Sand-dust storms in China: temporal-spatial distribution and tracks of source lands

Sand-dust storm is a special natural disaster that frequently occurs in deserts and their surrounding areas. With the data published onSurface Meteorological Monthly Bulletin andSurface Chart during 1971–1996, the temporal-spatial distribution and annual variation of sand-dust storms are analyzed on the basis of the case study of atmospheric processes. Furthermore, the tracks and source areas of sand-dust storms are determined with the aid of GIS. The results show that except some parts of Qinghai Province and Inner Mongolia as well as Beijing, sand-dust storms decrease apparently in time and space in recent decades in China. Sand-dust storms occur most frequently in spring, especially in April. According to their source areas, sand-dust storms are classified into two types, i.e., the inner-source and outer-source sand-dust storms. Most of the outer-source sand-dust storms move along the north and west tracks. The north-track outer-source sand-dust storms always intrude into China across the Sino-Mongolian border from Hami, a city in the eastern part ofXinjiang, to Xilin Gol, a league in Inner Mongolia, while the west-track ones intrude into China from both southern and northern Xinjiang. The source lands of inner-source sand-dust storms concentrate in the Taklimakan Desert and its surrounding areas in southern Xinjiang, southern part of the Junggar Basin in north of Xinjiang, the Hexi Corridor in western Gansu Province, the dry deserts of Inner Mongolia and the Qaidam Basin in Qinghai.

Implementation and application of a nested numerical storm surge forecast model in the East China Sea

A nested numerical storm surge forecast model for the East China Sea is developed. Aone-way relaxing nest method is used to exchange the information between coarse grid and fine grid. In the inner boundary of the fine grid model a transition area is set up to relax the forecast variables. This ensures that the forecast variables of the coarse model may transit to those of fine grid gradually, which enhances the model stability. By using this model, a number of hindcasts and forecast are performed for six severe storm surges caused by tropical cyclones in the East China Sea. The results show good agreement with the observations.

The influence of different underlying surface on sand-duststorm in northern China

In this paper, a quantitative research on the relationship between different underlying surface and sand-dust storm has been made by using 40 years meteorological data of five different types of underlying surface in northern China, which include farmland, grassland, sandland, gobi and salt crust. These metrological data comprise sand-dust storm days and strong wind days. By analyzing, we can find that there are certain correlations between the days of sand-dust storm and strong wind for different underlying surface, which has great influence on sand-dust storm. But there are pronounced differences in different types of underlying surface. The sand-dust storm days of grassland, gobi and salt crust, with smaller interannual variation are obviously less than strong wind days. On the other hand, the sand-dust storm days of farmland and sandland increase evidently, even in many years, are much more than strong wind days. The differences are mainly induced by the influencing mechanism of different underlying surface on sand-dust storm. Grassland, gobi and salt crust with stable underlying surface are not prone to sand-dust storm under strong wind condition. Whereas, the underlying surface of farmland and sandland is unstable, that is easy to induce sand-dust storm under strong wind condition.

Dust Storm Ensemble Forecast Experiments in East Asia

The ensemble Kalman filter （EnKF）, as a unified approach to both data assimilation and ensemble forecasting problems, is used to investigate the performance of dust storm ensemble forecasting targeting a dust episode in the East Asia during 23-30 May 2007. The errors in the input wind field, dust emission intensity, and dry deposition velocity are among important model uncertainties and are considered in the model error perturbations. These model errors are not assumed to have zero-means. The model error means representing the model bias are estimated as part of the data assimilation process. Observations from a LIDAR network are assimilated to generate the initial ensembles and correct the model biases. The ensemble forecast skills are evaluated against the observations and a benchmark/control forecast, which is a simple model run without assimilation of any observations. Another ensemble forecast experiment is also performed without the model bias correction in order to examine the impact of the bias correction. Results show that the ensemble-mean, as deterministic forecasts have substantial improvement over the control forecasts and correctly captures the major dust arrival and cessation timing at each observation site. However, the forecast skill decreases as the forecast lead time increases. Bias correction further improved the forecasts in down wind areas. The forecasts within 24 hours are most improved and better than those without the bias correction. The examination of the ensemble forecast skills using the Brier scores and the relative operating characteristic curves and areas indicates that the ensemble forecasting system has useful forecast skills.

