博斯腾湖流域气候变化及其对径流的影响

利用博斯腾湖流域开都河、黄水沟和清水河的出山口水文站月径流量和气象站月平均数据，开展变化特征分析和径流变化对气候因子的响应研究。结果表明，博斯腾湖流域年际气候变化以气温上升为主，降水量增加趋势不显著；域内主要河流径流量持续上升。突变检验发现，三条入湖河流90年代之前径流量增加主要是域内降水量增加的结果，随后受气温上升导致冰雪消融加快也对径流量的增加有贡献。相关分析结果显示，博斯腾湖三条入湖河流年径流量变化主要受4月和7月降水因子影响。此外，开都河的径流变化还表现出对8月气温和降水的显著响应，同时开都河流域集水区冰川的面积和占比均大于黄水沟和清水河流域，这表明冰川融水补给对开都河径流的影响大于黄水沟和清水河。所建立的气候因子-径流量多元线性回归模型，能够很好的模拟开都河、黄水沟和清水河的径流变化过程，证明了博斯腾湖流域水文变化受气候因子的显著影响。     

开都河流域面雨量与径流变化分析

对开都河流域及其附近的8个气象站和3个水文站的1961—2000年的年降水资料进行自然正交分解(EOF),利用梯度距离平方反比法(GIDS)作为差值公式,建立了主要特征向量与地理因子的插值模型,并以数字高程模型(DEM)的1km×1km网格数据为基础,推算出开都河流域平均年降水量的空间分布以及逐年面雨量序列。计算结果表明:开都河流域面雨量年平均为80.6×108m3,径流量与面雨量之比(R/P)平均为0.38,最大为0.53,最小为0.32。面雨量与径流量的年际相对变化幅度是一样的,变差系数Cv值为0.17。     

澜沧江源区气温与降水对径流变化的影响

为研究澜沧江源区水文气候变化特征,采用线性回归拟合分析方法、M-K非参数检验法对1960—2010年间澜沧江源区的水文气候变化趋势进行分析,计算了各季节气温变化对年气温变化的贡献量,并基于Pearson相关分析法和贡献率的计算讨论了降水量和气温对径流量变化的影响。结果表明:澜沧江源区年平均气温和各季节平均气温均呈显著上升趋势,其中,冬季的增温对年平均气温增加贡献最大(38%)。澜沧江流域源区年降水量无明显增减趋势,但春季降水量显著增加。澜沧江流域源区年径流量未呈现显著变化趋势,冬季和春季径流量呈现出显著的增加趋势。年际尺度上,径流量的主控因素是降水量,降水量对径流量年内变化的影响主要发生在降水相对丰沛的6—10月份;冬季和初春季节气温上升对径流量的改变存在一定的影响,且气温的贡献率要比降水的贡献率大,原因是气温升高加剧研究区内冰雪的消融,进而导致澜沧江源区的径流增加。     

博斯腾湖水位变化特征及其可能影响机制分析

应用开都河下游大山口水文站径流和博斯腾湖1956-2009年的逐月水位数据和流域内各气象站的气象数据,通过模糊聚类等统计方法,分析了博斯腾湖水位变化趋势及其可能影响因子.结果表明:博斯腾湖的水位年际变化受开都河流域径流的影响很大,当开都河流域径流量大时博湖水位较高,且开都河径流与其上、下游气温和降水关系密切.博斯腾湖水位逐年的月变化基本上可以分为5类,其中最主要的为第一类型和第二类型:第一类为递减型,特征为季节变化不明显,水位在春季较高,以后逐渐降低;第二类为递增型,特点是季节变化较第一大类明显,水位在夏末秋初的时候较高,整体呈现上升趋势.递增、递减型出现的主要原因是受上下游降水和大山口径流的影响,当上下游降水和径流偏多时水位月际变化出现递增型,反之易出现递减型.     

45年来塔里木河流域气候变化对径流量的影响研究

根据塔里木河流域40个气象站1961-2005年的降水、 气温资料及源区内7个水文站1957-2005年年径流量资料, 利用Mann-Kendall检验, 分析了近45年来塔里木河流域的气候变化的特征, 探讨了气候变化对塔里木河流域水资源的影响。结果表明： 整个流域除个别站点外, 塔里木河流域气温整体呈显著上升趋势, 且以秋季最显著, 降水增加以夏季最明显。特别是中天山南坡, 而流域西南部、 和田地区和巴州南部的降水量几乎没有增加。根据Mann-Kendall检验结果, 除阿克苏河年径流量呈显著增加趋势外, 其它3条源流（和田河、 叶尔羌河、 开都河）径流量近45年变化趋势均不显著。     

1961—2009年辽河流域水文气象要素变化特征

依据1961—2009年辽河流域5个气象观测站点逐日降水和气温观测资料,运用非参数检验方法（Mann-Kendall法）,对辽河流域降水和气温的变化趋势进行了分析。利用2006—2010年夏季共162d降水日的铁岭站日降水量与铁岭水文站径流量资料,探讨了日降水量与径流量之间的相关关系。结果表明：辽河流域年降水量减少趋势明显,降水量偏少年份明显增加,其主要原因为占全年降水量65%的夏季降水以7.4 mm/10 a的气候趋势倾向率递减,呈现出明显的减少趋势;辽河流域的年平均气温是在波动中逐渐上升的,且升温趋势明显,春季呈明显的升温趋势,夏季略有下降,秋季变化不大,冬季是气温上升最明显的季节;日降水量与径流量存在正相关关系,且日降水量与降水第二日的径流量相关显著。     

