乌鲁木齐城区冬季雾的分布特征及其影响因素

基于乌鲁木齐站（城南）和米东站（城北）2016—2020年冬季（11月—次年2月）的雾、雾日最小能见度、逐时能见度和月平均风速、月平均静风频次、月平均相对湿度等资料，利用统计学方法，分析乌鲁木齐城区冬季雾的分布特征,探讨城南和城北雾分布差异的主要影响因素。结果显示：近5 a冬季城南平均雾日44.6 d，少于城北54.2 d，两地均为1月最多，11月最少；雾日平均最小能见度城南和城北分别为335 m和390 m，城南雾总体强于城北；城南雾高发于17时—19时，常在11时和05时消散；城北雾主要在09时和20时—22时开始，大都在14时前后结束；城南和城北的雾均以持续24 h以内为主，分别占比93.5 %和86.3 %，其中持续3 h内的雾分别占37.2 %和33.3 %，城北的雾持续时间总体长于城南。风速较小、静风较多、相对湿度较大和地理环境是城北冬季雾多于城南的主要影响因素。     

厦门城市能见度和雾的特征与城市环境演变

利用厦门城市1980～2000年21年地面资料和探空资料，对能见度和雾演变特征及其物理成因进行分析，结果表明：厦门城市夏季能见度明显好于冬季，这可能与冬夏盛行风向不同，输送排放污染源地不同以及不同季节天气气候条件相关。厦门城市冬季和夏季能见度呈下降趋势，尤以夏季为突出，轻雾以上的频数也日益增加，其重要因素是城市的热岛效应。厦门城市能见度虽然明显好于污染较为严重的北京，但冬季厦门城市能见度与北京呈反位相演变趋势。夏季厦门城市能见度有着明显的日间变化，这与夏季海陆风日变化的垂直环流圈有密切关系。     

闽南沿海地区低能见度事件变化特征分析

利用2005-2010年闽南沿海地区9个气象站(厦门、同安、漳州、东山、漳浦、龙海、诏安、晋江和崇武)的日常观测能见度、相对湿度等气象资料,采用统计方法,探讨了闽南沿海地区低能见度事件的年、季和日变化等变化特征规律.分析发现,闽南沿海地区低能见度事件的年平均能见度一般在6 km左右,且低能见度在霾时总体要好于(轻)雾时;上半年低能见度事件持续时间较长且多发,下半年低能见度事件持续时间短且出现频率低于上半年.通常,08时的能见度最差,14时和20时转好,02时的能见度较08时要好,只有沿海测站东山站和崇武站在冬春季02时能见度较08时差.霾是造成闽南沿海地区出现低能见度事件的主要原因,(轻)雾次之,反映出该地区经济快速发展对能见度的影响.     

民航广汉机场气象能见度的周期性变化特征的初步分析

基于民航广汉机场1986~1995年每日逐时气象能见度的观测资料,利用相关性分析,功率谱分析、带通滤波,以及小波分析等方法,分析和研究了广汉机场气象能见度的周期性变化特征。研究结果表明,机场能见度的变化与机场相对湿度和低云量呈显著负相关,与机场地面温度和地面风速呈正相关特征。广汉机场气象能见度的变化明显具有10~20d的准双周振荡特征和30~50d准周期性季节内振荡特征。      

广州白云机场低能见度气候特征

利用广州白云机场1970～2000年逐时能见度观测资料，对白云机场低能见度的气候特征进行统计分析。结果表明：小于等于1km的低能见度有明显的8年周期变化，小于等于0．8kin和0．55km的低能见度主要振荡周期是6～10年；自20世纪70年代出现能见度小于等于1km的日数有逐年上升趋势，其中90年代出现的日数明显偏多，80年代相对偏少；低能见度有明显的季节变化和日变化特征；低能见度平均出现次数与持续时间明显成反比；造成低能见度障碍的天气现象仅有雾和雨。     

