1954-2013年湖北省黄石市极值气温变化特征分析

利用黄石市气象台1954年1月1日至2013年12月31日共60a的地面观测资料,选取逐日的平均气温、最高气温和最低气温做为研究对象,采用气候趋势分析、相关分析、Mann-Kendall突变检验分析和小波分析等方法对黄石市极值气温变化特征进行分析,结果表明:(1)1954-2013黄石市年平均气温、平均最高气温和平均最低气温呈波动上升的趋势,其中年平均气温和平均最低气温上升趋势显著,对于近60a黄石市年平均气温的升高,年平均最低气温的贡献是主要的;(2)近60a黄石市极端最高气温和极端最低气温均呈波动上升的趋势,其中极端最低气温上升趋势显著,1984-2013年极端最低气温的升高是造成近60年极端最低气温显著升高的主要原因;(3)近60a黄石市年最大日较差呈波动下降的趋势,但不显著,平均最低气温的上升速度明显大于平均最高气温的上升速度,极端最低气温的上升速度明显大于极端最高气温的上升速度,这造成了气温日较差的不断减小;(4)近60a黄石市气温(年平均气温、年最高\最低气温、极端最高\最低气温)的显著升高,与最高气温出现在20℃以上的天数增加和出现在20℃以下的天数减少有关,与最低气温出现在10℃以上的天数增加和出现在10℃以下的天数减少有关,其中T0℃的高温日数和低温日数的显著减少以及20≤T30℃的低温日数的显著增加贡献最大。     

中国北极村气候变暖特征

利用我国最北部的北极村气象站1963～2005年气温资料,通过计算气候倾向率和气候趋势系数,对该地区气候变化特点进行了分析。结果表明,43年来北极村气温有明显并稳定的上升趋势,年平均气温以每10年0．46℃幅度升高。各季及逐月平均气温都存在不同程度的变暖趋势,但是冬季升温最为剧烈,达每10年0．69℃,其中2月升温幅度为每10年1．02℃,为全年最大。秋季升温最弱,仅为每10年0．21℃。年平均最低气温（每10年0．59℃）和年极端最低气温（每10年0．74℃）比年平均最高气温（每10年0．37℃）和年极端最高气温（每10年0．27℃）升温幅度明显偏大。最低气温比最高气温对平均气温的年代际升温趋势贡献更为明显。     

聊城地区极端气温变化特征分析

选用1958—2009年聊城市3个国家气象站逐月极端最高气温和极端最低气温资料,采用累积距平、趋势系数方法,分析了聊城地区极端最高、最低气温变化的特征,得出：52a来聊城年极端最高气温变化趋势分为一个升温阶段和一个降温阶段,总体呈下降趋势,趋势系数为-0.3383。年极端最低气温变化趋势分为3个降温阶段和2个升温阶段,总体呈上升趋势,趋势系数为0.1849。极值年较差在减小;各季极端最高、极端最低气温呈非对称性变化。秋季各地极端最高气温增温幅度超过极端最低气温。春、夏、冬季极端最低气温增温而极端最高气温降温,且该特点在夏季表现得更突出;月极端气温变化范围在减小,极端温度变化趋于缓和,特别是进入21世纪,月极端最低和最高气温较20世纪90年代平均分别上升了1.6℃,1.1℃。     

商丘市气温日较差变化特征分析

利用商丘市8站1961-2006年逐日最高、最低气温资料,计算并分析了商丘市年、季及月气温日较差的线性变化趋势,结果表明:年最低气温呈明显上升趋势,最高气温上升趋势不显著,气温日较差呈显著减小趋势;春、夏、冬季季平均气温日较差均呈减小趋势,其中春季和冬季的减小趋势显著,秋季呈弱的增加趋势;全年有10个月的气温日较差呈减小趋势,其中1、3、5、8月气温日较差显著减小,1月减小幅度最大.城市化发展对气温日较差变化有一定影响,距城区较近的台站平均气温日较差显著减小,而距城区较远的台站气温日较差减小趋势不显著.     

