Abstract
Sensitivities of the forecast to changes in the initial state are evaluated for an Asian dust event, which affected the Korean Peninsula on 7 to 9 April 2006, to understand the impact of initial condition uncertainties on the forecast and thence to suggest the sensitive regions for adaptive observations of the Asian dust. To assess the forecast sensitivities, adjoint-based sensitivities were used. Sensitive regions are located over the northwestern part of Mongolia at the initial time, then propagate to Inner Mongolia and Manchuria. Close to the verification time, sensitive regions as determined by adjoint-based forecast sensitivities coincide with the passage of the Asian dust. Forecast error for the atmospheric circulation during the dust event is reduced 57.4% by extracting properly weighted adjoint-based forecast sensitivity perturbations from the initial state, and the correction occurs primarily in the upper troposphere where the forecast error is the largest. The improvement in the overall forecast implies that adjoint-based forecast sensitivities would be beneficial in determining the observational sites and in improving the forecast of Asian dust events. An additional experiment with another Asian dust event confirms the validity of adjoint-based forecast sensitivities to Asian dust events.
Original language | English |
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Pages (from-to) | 335-343 |
Number of pages | 9 |
Journal | Water, Air, and Soil Pollution |
Volume | 195 |
Issue number | 1-4 |
DOIs | |
Publication status | Published - 2008 Nov |
Bibliographical note
Funding Information:Acknowledgments This study was supported by the Korea Meteorological Administration Research and Development Program under Grant CATER 2006-2102. The authors wish to thank anonymous reviewers for their very helpful comments and Typhoon-Hwangsa Team in Korea Meteorological Administration for providing PM10 data and information on Asian dust observational sites for this study.
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Environmental Chemistry
- Ecological Modelling
- Water Science and Technology
- Pollution