Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach
In this study, an object-based verification method was used to reveal the existence of systematic errors in three satellite precipitation products: Tropical Rainfall Measurement Mission (TRMM), Climate Prediction Center Morphing Technique (CMORPH), and Precipitation Estimation from Remotely Sensed I...
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2011
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01480227_v116_n8_p_Demaria http://hdl.handle.net/20.500.12110/paper_01480227_v116_n8_p_Demaria |
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paper:paper_01480227_v116_n8_p_Demaria2023-06-08T15:13:07Z Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach Climatology Computer simulation Errors Neural networks Rain gages Remote sensing Satellites Space shuttles Storms Systematic errors Artificial Neural Network Austral summers Bias correction Climate prediction centers Error decomposition Fine structures Ground observations Hydrological models Macro scale Mesoscale Convective System Morphing techniques Multiple satellites Noisy measurements Object based PERSIANN Precipitation estimation from remotely sensed information Rainfall rates River basins Satellite precipitation Satellite products Significant impacts South America Southeastern South America Spatial location Tropical rainfall measurement missions Verification method Rain climate prediction error analysis hydrological modeling mesoscale meteorology noise precipitation assessment rainfall satellite imagery spatial analysis storm streamflow South America In this study, an object-based verification method was used to reveal the existence of systematic errors in three satellite precipitation products: Tropical Rainfall Measurement Mission (TRMM), Climate Prediction Center Morphing Technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN). Mesoscale convective systems (MCSs) for the austral summer 2002-2003 in the La Plata river basin, southeastern South America, were analyzed with the Contiguous Rain Area (CRA) method. Errors in storms intensity, volume, and spatial location were evaluated. A macroscale hydrological model was used to assess the impact of spatially shifted precipitation on streamflows simulations. PERSIANN underestimated the observed average rainfall rate and maximum rainfall consistent with the detection of storm areas systematically larger than observed. CMORPH overestimated the average rainfall rate while the maximum rainfall was slightly underestimated. TRMM average rainfall rate and rainfall volume correlated extremely well with ground observations whereas the maximum rainfall was systematically overestimated suggesting deficiencies in the bias correction procedure to filter noisy measurements. The preferential direction of error displacement in satellite-estimated MCSs was in the east-west direction for CMORPH and TRMM. Discrepancies in the fine structure of the storms dominated the error decomposition of all satellite products. Errors in the spatial location of the systems influenced the magnitude of simulated peaks but did not have a significant impact on the timing indicating that the system's response to precipitation was mitigating the effect of the errors. Copyright 2011 by the American Geophysical Union. 2011 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01480227_v116_n8_p_Demaria http://hdl.handle.net/20.500.12110/paper_01480227_v116_n8_p_Demaria |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Climatology Computer simulation Errors Neural networks Rain gages Remote sensing Satellites Space shuttles Storms Systematic errors Artificial Neural Network Austral summers Bias correction Climate prediction centers Error decomposition Fine structures Ground observations Hydrological models Macro scale Mesoscale Convective System Morphing techniques Multiple satellites Noisy measurements Object based PERSIANN Precipitation estimation from remotely sensed information Rainfall rates River basins Satellite precipitation Satellite products Significant impacts South America Southeastern South America Spatial location Tropical rainfall measurement missions Verification method Rain climate prediction error analysis hydrological modeling mesoscale meteorology noise precipitation assessment rainfall satellite imagery spatial analysis storm streamflow South America |
| spellingShingle |
Climatology Computer simulation Errors Neural networks Rain gages Remote sensing Satellites Space shuttles Storms Systematic errors Artificial Neural Network Austral summers Bias correction Climate prediction centers Error decomposition Fine structures Ground observations Hydrological models Macro scale Mesoscale Convective System Morphing techniques Multiple satellites Noisy measurements Object based PERSIANN Precipitation estimation from remotely sensed information Rainfall rates River basins Satellite precipitation Satellite products Significant impacts South America Southeastern South America Spatial location Tropical rainfall measurement missions Verification method Rain climate prediction error analysis hydrological modeling mesoscale meteorology noise precipitation assessment rainfall satellite imagery spatial analysis storm streamflow South America Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| topic_facet |
Climatology Computer simulation Errors Neural networks Rain gages Remote sensing Satellites Space shuttles Storms Systematic errors Artificial Neural Network Austral summers Bias correction Climate prediction centers Error decomposition Fine structures Ground observations Hydrological models Macro scale Mesoscale Convective System Morphing techniques Multiple satellites Noisy measurements Object based PERSIANN Precipitation estimation from remotely sensed information Rainfall rates River basins Satellite precipitation Satellite products Significant impacts South America Southeastern South America Spatial location Tropical rainfall measurement missions Verification method Rain climate prediction error analysis hydrological modeling mesoscale meteorology noise precipitation assessment rainfall satellite imagery spatial analysis storm streamflow South America |
| description |
In this study, an object-based verification method was used to reveal the existence of systematic errors in three satellite precipitation products: Tropical Rainfall Measurement Mission (TRMM), Climate Prediction Center Morphing Technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN). Mesoscale convective systems (MCSs) for the austral summer 2002-2003 in the La Plata river basin, southeastern South America, were analyzed with the Contiguous Rain Area (CRA) method. Errors in storms intensity, volume, and spatial location were evaluated. A macroscale hydrological model was used to assess the impact of spatially shifted precipitation on streamflows simulations. PERSIANN underestimated the observed average rainfall rate and maximum rainfall consistent with the detection of storm areas systematically larger than observed. CMORPH overestimated the average rainfall rate while the maximum rainfall was slightly underestimated. TRMM average rainfall rate and rainfall volume correlated extremely well with ground observations whereas the maximum rainfall was systematically overestimated suggesting deficiencies in the bias correction procedure to filter noisy measurements. The preferential direction of error displacement in satellite-estimated MCSs was in the east-west direction for CMORPH and TRMM. Discrepancies in the fine structure of the storms dominated the error decomposition of all satellite products. Errors in the spatial location of the systems influenced the magnitude of simulated peaks but did not have a significant impact on the timing indicating that the system's response to precipitation was mitigating the effect of the errors. Copyright 2011 by the American Geophysical Union. |
| title |
Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| title_short |
Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| title_full |
Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| title_fullStr |
Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| title_full_unstemmed |
Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach |
| title_sort |
evaluation of mesoscale convective systems in south america using multiple satellite products and an object-based approach |
| publishDate |
2011 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01480227_v116_n8_p_Demaria http://hdl.handle.net/20.500.12110/paper_01480227_v116_n8_p_Demaria |
| _version_ |
1768545460104986624 |