The atmospheric circulation patterns influencing the frequency of spring sand-dust storms in the Tarim Basin

Using NCEP/NCAR reanalysis data and the sand-storm frequency data fi＇om 37 weather stations in the Tarim Basin for the period 1961-2009, the relationship between the frequency of spring sandstorms in the Tafim Basin and the associated atmospheric circu- lation pattems is analyzed in this study. We found significantly negative correlations between sandstorm frequency and the 500-hPa geopotential height over the Paris Basin and midwestem Mongolia, while there were positive correlations over the Ural River region. The rising of the 500-hPa geopotential height in midwestem Mongolia and its falling over the Ural region corre- spond to a weakening of the large-scale wave patterns in the Eurasian region, which directly causes the frequency of the sand-dust storms in the Tarim Basin to decline. Also, the abrupt decline in the spring sandstorm frequency in the Tarim Basin observed in the last half-century is associated with profound changes in the atmospheric circulation in these key regions. At the interannual scale, the strengthened cyclonic atmospheric circulation patterns in the western part of Mongolia and the anticyclonic patterns over the East European plains at 500-hPa geopotential height, are responsible for frequent sandstorm occurrences in the Tarim Basin.

SAMPLE OPTIMIZATION OF ENSEMBLE FORECAST TO SIMULATE TROPICAL STORMS(MERBOK, MAWAR, AND GUCHOL) USING THE OBSERVED TRACK

Nowadays,ensemble forecasting is popular in numerical weather prediction(NWP).However,an ensemble may not produce a perfect Gaussian probability distribution due to limited members and the fact that some members significantly deviate from the true atmospheric state.Therefore,event samples with small probabilities may downgrade the accuracy of an ensemble forecast.In this study,the evolution of tropical storms(weak typhoon)was investigated and an observed tropical storm track was used to limit the probability distribution of samples.The ensemble forecast method used pure observation data instead of assimilated data.In addition,the prediction results for three tropical storm systems,Merbok,Mawar,and Guchol,showed that track and intensity errors could be reduced through sample optimization.In the research,the vertical structures of these tropical storms were compared,and the existence of different thermal structures was discovered.One possible reason for structural differences is sample optimization,and it may affect storm intensity and track.

Typhoon storm surge ensemble forecast based on GPU technique

The accuracy of typhoon forecasts plays an important role in the prediction of storm surges.The uncertainty of a typhoon’s intensity and track means it is necessary to use an ensemble model to predict typhoon storm surges.A hydrodynamic model,which is operational at the National Marine Environmental Forecasting Center,is applied to conduct surge simulations for South China coastal areas using the best track data with parametric wind and pressure models.The results agree well with tidal gauge observations.To improve the calculation efficiency,the hydrodynamic model is modified using CUDA Fortran.The calculation results are almost the same as those from the original model,but the calculation time is reduced by more than 99%.A total of 150 typhoon cases are generated by combining 50 typhoon tracks from the European Centre for Medium-Range Weather Forecasts with three possible typhoon intensity forecasts.The surge ensembles are computed by the improved hydrodynamic model.Based on the simulated storm surges for the different typhoon cases,ensemble and probability forecast products can be provided.The mean ensemble results and probability forecast products are shown to agree well with the observed storm surge caused by Typhoon Mangkhut.The improved model is highly suitable for ensemble numerical forecasts,providing better forecast products for decision-making,and can be easily implemented to run on regular workstations.

Detecting sand-dust storms using a wind-profiling radar

Sand-dust storm is a type of disastrous weather, typically occurring in arid and semi-arid climates. This study selected a region in the hinterlands of the Taklimakan Desert, called the Tazhong region, as the experimental area to quantitatively estimate the particle concentrations of sand-dust storms using the boundary layer wind-profiling radar. We thoroughly studied the radar echo signals and reflectivity factor features during the sand-dust storms. The results indicate that（1） under sand-dust storm conditions, boundary layer wind-profiling radar cannot capture the complete information regarding horizontal wind velocity and direction, but it can obtain the backscattering intensity of sand-dust storms; and（2） during sand-dust storms particle size distributions in the surface layer closely resemble log-normal distributions, with sand-dust particles sizes of 90–100 μm accounting for the maximum particle probability. Retrieved particle size distributions at heights of 600, 800, and 1000 m follow log-normal distributions, and the expected value of particle diameter decreases gradually with increasing height. From the perspective of orders of magnitude, the retrieved results for particle number concentrations and mass concentrations are consistent with previous aircraft-detected results, indicating that it is basically feasible to use boundary layer wind-profiling radar to quantitatively detect the particle concentrations of dust storms.

Storm-scale ensemble forecast based on breeding of growth modes

How to obtain fast-growth errors, which is comparable to the actual forecast growth error, is a crucial problem in ensemble forecast （EF）. The method, Breeding of Growth Modes （BGM）, which has been used to generate perturbations for medium-range EF at NCEP, simulates the development of fast-growth errors in the analysis cycle, and is a reasonable choice in capturing growing errors modes, especially for extreme weather by BGM. An ideal supercell storm, simulated by Weather Research Forecast model （WRF）, occurred in central Oklahoma on 20 May 1977. This simulation was used to study the application of BGM methods in the meso-scale strong convective Ensemble Prediction System （EPS）. We compared the forecasting skills of EPS by different pertubation methods, like Monte-Carlo and BGM. The results show that the ensemble average forecast based on Monte-Carlo with statistics meaning is superior to the single-deterministic prediction, but a less dynamic process of the method leads to a smaller spread than expected. The fast-growth errors of BGM are comparable to the actual short-range forecast error and a more appropriate ensemble spread. Considering evaluation indexes and scores, the forecast skills of EPS by BGM is higher than Monte-Carlo＇s. Furthermore, various breeding cycles have different effects on precipitation and non-precipitation fields, confirmation of reasonable cycles need consider balance between variables.

