脑血管病的气象危险指数预报研究

为预防脑血管病发生、发展,提高人群自我保健意识,利用西安市2010—2013年脑血管病死亡人数和同期气象数据,通过SPSS17.0对气象因子与脑血管疾病逐日死亡人数进行单因素相关分析,通过多元逐步回归方法按月建立脑血管病日死亡人数预报模型,并建立脑血管病气象危险指数等级,应用2014年资料检验预报模型及等级预报。结果表明:西安市不同月份与脑血管病死亡人数有显著相关的气象因素不同;按月建立的脑血管病预报模型准确率在78%以上,气象危险指数等级预报准确率达90%,预报模型及气象危险指数等级预报效果较好。     

南京市呼吸道疾病时间序列模型的建立与分析

利用1990～2000年南京市支气管哮喘与感冒逐月就诊人数病例资料和同期国家气象中心资料室的月平均压、温、湿等资料,讨论了2种疾病发病人数的月际和年际变化规律,分别建立了包含气象因子的预报2种疾病逐月就诊人数的条件异方差和动态回归模型。南京地区支气管哮喘就诊人数高峰期出现在春末与秋季,逐年的就诊人数呈现上升趋势,其发病与当月月平均气压、上一个月月平均温度有关。感冒就诊人数高峰期出现在夏秋季,其发病与月平均最低温度和月极端最低温度有关。将模型应用于2种疾病逐月就诊人数的等级预报中,其预报等级准确率分别达75．0％和66．7％,表明此建模方案是可行的,此类模型有一定的使用价值。     

市域脑卒中疾病与气象因素的关系及预测

为了帮助医疗机构合理调配医务力量、床位和医疗药物,同时也帮助脑卒中高危人群及时采取干预措施,降低发病风险。本文对某市[1]四家医院2013—2016年脑卒中的就诊病例进行数据分析,将日就诊人数分为6个等级。然后,调取相应时段当地的逐日气象资料,采用支持向量机(SVM)和随机森林(RF)方法分别建立了日就诊人数预测模型和日就诊人数与气象因素的关系模型。研究结果表明:(1)脑卒中的日就诊人数为不平衡数据,这种数据特征将导致传统的预测模型正确率较低;(2)通过不断调整SVM预测模型的初始权重,经历了4次优化之后,使得日就诊人数的预测正确率从52.46%上升到94.56%;(3)随机森林模型的结果显示,影响脑卒中发病率的三大气象因素分别是最高气温、最低气温和平均气温。基于机器学习模型的脑卒中疾病与气象因素的研究成果,提高了医疗气象统计模型的预报准确率,具有较高的应用和推广价值。     

西安呼吸系统疾病气象风险指数等级预报研究与应用

利用2010年1月1日—2014年12月31日西安市呼吸系统疾病死亡数据与相应的气象观测数据,选取与呼吸系统疾病有显著相关性的气象因子,采用多元逐步回归方法,建立呼吸系统疾病死亡人数预测模型和呼吸系统疾病气象风险指数等级预报方法,并对预测模型和等级预报进行了检验。结果表明：呼吸系统疾病日死亡人数预测模型准确率在795%以上,呼吸系统疾病气象风险指数等级预报准确率达到98%,预测预报效果较好。将呼吸系统疾病气象风险指数等级预报融入西安公共气象指数预报服务系统,制作呼吸系统疾病气象风险指数等级预报、预警产品,并通过全方位融媒体发布手段开展健康气象预报预警服务。     

武汉市居民中暑与气象因子的统计特点研究

利用武汉市1994～2006年共13年1464个中暑病例资料和同期逐日气象资料,分别统计逐日中暑人数、日平均中暑人数与气象因子的线性、非线性相关系数,筛选出关键气象因子,建立中暑与多气象因子的非线性模型,制订中暑气象等级标准.结果表明:气温是中暑发生的最关键影响因子,不利气象因子3天或3天以上的累积效应才能导致中暑群发,中暑人数与气象因子呈现非线性关系.建立了日平均中暑人数与前3日平均气温、前3 日平均最小相对湿度的指数模型.将日平均中暑人数划分为5级,并应用该等级标准进行历史样本同代检验和独立样本预报检验,效果较好.     

