How far are we from the use of satellite rainfall products in landslide forecasting?

Satellite rainfall products have been available for many years (since '90) with an increasing spatial/temporalresolution and accuracy. Their global scale coverage and near real-time products perfectly fit the need of an earlywarning landslide system. Notwithstanding these characteristics, the number of studies employing satelliterainfall estimates for predicting landslide events is quite limited.In this study, we propose a procedure that allows us to evaluate the capability of different rainfall products toforecast the spatial-temporal occurrence of rainfall-induced landslides using rainfall thresholds. Specifically, theassessment is carried out in terms of skill scores, and receiver operating characteristic (ROC) analysis. Theprocedure is applied to ground observations and four different satellite rainfall estimates: 1) the Tropical RainfallMeasurement Mission Multi-satellite Precipitation Analysis, TMPA, real time product (3B42-RT), 2) theSM2RASC product obtained from the application of SM2RAIN algorithm to the Advanced SCATterometer(ASCAT) derived satellite soil moisture (SM) data, 3) the Precipitation Estimation from Remotely SensedInformation using Artificial Neural Network (PERSIANN), and 4) the Climate Prediction Center (CPC) MorphingTechnique (CMORPH). As case study, we consider the Italian territory for which a catalogue listing 1414 rainfallinducedlandslides in the period 2008-2014 is available.Results show that satellite products underestimate rainfall with respect to ground observations. However, byadjusting the rainfall thresholds, satellite products are able to identify landslide occurrence, even though withless accuracy than ground-based rainfall observations. Among the four satellite rainfall products, CMORPH andSM2RASC are performing the best, even though differences are small. This result is to be attributed to the highspatial/temporal resolution of CMORPH, and the good accuracy of SM2RSC. Overall, we believe that satelliterainfall estimates might be an important additional data source for developing continental or global landslidewarning systems.