Back to Search
Start Over
Validation of Satellite, Reanalysis and RCM Data of Monthly Rainfall in Calabria (Southern Italy)
- Source :
- Remote sensing (Basel) 11 (2019). doi:10.3390/rs11131625, info:cnr-pdr/source/autori:Giulio Nils Caroletti, Roberto Coscarelli, Tommaso Caloiero/titolo:Validation of Satellite, Reanalysis and RCM Data of Monthly Rainfall in Calabria (Southern Italy)/doi:10.3390%2Frs11131625/rivista:Remote sensing (Basel)/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume:11, Remote Sensing, Volume 11, Issue 13, Remote Sensing, Vol 11, Iss 13, p 1625 (2019)
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- Skills in reproducing monthly rainfall over Calabria (southern Italy) have been validated for the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) satellite data, the E-OBS dataset and 13 Global Climate Model-Regional Climate Model (GCM-RCM) combinations, belonging to the ENSEMBLES project output set. To this aim, 73 rainfall series for the period 1951&ndash<br />1980 and 79 series for the period 1981&ndash<br />2010 have been selected from the database managed by Multi-Risk Functional Centre of the Regional Agency for Environmental Protection (Regione Calabria). The relative mean and standard deviation errors, and the Pearson correlation coefficient have been used as validation metrics. Results showed that CHIRPS satellite data (available only for the 1981&ndash<br />2010 validation period) and RCMs based on the ECHAM5 Global Climate performed better both in mean error and standard deviation error compared to other datasets. Moreover, a slight appreciable improvement in performance for all ECHAM5-based models and for the E-OBS dataset has been observed in the 1981&ndash<br />2010 time-period. The whole validation-and-assessment procedure applied in this work is general and easily applicable where ground data and gridded data are available. This procedure might help scientists and policy makers to select among available datasets those best suited for further applications, even in regions with complex orography and an inadequate amount of representative stations.
- Subjects :
- validation
010504 meteorology & atmospheric sciences
Mean squared error
Science
0207 environmental engineering
Orography
02 engineering and technology
precipitation
01 natural sciences
Standard deviation
Pearson product-moment correlation coefficient
symbols.namesake
Satellite data
Climatology
symbols
RCMs
General Earth and Planetary Sciences
Environmental science
Satellite
Climate model
Precipitation
020701 environmental engineering
satellite data
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 20724292
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....86402913ca0cab734f87d53da25c7cb8
- Full Text :
- https://doi.org/10.3390/rs11131625