs \\
3B42 RT V7 & U.S. & Daily & 3B42 RT: 2-18\% & & all data \\ \hline IMERG V06 & U.S., & Annual & IMERG: \(-\)1.25\%;3B42: \(-\)7.17\% & & [184] & Tropical cyclone \\
3B42 V7 & Mexico & hourly & \begin{tabular}{l} IMERG: 501-54.9\%;3B42: 2.9-5\% (TCP) \\ (statistically significant differences (\(p<0.05\)) \\ \end{tabular} & & & precipitation (TCP) \\ \hline IMERG V05 & China & Annual & \begin{tabular}{l} IMERG \(-\)0.07 \\ 3B42 V7 \\ \end{tabular} & 42.51 & [183] & Extreme precipitation \\ \hline IMERG V06 & & & \begin{tabular}{l} IMERG: 5\% (\(-\)5-10\%) \\ 3B42 V5 \\ CMORPH V1.0 \\ CMORPH V1.0 \\ CMORPH V.07 \\ PERSIANN-CDR \\ \end{tabular} & China & Daily & \begin{tabular}{l} IMERG: 5\% (\(-\)5-10\%) \\ 3B42 -5\% (\(-\)10-5\%) \\ CMORPH V.08 \\ CMORPH V.09 \\ CGR-8\% (\(-\)5-115\%) \\ \end{tabular} & & & & \\ \hline \multirow{6}{*}{3B42 RT V7 } & \multirow{6}{*}{Iran} & \multirow{6}{*}{6-Hourly} & bias/\% & POD & FAR & \\ \cline{3-5}  & & & 3B42 RT & \(-\)56.06 & 0.05 & 0.89 & \\ \cline{3-5}  & & & \begin{tabular}{l} PERSIANN \\ \end{tabular} & 144.08 & 0.36 & 0.13 & & 3B42 RT V7 \\ \cline{3-5}  & & & \begin{tabular}{l} CMOROH \\ \end{tabular} & \(-\)8.01 & 0.44 & 0.91 & & \\ \cline{3-5}  & & & \begin{tabular}{l} bias/\% \\ \end{tabular} & Daily & Monthly & Annual & & \\ \cline{3-5}  & & & \begin{tabular}{l} 3B42 RT \\ \end{tabular} & \(-\)56.12 & \(-\)56.13 & \(-\)56.14 & & \\ \cline{3-5}  & & & \
\begin{tabular}{l} PERSIANN \\ \end{tabular} & 143.86 & 143.84 & 143.84 & & \\ \cline{3-5}  & & &
\begin{tabular}{l} CMOROH \\ \end{tabular} & \(-\)8.08 & \(-\)8.10 & \(-\)8.10 & & \\ \hline \end{tabular}
\end{table} 
Table 4: _Cont._ \begin{table}
\begin{tabular}{l l l l l l} \hline
**SPF** & **Region** & **Scale** & **Main Results** & **Reference** & **Remarks** \\ \hline
3b42 V7 & & & 3b42 RT/3b42/CMORPH+RAW/CMORPH: & & & \\
3b42 RT V7 & & & POD \(<\) 30\%, miss 70\%; & & \\  & CMORPH+RAW & & GSMP, Gauge: POD \(>\) 60\%; FAR \(<\) 30\%; & Winter \\ CMORPH+ V10 & Central & & PESIANN-CD: POD \(>\) 60\%, FAR \(>\) 40\% & [212] & \\ CMORPH+MVK & Asia & & & & \\ GSMP-gauge V6 & & & all SPPs; the worst performance, POD \(<\) 30\%, highest misses, FAR \(>\) 60\% & Over the desert region \\  & PERSIANN-RAW & & & CMORPH, RAW, CMORPH, miss up to 100\% & in summer \\  & PERSIANN-CD & & & \\ \hline CMORPH V0.x & Mountains & Monthly & 3b42\(\textascifrac{-14}{\%}\);3b42 RT: 13\%; CMORPH: 11\% & [23] & \\
3b42 V6 & Highlands of & & & & \\
3b42 RT V6 & Columbia & Monthly & 3b42\(\textascifrac{-16}{\%}\);3b42 RT: 17\%; CMORPH \(-\)9\% & & \\ \hline IMERC & & & & \\ CMORPH+RAW & & & RMSE/mm & & \\ V1.0 & & IMERG: 0.6\(\textascifrac{-1}{\%}\); CMORPH: 0.9\(\textascifrac{-5}{\%}\) & & \\ CSMP, \(\textascifrac{-1}{\%}\) & Africa & Daily & GSMP, 0.8\(\textascifrac{-4}{\%}\); PERSIANN: 0.7\(\textascifrac{-5}{\%}\) & [171] & PESIAN, CDR and \\  & PERSIANN-CDR- & & & & GSMP, NRT \\  & & & & Corrected satellite products depict notable agreement for POD and FAR & \\  & & & & \\ \hline
3b43 V6 & & & & & \\
3b42 V5 & Complex & & GPCP: 20\%; CMAP: 9\%; 3b43: 8\% & & \\ CMAP V1.2 & Complex & & & \\ GPCP V2 & topography, East & Monthly & & \\ GPCP IDD & Africa & & & \\ \hline
3b42 RT V6 & Ethiopian river & & & \\ CMORPH 70.x & basins & Monthly & CMORPH 11\%; 3b42 RT: 5\%; PERSIANN: \(-\)43\% & [175] & \\  & PERSIANN & & & \\ \hline CMORPH V1.0 & & & & \\
3b42 RT V7 & Southern South & & & \\ CMORPH \(-\)73-81\% & & & & \\ \hline \end{tabular}
\end{table} 
Table 4. Cont. Quantifying SPE errors is an immensely challenging task due to their association with a multitude of factors, particularly at fine spatiotemporal resolutions. The anticipated performance of SPEs may be hindered by various common underlying factors, climatic and meteorological conditions, seasonal variations, precipitation intensities, and latitudes.