Evaluation of Precipitation Estimates CMORPH-CRT on Regions of Mexico with Different Climates

Satellite-based precipitation (SBP) products with global coverage have the potential to overcome the lack of information in places where there are no rain gauges to perform hydrological analyses; however, it is necessary to evaluate the reliability of the SBP products. In this study, we evaluated th...

Full description

Saved in:
Bibliographic Details
Published in:Water (Basel) 2019-08, Vol.11 (8), p.1722
Main Authors: Bruster-Flores, José L., Ortiz-Gómez, Ruperto, Ferriño-Fierro, Adrian L., Guerra-Cobián, Víctor H., Burgos-Flores, Dagoberto, Lizárraga-Mendiola, Liliana G.
Format: Article
Language:English
Subjects:
Algorithms
Bias
Climate
Climate prediction
Correlation coefficient
Correlation coefficients
False alarms
Gauges
Hydrology
Indicators
Morphing
Precipitation
Rain
Rain gauges
Rainfall
Reliability analysis
Root-mean-square errors
Statistical analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Satellite-based precipitation (SBP) products with global coverage have the potential to overcome the lack of information in places where there are no rain gauges to perform hydrological analyses; however, it is necessary to evaluate the reliability of the SBP products. In this study, we evaluated the performance of the Climate Prediction Center morphing technique with corrected bias (CMORPH-CRT) product in 14 sites in Mexico. The evaluation was carried out using two approaches: (1) using categorical metrics that include indicators of probability of detection (POD), false alarm rate (FAR), critical success index (CSI), and frequency bias index (FBI); and (2) through statistical indicators such as the mean absolute error (MAE), root mean square error (RMSE), relative bias (RB), and correlation coefficient (CC). The analysis was carried out with two levels of temporal aggregation: 30 min and daily. The results indicate that the CMORPH-CRT product overestimates the number of precipitation events in most cases since FBI values greater than 1 in 78.6% of analyzed stations were obtained. Also, we obtained CC values in the range of 0.018 to 0.625, which implied weak to moderate correlations, and found that in all stations, the CMORPH-CRT product overestimates the precipitation (RB > 0).
ISSN:2073-4441
2073-4441
DOI:10.3390/w11081722