不同气象条件下济宁城市热岛效应的变化特征

利用1981—2013年济宁、兖州、嘉祥、汶上站逐日4个时次的平均气温、平均风速、降水量、云量和能见度资料,对不同天气条件下济宁市的城市热岛效应进行研究.结果表明:济宁城市热岛效应具有明显的月季变化特征和日变化特征,具体为冬半年明显高于夏半年,白天的热岛强度明显低于夜间,中午前后最弱;济宁市四季热岛强度的变化规律是冬季最强,夏季最弱,春秋居中,除秋季外均呈现缓慢上升趋势.在不同气象条件下,济宁城市热岛强度也存在很大差异,其中在晴朗无风气象条件下表现最为突出,平均值达到0.79 ℃,其昼夜变化幅度也最大;在降雨时城市热岛强度最小,平均仅有0.09 ℃,其昼夜变化幅度也最小;大于等于4.0 m/s大风天气和雾均多发生在秋冬季,且雾对城市热岛的形成和昼夜变化影响明显大于风对城市热岛的影响;在晴朗无风和大雾条件下,02时热岛强度最强,当有降水出现时,20时热岛强度最强,出现大风天气时,08时热岛强度最强,所有研究天气条件下,14时热岛强度均表现为最弱.     

北京夏季高温变化特征及对城市热岛强度的影响

随着全球气候变暖和快速城市化，城市夏季高温及热浪出现频次和强度明显增加，但人口高度集聚的特大城市中夏季高温长期变化特征对城市热岛的影响程度和作用机制仍不甚明了。本文选择京津冀特大型城市群的核心城市北京为研究对象，基于长期气象观测数据计算夏季高温和城市热岛强度，阐明5—8月夏季高温长期变化特征及对城市热岛强度的影响。研究发现，1978—2020年北京城区夏季高温日数、强度和极端高温均呈现显著增加趋势，相伴随的是高温起始时间明显提前，结束时间显著推迟；高温天最高气温热岛强度呈显著降低趋势，而平均气温和最低气温热岛强度则呈轻微下降趋势；5—8月高温天最高、平均和最低气温多年平均热岛强度分别为0.73 ℃、1.61 ℃和2.40 ℃，明显高于非高温天的0.09 ℃、0.80 ℃和1.40 ℃，高温和非高温天热岛强度差值均在0.6 ℃以上，表明夏季高温放大城市热岛强度。预估未来全球变暖和快速城市化背景下北京城市热岛效应将进一步加剧，会形成更频繁和持续更长的夏季高温，给城市居民带来严重的健康风险。     

1960～2008年江西省极端降水变化趋势

利用江西省17个国家级台站1960～2008年逐日降水量资料,对日降水量超过绝对阈值(25mm和50mm)和百分位数阈值(95%和99%)的极端降水变化情况进行了分析。结果表明,江西省近50年极端降水频率和强度均呈波动上升趋势,大雨和强降水频率的增加最为迅速,暴雨和极端强降水事件强度增加最大;夏季各种极端降水事件频率均有明显升高;冬季大雨和强降水事件频率也有显著增加;春季和秋季极端降水强度有明显增加,特别是暴雨和极端强降水事件强度增加迅速;夏季暴雨和极端强降水强度有所降低或略有增加;江西省极端降水的频率和强度变化趋势较为一致,特别是1990年代;极端降水的增加以发生频数的增加为主,降水强度的增加并不显著;近50年江西省大部分地区的极端降水事件频率和强度均有增加,但高值区的分布有较大的差异。极端强降水事件强度在鄱阳湖平原附近减小,而在周边的大部分地区呈增长趋势。进一步的分析发现,极端降水强度的变化与地形有显著的正相关关系。     

1962—2013年清远市极端强降水的变化

根据1962—2013年清远市7个地面气象观测站逐日有效降水资料,对极端强降水变化的时空分布特征及变化趋势进行分析。分析表明:清远市极端强降水的阈值、总量和强度的分布呈东南向西北逐渐减少、频数呈西北向东南逐渐减少。阈值佛冈呈减少趋势,其余测站呈增加趋势;总量、频数和强度在南部站呈减少趋势、北部站则呈增加趋势。总量和频数在年变化上呈减少趋势,强度呈增加趋势。极端降水主要集中在4—9月,5—6月最为集中。总量、频数和强度都在20世纪90年代初出现突变现象,总量和强度呈增大、频数呈显著减少的趋势。极端强降水以持续1 d为主;21世纪后,持续1 d的极端强降水事件频数呈明显减少趋势。     

上海市极端高温天气变化特征

利用1960—2013年上海市徐汇站日最高气温、日最低气温和相对湿度及2004—2014年上海市10个气象站夏季日最高气温与日最低气温等观测资料,采用夏季日最高气温、高温日数、暖夜日数、高温热浪指标、炎热日数和广义极值分布等分析了上海市极端高温天气的变化特征。结果表明:1960—2013年上海市夏季日最高气温明显升高,暖夜日数和高温热浪指标明显增加,均在2013年达最大值,炎热日数和广义极值分布在1976年出现转折呈两种变化趋势。2004—2014年上海市徐汇站极端高温现象最显著,奉贤站、金山站和崇明站极端高温现象最不显著。不同极端高温指标可综合表征极端高温事件的变化趋势。     