北半球平流层低层大气季节内振荡特征

利用奇异谱分析方法（SSA）分析了1975年1月1日至12月31日北半球30hPa高度场变化特征，结果发现:平流层低层大气除了年变化及季节变化趋势外，还存在明显的季节内振荡，最显著的周期为20～60天；在持续性异常多发地区，30hPa高度场变化中20～40天周期振荡占优势，而在其它一些地区则盛行40～60天周期振荡；对流层持续性异常主要同对流层高度场的20～40天振荡有关，并可能通过这种周期振荡同平流层低层相同周期的振荡的相互作用影响平流层低层大气季节内变化。     

L波段雷达资料在雾的边界层逆温特征中的应用

本文利用沙坪坝基本气象站2005~2010年逐日08,20时L波段雷达探空资料,对不同类型雾日期间边界层逆温特征进行分析。结果表明:从季节上来看雾日主要发生在秋冬季节,雾日期间不论是08时还是20时均有多层逆温存在,各类型雾日逆温温差均为08时大于20时,而逆温强度表现为20时大于08时,不论是雾日,轻雾日还是浓雾日,08时逆温层厚度都比20时要厚。总的来说,浓雾日的逆温层各要素都体现逆温特征较为明显的特点,逆温温差越大,逆温层厚度越厚,也就更容易形成浓雾,同时08时的各逆温要素均高于20时,08时逆温特征也更为明显,在这时段也就更容易形成雾。      

梧州市两次致洪暴雨诊断分析

利用南宁城市1980-2002年地面资料和探空资料，对能见度和雾的演变特征及其物理成因进行分析，结果表明：南宁城市夏季能见度明显好于冬季，这可能与冬夏季不同季节盛行风向不同，输送排放污染源地的差异以及不同季节天气气候条件相关。夏季南宁主要受大陆高压的控制，城市能见度高，雾日少，而在冬季，由于冷空气的频繁影响和南宁上空逆温层的存在，轻雾以上的日数增加，城市能见度也随之下降。近几年来，南宁的城市能见度呈下降趋势，轻雾以上的雾日数呈上升趋势，雾日的频数也随之增加，这可能与南宁城市下垫面的改变，局地气候的变化和人类活动等因子有着密切的关系。     

北京城市能见度及雾特征分析

利用北京及市郊16个标准国家气候站的1980至2000年21年能见度与雾特征等资料,对北京及周边地区的能见度和雾特征及其演变进行了研究结果表明,近20年北京能见度的变化存在显著季节性差异.近20年来,北京市区能见度冬季和夏季呈两种不同的变化.冬季能见度有转好趋势,夏季,80年代以来,北京市城区海淀、京西门头沟、石景山、丰台等地、北部及东部等地能见度有逐年转差趋势,冬季和夏季能见度距平呈反位相变化. 近十年上述能见度转差地带,雾日也是增加的.20世纪的最后10年与80年代开始的10年相比,夏季7、8、9月份北京城市和郊区的雾日有显著增加.雾日的高峰值出现在以海淀区为中心的北京城区的全境,包括京西的石景山、丰台、门头沟等地;另一个雾日数高峰区位于北京东部地区.北京夏季雾增加与能见度减低的地区分布趋于一致可能与北京特殊的"马蹄形"大尺度地形堆积影响有关. 尺度过滤分析研究表明,夏季,从北京城区向东南方向伸展至河北一带地区,有个显著的带状能见度减弱区.这个能见度减弱带与尺度分离揭示的城区内更小尺度的雾增大特征现象有关,有可能与最近10年北京以南地区其他的工业排放或污染源对北京的输送及城市发展变化有一定关系,即与大气气溶胶分布和北京特定的气象条件和城市变化状况有关.     

