Impact of GNSS-IPW observations on NGFS

The accurate estimation of water vapour with high spatial and temporal resolution is needed for operational weather forecasts and weather and climate research. Moisture representation in numerical weather prediction models is inadequate for forecasting meso-scale precipitation events and accurate information of middle and upper tropospheric moisture determines strength, effectiveness and longevity deep convective processes. Global Navigation Satellite System (GNSS) provides a way for measuring atmospheric humidity continuously at a low operational cost by co-locating GPS receiver with meteorological sensor. Impact of assimilation of GPS-IPW observations from NOAA-NWS and EUMETNET network on NCMRWF GFS forecast is investigated during May-June period in 2014. Impact of assimilation of GPS-IPW observations are not only confined to the regions of dense GPS-IPW network, but can be seen in other regions also. Ingestion of IPW observations impacted prediction of rainfall over the Indian monsoon region even though very few IPW stations located in the region. Impact of assimilation is not uniform on temperature, wind and humidity and different over different region. GPS-IPW observations can impact forecast of individual rainfall events at large and major impact on rainfall forecast is seen in the regions of large integrated precipitable water in the model. In India MoES has already setup many GPS-IPW stations and also some more are in the pipeline . The quality of these present observations from MoES and plans for the future GPS-IPW stations are discussed.