1961—2008年淮河流域气温和降水变化趋势

利用淮河流域170个地面气象观测站观测数据,统计分析了淮河流域1961—2008年间气温和降水的时空变化趋势。结果表明:48 a间淮河流域年平均气温呈显著上升趋势,冬季平均气温的增温幅度最大,春、秋次之;年极端最低气温亦呈显著上升趋势,年极端低温日数(满足该站极端低温阈值)则呈明显下降趋势;流域西北部年极端最高气温呈显著下降趋势,流域西部年极端高温日数(满足该站极端高温阈值)呈显著下降趋势;降水量总体变化趋势未通过统计检验,但1990s开始,秋季降水量呈下降趋势,2000年之后年降水量明显增加,夏季降水量亦增加;春季和秋季降水日数呈显著下降趋势,夏季和冬季无明显变化。     

1961~2010年西北地区极端气候事件变化特征

利用1961~2010年西北地区131个气象站的逐日平均气温、最高和最低气温及逐日降水资料,分析了西北地区极端气候事件的变化趋势及空间分布特征。结果表明:气候变暖背景下,西北地区近50 a来气温整体呈增加趋势,极端高温事件增多,极端低温事件减少;降水量呈微弱的增加趋势,极端降水事件增多;极端高温日数分别在1982年和1996年发生转折,95%、99%极端低温日数均在1980年前后发生突变,95%、99%极端降水日数分别在2000年和1980年出现转折,这与气温和降水的变化趋势一致。极端低温日数减少的幅度大于极端高温日数增加的幅度,表明气温日较差呈减小趋势,存在非对称性增温特征。空间上,增温率大的区域其极端高温日数增加,极端低温日数显著减少;95%、99%极端降水日数增率大的区域多位于降水量倾向率较高的地区。     

山东省降水量与不同强度降水日数变化对干旱的影响

采用山东省82个地面气象站1961～2004年日降水量,统计了历年的降水量、不同强度降水日数;利用累积距平及t检验法分析了干旱受灾面积、降水量和不同强度降水日数的长期变化趋势并进行了突变检验,相关分析方法研究了干旱气象灾害对降水量和不同强度降水日数变化的响应。结果表明:干旱受灾面积、年降水量及中等强度以上降水日数的转折年大都出现在1976年,微量降水日数、0.1～4.9 mm/d降水日数及总雨日数的转折年出现在1988年全球气候变暖背景下,转折年后年降水量及不同强度的雨日数异常偏少年份频繁出现;干旱受灾面积与降水量和不同强度降水日数呈显著的负相关,降水量或不同强度的降水日数异常偏少都将导致干旱的发生。20世纪70年代中期以后随着全球气候变暖,降水量和5.0～99.9 mm/d以上降水日数异常偏少年份增多是极端干旱气候事件频繁发生、干旱面积扩大的最主要原因。     

青海省干旱评估方法探讨及系统研制

本文考虑到气候变暖的影响,以降水量、平均气温和降水日数作为地区干旱强度的物理量,设计根据降水量距平百分率、气温距平、降水日数距平和影响权重系数的干旱强度评估方法,并利用VB6.0编译语言制作应用系统。     

MM5模式精细化预报显示系统

利用VisualC 6.0编译系统开发了华云神箭MM5模式精细化预报显示集合系统,实现各种精细化数值预报产品在全省区域、江河流域的分布、统计、显示、打印、图形化、表格化等功能,并实现在同一地形图上、流域图上用不同的颜色对比显示逐时、逐日气温、最低气温、最高气温、风速、风向、湿度、降水和实况降水量,还可统计全省97个台站任意降水时段的降水量值和极值。     

长治市极端气候事件的分析及对农业生产的影响

利用长治市3个代表站1961年～2005年逐日气象资料,对长治近45年的极端气候事件的变化趋势及其对农业生产的影响作了分析。结果表明：作为极端气候事件的暴雨、大暴雨日数具有较为一致的变化特点,在20世纪90年代开始出现了增多的趋势。1992年以后干旱事件开始减少,1999年开始洪涝事件有所增加。1993年以后极端低温与极端高温出现日数先后开始增加。研究发现极端气候事件的变化与气温突变及显著升高有极为明显的关系。     

