http://www.cnr.it/ontology/cnr/individuo/prodotto/ID193268
Comparison of TRMM satellite rainfall estimates with rain gauge data and landslide empirical rainfall thresholds under different morphological and climatological conditions in Italy (Abstract/Poster in rivista)
- Type
- Label
- Comparison of TRMM satellite rainfall estimates with rain gauge data and landslide empirical rainfall thresholds under different morphological and climatological conditions in Italy (Abstract/Poster in rivista) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Alternative label
M. Rossi (1,2), D. Kirschbaum (3), S. Luciani (1,2), and F. Guzzetti (1) (2012)
Comparison of TRMM satellite rainfall estimates with rain gauge data and landslide empirical rainfall thresholds under different morphological and climatological conditions in Italy
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- M. Rossi (1,2), D. Kirschbaum (3), S. Luciani (1,2), and F. Guzzetti (1) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- (1) Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica, Perugia, Italy
(mauro.rossi@irpi.cnr.it, +39 075.5014420)
(2) Dipartimento di Scienze della Terra, Università degli Studi di Perugia, Italy
(3) NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, Md., Unites States (literal)
- Titolo
- Comparison of TRMM satellite rainfall estimates with rain gauge data and landslide empirical rainfall thresholds under different morphological and climatological conditions in Italy (literal)
- Abstract
- Quantitative information on rainfall is necessary to predict the possible occurrence of rainfall-induced landslides.
Landslide early warning systems attempt to predict rainfall-induced landslides through the comparison of quanti-
tative rainfall information with empirical rainfall thresholds for the possible occurrence of landslides. Most of the
systems exploit rainfall measurements obtained from networks of gauges, and only a few systems use satellite rain-
fall estimates. All the systems exploit empirical rainfall thresholds defined using rainfall measurements obtained
from networks of rain gauges. Despite the availability of quantitative satellite rainfall estimates, and their experi-
mental use in existing warning systems, surprisingly limited research has been done to compare satellite rainfall
estimates and rain gauge rainfall measurements, for the forecasting of possible landslide occurrence. In this work,
we analyse the relationships between rainfall measurements obtained from a network of > 1950 rain gauges in
Italy and rainfall satellite estimates for the same area obtained by the NASA Tropical Rainfall Measuring Mission
(TRMM-RT and TRMM-v6), for the period 2009-2010. Coupling point rain gauge measurements and TRMM
rainfall estimates at individual grid cells (0.25o latitude × 0.25o longitude), we evaluate the correlation between
the gauge rainfall measurements and the satellite rainfall estimates in different morphological and climatologi-
cal conditions, using linear and power-law fitting models. We use cumulative rainfall measurements/estimates for
different periods, from 3 to 72 hours. We analyse and compare the distributions of the ground-based rainfall mea-
surements and the satellite rainfall estimates using standard non-parametric and parametric statistical methods. We
observe significant differences in the obtained distributions for different morphological and climatological areas
in Italy. Differences are larger in mountainous areas, and collectively reveal a complex relationship between the
ground-based rainfall measurements and the satellite rainfall estimates. Power law correlation models have the best
fitting performance, at the expenses of large prediction intervals, particularly for large values of cumulated rainfall.
An exponential distribution provides a better fit for satellite rainfall estimates, compared to rain gauge measure-
ments. The preliminary results indicate that specific empirical rainfall thresholds have to be defined to fully exploit
satellite rainfall estimates in existing early warning system. (literal)
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