Regional and country-level predictions of change on climate, water and crop production

Climate is the average weather pattern at a given location and time of year. We expect weather to change from day to day, but climate remains relatively constant if the climate does not remain constant, we call it climate change.

Global climate change impact assessment studies such as the IPCC reports show the need for improved local climate simulation as the outputs of General Circulation Models (GCMs) which cannot be used directly in any regional hydrological or crop models. GCMs are the most effective tool to simulate the impact of increased concentrations of atmospheric greenhouse gases on climate variables globally. They perform well in simulating climate variables at large spatial scales (>104 km2) but perform poorly at higher resolution and shorter time scales relevant to regional climate analyses. Therefore, the outputs of GCMs must be “downscaled” to provide useful tools for regional analyses similar to the MAWRED knowledge hub

Currently over 20 GCMs are produced by research centers around the world (http://cmip-pcmdi.llnl.gov/cmip5/). ICBA assesses models which best represent the climatology of the Middle East and North Africa region and then use downscaling techniques to derive more specific local data. Downscaling connects global climate variables and anomalies to regional and/or local-scale meteorological and hydrological variables. Downscaling also provides tools to generate synthetic weather data that is required for climate change impact assessment studies. At ICBA dynamical downscaling is used with low-resolution climate model data and local weather-forecasting models (WRF model) to produce high-resolution climate data. Usually, a regional climate model is used to provide climate parameters for input into hydrological and crop models to assess local climate change impacts.

The resulting downscaled data is used in many subsequent analyses. The trends for future 20-year periods are mapped for various key climatic indices such as consecutive dry days, as well as average annual temperature and precipitation trends. The new atmospheric data is used to drive water and crop models to examine the impacts on resources and yields. The identified trends are key to understanding the implications of changes in the general trends as well as in extreme events such as droughts on current agricultural and water systems. This also helps to identify areas of increased vulnerability where adaptation activities need to be focused.