Abstract
Abstract. CUACE/Dust, an operational mesoscale sand and dust storm (SDS) forecasting system for East Asia, has been developed by online coupling a dust aerosol emission scheme and dust aerosol microphysics onto a regional meteorological model with improved advection and diffusion schemes and a detailed Northeast Asia soil erosion database. With improved initial dust aerosol conditions through a 3-DVar data assimilation system, CUACE/Dust successfully forecasted most of the 31 SDS processes in East Asia. A detailed comparison of the model predictions for the 8–12 March SDS process with surface network observations and lidar measurements revealed a robust forecasting ability of the system. The time series of the operationally forecasted dust concentrations for a number of representative stations for the whole spring 2006 (1 March–31 May) were evaluated against surface PM10 monitoring data, showing a good agreement in terms of the SDS timing and magnitudes at and near the source regions where dust aerosols dominate. For the operational forecasts of spring 2006 in East Asia, a TS (threat score) system evaluated the performance of CUACE/Dust against all available observations and rendered a spring averaged TS value of 0.31 for FT1 (24 h forecasts), 0.23 for FT2 (48 h forecasts) and 0.21 for FT3 (72 h forecasts).
Highlights
As a natural weather phenomenon, sand and dust storm plays an important role in global climate change
Threat Score (TS) scores for all the 31 sand and dust storm (SDS) processes and spring mean TS for each grid in the results-domain have been presented in the paper for the overall model evaluation in 2006 spring dust season
Its robust forecast ability has been demonstrated through predicting a heavy SDS process in 8–12 March by comparing with the surface concentrations and synoptic SDS records
Summary
As a natural weather phenomenon, sand and dust storm plays an important role in global climate change. Using a 4-DVar (4-Dimensional Variation) data assimilation method and NIES lidar observations, Yumimoto et al (2007) has proposed an inverse scheme to improve the dust emission for an extreme SDS process and has mitigated the underestimate of dust concentrations and vertical profiles of the SDS. Even though this 4-DVar technique has not been used in operational forecasts, it has certainly shed some lights in improving the operational forecasts and general simulation of a SDS. This paper focuses on the application of CUACE in SDS forecasts
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
