Verification of the New Nonhydrostatic Multiscale Model on the B Grid (NMMB): A View on Global Predictability of Surface Parameters

Abstract

global verification of temperature, dewpoint temperature, and wind speed for the new Nonhydrostatic Multiscale Model on the B Grid (NMMB) is computed for a 3-yr period (2010?12) using over 9000 weather stations. The raw model forecasts, as well as bias-removed MOS forecasts, are analyzed and compared to NOAA?s operational GFS. In comparison to the GFS, the NMMB forecasts of temperature, dewpoint temperature, and wind speed are about 10% better, even though the NMMB is run at much coarser resolution and does not yet have its own data assimilation system. However, as a result of several changes in the GFS during the 3-yr period, the MOS computations for GFS are not optimal. Using unbiased MOS forecasts, the global distribution of spatial predictability can be analyzed. Clear spatial patterns emerge, which are partly dependent on the variable. For temperature, the best forecasts can be made for small islands and coastlines, and a clear gradient of decreasing skill with increasing distance from the sea is visible on the continents. For wind speed, this pattern is almost reversed. Dewpoint temperature shows the largest patterns, mainly controlled by the humidity of the climate. Combining temperature, wind speed, and dewpoint temperature in a gross predictability index reveals a clear large-scale pattern. Remarkably, smaller-scale features like mountain ranges are not readily apparent in the bias-free predictability pattern, indicating that the spatial pattern of the gross predictability is controlled at the very large scales.