CNR

 The RU at CNR (Consiglio Nazionale delle Ricerche) will provide well-known expertise in remote sensing of precipitation and in the statistical analysis of remotely-sensed rainfall. In particular, the Institute of Atmospheric Sciences and Climate (CNR-ISAC) has more than 20-year experience in climate sciences and is recognized internationally through its international collaborations, in Europe and elsewhere. The PI F. Marra is expert in the use of novel statistical methods, such as MEVD, for the analysis of extremes, and has vast research experience in the remote sensing of precipitation and in their application for natural hazards monitoring. In the research tasks, PI F. Marra will be assisted by an experienced researcher (Post-Doc) to be specifically hired for INTENSE. CNR will 1) manage INTENSE activities and organize the synergies between the four RUs, 2) lead WP3, in which spatial patterns and temporal changes in rainfall extremes will be quantified, 3) collaborate with UNIPD in developing and performing probability distribution-based bias corrections on satellite rainfall retrievals, 4) collaborate with UNIUD in the generation of synthetic climatic time series for WP4.

UNIUD

The RU at UNIUD (University of Udine) is led by the Associated Investigator and Co-PI E. Arnone, who will provide her expertise in the field of rainfall-induced landslide modeling. More in detail, her experience focuses on exploiting physically-based approaches for understanding hydrological and geomorphological processes evolution at the basin scale. Such an approach is especially appropriate to assess the impacts of extreme rainfall events and climate changes on catchment natural hazards. The team counts on the strong and long collaboration with the RU at UNIPA and on international collaborations in the field of physically-based modeling. The group already has the workstation needed for the numerical modeling (HP Z800, CPU Intel(R), Xeon(R), CPU X5680, 3.33G Hz - 2 x 6 = 12 core , RAM 24 GB). Co-PI Arnone has strong interactions with regional stakeholders, such as ARPA-FVG, which are highly interested in rainfall-induced hazards (see letter in Fig 2). UNIUD will 1) collaborate with PI for managing project requirements 2) organize and lead the activities of WP4 to assess the impacts of extreme rainfall on landslides initiation 3) develop the methodologies of 4.3 aimed at the assessment of landslide probabilities under extreme events in collaboration with UNIPA, 4) collaborate with CNR for the activities of task 4.2 of generation of synthetic climate time series.

UNIPD

The RU at UNIPD (University of Padova) contributes expertise in the field of rainfall modeling, extreme value theory, analysis and downscaling of satellite rainfall estimates. In recent years, the Associated Investigator Marani and collaborators have developed the novel MEVD approach to extreme value modeling, which is key in using all the relatively short rainfall records from satellite observations to infer extreme rainfall quantiles. The research group at UNIPD has also developed the methods that will be used for downscaling rainfall in space and time to enable comparisons of downscaled satellite estimates with point-scale rain-gauge observations and the quantification of estimation uncertainty. In addition to AI Marani, the group includes one PhD student who is already experienced in extreme-value analysis, and will be extended by inclusion of a Post-Doc hired under INTENSE. The group has long-standing collaborations with ARPA Veneto, who formally expressed its intention to actively interact with the INTENSE research team to contribute to the practical implementation of project results. Using the new MEVD approach, the UNIPD unit will 1) lead efforts in task 1.1., in collaboration with CNR and UNIPA, to produce novel methods to downscale satellite rainfall estimates in space and time to the point scale and the hourly scale, 2) lead efforts in task 1.2 to test extreme value probability distributions obtained from remotely sensed information against ground truthing observations at the national scale.

UNIPA

The RU at UNIPA (University of Palermo) has multi-year experience in rainfall monitoring at different space-time scales and in extreme rainfall analysis, also using satellite-based remote sensing. In the last decade an important research focus of the UNIPA RU has been the detection of potential signals of climate changes in rainfall regimes at different scales. Additionally, over the past several years, UNIPA has deployed, over the dense urban area of Palermo (about 250 square km area), a complex rainfall monitoring system composed of two X-band weather radars, a network of tipping-bucket rain gauges (10 gauges), an optical disdrometer, a weight rain gauge, and a complete weather station (Pumo et al., 2016). UNIPA has long-term partnership with regional stakeholders, such as AdB-Regione Siciliana, DRPC (Regional Civil Protection) and SIAS, which have expressed highest interest in the outcomes of INTENSE. UNIPA will 1) lead WP2 on the collection and organization of WR and raingauge data in the Palermo area aimed to the implementation and application of calibration/correction procedures of weather radar data, and to exploit radar rainfall estimates of Civil Protection National Mosaic for investigating extreme sub-daily rainfall scaling relations; 2) collaborate in WP3 (task 3.1) with CNR to evaluate past changes in extreme rainfall using the rain gauge and satellite data and to incorporate nonstationarity in depth-duration-frequency curves; 3) collaborate in WP4 (task 4.3) with UNIUD to the modelistic framework aimed to assess the impact of extreme rainfall characteristics on landslides activation.