近50年乌鲁木齐市太阳能资源时空变化分析

利用新疆乌鲁木齐地区9个气象站1961-2010年的逐日日照时数资料和乌鲁木齐站逐日太阳总辐射资料,在使用气候学方法估算出各站逐月太阳总辐射的基础上,采用线性趋势分析和Mann Kendall检测对全市冬、春、夏、秋四季和年日照时数、太阳总辐射变化趋势以及突变特征进行分析,应用混合插值法,在ArcGis平台上完成基于数字高程模型(DEM)数据的四季和年日照时数、太阳总辐射及其突变前后变化量的精细化分布式模拟.结果表明:乌鲁木齐市春、夏、秋季和年的日照时数及太阳总辐射总体呈现“平原多,山区少”的空间分布格局,冬季日照时数、太阳总辐射呈现“山区多,平原少”的分布特点.近50年来,乌鲁木齐市春、夏季日照时数、太阳总辐射变化趋势不显著,但秋、冬季和年的日照时数及太阳总辐射呈显著的减少趋势,并于1981和1991年分别发生了突变性的减少,突变前后秋、冬季和年日照时数、太阳总辐射的变化具有明显的区域性差异,减少幅度的空间分布总体呈现“平原多,山区少”的特点.     

近50年甘肃日照时数时空变化特征及突变分析

利用甘肃省26个气象站1961—2010年逐月日照时数资料,采用线性趋势分析、异常年份分析、Mann-Kendall和功率谱等方法,分析了日照时数的时空变化及突变特征.结果表明:50年来,甘肃年日照时数表现为缓慢的下降趋势,气候倾向率为-0.29 h·(10 a)^-1,1997年以来显著减少;夏、冬季日照时数呈下降趋势,春、秋季则呈增加趋势;年日照时数异常偏少年份主要出现在20世纪80年代,而异常偏多的年份多发生在20世纪90年代至今;甘肃年日照时数空间差异明显,分布趋势基本上呈由东南向西北逐渐增多形势.Mann-Kendall和Yamamoto突变检验表明,四季日照时数未发生显著突变.周期分析表明,甘肃年日照时数存在2 a的振荡周期,通过了90%置信度检验.     

1965—2015年广东省日照时数时空变化特征

基于广东省86个国家气象观测站1965—2015年逐月日照时数资料,利用趋势分析和M-K突变检验等方法,对全省多年平均年、季日照时数的空间分布特征和时间变化规律进行研究。结果表明:(1)年日照时数的大值区位于沿海地区,小值区则位于粤北地区。(2)4个季节日照时数均呈下降趋势,秋季下降最明显,其次是夏季,显著下降的区域主要位于珠三角地区。(3)年平均日照时数在1977年左右发生突变。春、夏季日照时数突变分别发生在1997、1992年,冬季突变发生在2008年,但趋势并不明显。     

近58年福泉日照时数变化特征分析

本文利用福泉市气象站1961-2018年的日照时数数据,应用线性趋势发、M-K突变分析法,对福泉市日照资料序列进行分析,结果表明：近58年福泉市年日照时数呈现减少的趋势,突变出现2000年。月分布上只有2月是增加的趋势,其余月份日照时数呈现减少的趋势。     

近58 a福泉日照时数变化特征分析

该文利用福泉市气象站1961—2018年的日照时数数据,应用线性趋势法、M-K突变分析法,对福泉市日照资料序列进行分析,结果表明:近58 a福泉市年日照时数呈现减少的趋势,突变出现2000年。月分布上只有2月是增加的趋势,其余月份日照时数呈现减少的趋势。     

新疆哈密地区近54a日照时数的均一性分析及其影响因素

以新疆哈密地区1961-2014年6个气象观测站地面气象观测资料为依据,利用线性趋势分析、相关性分析、M-K突变检验分析等方法,对哈密地区近54a四季及年平均日照时数的变化趋势、异常年份、突变检验及影响因子进行分析,得出以下结论：近54a哈密地区春季与年平均日照时数均呈上升趋势,而夏、秋、冬季变化比较平稳;年日照时数异常偏少出现在1998年,但从未出现过异常偏多年;年日照时数在1973年和2008年发生两次突变,减少、增加趋势不显著;年、春季日照时数增加与低云量的减少关系密切。     

