Redirigiendo al acceso original de articulo en 22 segundos...
Inicio  /  Water  /  Vol: 10 Núm: 2 Par: 0 (2018)  /  Artículo
ARTÍCULO
TITULO

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM) for Rainfall Variability over the Pacific Slope and Coast of Ecuador

Bolívar Erazo    
Luc Bourrel    
Frédéric Frappart    
Oscar Chimborazo    
David Labat    
Luis Dominguez-Granda    
David Matamoros and Raul Mejia    

Resumen

A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC). A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965?2015. This product is compared with the Global Precipitation Climatology Centre (GPCC) dataset, the Climatic Research Unit?University of East Anglia (CRU) dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7) dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias) indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7%) but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of -28%). The average RMSE and Rbias of 68.7 and -2.8% of TRMM are comparable with the GPCC (69.8 and 5.7%) and CRU (102.3 and -2.3%) products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event) over the EPSC and specifically towards the center-south of the EPSC (Guayas basin) but present underestimations for the moderate El Niño of 2002?2003 event and the weak 2009?2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

 Artículos similares

       
 
Jeonghoon Lee, Okjeong Lee, Jeonghyeon Choi, Jiyu Seo, Jeongeun Won, Suhyung Jang and Sangdan Kim    
The effect of mountainous regions with high elevation on hourly timescale rainfall presents great difficulties in flood forecasting and warning in mountainous areas. In this study, the hourly rainfall?elevation relationship of the regional scale is inves... ver más
Revista: Water

 
Abdelmounim Bouadila, Ismail Bouizrou, Mourad Aqnouy, Khalid En-nagre, Yassine El Yousfi, Azzeddine Khafouri, Ismail Hilal, Kamal Abdelrahman, Lahcen Benaabidate, Tamer Abu-Alam, Jamal Eddine Stitou El Messari and Mohamed Abioui    
In semi-arid regions such as the southwestern zone of Morocco, better management of water resources is crucial due to the frequent flooding phenomena. In this context, the use of hydrological models is becoming increasingly important, specifically in the... ver más
Revista: Water

 
Yakob Umer, Victor Jetten, Janneke Ettema and Gert-Jan Steeneveld    
This study configures the Weather Research and Forecasting (WRF) model with the updated urban fraction for optimal rainfall simulation over Kampala, Uganda. The urban parameter values associated with urban fractions are adjusted based on literature revie... ver más
Revista: Hydrology

 
David Kemp and Guna Hewa Alankarage    
In the field of hydrology, event-based models are commonly used for flood-flow prediction in catchments, for use in flood forecasting, flood risk assessment, and infrastructure design. The models are simplistic, as they do not consider longer-term catchm... ver más
Revista: Hydrology

 
Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche and Soltane Ameur    
To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Genera... ver más
Revista: Hydrology