南阳市大气能见度变化趋势及影响因子分析

利用南阳市1995-2005年大气能见度和地面气象要素的观测资料及南阳市环境检测站提供的近3 a空气污染物监测数据,统计分析了近10 a南阳市大气能见度变化特征及其与气象要素和空气污染物的关系,结果表明:南阳市能见度年际变化呈缓慢波动上升趋势,夏秋季节2001年之后呈波动下降趋势;冬季能见度最低,春季最高;能见度月变化呈双峰型,第一个峰值在5月份,第二个峰值在9月份;一日之中,08时能见度最差,14时最好.能见度与同期气象要素及污染物浓度的相关分析表明,能见度与相对湿度、空气污染物PM10浓度呈显著性负相关,与NO2、SO2浓度负相关性较弱,与风速和气压呈弱的正相关,与温度的相关性较为复杂,雾是影响能见度的主要天气现象之一.     

青岛市水平能见度变化特征及气象影响因子分析

利用青岛市2005-2007年的常规气象资料,通过统计学和小波分析的方法分析了青岛市水平能见度的变化特征和气象影响因子,发现青岛市能见度有明显的日、天气尺度、准双周、季节和半年的振荡周期,其变化特征和温度、相对湿度、风向、风速、地面气压、海雾以及边界层高度等要素都存在一定的关联.     

1966—2016年重庆南川降水的多尺度分析

利用1966—2016年南川国家站的逐日降水观测资料,分析了南川降水的年内分布及次季节变化和暴雨的气候变化特征、年际、年代际和趋势变化特征。结果表明:南川降水的年内分布差异大,降水量峰值出现在6月,月降水强度最大在7月;南川的降水具有明显的次季节变化,且准双周变化信号(10~25 d)大于低频季节内振荡(25~90 d);南川的暴雨日数和暴雨量与年降水量有很好的正相关性;暴雨出现在3—11月,其分布呈单峰型,峰值出现在6月;年平均暴雨日为2.5 d,暴雨日数年际变化的线性趋势不显著;暴雨日总降水量在1966—1994年存在10~12 a的年代际变化信号,在1996—2016年主要存在13~15 a的年代际变化信号,在1976—1984年还存在2~4 a的年际变化信号;南川的暴雨特征量年际、年代际变化大,但没有显著的升降趋势,说明南川暴雨的总体气候特征是比较平稳的。     

Daily atmospheric variability in the South American monsoon system

The space–time structure of the daily atmospheric variability in the South American monsoon system has been studied using multichannel singular spectrum analysis of daily outgoing longwave radiation. The three leading eigenmodes are found to have low-frequency variability while four other modes form higher frequency oscillations. The first mode has the same time variability as that of El Nino-Southern Oscillation (ENSO) and exhibits strong correlation with the Pacific sea surface temperature (SST). The second mode varies on a decadal time scale with significant correlation with the Atlantic SST suggesting an association with the Atlantic multidecadal oscillation (AMO). The third mode also has decadal variability but shows an association with the SST of the Pacific decadal oscillation (PDO). The fourth and fifth modes describe an oscillation that has a period of about 165 days and is associated with the North Atlantic oscillation (NAO). The sixth and seventh modes describe an intraseasonal oscillation with a period of 52 days which shows strong relation with the Madden-Julian oscillation. There exists an important difference in the variability of convection between Amazon River Basin (ARB) and central-east South America (CESA). Both regions have similar variations due to ENSO though with higher magnitude in ARB. The AMO-related mode has almost identical variations in the two regions, whereas the PDO-related mode has opposite variations. The interseasonal NAO-related mode also has variations of opposite sign with comparable magnitudes in the two regions. The intraseasonal variability over the CESA is robust while it is very weak over the ARB region. The relative contributions from the low-frequency modes mainly determine the interannual variability of the seasonal mean monsoon although the interseasonal oscillation may contribute in a subtle way during certain years. The intraseasonal variability does not seem to influence the interannual variability in either region.     

