气象干旱指标在青海东部农业区的适用性研究

利用青海东部农业区5个地区1961—2005年降水资料和实际干旱受灾面积资料,分析了降水距平百分率(Pa)、SPI指数、Z指数、K指数4个干旱指标在这些地区的适用性,结果表明:在青海东部农业区,SPI和Z指数具有较好的适用性,与其他指标相比两者具有较好的一致性,基本能反映当地的旱涝状况,可以在海东地区气象干旱预测预报及评估中实际应用;Pa指数适用性较差,K指数适用性最差。     

2017年春夏呼伦贝尔草原干旱过程多种监测指数对比分析

以2017年春夏季呼伦贝尔草原干旱过程为研究对象,利用呼伦贝尔草原范围内6个气象站的气温、降水数据和MODIS NDVI数据,分析对比2017年4—9月多种气象干旱指数（Pa30、SPI30、SPEI30、CI、MCI）与植被状态指数（VCI）的监测情况。结果表明：只考虑单一降水的气象干旱指数（Pa30、SPI30）在4月波动较大,且此类指数无法反映出高温等其他气象条件对干旱发展的影响。综合气象干旱指数(CI、MCI)由于引入多时间尺度干旱进行计算,旱情缓解时轻旱等级持续的时间过长,且草原植被在降水增加后的恢复速度较快,造成干旱缓解期间植被与监测结果差异较大。MCI与同期和前1期VCI的相关性最好,CI和SPEI30与前1期和前2期VCI的相关性较好,而只考虑单一降水的气象干旱指数与VCI的相关性普遍偏差。植被对SPEI30的响应时间更长,更适宜草原生态干旱的早期预警使用。     

基于大气-土壤-植被系统干旱发生发展过程的综合干旱指标构建与应用

适宜的干旱指标和高分辨率数据是准确监测干旱的基础。本研究从气象干旱和土壤干旱以及植被对干旱的响应出发,整合中国国家气象观测站、中国气象局陆面数据同化系统（CLDAS）土壤湿度（0.0625°×0.0625°）和MODIS叶面积指数（500 m×500 m）等多源数据信息,构建了基于气象干旱指数（标准化降水蒸散指数）、土壤干旱指数（土壤湿度百分位）和植被干旱指数（叶面积指数百分位）的综合干旱指数,并在中国东北地区开展了典型站点和区域10 km×10 km空间分辨率干旱监测试验。结果表明,综合干旱指数克服了单一气象干旱指数不能准确反映农业旱情及单一植被长势指数会将其他灾害引起的植被长势变差误判为干旱的不足,能够反映灌溉对干旱的影响,实现对大气-土壤-植被系统干旱发生、发展及其影响的监测。      

利用条件植被指数评价西藏植被对气象干旱的响应

基于2000—2014年4—10月西藏气象站遥感干旱指数 (条件植被指数,VCI) 和气象干旱指数 (标准降水指数,SPI) 之间的相关性,评估植被对气象干旱的响应特征,通过分析气候环境要素对响应特征的影响并归纳相应规则,获取西藏地区植被对气象干旱有明显响应的区域分布。结果显示:VCI与12周时间尺度的SPI具有较强相关性,说明西藏地区植被生长对降水的响应大约滞后12周;植被对气象干旱响应不敏感的原因主要包括气候极度干燥或极度湿润、土地覆盖类型为森林、年平均归一化植被指数 (NDVI) 值过小、多年NDVI变化标准差过小、有降水之外的其他水源补给等;基于对区域气候环境要素特征的分析,可以得出西藏中部偏南地区植被对气象干旱有明显响应,主要包括拉萨地区、山南地区北部、日喀则地区东部、那曲地区中部和西南部、阿里地区的东南部。     

利用MODIS资料估算西北雨养农业区地表净辐射

应用定西地区的气象资料和4次EOS-MODIS卫星资料,对典型的西北半干旱雨养农业区的基本地表特征参数进行反演,并在此基础上对地表净辐射量进行估算,进而分析了它的季节变化。结果表面,应用卫星数据估算的净辐射结果与实际观测值基本接近,相对误差在16%以内,基本反映了当地的实际情况;雨养农业区净辐射的季节变化表现为冬季最小,其次是秋季,夏春两季最大,并且四季相差比较大;净辐射四季变化也呈现出不均匀的分布特性,频率分布范围较宽。     