气象要素对南京市呼吸系统疾病的影响研究

利用2007—2012年南京市逐日气象资料和同期某三甲医院呼吸系统疾病逐日急诊和门诊就诊人数资料,采用常规统计方法,分析了主要气象要素与疾病就诊人数的关系,揭示了气象条件对人群呼吸系统疾病的影响程度,为当地居民防病养生提供气象指导。结果表明:呼吸系统疾病发病与气象要素之间存在1~2 d的滞后效应,且与日平均气温、日最高气温和日最低气温的相关最显著,尤其当平均气温低于0℃时,全人群就诊人数明显增加;此外,当寒潮过程发生时,全人群和老年人(65岁)就诊人数增加率分别为35%和53%,且表现出1 d的滞后性;与之相比,儿童(6岁)就诊人数没有表现出滞后效应,寒潮结束当日,就诊人数增加了2倍以上。     

贵州玉舍冬季滑雪气象指数等级制订

运用1988~2017年贵州省玉舍滑雪场附近30年气候资料和2015~2016年冬季滑雪场客流量资料,分析贵州高海拔地区滑雪运动与气象条件的关系,进而进行滑雪气象指数等级研究。结果表明:(1)玉舍滑雪场冬季具有少雨、低风、温度适宜的气候特点,可以开展滑雪运动。(2)玉舍的滑雪人数与气象因子风速、气温、相对湿度、降水量呈显著反相关。(3)根据玉舍滑雪场气候背景特征,分别对降水量、相对湿度、舒适度指数三个气象要素进行分级,通过实际滑雪人数分级与滑雪气象指数等级预报进行的检验表明:实际滑雪气象指数等级与指数预报等级相同(即绝对值之差为0)的准确率达26.4%,实际滑雪气象指数等级与指数预报等级绝对值之差为1的准确率达66.7%,即预报滑雪气象指数等级与实际滑雪气象指数等级之差≥1的准确率达93%。     

气象条件对北京夏季中暑的影响及预测研究

利用2009-2012年北京市467例中暑病例与同期9个气象要素资料和当日及前期1-4 d累积平均气象要素共45个气象因子,采用相关分析法分析北京夏季中暑发病人数与气象因子之间的关系|采用多元线性回归和非线性拟合方法构建了改进的北京中暑气象预报模型,选取拟合优度较好的模型对中暑人数进行回代及预测检验,并与现用模型进行对比。结果表明：气温是引发北京夏季中暑的决定性因子|气温、水汽压、气压及降水的两日累积效应均高于当日效应,表明气象要素的连续累积作用对人体中暑影响较大|建立的中暑预报模型具有较好的历史拟合及预测效果,中暑等级划分较合理,对北京市中暑气象等级预报服务和公众有效防范中暑有实际的指导意义。     

贵州省健康气象指数预报模型构建及技术

该文旨在重新梳理贵州省健康气象指数类型及预报方法,构建切合贵州省实际的健康气象指数预报模型。通过对各待考察疾病的门诊病例的标准化统计分析,与气象因子的相关性分析,重新拟定了贵州省健康气象指数类型,揭示了几个待考察疾病发病率与气象因子之间的相关性,并运用回归分析方法构建了预报模型。对贵州省健康气象指数进行了新的等级划分及模型回代检验,各预报模型的预报准确率在90%以上,可以此为基础建立新的业务系统。     

北方地区小麦蚜虫气象适宜度预报模型构建

根据1958—2015年我国北方地区8个主产省（市）小麦蚜虫分省发生面积和发生程度资料、1958—2015年601个气象站点相应逐日气象资料和农业气象站小麦发育期资料,采用相关分析、主成分分析和逐步回归等方法,并利用相关系数法进行因子普查,结合小麦蚜虫适宜生理气象指标和华北、黄淮小麦生育期规律,筛选影响小麦蚜虫年发生程度的关键气象因子,构建分区域的小麦蚜虫气象适宜度预报模型,并将气象适宜度指数划分为非常适宜、适宜、较适宜、不适宜4个等级,以反映气象条件对小麦蚜虫发生发展的适宜程度。结果表明:筛选出影响华北小麦蚜虫年发生程度的8个关键气象因子,影响黄淮小麦蚜虫年发生程度的6个关键气象因子。建立的华北、黄淮模型回代检验等级准确率分别为91.2%,93.1%,2016—2018年3年外推预报平均准确率均在75%以上;利用黄淮模型反演苏皖两省2016—2018年小麦蚜虫发生等级、异地检验3年预报效果均较理想。模型适用于从气象角度对华北、黄淮及江淮地区小麦蚜虫发生等级进行监测和预报。     

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;