1991、1998和2016年三个大水年长江中下游夏季降水季节内特征的对比

针对长江中下游三个大水年1991、1998和2016年,利用NCEP/NCAR大气环流再分析资料和CMAP降水资料,对比了夏季降水的季节内特征,分析了引起降水季节内变化的大气环流季节内振荡ISO演变及源地。小波分析表明,三年季节内降水周期差异明显,分别为20~30 d、20~40 d和10~20 d。随之,以东亚季风区季节内振荡指数及热带外Rossby波活动通量,诊断了引起三年季节内活动异常的热带和中纬度ISO变率特点。结果显示影响三年季节内降水的ISO差异较大。1991年受到来自印度洋10~30 d和中纬度高层Rossby波10~30 d的ISO共同影响,造成周期为20~30 d的低频降水;1998年ISO来源路径单一,受中北太平洋30~60 d和10~30 d的ISO西传叠加作用,降水表现为20~40 d的振荡;引起2016年季节内降水异常的ISO源地较多,既有来自印度洋向东北传播30~60 d的ISO,又有来自太平洋向西北传播10~30 d的ISO,还有来自热带外10~30 d的ISO,三者在长江中下游汇合,引起降水10~20 d的振荡。研究结果对认识长江中下游夏季集中降水的形成有重要意义。      

Quasi-two weeks oscillation in the tropical atmosphere

Summary Based on analysis of ECMWF data (1981–1987) and numerical simulations using a general circulation model (GCM), a quasi-two-week (10–20 day) oscillation in the tropical atmosphere is studied in this paper. It is shown that the kinetic energy of the quasi-two-week oscillation is larger than that of the intraseasonal oscillation, and is another important low-frequency system in the tropical atmosphere. By comparing it with the intraseasonal oscillation, some obvious differences can be found. For example, the zonal scale of the quasi-two-week oscillation is dominated by perturbations with wavenumber 2–4; its vertical structure mainly shows barotropic features; the zonal propagation is basically westward; and its meridional and zonal components the same size.With 10 Figures     

Interannual spring Wyrtki jet variability and its regional impacts

The role of spring Wyrtki jets in modulating the equatorial Indian Ocean and the regional climate is an unexplored problem. The source of interannual variability in the spring Wyrtki jets is explored in this study. The relationship between intraseasonal and interannual variability from 1958 to 2008 and its relation with Indian Summer Monsoon is further addressed. Analysis reveals that the interannual variability in spring Wyrtki jets is controlled significantly by their intraseasonal variations. These are mostly defined by a single intraseasonal event of duration 20 days or more which either strengthens or weakens the seasonal mean jet depending on its phase. The strong spring jets are driven by such intraseasonal westerly wind bursts lasting for 20-days or more, whereas the weak jets are driven by weaker intraseasonal westerlies. During the years of strong jets, the conventional westward phase propagation of Wyrtki jets is absent and instead there is an eastward phase propagation indicating the possible role of Madden Julian Oscillation (MJO) in strengthening the spring Wyrtki jets. These strong intraseasonal westerly wind bursts with eastward phase propagation during strong years are observed mainly in late spring and have implications on June precipitation over the Indian and adjoining land mass. Anomalously strong eastward jets accumulate warm water in the eastern equatorial Indian Ocean (EIO), leading to anomalous positive upper ocean heat content and supporting more local convection in the east. This induces subsidence over the Indian landmass and alters monsoon rainfall by modulating monsoon Hadley circulation. In case of weak current years such warm anomalies are absent over the eastern EIO. Variations in the jet strength are found to have strong impact on sea level anomalies, heat content, salinity and sea surface temperature over the equatorial and north Indian Ocean making it a potentially important player in the north Indian Ocean climate variability.     