湘西自治州日照气候特征及影响因素分析

应用线性分析,小波分析、M-K突变检验等方法对湘西自治州1960-2013年各县（市）日照时数地域分布特征、年变化特征进行分析。结果表明：湘西自治州近54a年均日照时数总体呈减少趋势,但只有个别站表现较为明显。年日照时数从地域分布来看,总体东南多西北少,但在不同的月份有不同的特征,与省内同纬度台站比较,湘西自治州各地日照时数在冬半年偏少明显;各县（市）年日照时数存在较为明显准2a、准5a、准16a、准28a时间特征尺度;M-k突变检验,总体平均值在1970s后期存在一次明显的突变,但个别县（市）部分站突变不明显;湘西自治州日照时数各季节的变化与控制本地天气系统的季节变化有较好的相关性。     

1959—2014年略阳县气候变化趋势分析

利用略阳国家基准气候站1959—2014年逐月气温、降水、日照时数、风速资料,采用线性趋势法、Mann\|Kendall突变检验法,分析了略阳县近56年气候变化特征。结果表明:1959年以来略阳县气候变暖趋势显著,年平均气温的线性趋势率为015 ℃/10 a,并在1994年发生突变,突变后气温显著上升;年降水量呈减少趋势,但不显著,20世纪70年代中期到80年代末降水偏多,90年代初降水开始持续减少;年日照时数也呈现减少趋势;年均风速为减小趋势,其中70年代年均风速均高于多年平均值;年降水量、年日照时数和平均风速均未发生明显突变。近56年略阳县气候存在“暖干化”趋势。

     

1961—2010年松花江流域实际蒸散发时空变化及影响要素分析

采用1961—2010年松花江流域60个气象站逐日资料,基于平流-干旱模型(AA模型)计算并分析了流域实际蒸散发时空变化特征,采用相关分析方法研究了影响实际蒸散发变化的主要气象要素。结果表明,1961—2010年,松花江流域年均实际蒸散发为420.8 mn,总体呈现增加趋势,增加速率为4.9 mm/10a,呈"减-增-减-增"年代际波动变化。季节上,春、冬两季实际蒸散发增加趋势较明显,夏、秋两季则呈现与年实际蒸散发类似的年代际波动。春、夏、秋三季和年实际蒸散发的空间分布特征基本一致,高值主要出现在流域南部,低值区主要分布在流域西部。冬季绝大部分区域的实际蒸散发呈现微弱上升趋势。1961-2010年,松花江流域年和四季的平均气温、最高气温和最低气温都呈上升趋势,其中平均气温和最低气温上升显著,日照时数和风速大都呈现显著下降趋势。相关分析结果表明,松花江流域实际蒸散发的时空变化是各气象要素共同影响的结果,而且各气象要素在不同时期对实际蒸散发的影响是有差异的。总体上看,松花江流域实际蒸散发的增加主要是由平均气温,特别是最低气温的增加引起,特别在春、冬季体现得较为明显。夏、秋季节,影响实际蒸散发的要素包括气温日较差、实际水汽压、平均风速及降水量等气象要素,但夏、秋季节这些要素的多年变化趋势不明显,导致夏、秋实际蒸散发的总体变化趋势并不明显。     

1960—2019年遂宁市日照时数的变化特征及影响因素

利用1960—2019年遂宁市3个国家气象站的气象资料,运用线性趋势、M-K检验、小波分析、IDW空间插值等方法分析了遂宁市日照时数的时空变化特征,基于相关分析法找出其影响因子,结果表明：时间变化上,遂宁市日照时数的年、季节变化均呈现减少的趋势,且年变化减少趋势显著,夏季减少幅度为四季中最大,对全年日照时数减少的影响最明显,在1988年日照时数出现了突变,各月日照时数呈现单峰型特征,8月达到峰值;空间分布上,日照时数表现为“南少北多”的特征;日照时数有着明显的17~23 a的周期振荡;影响因子方面,日照时数与总云量和降水日数呈极显著负相关,与降水量呈显著负相关。     

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.     

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.     

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.     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.