干旱严重指数（DSI）在内蒙古地区的适用性分析

利用MODIS遥感产品计算内蒙古地区2000—2019年植被生长季的干旱严重指数(DSI),并结合气象干旱综合指数(MCI)、植被状态指数(VCI)等干旱指数和典型干旱过程,对DSI在内蒙古地区的适用性进行分析。研究表明,DSI与MCI、VCI的平均相关系数为0.509和0.839,分别通过0.05和0.01的显著性检验,具有较好的一致性。与MCI相比,DSI具有更高的空间分辨率,能反映不同植被类型抗旱能力的差异和区域植被改善后抗旱能力的增强。与VCI相比,DSI受高植被覆盖区归一化植被指数(NDVI)饱和现象的影响更小,并在干旱缓解期的灵敏性更高。DSI在内蒙古地区的适用性较好,可在干旱监测研究与业务中进行尝试和使用。     

近45年兴海地区气候变化对草场土壤湿度的影响

根据近45a气象资料和近10a土壤水分观测资料,利用气候线性数理统计方法,分析了兴海县高寒山地草原气候变化趋势及其对土壤水分变化的影响,结果表明：兴海县高寒山地草原区近45a气候变化趋势与青藏高原气候变化规律相一致;影响土壤湿度的气象因子主要有降水和蒸发,而温度则通过影响蒸发间接影响着土壤湿度,蒸降差是分析气候变化对土壤水分影响的直观指标。     

西藏藏北高原典型植被生长对气候要素变化的响应

选取西藏藏北高原西部高寒草原植被、中部高寒草甸植被及东南部高寒灌丛草甸植被 3 种藏北地区最典型的植被类型, 结合临近 3 个气象观测站的资料, 分析这 3 种典型植被类型地区 1999—2001 年旬平均气温、旬总降水量和 SPOT VEGETATION 卫星 10 d 最大值合成归一化植被指数 (NDVI) 变化特征以及 3 种典型植被基于 SPOT VEGETATION NDVI 的生长变化对旬平均气温和旬总降水量两个主要气候要素变化的响应关系。 结果表明: 藏北地区降水资源的空间分布特点是东南部向西北部逐渐减少, 气温则由南向北逐渐递减, 与降水资源分布相反, 蒸发量西部高, 东部低; SPOT VEGETATION NDVI 能够较为准确地反映 3 种典型植被生长变化特征, 所反映的植被返青期和枯黄期等重要植被生长阶段与由积温计算的植被生长特征基本一致; 藏北地区基于 SPOT VEGETATION NDVI 的植被生长变化与气温的相关系数明显高于与降水的相关系数 , 其中以那曲为代表的高寒草甸植被的 NDVI 与旬气温和旬降水总量的相关系数最大, 分别为 0.81 和 0.68 , 表明藏北地区由于海拔高, 气候寒冷, 气温对该地区植被生长的影响明显高于降水的影响, 即该地区植被生长变化对气温的响应程度明显高于对降水的响应程度 , 是植被生长的限制性因素; 不同植被类型对气温和降水两个要素的响应程度大小依次是高寒草甸、高寒灌丛草甸和高寒草原。     

应用长时序NDVI评价雨养农业区冬小麦全生育期受旱状况

为了能够利用卫星遥感数据对不同年份冬小麦受旱状况进行客观定量的评价,以甘肃陇东雨养农业区为研究区域,应用1981-2006年NASA GIMMS NDVI数据以及同期的降水、土壤水分和冬小麦产量数据,通过研究25个冬小麦生长季NDVI(Normalized Difference Vegetation Index)特征以及与降水、土壤水分和生育期的相互联系,提出了能对冬小麦全生育期受旱状况进行客观定量评价的冬小麦受旱指数WWDI(Winter wheat drought index),并根据气象数据、冬小麦产量和历史年鉴资料对WWDI监测的冬小麦受旱状况的准确性进行检验。结果表明:WWDI能够很好地监测冬小麦的全生育期的受旱状况,应用WWDI确定的1981-2006年间冬小麦受旱最严重的几个年份分别是1995,2000和1992年,这几年冬小麦的受旱程度与其气象条件和农业生产状况非常一致; WWDI与冬小麦产量存在极显著的相关关系(p0. 001),可以作为定量评估冬小麦整个生育期受旱状况的指标。     

青海省2007年夏季气候

2007年夏季（6—8月）青海省气候特点是：全省气温偏高，大部分地区降水偏多，日照时数偏少。主要的天气气候事件是6月上旬东部农业区部分地区出现的干旱，8月下旬全省首次出现入夏以来大范围的高温天气，洪涝、冰雹、雷击等气象灾害以及强降水引发的山体滑坡、泥石流等次生灾害。     

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.     

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.     

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.     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;