Climate and Hydrology Modeling
An important part of SWAP is the quantitative modeling of Middle East climate and hydrology. Only by constructing numerical models of the dominant physical processes can we hope to understand the past and present water resources and vegetation in the region and predict their future development. At the current state of our work, our modeling effort is divided in two parts.
The Regional Climate Model (RCM) is used in our work to downscale atmospheric and surface processes from the global to the regional scale. We have nested a two well-tested regional climate models (RegCM2, MM5/Noah), into the SWAP regions using boundary conditions from a global analysis. These are sophisticated state-of-the-art models encompassing hundreds of competing and cooperating physical processes (clouds, precipitation, radiation, turbulent heat flux, fronts, convection, transport etc.) to predict the mesoscale details of weather over the region. Model output can be analysed event by event, or statistically analysed to determine the climate characteristics.
The high resolution output of the RCMs can also be used to investigate the regional scale atmospheric dynamics including interactions between the land-surface and the atmosphere. RCM projects have investigated the influence of increasing irrigation areas, the impact of the Zagros mountains as an elevated heat source, as well as the transport of water vapor through the region
The Hydrology Model is used in our work to estimate the seasonal cycle of hydrological variables such as ground water, snow depth and runoff in response to the seasonal cycle of temperature and precipitation. The model is a simple "bucket" scheme which accounts for evaporation as a function of temperature, snow storage and melting, storage of water in the soil and runoff. It is run on a 5km grid which allows it to capture the effect of terrain. Currently the model is driven with a 20-year climatology. Possible climate change scenarios have also been tested. The model output has been compared with the vegetation distribution and the local of winter snow cover in the mountains. The predicted runoff has also been compared, for each watershed, against historical streamflow data.