Impacts of the new satellite derived land products on mesoscale precipitation processes

Using the new MODIS_IGBP land-use data in the NMMB, the next NWS operational mesoscale model, the daytime temperature (at 2-m level) warm bias is reduced. In comparing to the old 5-year climatology monthly Green Vegetation Fraction (GVF), the new 25 year averaged weekly data shows a greener GVF field. At the 2-m level, compared with summer observations, the use of the new GVF data reduces the NMMB temperature warm biases, relative humidity dry biases, and their root-mean-square-errors (RMSEs). The MODIS_IGBP land-use and adjusted GVF data sets together have been implemented in NMMB. Sensitivity test over a period of 4 months of the summer of 2009 has been conducted, and there is an on-going effort on parallel run with the present NWS mesoscale operational model. Note that GVF data north of 60 degree N latitude are missing in winter due to the low sun angle. Missing data are filled through interpolation, with tanh(x) as a weighting function, in order to obtain a smooth transition. Development and model application of high-resolution data of maximum albedo for deep snow and snow-free albedo will also be reported and discussed. As these data sets cover the whole globe, these data are useful for various regions, global and climate models. Critical analyses of the impact of the aforementioned implementations to mesoscale numerical weather prediction models and precipitation processes will be discussed. Results of quantitative precipitation forecast (QPF) such as equitable threat score will also be reported.