Sand-dust Storm, Population and Environment in Northwest China

Sand-dust storms are the result of the integrated influences of climate, geography, society and human factors. A theoretical framework is built to explain the coherence of population growth, agriculture change and environmental degradation. On the basis of the analysis of the causes of the sand-dust storm in terms of human factors, a discussion will be given to show that these factors are internally consistent with the theoretical framework. After that, it will look at China's Agenda 21 and try to find relevant measures to reduce such large sand-dust storms happening in Northwest China and eventually make this area develop sustainably.

A Simulation Study on Channel Estimation for Cooperative Communication System in Sand-dust Storm Environment

There are many factors that influence the propagation of electromagnetic wave in the sand-dust storm environment, the scattering effect of dust particle is one of the major factors, so this paper focuses on the dust particles scattering function. The scattering of dust particles inevitably brings the multipath transmission of the signal, multipath propagation will bring the multipath fading of the signal. In this paper, we first investigate the use of AF and DF modes in a sand-dust storm environment. Secondly, we present a low-order modulation method should be used in cooperative communication system. Lastly, we evaluate the system performance for both of the moving nodes and power allocation. Experimental results validate the conclusion of theoretical derivation: the multipath fading is one of the main factors that affect the quality of signal transmission. Cooperative communication technology has good anti-fading ability, which can guarantee the signal transmission timely and correctly.

PROBLEMS CONCERNING SAND-DUST STORMS IN NORTHWEST CHINA

This paper describes an exceptionally severe sand-dust storm that occurred in Northwest China in 1993, and outlines the damage, characteristics and formative factors of the sand-dust storm and the demarcation of its prone zones, laying emphasis on the countermeasures to prevent and reduce such disasters. Finally the authors suggest setting up protective systems for oases and taking action to rehabilitate the blown sand-land on the northern side of the Great Wall on the Loess Plateau.

江淮地区一次特大暴雨过程预报偏差分析

利用加密自动气象观测站资料、ERA5再分析资料和欧洲中心ECMWF(European Centre for Medium-Range Weather Forecasts)模式、中国气象局CMA-MESO(China Meteorological Administration Mesoscale Model)模式产品,对2020年7月17—18日江淮地区一次特大暴雨过程的预报效果进行检验与分析,并对数值模式降水预报出现偏差的可能原因进行了讨论。结果表明:低涡切变和低层急流的共同影响,为强降水提供了充沛的水汽和有利的动力条件。高空干冷空气叠加在低层暖区之上形成的位势不稳定层结和垂直风切变为强降水的发生提供了不稳定条件。17日20时—19日08时CMA-MESO模式逐12 h暴雨、大暴雨以及暴雨以上量级降水的TS评分均优于ECMWF模式,但2种模式对18日08—20时暖区降水的预报结果均较差。CMA-MESO模式预报的降水区域和实况区域重叠面积的比例均显著高于ECMWF模式,预报形态也与实况更为接近。模式对冷空气强度预报偏弱造成了冷切辐合偏北,对中层湿舌的位置预报偏北,水汽强度预报偏弱,与强降水落区预报偏北相对应,可能是降水预报出现明显偏差的原因。

主客观融合精细化降水预报方法及防汛业务应用

基于水利部现有预报数据和资源,开展主客观融合的精细化降水预报方法研究,研制了一套技术方法。选取2022—2023年4次较强洪水过程,对主客观融合预报、主观预报、欧洲中期天气预报中心(ECMWF)客观预报在9个流域的预报结果对照实况进行检验,结果表明,主客观融合预报在空间融合与时间拆分效果上优于主观预报和客观预报。

基于神经网络的未来3天Kp指数预报建模与可解释AI应用

当前业务中对未来3天Kp指数预报需求强烈.但地磁暴中多参数耦合导致难以量化各预报因子对Kp值的贡献,制约了预报精度提升.本文构建了神经网络3天Kp指数预报模型,并使用人工智能(AI)可解释性算法定量化各因子贡献.结果显示,行星际磁场南向分量在提前3 h对Kp指数的贡献为37.15%,为主要因子,说明模型能捕捉符合物理特征的主要预报因子.Kp指数历史特征贡献随提前量逐渐增加,提前3天总体贡献占68.06%,验证了对冕洞高速流引起的地磁暴事件的预报能力.对2015和2017年特大地磁暴进行贡献分析,模型准确捕捉了地磁暴多参数耦合的复杂特性.研究表明,可解释AI算法在一定程度上能定量化各预报因子对Kp指数的预报贡献,有助于改进未来3天Kp指数AI预报模型.

