To study the climatic contribution to dust storm increases in Inner Mongolia in recent years, an analysis has been conducted of such factors in the last 40 years as annual and spring (March-May) precipitation, temperature, cold waves and strong gusty winds. In addition, such factors have been studied statistically regarding their impact upon atmospheric circulation with regard to the zonal circulation of Asia, the deep trough over East Asia and the geopotential height of Qinghai-Xizang Plateau. This study shows that the increased occurrences of dust storms likely result from a decrease in annual precipitation during 1999-2001; the precipitation recorded proved to be constantly below average, especially in spring. In addition, warmer temperatures with frequent cold-air outbreaks created unstable atmospheric stratification, thus leading to more gales and subsequently, more dust storms. In the springs of 2000 and 2001, large-scale atmospheric circulations provided the conditions for increased occurrences of dust storms due to stronger zonal circulation and a more westerly positioned trough over East Asia that became more intense in the winters. Furthermore, geopotential height over the Qinghai-Xizang Plateau seems to have an opposite trend as against dust storm frequency tendency. El Niño-southern oscillation activity might be an indirect factor.
From 1961 to 2008, the overall frequency of dust storms in northern China has shown an unquestionable reduction. However, the Hunshdak Sandy Lands of northern China display an increasing frequency in dust storm activities, especially during the period 2001 to 2008. In an attempt to explore the cause of this increase, a comprehensive investigation was conducted by examining the climate variables, the average normalized difference vegetation index (NDVI) and the local inhabitant migrations. The climate variables include local precipitation, temperature, aridity, evaporation, relative humidity, soil moisture and wind speed. Moreover, by analyzing the 2001-2008 average anomaly charts (relative to the 30 year climatology of 1971-2000) of the upper air and surface conditions, an advantageous atmospheric circulation background for drought development over the Hunshdak was confirmed. Meanwhile, a multivariable step-regression model was employed to distinguish the significant variables of the climate elements mentioned before. The model output suggests that aridity is the leading factor impacting the Hunshdak dust storm frequency. During 2001 to 2008, the lack of local precipitation, higher temperature and strong evaporation deteriorated the local surface condition to below that before 2000, which is verified by the reduction of vegetation cover (NDVI), soil moisture and relative humidity. Furthermore, compared to the 30 year climatology of the wind speed observed during dust storm occurrence time, the mean velocity of 2001-2008 was reduced by 3.0 m s −1 , indicating that even with relatively weaker winds, dust storms still occurred primarily due to the degeneration of surface conditions around the Hunshdak.
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.
ABSTRACT:The evolutionary characteristics of dust storms in spring in northern China springs are determined by synthesizing the previous patterns and analyzing the geopotential height at 500 hPa. Some potential seasonal predictors are found through detecting the atmospheric circulation factors in both qualitative and quantitative analyses. Based on the frequency series obtained through comprehensive investigations of dust storm events which occurred from 1970 to 2005, two sample sets, each containing 6 years, are selected to represent the most frequent and infrequent occurrences of spring dust storms. For the first set, most of the West Pacific subtropical highs in the previous summer are relatively small and weak compared to those in normal years. In the previous winter, the mid-latitude region of the Eurasian continent is strongly controlled by a large and active low system, simultaneously with a strong and westerly positioned trough over East Asia. The northern hemisphere polar vortex, in general, changes from weak to strong with a large area from the previous winter to the current spring. The geopotential height over the Tibetan Plateau keeps a lower than normal value with a relatively strong India-Burma trough from the preceding summer in to the spring. For the second set, the evolution displays opposite features. Furthermore, by using a bootstrapping technique, indices of the atmospheric circulation elements are detected quantitatively. The forecast skill score of the 36 year hindcast indicates that those indices can provide forecast signals in certain situations for spring dust storm seasonal predictions in northern China.
Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. The results are as follows: (1) the HRCLDAS and ERA5 near-surface wind data trend was basically the same as the observation data trend, but there was a smaller bias, smaller root-mean-square errors, and higher correlation coefficients between the near-surface wind data from HRCLDAS and the observations; (2) the quality of HRCLDAS and ERA5 near-surface wind data was better over the islands of the South China Sea than over Hainan Island land. However, over the coastal areas of Hainan Island and island stations near Sansha, the quality of the HRCLDAS near-surface wind data was better than that of ERA5; (3) the quality of HRCLDAS near-surface wind data was better than that of ERA5 over different types of landforms. The deviation of ERA5 and HRCLDAS wind speed was the largest along the coast, and the quality of the ERA5 wind direction data was poorest over the mountains, whereas that of HRCLDAS was poorest over hilly areas; (4) the accuracy of HRCLDAS at all wind levels was higher than that of ERA5. ERA5 significantly overestimated low-grade winds and underestimated high-grade winds. The accuracy of HRCLDAS wind ratings over the islands of the South China Sea was significantly higher than that over Hainan Island land, especially for the higher wind ratings; and (5) in the typhoon process, the simulation of wind by HRCLDAS was closer to the observations, and its simulation of higher wind speeds was more accurate than the ERA5 simulations.
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