The availability of reliable spatial and temporal data at proper spatial and temporal scale about extreme weather events represents a pivotal challenge for supporting Disaster Risk Reduction (DRR) policy and practice.
The availability of reliable spatial and temporal data at proper spatial and temporal scale about extreme weather events represents a pivotal challenge for supporting Disaster Risk Reduction (DRR) policy and practice. In recent years several gridded observational datasets have been developed for Europe and for specific European countries; these products feature different temporal (from hourly to daily) and spatial (from ≃ 1 km to ≃ 10–20 km) resolutions, covering different time spans, and their reliability is strictly related to the density of station networks from which they derive.
A potential alternative solution to ensure homogeneity and continuity of data is represented by the use of climate reanalysis. In general, a climate reanalysis delivers a complete and consistent picture of the weather and climate of the past as close to reality as possible, by adopting a numerical weather prediction model to assimilate historical observations provided by different sources (satellite, in situ, etc) but not homogeneously distributed around the globe.
The data produced by the reanalysis are widely used and provide many kinds of information, not only about the atmosphere, such as temperature, wind and precipitation, but also about the ocean and the land surface.
Read more at CMCC Foundation - Euro-Mediterranean Center on Climate Change
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