2023年广西高影响强对流天气特征及预报预警回顾

利用多源气象探测资料,对2023年广西高影响强对流天气特征及预报预警难点进行综合分析。结果表明:(1)全年出现5次区域性及以上强对流天气过程,总体偏少。冰雹集中出现在3月到5月。雷暴大风主要出现在3—9月,极大风速为34.9 m·s^(-1)。(2)产生冰雹的超级单体主要触发在锋面及锋前暖区,强的对流不稳定、能量和垂直风切变条件下锋前暖区需关注迅速发展降雹的超级单体,提前发布预警信号。(3)西南涡背景下的飑线大风天气由地面静止锋和干线触发;短临预报应考虑线状对流自组织作用将落区向南调整。(4)对类高架、暖区冰雹天气数值模式预报能力差,需加强机理研究提升客观化预报预警技术。

浙江省台风影响预测及沿海风险识别系统研究

浙江省台风灾情频发,为科学应对台风威胁,通过优化相似台风匹配算法、对历史台风资料进行整理并作降雨网格化处理、海岸增水数据网格处理和海岸风险分析,切实解决了目前系统存在相似台风匹配不精确、无台风降雨过程和沿海增水展示不直观、缺少海岸线风险识别等问题,为新形势下的台风预报预警提供有力的技术支撑。

Features of Sand-dust Deposits in Harbin City,China

From the sedimentologic view, this paper analyses the grain-size distribution and the chemical composition of the deposits from sand-dust storm, occurring in Harbin on March 20, 2002. The result indicates that there exist plentiful coarse matters in the sand-dust deposits in Harbin, and the sand-dust composition presents obvious three peak distribution characteristics, indicating that the sand-dust in Harbin is composed of multi-origin components. The grain-size composition consists of silt （4-8Φ）, accounting for 71.18% of the total, sand （〉4Φ）, 21.70%, and clay （〈8Φ）, only 7.13%. The average grain size （Mz） is 5.14Φ. The chemical elements of the deposits are mainly SiO2 and A1203 and Fe203, totally occupying 77.8%. The enrichment factors （EF） of Mg, K, Si, Fe, Mn, P, Ti, Co, Ni and V elements are all about 1, which mainly come fi＇om lithosphere source, while parts of Cu, Pb, Zn, Cr and Se elements are from pollution sources out of lithosphere source, and As, Cd and Sb elements are mainly from pollution sources. Based on the comprehensive analysis of grain-size, chemical composition, enrichment factor （EF）, discriminant function （DF） and matter source index （PI）, this paper points out that the grain-size distribution and element composition of the sand-dust deposits in Harbin are evidently different from the loess and sand-dust in Lanzhou, and that matter source of the sand-dust in Harbin is different from the loess in Northwest China and the sand-dust in Lanzhon. The sand-dust deposits in Harbin are an admixture of coarse grains transmitted in short distance and fine grains transported in long distance. The plentiful coarse grains of the sand-dust deposits in Harbin origin from sand of local spot, and are the near-souroe deposits transported by low altitude airflow.

Validation of an operational forecasting system of sea dike risk in the southern Zhejiang Province, South China

In this study,an operational forecasting system of sea dike risk in the southern Zhejiang Province,South China was developed based on a coupled storm-surge and wave model.This forecasting system is important because of the high cost of storm-surge damage and the need for rapid emergency planning.A comparison with astronomical tides in 2016 and the validation of storm surges and high water marks of 20 typhoons verified that the forecast system has a good simulation ability.The system can forecast relatively realistic water levels and wave heights as shown under the parametric atmospheric forces simulated in a case study;the sea dikes in credible high risk were mainly located in the estuaries,rivers,and around the islands in the southern Zhejiang.Therefore,the forecast system is applicable in the southern Zhejiang with a support to the effective prevention from typhoon storm-surge damage.

PRELIMINARY STUDY ON SAND - DUST STORM DISASTER AND COUNTERMEASURES IN CHINA

As a kind of natural disasters, sand dust storms frequently occur in deserts and their surrounding areas. The occurrence of this disaster in China′s northwest and north China has exerted an extremely adverse effect upon the environment in China. The management of sand dust storms is of a systematic project closely related with the environment such as agriculture, ecosystem, forestry, water conservancy, meteorology and other aspects. Therefore, studies of the formation, the basic features, causes, temporal spatial distribution, developing trend and related disasters of sand dust storms in China are conducted based on satellite data. The experience of sand dust storms control and countermeasures in the United States and some other countries are referred. Meanwhile, preliminary countermeasures relating to sand dust storms in China are proposed.