基于DERF2.0模式产品对单站旬、月极端降水日数的预测

该文利用1951—2013年贵阳站逐日降水量观测资料分析其极端降水日数的气候特征,结合DERF2.0月动力延伸预测模式输出的500 h Pa高度场格点资料,将高度距平场与该站极端降水日数距平值利用线性回归及逐步回归的方法建立5月26日起报1~40 d的预测模型,并对预测效果进行检验。结果表明:贵阳站20世纪80年代中期至90年代中期是极端降水日数偏多的时段,其余时段呈现偏少特征,在21世纪10年代之后极端降水日数呈增加趋势;影响贵阳站各旬极端降水日数的天气系统在月内具有阶段性的调整和变动,相比月尺度大气环流信号的稳定性较弱;对比固定时段建模和滑动时段建模下极端降水日数的预测结果,发现固定时段建模的预测结果与实况较为一致,尤其是月尺度预测值与实况值的相关系数较稳定,旬尺度预测值与实况值的稳定性较弱。     

1955—2014年杭州极端气温和降水指数变化特征

根据杭州市1955—2014年降水量、气温逐日资料,采用国际通用的极端天气指数和线性倾向估计、M-K检验等方法,分析了杭州市近60 a极端气温和降水的变化特征。结果表明：1）杭州市近60 a的气温呈一致升高趋势,且变化显著,表现为极端高温阈值和极端低温阈值的升高及极端高温日数的增多;极端冷事件显著减少,暖事件显著增多。2）极端降水指数中只有强降水量的增加较明显,主要贡献为夏季和冬季强降水量的增强。3）冬季平均气温、极端低温阈值、霜冻日数等极端冷事件的突变发生于20世纪80年代初中期,夏季平均气温、极端高温阈值、高温日数等极端暖事件的突变发生于20世纪末21世纪初,与全国范围内的气候增暖进程基本一致。另外,降水强度、极端降水阈值等极端降水指数的突变时间在2008年左右,即2008年后气温升高和降水强度的增加突变期叠加,尤其在夏季和冬季表现更突出,可能诱发更多的异常天气。     

崇明生态岛气候变化及影响评估研究

基于上海崇明气象站气温、降水、日照、风速等数据和主要天气现象记录资料,利用气候统计诊断方法研究了崇明生态岛主要气候要素和天气现象的变化特征及其生态影响。结果表明,1961—2016年期间,崇明气温显著上升,高温日数和极端最高气温增加;降水量显著增多,暴雨日数增加,小雨、中雨和大雨对全年总降水量的贡献下降,而暴雨和大暴雨的贡献增加;风速显著减小,大风日数和极端最大风速减少;日照时数和相对湿度明显减少,雾日数增加。在气候变化影响下,崇明作物无霜期初日提前,终日推后,无霜期日数增加,有效积温增多,人体舒适度日数增加。但气候变化会导致当地风能资源减少,大气环境条件不利于污染物的扩散和稀释。研究结果可为绿色、平安崇明建设和世界级生态岛的可持续发展布局提供借鉴。     

2005年河南异常气候事件及影响

1 基本气候特点 2005年河南基本气候概况为：全省年平均气温基本正常，其中冬季气温明显偏低，为1986年以来最冷的冬天，春、夏、秋季气温偏高。全省年降水量较常年偏多，其中冬季降水正常，春季降水偏少，夏、秋季降水偏多。全省年日照时数偏少。年内相继出现了冬季低温冻害、春季北中部干旱、初夏持续性高温、盛夏暴雨洪涝和秋季连阴雨等多种气象灾害，大雾和雷雨大风、冰雹等强对流天气也时有发生，但总体而言，本年度气象灾害偏轻，气候条件总体正常，属于偏好年景。     

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.     

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     

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.     

Information for Authors

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     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.