鹤壁市秋季中雨预报系统

利用鹤壁市1986～1999年秋季高空图资料,确定了48h和24 h中雨高空要素预报指标;利用1995～2000年Micaps数据格式的物理量场分析结果,确定了24 h中雨物理量预报指标.鹤壁市秋季中雨预报系统根据预报指标和人工神经元网络预报结果,对秋季降水进行逐级判别,综合做出预报结论.     

B—P网络在夏秋季强降水预报中的应用

利用鹤壁1986—1999年夏秋季强降水资料，寻找出鹤壁市夏秋季强降水消空指标和预报指标。利用48h、24h夏秋季强降水预报指标和人工神经元B—P网络降水量预报结果，定量做出鹤壁市夏秋季强降水预报。     

B-P网络在夏秋季强降水预报中的应用

利用鹤壁1986～1999年夏秋季强降水资料,寻找出鹤壁市夏秋季强降水消空指标和预报指标.利用48 h、24 h夏秋季强降水预报指标和人工神经元B-P网络降水量预报结果,定量做出鹤壁市夏秋季强降水预报.     

郑州地区2000年首场汛雨天气过程分析

利用高空实时资料 ,对郑州首场汛雨天气的环流形势进行剖析 ,并结合本局汛期研制的物理量 4级动态相似预报方法提供的若干物理量场进行诊断分析 ,得出有关首场汛雨预报的一些有意义的启示。     

渭南市近50年秋季降水气候变化及趋势分析

本文利用高空及地面资料、实况物理量场数据、预报经验指标、数值预报产品、卫星云图等综合分析了大到暴雪天气过程的成因，为今后预报忻州市冬末初春大到暴雪天气过程总结出了前期环流形势和各高度层物理量指标。     

基于物理量参数的江苏短时强降水预报模型的研究

本文利用2004—2013年6—8月江苏省三个常规探空站(徐州、射阳、南京)的逐日高空探测资料,计算了51个物理量参数。在物理量参数与短时强降水事件(观测时刻后0~6 h内出现的短时强降水天气)相关系数的显著性检验基础上,根据物理量参数在短时强降水样本和非短时强降水样本中值域分布特征,最终选定了具有预报意义的16个物理量参数。通过分析不同类型物理量参数对短时强降水天气的指示作用,根据各物理量参数在各月短时强降水事件中的阈值,确定了江苏短时强降水预报的判定指标。采用隶属函数转换法,建立江苏夏季短时强降水预报模型,经实况拟合检验,效果良好。     

数值预报产品在冬半年暴雪预报中的释用

利用天气学原理分型统计了1981～2000年鹤壁市12h暴雪预报指标，采用N-T方法对T213和HLAFS数值产品预报场进行反演，并应用于2002年冬半年12h暴雪分段预报中，还对两种数值产品的预报效果进行了对比检验。     

2000—09—24郑州暴雨衣过程物理量演变特征

利用郑州实时探空资料，分析了2000年9月24日本区暴雨衣发生前郑州站物理量演变特征，为秋季暴雨预报提供了思路和线索。     

丹东暴雨物理量诊断分析预报

对T106数值预报产品进行统计分析，确定了与暴雨关系密切的物理量；通过对物理量场与暴雨落区之间关系的定性诊断分析以及对物理量的定量计算，确定了物理量的临界值，并以此作为预报暴雨发生的限制条件；将T106数值预报产品的3种物理量预报场与临界值对比，判断未来24h有无暴雨。     

郑州地区2000年首扬汛雨天气过程分析

利用高空实时资料，对郑州首场汛雨天气的环流形势进行剖析，并结合本局汛期研制的物理量4级动态相似预防方法提供的若干物理量场进行诊断分析，得出有关首场汛雨预报的一些有意义的启示。     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

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正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted