安徽大别山区5—8月不同阶段降水时空分布特征

利用2008—2016年中国区域CMORPH（Climate Prediction Center Morphing）多卫星降水数据相融合的、分辨率为0.1°×0.1°的逐时降水量数据集，将每年5—8月分为梅雨前（5月1日至入梅前1日）、梅雨期（入梅当日至出梅当日）和梅雨后（出梅次日至8月31日），分析了大别山区梅雨季节降水的时间和空间演变趋势。大别山区梅雨期间年平均降水量360.3 mm，梅雨前平均降水量279.7 mm，梅雨后平均降水量287.0 mm。梅雨季节主要存在3个降水大值区：山区北侧中段、主峰东南侧和西南侧。从日变化情况来看，梅雨期降水日变化呈现双峰特征，出现峰值的时间分别是09:00、16:00。梅雨前、梅雨后降水日变化呈单峰特征。强降水出现频率的空间分布大值区也随着梅雨前—梅雨期—梅雨后的时间变化逐渐北抬。     

京津冀地区暖季降水日变化特征分析

使用2007—2017年京津冀地区156个气象站暖季（5—9月）逐小时降水观测数据,根据地形将研究区域分为6个分区,分析各分区降水量季节内变化和日变化特征,结果表明：1）京津冀的多雨区主要位于沿燕山南麓到太行山,存在多个降雨中心。2）各分区降水量季节内特征总体表现为单峰型,即7月降水量最大,7月第3候至8月第4候是主汛期,8月降水量次之,5月最少。3）降水呈夜间多,白天少的特点,7月初之前的前汛期降水多发生在16—21时;主汛期降水呈双峰型,峰值在17—22时,次峰值出现在00—07时;8月中旬以后的后汛期多夜间降水,峰值多出现在00—08时。4）高原山区多短历时降水,长历时累计降水对季节降水贡献率大值区位于平原地区,而持续性降水贡献率大值位于太行山区和燕山迎风坡的西部。     

基于CLDAS的贺兰山区5—9月降水时空分布特征及其与地形的关系分析

利用2008—2016年5—9月中国气象局陆面数据同化系统(CLDAS)格点融合分析降水资料以及降水观测资料,在对CLDAS格点降水融合资料进行验证的基础上,对贺兰山区降水时空分布特征以及与地形的关系进行了分析。结果表明：贺兰山区降水呈“东多西少、南多北少”的分布特征,贺兰山主峰偏西0.1°存在一个超过240 mm的降水高值中心,日降水量极值西侧高于东侧。8月降水量和短时强降水次数最多,11:00—18:00降水次数最多,午后到前半夜短时强降水次数最多。贺兰山区降水以小雨为主,其次是中雨,中雨和小雨雨量占区域总雨量的比例高达85%。贺兰山区降水量随海拔高度的增加而增加,西坡降水随高度的增加率为5.1 mm/hm,东坡降水随高度的增加率为2.1 mm/hm,西坡明显高于东坡。中雨日数与地形高度的相关性较好,其它级别降雨日数与地形相关性不强。     

北京地区自动站降水特征的聚类分析

利用2007—2010年北京123个自动气象站逐时降水观测资料,采用聚类分析方法,对北京的主城区、西部和北部区、东北区、东南区共分为4个区域的逐时降水时空分布特征进行了分析。结果表明:通过与实际地形和下垫面类型比较,自动站分类较为合理,避免了在区域划分方面的主观因素影响。主城区降水集中时段最为突出,集中出现在7月逐日20—00时,且降水强度最强,降水量较大,降水小时数不多。西部和北部区降水集中出现在6月逐日18—20时、7月逐日23时至次日03时,降水小时数最多,降水强度不大,降水量不大。东北区降水主要集中出现在7月逐日00—08时和17—23时,降水小时数较多,降水强度不大,降水量最大;东南区降水主要集中出现在7月的逐日02—04时,降水小时数少,降水强度较大,降水量较大。     

新疆夏季降水日变化特征

利用1991-2014年新疆16个国家基准气象站逐时降水资料,分析了新疆夏季不同区域降水日变化基本特征,揭示出新疆夏季降水日变化呈现显著的南、北疆区域差异,有别于我国中东部的一些新事实。结果显示:北疆降水量日变化呈现准单峰型特征,峰值主要发生在傍晚前后（16:00-20:00,地方时,下同）;南疆降水量日变化呈现三峰特征,峰值分别出现在傍晚（17:00-18:00）、午夜后（00:00-01:00）和上午（10:00）。新疆夏季降水事件以6 h以内的短历时性质为主（平均为85%,比例明显高于我国中东部）,而持续12 h以上的较长历时降水事件偶有发生;在天山东麓以外的新疆绝大部分地区,6 h以内短历时降水事件对总降水量的贡献率达54%,高于我国中东部地区。新疆西部和北疆北部降水量日变化主峰的贡献者是2~3 h短持续性降水为主的事件;而天山中-东部降水量日变化峰值则是来自于12 h内各不同持续时间降水事件的大致均等贡献。     

运城市降水集中度和集中期的时空特征分析

利用运城市9个气象站1960—2014年逐候降水资料,运用线性趋势、MannKendall曲线、相关系数和合成分析等方法探讨了运城市近55 a来年降水量、降水集中度(PCD)和集中期(PCP)的时空特征。结果表明:时间上,年降水量呈减少趋势,变化倾向率为-7.94 mm/10 a;PCD年际变化显著,在0.30~0.72,多年平均为0.53;PCP多年平均41.63候,最早与最晚相差13候。空间上,年降水量区域差异明显,由东南向西北递减;PCD从西南向东北递增,有2个大值和2个小值中心,PCP呈现"南早北晚"形势。PCD、PCP与年降水量、汛期降水量、月最大降水量、候最大降水量和日最大降水量之间都存在正相关,表明汛期降水量、月最大降水量、候最大降水量和日最大降水量越大的年份,PCD值就越大,降水就越集中,出现洪涝灾害的可能性就越大;降水集中期出现的越晚。     

三穗汛期强降水特征及地形影响分析

该文利用2010—2020年三穗县9个乡镇气象观测站降水资料,结合地形特征,运用对比分析方法,探讨三穗强降水天气时空分布特征与地形的关系。结果表明:5—9月是三穗强降水高发期,占全年强降水总次数的86.7%;在汛期相同环境条件下,由于三穗地形四周高、中心低,强降水大值中心分布在台烈—良上等偏西偏南一带,与三穗南高北低、西高东低的地形基本吻合,且降水不同量级日数分布与地形分布存在一致性,均呈现南部多于北部。另外,雨带多从偏西北、偏西、西南等方向进入并影响三穗,但受地形的影响降水呈不同的分布,尤其西南部地势较高并处于迎风坡,交汇气流在此停留时间较长,导致该处更容易出现强降水天气过程,且降水量往往更大。     

近50年黄河上游流域年均降水与极端降水变化分析

利用1970-2017年45个气象台站逐日降水资料分析了黄河上游流域降水空间分布规律以及年均降水和极端降水的变化趋势,将黄河上游流域按照地形地势、海拔、气候带分布等多种因素划分成源头区、产流区、出口区,并结合极端降水指数采用Mann-Kendall法、小波分析法分析了不同时间尺度下降水序列变化的周期和突变点,研究极端降水时空变化。结果表明,黄河上游流域年均降水从东南向西北扇形递减,源头区和产流区是年降水量的主要贡献区域;年均降水和极端降水均存在明显的周期振荡特征,其中源头区和产流区在22年左右,出口区在18年和8年左右;整个上游区域,极端降水和年均降水的变化趋势较为一致,但年降水量近年来呈现增长趋势,而极端降水事件的发生频率则有所降低。     

2012—2018西藏“雨窝”降水特征及其成因分析

本文采用2012—2018年西藏74个气象站的降水资料,以及墨脱站小时、日、月、季、年的降水资料,对西藏的降水日数、累计降水量、强降水的空间分布进行了分析,结果表明:(1)墨脱是西藏降水日数最多、累计降水量最大的中心,也是出现极端强降水概率最高的区域。(2)墨脱的降水主要集中在3—10月,降水呈现双峰型,峰值分别出现在6月和9月,其中9月的降水量跟年降水量有很好的相关性。(3)墨脱出现暴雨次数最多的是5、8、9月,其中5月的暴雨日数突增,与8、9月的暴雨日数相当。(4)墨脱干湿季分明,多夜雨,凌晨03:00—07:00出现降雨的概率达到50%以上。墨脱位于西藏的最南端,海拔从最低的115m上升到1200m,印度洋的湿润气流沿着雅鲁藏布河谷长驱直入,在地形抬升作用下,使得墨脱的降水量堪比同纬度的内地沿海城市,因此墨脱为西藏的"雨窝"。     

云南雨季和干季小时降水的时空特性分析

利用云南省2325个国家级台站和区域自动观测站逐小时降水数据,分析了2014~2018年云南雨季和干季的降水量、降水频次和降水强度的空间分布特征以及关键区域的降水日变化演变特征。结果表明:受复杂地形影响,云南不同区域降水特征差异显著,且与我国东部地区显著不同。年均降水量大体呈西南高、西北低的分布特征。对于云南西北部的怒江河谷地区,干、雨季降水均为夜间峰值,降水频次高,但强度较弱。对于云南最西部（99°E以西）的保山德宏地区,该地区累计降水量为云南最大,这一区域各台站日变化峰值均较为一致地出现在上午,在陆地地区较为少见。相邻的普洱和元江河谷位于云南南部（23°N以南）,雨季两区域降水相当,但元江河谷在干季与雨季均为突出的夜间至清晨降水峰值,普洱地区雨季则是明显的午后降水峰值。云南中部地区降水量较周边地区明显偏小,该地区降水频次在雨季主要表现为清晨峰值,而在干季却是午后峰值更为突出,这也与我国东部地区降水日变化特征差异明显。      

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.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

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     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

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.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.