Comparison of GNSS integrated water vapor and NWM reanalysis data over Central and South America

L. FERNÁNDEZ; L. MENDOZA; P. NATALI; A. MEZA; C. BIANCHI

Viena

Congreso; EGU General Assembly 2017; 2017

European Geosciences Union

Integrated water vapor (IWV) derived from Global Navigation Satellite Systems (GNSS) and Numerical WeatherModels (NWM) reanalysis data were compared in order to assess the consistency between the different datasetsover the extended geographical region of Central and South America. The investigation was performed forthe seven-year period between 2007 and 2013. We analyzed two different reanalysis: the European Centre forMedium-Range Weather Forecast (ECMWF) reanalysis data (ERA Interim) and the Modern-Era Retrospectiveanalysis for Research and Applications (MERRA2) from the National Aeronautics and Space Administration(NASA). The statistical analysis of the differences was performed in 110 GNSS sites (GPS +GLONASS), althoughthe most interesting results came from the 73 sites which have more than 5 years of data. The study of the spatialdistribution of the differences in the selected area involves different climate types, from polar to tropical, and it ischaracterized by large temporal variability of the integrated total humidity content. The inter-comparison was alsoperformed on several time scales: from hours to years.In this study, not only the IWV values given by the different reanalysis where compared with the respective GNSSderived values but also the numeric integral of the IWV. This is nothing but the total vertically integrated watervapor of a unit air column each station but considering its real geopotential height. To that end, multilevel datafrom each reanalysis was also used.Moreover, the scarce coverage of operational radio sounding stations is noticeable in large areas of the selectedregion. Hence the contribution of IWV-GNSS is essential to improve the weather understanding. Consideringthat the atmospheric water vapor has a highly variable and complex distribution which knowledge is essential forweather prediction and local meteorological studies, this study aims to provide IWV-GNSS observations able tobe assimilated by operational weather centers for both, prediction and simulation, as well for improving regionalmodeling.