Precipitation forecasting using doppler radar data, a cloud model with adjoint, and the weather research and forecasting model: Real case studies during soWMEX in Taiwan

Sheng Lun Tai, Yu Chieng Liou, Juanzhen Sun, Shao Fan Chang, Min Chao Kuo

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The quantitative precipitation forecast (QPF) capability of the Variational Doppler Radar Analysis System (VDRAS) is investigated in the Taiwan area, where the complex topography and surrounding oceans pose great challenges to accurate rainfall prediction. Two real cases observed during intensive operation periods (IOPs) 4 and 8 of the 2008 Southwest Monsoon Experiment (SoWMEX) are selected for this study. Experiments are first carried out to explore the sensitivity of the retrieved fields and model forecasts with respect to different background fields. All results after assimilation of the Doppler radar data indicate that the principal kinematic and thermodynamic features recovered by theVDRASfour-dimensional variational data assimilation (4DVAR) technique are rather reasonable. Starting from a background field generated by blending ground-based in situ measurements (radiosonde and surface mesonet station) and reanalysis data over the oceans, VDRAS is capable of capturing the evolution of the major precipitation systems after 2 h of simulation. The model QPF capability is generally comparable to or better than that obtained using only in situ observations or reanalysis data to prepare the background fields. In a second set of experiments, it is proposed to merge theVDRAS analysis field with the Weather Research and Forecasting Model (WRF), and let the latter continue with the following model integration. The results indicate that through this combination, the performance of the model QPF can be further improved. The accuracy of the predicted 2-h accumulated rainfall turns out to be significantly higher than that generated by using VDRAS or WRF alone. This can be attributed to the assimilation of meso- and convective-scale information, embedded in the radar data, into VDRAS, and to better treatment of the topographic effects by the WRF simulation. The results illustrated in this study demonstrate a feasible extension for the application of VDRAS in other regions with similar geographic conditions and observational limitations.

Original languageEnglish
Pages (from-to)975-992
Number of pages18
JournalWeather and Forecasting
Volume26
Issue number6
DOIs
StatePublished - Dec 2011

Keywords

  • Forecasting techniques
  • Mesoscale forecasting
  • Numerical weather prediction/forecasting
  • Precipitation

Fingerprint

Dive into the research topics of 'Precipitation forecasting using doppler radar data, a cloud model with adjoint, and the weather research and forecasting model: Real case studies during soWMEX in Taiwan'. Together they form a unique fingerprint.

Cite this