Validation of the Global Environmental Multiscale Model (GEM) for Iran
Abstract The Global Environmental Multiscale Model (GEM) is an integrated forecasting and data assimilation system developed by Environment and Climate Change Canada. The model is currently in operational use for data assimilation and forecasting at global 25 km to 15 km scales; regional 10 km scales over North America; and 2.5 km scales over Canada. To demonstrate the performance of the GEM model for forecasting applications, global forecast outputs of GEM at the 25 km scale were compared to temperature and precipitation datasets collected over an area of 1,648,000 km2 especially representative of the country of Iran on a daily temporal scale. Using the De Martonne method for climate classification and data from 177 meteorological stations, the country of Iran was classified into three zones: an arid zone with 87 stations; a semi-arid zone with 63 stations; and a humid zone with 27 stations. GEM model outputs were compared to observations in each of these demarcated zones. The results show good agreement between modelled and measured daily temperatures with Kling-Gupta efficiencies of 0.76, 0.71 and 0.78 in arid, semi-arid and humid regions respectively, and a moderate agreement between modelled and measured annual precipitation with 50.06%, 35.6% and 15.38% differences in arid, semi-arid and humid regions, respectively. The results also indicate that there is a significant systematic error between the elevation of the stations and the average elevation of corresponding GEM grid cells (13%). The results provide an evaluation of the model performance for Iran to be utilized for climate change applications in a regional context and can serve as a basis for the development of future high-resolution GEM model versions on a global scale.