| Abstract: | In this study, the observational data acquired in the South China Heavy Rainfall Experiment (SCHeREX) from May to July 2008
and 2009 were integrated and assimilated with the US National Oceanic and Atmospheric Administration’s (NOAA) Local Analysis
and Prediction System (LAPS; information available online at ). A high-resolution mesoscale analysis dataset was then generated at a spatial resolution of 5 km and a temporal resolution
of 3 h in four observational areas: South China, Central China, Jianghuai area, and Yangtze River Delta area. The quality
of this dataset was evaluated as follows. First, the dataset was qualitatively compared with radar reflectivity and TBB image
for specific heavy rainfall events so as to examine its capability in reproduction of mesoscale systems. The results show
that the SCHeREX analysis dataset has a strong capability in capturing severe mesoscale convective systems. Second, the mean
deviation and root mean square error of the SCHeREX mesoscale analysis fields were analyzed and compared with radiosonde data.
The results reveal that the errors of geopotential height, temperature, relative humidity, and wind of the SCHeREX analysis
were within the acceptable range of observation errors. In particular, the average error was 45 m for geopotential height
between 700 and 925 hPa, 1.0–1.1°C for temperature, less than 20% for relative humidity, 1.5–2.0 m s−1 for wind speed, and 20°–25° for wind direction. The above results clearly indicate that the SCHeREX mesoscale analysis dataset
is of high quality and sufficient reliability, and it is applicable to refined mesoscale weather studies. |
