Constraint Objective Analysis Over The Tibetan Plateau: Method And Application

Using flux data on the top and the bottom of a column to keep the column’s mass, moisture and static energy constraint, thermal and dynamic coordinated datasets are generated with the analysis method based on constrained objective analysis. Datasets quality and observational influences on the datasets are tested. The main results are as follows:(1) A column centered in Naqu with radium of 200 km is set up over the Tibetan Plateau and constrained objective analysis is used to get thermal and dynamic coordinated datasets. The method based on the variational analysis is able to deal with observations of different kinds and different temporal and spacious resolutions, adjusting sonde variables such as wind, temperature and moisture, deriving variables such as vertical velocity, temperature and moisture advection, apparent heat source and apparent moist sink. The method has great advantages in data processing.(2) Datasets characteristics are analyzed and data quality is checked by comparing it with ERA-Interim reanalysis and L-band radiosonde. The results show that(i) the column averaged surface pressure is about 595 hPa in August of year 2014, during strong precipitation there is upward motion strongest in 400~300 hPa, and maximum Q1 and Q2 with the former located in 350 hPa and the later located in 400 hPa, indicated that latent heat is the main heat source during precipitation period;(ii) the output variables at the top and bottom of the column, obtained directly from observations, are superior to the reanalysis;(iii) the multi-layer wind, temperature and moisture, which mainly depend on the radiosonde, are close to observations and have no missing data;(iv) derived variables, such as vertical velocity, has a good relationship with the precipitation.(3) Influences of observations on constrained objective analysis over the Plateau are discussed. The results are as follows.(i) The method based on the constrained objective analysis has stable performance.(ii) The radiosonde has a large influence on the multi-layer wind, with zonal wind changing great in 450~150 hPa and great meridional wind changes below 300 hPa.(iii) Precipitation affects the vertical velocity during the precipitation period. The upward motion derived from ERA-Interim reanalysis precipitation data is stronger than that from auto station observation and CMORPH mixed data. There is reasonable upward motion during precipitation with auto station observation, while the motion is not obvious by using CMORPH mixed data.(iv) Adding flux data do enhance the downward motion when there is no precipitation.