Advances in Atmospheric Sciences

, Volume 22, Issue 2, pp 300–312

Four-dimensional variational data assimilation experiments for a heavy rain case during the 2002 IOP in China

  • Zhang Lin
  • Ni Yunqi

DOI: 10.1007/BF02918519

Cite this article as:
Lin, Z. & Yunqi, N. Adv. Atmos. Sci. (2005) 22: 300. doi:10.1007/BF02918519


A heavy rainfall event along the mei-yu front during 22–23 June 2002 was chosen for this study. To assess the impact of the routine and additional IOP (intensive observation period) radiosonde observations on the mesoscale heavy rainfall forecast, a series of four-dimensional variational (4DVAR) data assimilation and model simulation experiments was conducted using nonhydrostatic mesoscale model MM5 and the MM5 4DVAR system. The effects of the intensive observations in the different areas on the heavy rainfall forecast were also investigated. The results showed that improvement of the forecast skill for mesoscale heavy rainfall intensity was possible from the assimilation of the IOP radiosonde observations. However, the impact of the IOP observations on the forecast of the rainfall pattern was not significant. Initial conditions obtained through the 4DVAR experiments with a 12-h assimilation window were capable of improving the 24-h forecast. The simulated results after the assimilation showed that it would be best to perform the intensive radiosonde observations in the upstream of the rainfall area and in the moisture passageway area at the same time. Initial conditions created by the 4DVAR led to the low-level moisture convergence over the rainfall area, enhanced frontogenesis and upward motion within the mei-yu front, and intensified middle- and high-level unstable stratification in front of the mei-yu front. Consequently, the heavy rainfall forecast was improved.

Key words

intensive radiosonde observations four-dimensional variational assimilation 

Copyright information

© Advances in Atmospheric Sciences 2003

Authors and Affiliations

  • Zhang Lin
    • 1
  • Ni Yunqi
    • 2
  1. 1.Department of Atmospheric SciencesNanjing UniversityNanjing
  2. 2.State Key Laboratory of Sever WeatherChinese Academy of Meteorological SciencesBeijing