1.State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences;2.Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies,School of Atmospheric Sciences,Sun Yat-sen University,Southern Marine Science and Engineering Guangdong Laboratory Zhuhai;3.National Meteorological Information Center
A physically consistent atmospheric objective analysis model based on the constrained variational analysis (CVA) method was applied to the Tibetan Plateau for large-scale atmospheric structure analysis. This objective analysis model can deal with multi-source measurements with different spatial and temporal resolutions, and satisfy the conservation of column-integrated mass, heat, moisture, and momentum by using surface precipitation and flux data at the surface and top of the atmosphere to constrain the sounding measurements. An experiment during August 2014 around Naqu in the Tibetan Plateau shows that those state variables generated by the model can retain observational characteristics. The analyzed large-scale derivatives such as vertical velocity, divergence, temperature and water vapor advection, apparent heat source and apparent moisture sink by the objective analysis model can reasonably demonstrate dynamic, thermal, and moisture structures during the analysis period, which is conducive to the precipitation process studies. It shows that the layer of 350~400hPa is an important change center of dynamics, heat, and water vapor in the analysis region during August 2014. In this model, different sources of measurements have different impact on the final analysis fields. Sounding measurement has a significant impact on the upper-level wind. However, the amplitude of this impact is small within 1 m/s. Precipitation and flux measurements mainly affect the large-scale derivatives such as vertical velocity, in which precipitation mainly affects the upward movement during precipitation periods, and flux data mainly affect the downward movement during light/no rain periods. In general, the physically consistent atmospheric variational objective analysis model has high stability and strong validity.