西北地区极端高温变化及其对气候变暖停滞的响应

利用国家气候中心整编的中国西北地区日最高气温的观测资料,通过对中国西北地区极端高温变化特征进行较全面的分析,揭示了近20 a(1996—2015年)与近55 a(1961—2015年)中国西北地区极端气温变化的新特征。结果表明:除新疆维吾尔自治区部分和陕西省南部部分地区外,1961—2015年西北地区极端高温事件出现频次普遍呈增加的趋势,大值中心集中分布在新疆维吾尔自治区东南部、青海省北部、甘肃省西部和宁夏回族自治区中部地区,线性增加率为3.00次/10 a以上,其中大部地区增加趋势通过了99.5%以上信度的显著性检验,与全球气候变暖的特征较为一致。近20 a来西北地区极端高温事件出现频次呈西部和南部地区增多、东部和北部地区减少的空间变化特征。近20 a西北地区极端高温事件出现频率呈"西南部地区多、北部和东部地区少"的变化趋势,与前20 a(1961—1980年)极端高温事件出现频次的变化趋势相近,与近30 a(1981—2010年)极端高温事件出现频率的"西南部地区少、中东部地区多"的变化趋势相反。近55 a西北地区极端高温事件平均出现频次呈增加的趋势,平均值为1.73次/10 a;主要阶段变化率分别为:前20 a极端高温事件平均出现频次为0.06次/10 a,近30 a极端高温事件平均出现频次为3.90次/10 a,近20 a极端高温事件平均出现频次为-0.46次/10 a。近20 a西北地区极端高温事件出现频次呈弱递减的趋势与全球1998年以后增温的停滞现象较一致,说明西北地区的区域极端高温事件减少的特征对全球气候变暖停滞现象存在响应。由西北地区极端高温事件出现频次异常偏多年和偏少年的典型温度场可知,西北地区夏季异常高温变化对印度洋和太平洋的海温变化具有明显的正响应。西北地区极端最高气温和极端高温事件的温度强度分布主要取决于海拔高度,其次与局地地形和下垫面性质有关。     

伊犁河谷春夏季极端天气气候的变化分析

利用1961-2005年降水、气温、冰雹、大风资料,分析了伊犁河谷春夏季极端天气气候事件的长期变化趋势.结果发现暴雨(日降水>24mm)频次20世纪90年代以后明显增加,分析最大日降水量发现,降水强度也明显增大,这和伊犁河谷降水变化趋势是一致的;春夏季极端温度的变化不显著,夏季极端高温频次和强度有微弱的减小,春季极端低温频次和强度也有微弱的减小;春夏季伊犁河谷冰雹和大风极端天气显著减少.     

新、旧气候态差异及对中国地区气候和极端事件评估业务的影响

利用1961—2020年中国区域2089个地面观测站资料,分析了1991—2020年和1981—2010年新、旧气候态下,平均气温、最高气温、最低气温和降水量等变量的空间变化特征,探讨对气候距平值、极端事件等评估结果的影响。结果表明：新气候态下,全国三类气温年和季节平均均一致升高,年降水增加,空间上气温偏高（低）、降水偏多（少）的特征将弱（强）化;华北东部、华东中部和北部以及青海西南部的年平均风速和日照时数距平增加;极端高温年减少,低温年增多,其中平均气温和最低气温受到的影响较最高气温更大;夏季南北方两条雨带极端强降水年的发生概率降低,冬季东北中部和南部、华北、华东北部、西北东部极端弱降水年概率显著增加;全国超过一半的站点极端日高温、低温和强降水事件的历史频次发生改变;新气候态还减弱了极端日高温事件的增速,加快了极端日低温事件的降速。     

北京中央商务区(CBD)城市热岛效应的研究

利用2012~2013年北京中央商务区（Central Business District,CBD）加密观测资料,分析CBD区域城市热岛（Urban Heat Island,UHI）强度日变化和空间变化特征及其影响因子。研究发现,CBD区域气温高于周边自动站气温,平均偏高0.64℃;CBD区域城市热岛强度呈现夜间强、白天弱的现象,中午甚至存在“城市冷岛”现象。季节平均UHI日变化表现为:在夜间,秋季最强,冬季次之,春季和夏季较弱;在白天,夏季最强,冬季次之,春季和秋季较弱。相对于晴朗无风天气,雾、雨、大风等天气对城市热岛有抑制作用,并结合小波分析结果发现,秋季城市热岛强度强于冬季是由于冬季雾、雨、大风等天气过程发生比例较高的缘故。CBD区域城市热岛空间变化特征研究发现,花园、学校等绿地有助于缓解城市热岛效应。雾日、雨日和大风日的CBD区域城市热岛强度空间变化标准差比晴朗无风日小。     

不同气象条件下廊坊城市热岛效应变化特征

利用2005年9月—2008年8月廊坊市区域加密自动站逐时气温资料,采用城、郊气温对比法研究了不同气象条件对廊坊城市热岛效应的影响。结果表明：廊坊城市热岛强度夜间大于白天,但变化幅度白天大于夜间;在四季不同时段存在“城市冷岛”现象。不同气象条件下,廊坊城市热岛强度及变化存在明显差异,晴朗无风时城市平均热岛强度最大,平均强度达1.25℃,阴雨气象条件下城市平均热岛强度最小,平均强度仅有0.10℃。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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