A Prototype High-Resolution Data-Assimilation System for Israel

Climate change is already here, but our understanding of its local impacts in Israel is still lacking. Although large networks of in-situ observations cover Israel, and there is an increasing amount of information coming from satellites, there are still spatial and temporal gaps that are not expected to be solved in the coming decades. The problem is more pronounced in Israel than in other locations due to its complex terrain and high climate variability. These characteristics necessitate more observations (relative to other regions) to reliably sample the regional variability and allow for regular temporal and spatial data interpolation. Reanalysis datasets have become more popular in the last few decades due to their regularity in space and time, which is achieved by combining observations with model outputs using a predefined data assimilation method. However, current reanalysis products are still too coarse to represent the high climate variability in Israel, and therefore, their use is limited. In this presentation, we will describe our effort to generate a prototype high-resolution convection-permitting ensemble-based data-assimilation system and a reanalysis product for Israel.