The Convective Rainfall Rate from Cloud Physical Properties Algorithm for Meteosat Second Generation Satellites: Microphysical Basis and Intercomparisons using an Object-Based Method

Tapiador, Francisco J.; Marcos, Cecilia; Sancho, Juan Manuel

doi:10.20944/preprints201901.0048.v1

Cited by 6 publications

References 39 publications

(48 reference statements)

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Accuracy Assessment of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations over Epirus Region, Greece

et al. 2022

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The study concerns the quantitative evaluation of a satellite-based rain rate (RR) estimation algorithm using measurements from a network of ground-based meteorological stations across the Epirus Region, Greece, an area that receives among the maximum precipitation amounts over the country. The utilized version of the rain estimation algorithm uses the Meteosat-11 Brightness Temperature in five spectral regions ranging from 6.0 to 12.0 μm (channels 5–7, 9 and 10) to estimate the rain intensity on a pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The rain recordings of the meteorological stations’ network were spatiotemporally correlated with the satellite-based rain estimations, leading to a dataset of 2586 pairs of matched values. A statistical analysis of these pairs of values was conducted, revealing a Mean Error (ME) of −0.13 mm/h and a correlation coefficient (CC) of 0.52. The optimal computed Probability of False Detection (POFD), Probability of Detection (POD), the False Alarm Ratio (FAR) and the bias score (BIAS) are equal to 0.32, 0.88, 0.12 and 0.94, respectively. The study of the extreme values of the RR (the highest 10%) also shows satisfactory results (i.e., ME of 1.92 mm/h and CC of 0.75). The evaluation statistics are promising for operationally using this algorithm for rain estimation on a real-time basis.

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Accuracy Assessment of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations over Epirus Region, Greece

et al. 2022

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Efficiency of the NWC SAF Version 2021 CRRPh Precipitation Product: Comparison against Previous NWC SAF Precipitation Products and the Influence of Topography

Karagiannidis

Lahuerta

Calbet

et al. 2023

Climate

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The algorithm of the Convective Rainfall Rate with Microphysical Properties (CRRPh) product of the 2021 version of the Nowcasting and Very Short Range Forecasting Satellite Application Facility (NWC SAF) presents innovative characteristics. It was developed employing principal components analysis to reduce the number of utilized parameters and uses the same mathematical scheme for day and night, simulating the missing visual channels and satellite-derived cloud water path information that is unavailable during nighttime. Applying adequate statistical methodologies and scores and using rain gauge data as ground truth, it is shown that the new algorithm appears to be significantly improved compared to its predecessors in regard to the delineation of the precipitation areas. In addition, it minimizes the day–night difference in the estimation efficiency, which is a remarkable achievement. The new product suffers from slightly higher errors in the precipitation accumulations. Finally, it is shown that topography does not seem to affect the estimation efficiency of the product. In light of these results, it is argued that, overall, the new algorithm outperforms its predecessors and, possibly after adequate adaptations, can be used as a real-time total precipitation product.

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Evaluation of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations. Preliminary Results in a Region with Complex Terrain

Kolios

Hatzianastassiou

Lolis

2020

The 3rd International Electronic Conference on Atmospheric Sciences

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The present study is a first attempt to quantitatively evaluate an existing satellite-based rain estimation algorithm using measurements from a network of ground-based meteorological stations. The study domain is the Epirus Region (the rainiest region in Greece) where the laboratory of Meteorology and Climatology of Ioannina University operates eight meteorological stations distributed across the study domain. The utilized version of the rain estimation algorithm is using the Meteosat-11 Brightness Temperature in the 10.8 μm channel (BT10.8μm) to estimate the rain intensity on a 4 Κm pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The rain recordings of the meteorological stations' network were spatiotemporally correlated with the Meteosat-11 data. These correlations led to a dataset with 1323 pairs of rain recordings and their relative rain estimations from the satellite-based algorithm. A statistical analysis of these pairs of values was conducted revealing a Mean Error (ME) of 0.22 mm/hr (14% error with respect to the mean value of the recordings). The computed Probability of False Detection (POFD), Probability of Detection (POD) and the bias score are equal to 0.22, 0.69 and 0.88, respectively. The evaluation statistics are promising for operationally using this algorithm for rain estimation on a real-time basis.

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The Convective Rainfall Rate from Cloud Physical Properties Algorithm for Meteosat Second Generation Satellites: Microphysical Basis and Intercomparisons using an Object-Based Method

Cited by 6 publications

References 39 publications

Accuracy Assessment of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations over Epirus Region, Greece

Accuracy Assessment of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations over Epirus Region, Greece

Efficiency of the NWC SAF Version 2021 CRRPh Precipitation Product: Comparison against Previous NWC SAF Precipitation Products and the Influence of Topography

Evaluation of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations. Preliminary Results in a Region with Complex Terrain

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