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The Global Navigation Satellite System (GNSS) zenith total delay (ZTD) observations canprovide moisture-related information with high spatial and temporal resolution and have beenan important data source of assimilation and forecast system. In this study, the impact ofassimilating ZTD observations within the weather research forecast (WRF) model isevaluated. The ZTD observations from 75 stations of Hubei CORS in central China areobtained during the period of Feb. 28 to Mar. 2, 2018 which precipitation event occurs.Different experiments are implemented including a reference experiment with no dataassimilated, a GNSS experiment with only ZTD data assimilated and a multi-source dataexperiment with ZTD and other meteorological observations assimilated simultaneously. Theresult demonstrates a positive impact on short-range precipitation forecasts whenGNSS ZTD observations are assimilated and the most significant improvementin forecast is obtained when GNSS ZTD data are assimilated together with othermeteorological observations into the WRF model. In addition, we have appliedthe ZTDs derived from WRF forecast products into the real-time precise pointpositioning (RT-PPP) as a constrained condition. The accuracy of WRF-derivedZTDs is assessed against with the post-processed GNSS-derived ZTDs. The resultshows that the WRF-derived ZTDs agree well with the GNSS-derived ZTDs. Theconvergence time of RT-PPP is also discussed, and result indicates that an improvementin convergence time is achieved by comparison with the standard PPP solution. [ABSTRACT FROM AUTHOR]

Global warming is typically evaluated using trends in mean temperature. However, temperature is affected quite differently on sunny and cloudy days, with sunny days typically showing higher maximum temperature and greater diurnal temperature range. Here, we show that global warming is considerably stronger on sunny days. To do so, we evaluated warming trends using observations from meteorological stations in China and distinguish between sunny and cloudy days using rainfall records as a proxy. We find that warming trends on sunny days are about 50% higher than on cloudy days, and that 70-80% of the total temperature increase is contributed by sunny days. The main reason is likely to be a stronger sensitivity of atmospheric emissivity to water vapor on sunny days, which would be dominated by clouds on cloudy days, resulting in a stronger water vapor feedback on sunny days. Our results are consistent with observations that drier regions show stronger warming trends and imply that the anticipated greater frequency of heatwaves under global warming may mostly be attributable to this greater sensitivity of sunny days to the greenhouse forcing. [ABSTRACT FROM AUTHOR]