基于BCC-CSM2-MR模式CMIP6试验的辽河流域气温降水模拟与预估

基于国家气候中心中等分辨率模式版本BCC-CSM2-MR开展的第六次耦合模式比较计划(CMIP6)模拟结果, 首先利用辽河流域80个气象站点观测资料对模式的性能进行了评估, 然后分析了未来不同共享社会经济路径(SSP)情景下的气温降水变化趋势。结果表明: 模式能较好的模拟气温和降水的月、季、年变化, 模拟的气温较观测气温偏低, 模拟的降水略偏多; 模式对秋季和冬季气温的模拟性能明显优于夏季和春季, 对夏季降水的模拟性能较好。模式较好地模拟了辽河流域气温南高北低的纬向分布以及降水自东南向西北逐渐减少的空间分布形势, 较好地模拟出辽河流域冷暖中心位置, 模拟的降水偏少地区位于辽河流域水系稀疏地区。相对于基准期(1995—2014年), 未来辽河流域气温、降水基本呈增加趋势, 未来不同时期不同情景气温增幅均表现为平均最低气温>平均气温>平均最高气温, 冬季和春季增温幅度较大, 夏季降水量增幅最显著。随着排放情景升高, 平均气温和平均最低(最高)气温增幅持续增大, 显著增温地区集中于辽河流域东北部。SSP1-2.6和SSP2-4.5情景下预估降水的增幅自西南向东北递减, 降水增加大值区位于辽宁西部; SSP3-7.0和SSP5-8.5情景下降水增幅自西向东逐渐递减, 降水增幅显著区域位于辽河流域上游的内蒙古和辽宁西部。     

IPCC AR4多模式对海河流域气候模拟能力的评估及预估

根据海河流域1961-2010年气象观测资料,检验IPCC AR4中全球气候模式和多模式集合的模拟能力,并预估未来2011-2050年气候变化的可能趋势,结果表明:全球气候模式以及多模式集合对海河流域都具有一定的模拟能力,其中MIUB_ECHO_G模式和多模式集合具有相对较好的模拟能力.海河流域气温和降水未来情景预估表明:气温整体呈现增加趋势,尤其是A1B情景下各模式的年升温率均高于全国水平;未来降水也呈现增加趋势,在A1B和B1情景下,各模式都为夏季降水增加显著.A2情景下,春季时各模式降水均增加显著,A1B情景下,MIUB_ECHO_G模式模拟在2013年出现突变,降水量出现显著增长,A2情景下,MIUB_ECHO_G模式和多模式集合模拟的降水量则是在2031年和2001年出现突变,出现显著增长.     

怒江跨境径流量变化与云南气候变化的相关特征

利用以云南纵向岭谷区怒江流域历年逐月径流量观测资料和云南同期逐月雨量场和气温场观测资料,应用相关分析方法,研究了云南纵向岭谷区怒江跨境径流量变化与云南雨量场和气温场变化的相关特征。结果表明,在纵向岭谷区,怒江跨境径流量变化与云南雨量场变化的相关总体很显著,其中以春季最好,夏季次之,再次之是秋季,冬季的相关不显著。怒江跨境径流量变化与云南气温场变化的负相关不显著,其中以春季较好,夏季次之,秋季和冬季的负相关不显著,相反在25°N以南,与气温的正相关却较为显著,其中秋冬季较好,春夏季不显著。怒江跨境径流量的变化主要依赖于降水量的变化,气温变化的影响相对较小。     

帕米尔高原东部径流量变化及其对气候变化的响应

水资源是制约中国西北干旱区社会经济可持续发展和生态安全的关键因素。以发源于帕米尔高原东部的喀什噶尔河和叶尔羌河流域为研究区,基于该区6个气象站月平均气温和降水量观测资料,以及5条代表性河流的出山口水文站1950年代晚期以来的月径流量观测数据,分析了该区域气候和水文年际变化特征,以及气候变化背景下径流量的响应特征。结果发现：(1)研究区降水、气温都呈显著上升趋势,除盖孜河外,所有河流径流量均呈显著上升趋势。河流径流量的年内分布和年际变化特征反映了各河流径流主要补给来源的差异。(2)帕米尔高原东部河流出山口径流量受到气温和降水的共同影响,其中以冰川补给为主的叶尔羌河、库山河和盖孜河年径流量与当年夏季（6—8月）气温显著正相关（P<0.001);以降水和积雪补给为主的提孜那甫河和克孜河年径流量与上年7月至当年6月降水量显著正相关（P<0.001)。(3)随着气温升高和降水量增加,流域的蒸发加剧,帕米尔高原东部河流径流量对气候变化的响应出现了明显的变化：年径流量与夏季气温的正相关关系减弱,与上年7月至当年6月降水量正相关增强。     

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