A seasonal forecast scheme for spring dust storm predictions in Northern China

Abstract

ABSTRACT:The theme discussed in the present study is that of spring dust storm seasonal forecasts in Northern China. A comprehensive investigation of observations collected from 65 stations in Northern China, which studied strong winds for 35 years and dust storms for 48 years , concluded that strong winds, which are recognized as a crucially dynamic factor, have unsurprisingly proven to be strongly related to dust storm activity. Therefore, determining effective predictors for strong winds should be helpful in spring dust storm forecasts. By employing this idea, comprehensive correlation analyses among the strong winds, dust storms and other influential elements from the oceans and the atmospheric circulations can be seen. From the spatial correlation fields between prior sea surface temperatures and the strong winds, four regions with higher oceanic coefficiencies are confirmed. The method of EOF (Empirical Orthogonal Function) decomposition is adopted to extract forecast signals from prior precipitation in Northern China and sea surface temperatures of those regions. The multivariable step-regression model is employed to select efficient predictors and the multivariable regression model is used to create forecast equations. With the cross validation approach, six series of 48 year hindcasts with six different predictor sets are conducted. Furthermore, the three-classification forecast method is used to judge successful or failed dust storm forecasts. Together, forecast skills of probability of detection and skill score suggest that series forecasts are better than random forecasts. The best forecast skill is gained from using the predictor set selected by the multivariable step-regression model.

Impacts of climate abnormality on remarkable dust storm increase of the Hunshdak Sandy Lands in northern China during 2001–2008

“…A station in northern China will be given a strong wind score if the maximum daily wind velocity equals to or over 17 m s −1 . The severe wind event is identified if there are more than five stations in the region with the scores on the worst windy day (Gao et al , 2010b). However, the detailed investigated result does not exhibit any significant connection between severe winds and dust storm events in the Hunshdak Sandy Lands.…”

“…Furthermore, based on detailed analyses of the influence of previous sea surface temperature, atmospheric circulation conditions and indices, some climate controlling elements and potential climate predictors have been examined in the research of Gao and Han (2010a). Despite the achievements mentioned above, some studies also focused on designing dust storm weather or seasonal prediction models and have developed some acceptable forecast results (Sun et al , 2003; Gao et al , 2009, 2010b). In addition, dust storms and associated pollution events in Beijing and Asia are explored by Fang et al (2003) and Seinfeld et al (2004).…”

Dust storm frequency change in relation to climate drivers

“…China is another typical region of dust storm source in the central and eastern Asia. Poorly vegetated areas in this region is one of the main factors on dust storm emission (Gao and Xuebin, 2010, among others). There are many studies in China regarding the relationship between DSF and related factors.…”

“…Gao and Xuebin (2010) suggested strong winds to be used in spring dust storm forecasting. They also developed a multivariate regression model between climate predictors such as wind speed and sea surface temperature and dust frequency.…”

“…Surface wind speed from 6 to 20 mÁs −1 was highlighted by Natsagdorj et al (2003) as an effective factor on frequency of dust storms in Mongolia as well. Gao and Xuebin (2010) suggested strong winds to be used in spring dust storm forecasting. They also developed a multivariate regression model between climate predictors such as wind speed and sea surface temperature and dust frequency.…”