Spatial and temporal characteristics of intraseasonal oscillations of precipitation over the United States

Summary  This study shows that precipitation over the United States has two time scales of intraseasonal variation at about 37 days and 24 days. The results are derived from the application of a combination of statistical methods including principal component analysis (PCA), singular spectrum analysis (SSA), and multi-channel singular spectrum analysis (MSSA) to over 10 years of gridded daily precipitation records. Both oscillations have largest amplitude during the cold season. The 37-day oscillation has larger interannual variability. Intraseasonal oscillations are most significant in the Pacific Northwest. The 37-day oscillation has opposite phases between the western and eastern United States, while the 24-day oscillation has the same phases. These intraseasonal time scale precipitation variations may be associated with previously revealed mid-tropospheric circulation anomalies that oscillate at similar time scales. Received February 7, 2000 Revised October 20, 2000     

Intraseasonal variability in subtropical South America as depicted by precipitation data

Daily precipitation data from three stations in subtropical Argentina are used to describe intraseasonal variability (20–90 days) during the austral summer. This variability is compared locally and regionally with that present in outgoing longwave radiation (OLR) data, in order to evaluate the performance of this variable as a proxy for convection in the region. The influence of the intraseasonal activity of the South American Seesaw (SASS) leading convection pattern on precipitation is also explored. Results show that intraseasonal variability explains a significant portion of summer precipitation variance, with a clear maximum in the vicinity of the SASS subtropical center. Correlation analysis reveals that OLR can explain only a small portion of daily precipitation variability, implying that it does not constitute a proper proxy for precipitation on daily timescales. On intraseasonal timescales, though, OLR is able to reproduce the main features of precipitation variability. The dynamical conditions that promote the development of intraseasonal variability in the region are further analyzed for selected summers. Seasons associated with a strong intraseasonal signal in precipitation variability show distinctive wet/dry intraseasonal periods in daily raw data, and are associated with a well defined SASS-like spatial pattern of convection. During these summers, strong large-scale forcing (such as warm El Niño/Southern Oscillation (ENSO) events and/or tropical intraseasonal convective activity), and Rossby-wave-like circulation anomalies extending across the Pacific Ocean, are also observed.     

Space-time spectra of the atmospheric intraseasonal variability in the extratropics and their dependency on the El Niño/Southern Oscillation phenomenon: model versus observation

By comparing the results obtained from two sets of simulations with the ECHAM3 and the ECHAM4 atmospheric general circulation models with results derived from the ECMWF re-analyses, we not only investigate the models’ capability to reproduce aspects of the intraseasonal variability in the extratropics realistically, but also evaluate the impact of the changes between the two different versions of the ECHAM model. Moreover, we assess the impact of the marked variations of sea surface temperatures in the tropical Pacific associated with the El Niño/Southern Oscillation (ENSO) phenomenon on the characteristics of the intraseasonal variability in the midlatitudes. Both models realistically reproduce many aspects of the intraseasonal variability in the extratropics, i.e. the partition of the variability into the contributions of the transient cell and of the stationary and transient eddies and its seasonal variation, and also the spectral distribution of the contribution of the transient waves to the intraseasonal variability. The most severe deficiency of the models is a considerable underestimation of the contributions of the transient waves to the intraseasonal variability, mainly in the low-frequency part of the spectrum. In the recent version of the ECHAM model (ECHAM4) some of the model’s shortcomings in simulating the intraseasonal variability realistically, in particular those in the Southern Hemisphere, are noticeably reduced compared to the previous version (ECHAM3). Yet some aspects are more realistically captured by ECHAM3. Both the ECMWF re-analyses and the two sets of simulations with the ECHAM models reveal a distinct impact of the ENSO phenomenon on the characteristics of the intraseasonal variability within the extratropics in boreal winter. In the Northern Hemisphere the most prominent effect is that the activity of the stationary waves is enhanced during El Niño events at the expense of the transient waves. In the Southern Hemisphere, on the other hand, all the different contributions to the variance on intraseasonal time scales (transient cell, transient and stationary eddies) are stronger during El Niño than during La Niña events. Concerning the transient waves, this mainly reflects changes in the low-frequency part of the spectrum associated with the activity of ultra-long planetary waves.