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This WP aims at giving the methods and data needed to carry out any planning activity needed for mitigation and adaptation to hazards induced by climate changes. This is accomplished through the sequence Climate change models projections→ Web based Archive of climate and territorial data → Probabilistic hazard scenarios, which is reflected in the 3 Tasks:

Task 1.1 Model projections of climate change
An ensemble of six global projections of climate change based on the IPCC AR4 and the new AR5, will be used to obtain high resolution climate data over the African continent, by using different high-resolution atmospheric models applied at the CMCC and the CSIR. The ultimate products of this task will be:
  1. high resolution (50 to 80 km) regional climate simulations of both present-day and future climate over the African continent, using the COSMO-CLM and CCAM global climate models;
  2. 5 to 8 km resolution sub-regional scale simulations around the selected cities with COSMO-CLM and CCAM regional climate models.
The use of different climate models within a multi-model ensemble approach is very useful to describe the range of uncertainty associated with future climate change over the cities under consideration. This is a crucial issue for any decision about mitigation actions of risks related to climate change induced hazards.

Task 1.2 Web Climate Mapping Services
The work that will be performed here concerns the editing of the material produced by task 1.1 (Assessments concerning climate change) in such a way that it will meet the needs of Task 1.3 and WP2. For this reason, Web Mapping Services will be created, which will provide a simple HTTP interface for requesting climate maps (returned as JPEG, PNG, etc), extreme climatic indices (for example, indices calculating the percentage of days with maximum temperature > 90th percentile, the precipitation intensity, the maximum length of dry or wet spell), as well as tables and statistical datasets in simple format (for example ASCII files). The information will derive from both groups of models as it is essential that the output of both modelling groups is made available to the impact/vulnerability researchers. Furthermore, a query made by researchers defines the African area and/or the city of interest to be processed and the info of interest.

Task 1.3 Probabilistic scenarios of natural hazards
The activities of this task starts from the outputs provided by task 1.1 the fundamental climate parameters of interest to derive hazard variations are: temperature, humidity, wind patterns and velocities, regime of rain. Variations of these parameter will condition different hazards at different time-scales This information from Task 1.1 will be applied to single hazard scenarios built from existing geological, morphological and historical data for the test cities and the surrounding regions .The process of hazard enhancement by climate change can be considered as a cascade of events and treated consequently. Different hazards can intersect with each others (e.g. hurricanes can trigger floods that can trigger landslides, etc) creating further steps of the cascade. Among the hazardous events considered in this project, we identify possible scenarios of cascade events for different space-time scales. This task requires the identification of the conditions that have to be met to get a significant increase of the total risk due to interaction among events. The interaction among hazards may lead to amplification of single risks and/or to trigger different threatening events. A particular emphasis will be devoted to the temporal aspect, because cascade conditions strongly depend on the time scale that we are considering. Multi-hazards calculated over decades or daily time scale have typically different scenarios of cascade events.
A methodology for a probabilistic assessment of climate dependent hazard scenarios and relative uncertainties at urban level will be developed and a procedure will be set up to improve the reliability of each scenario in future, both utilizing easily available low cost data (e.g. some satellite EO data) and improving the basic monitoring network. This method will also deal with interaction among different hazard types and possible cascade effects. (Granger et al., 1999, Marzocchi et al., 2009).
The developed methods will be applied to the test cities in order to derive probabilistic scenarios of the relevant hazard and their reliability. Procedures will be indicated to update the data base with the input of new observational data, new model projections of climate change, etc.