近60年商洛市气温变化特征分析

利用商洛市7个国家气象站1961—2020年近60 a的日平均气温、月平均气温、月最高气温、月最低气温等资料,选取10种极端气温指数,采用线性趋势分析、Mann-Kendall非参数检验、累积距平法,对商洛平均气温、最高气温、最低气温的年际、年代际、季节变化特征,异常性及极端性进行了分析。结果表明：近60 a来商洛年平均气温、平均最高气温、平均最低气温的年际变化呈上升趋势,其中平均最高气温的线性倾向率最大;除平均最低气温冬季线性倾向率呈下降趋势外,平均最低气温的春季、夏季、秋季和年平均气温、平均最高气温四季变化均呈上升趋势,年平均气温、平均最高气温春季线性倾向率最大,平均最低气温夏季线性倾向率最大;季节气温的年代际变化特点为20世纪60—90年代为相对偏冷期,21世纪为相对偏暖期;通过M-K突变检验和累积距平法得出商洛年平均气温发生了由低温到高温的突变,突变时间在1987—1988年;分析平均气温异常性得出偏暖年份多出现在21世纪之后,偏冷年份多出现在20世纪90年代以前,尤其集中在60年代中期左右,秋季偏暖年份最多,春季偏冷年份最多;近60 a极端最高气温有显著的年际变化,暖夜日数呈增多趋势,冷夜日数呈减少趋势,暖昼日数较冷昼日数增多明显,昼指数变化较夜指数变化明显,热指数呈上升趋势,冷指数呈下降趋势,进一步说明商洛呈增温趋势。     

华中区域1960～2005年平均最高、最低气温及气温日较差的变化特征

利用华中区域(河南、湖北、湖南3省)42站1960～2005年逐月平均最高、最低气温资料,计算并详细分析了该区域年(季、月)平均最高、最低气温和气温日较差的线性变化趋势、突变性及周期性特征。结果发现:1)华中区域年平均最高、最低气温均呈现上升趋势,年平均气温日较差呈减小趋势,其中年平均最低气温变化最显著。2)平均最高气温在春、秋、冬均呈上升趋势;平均最低气温四季均呈上升趋势,其中春、冬季变化显著;平均气温日较差在夏、冬季下降趋势较为明显,其中以冬季降幅最大。3)全年有4个月平均最高气温呈下降趋势,其中8月最为显著;平均最低气温在冬、春季为明显上升趋势,其他月变化趋势不显著;平均气温日较差在冬、夏季呈明显下降趋势,其中1月最为显著。4)年平均最高、最低气温在20世纪90年代经历了一次由冷变暖的明显突变;四季中,平均最高气温春、冬季突变显著,平均最低气温春、夏季突变显著。5)年平均最高、最低气温存在显著的2～4a周期变化。     

南京极值温度长期变化及其与平均温度的关系

利用1951—2009年南京日平均气温、日最高气温以及日最低气温等资料,分析了南京日最高气温和最低气温的长期演变趋势及其与平均温度的关系。结果表明：近60 a来,南京年平均气温、年平均最高气温、年平均最低气温均呈变暖趋势,20世纪90年代增温尤为明显;日最高气温,除夏季表现为降温趋势外,其他季节均为升温趋势;而四季平均气温和平均最低气温均为增温趋势;夏季气温日较差下降趋势明显,导致夏季昼夜温差减小;极端高温、低温的发生日数均呈下降趋势。极端气温与平均气温之间存在明显的相关性,且极端低温对平均气温影响更为明显。     

兰州最高最低气温的非对称变化

分析了兰州1932～2002年年平均气温、年平均最高和最低气温及年平均气温日较差的气候变化特征。分析表明：1932年以来，4个气温要素的线性增温率依次为每10年0．14℃、0．06℃、0．38℃、-0．32℃。兰州20世纪40年代最高气温对增暖的贡献大，80年代最低气温对增暖的贡献大，而90年代的异常偏暖表现为最高和最低气温的同时上升。另外，在40年代各季平均最高和最低气温均呈相反的趋势，表现为最高气温的上升和最低气温的下降；在1950～1970年间最高和最低气温的变化趋势和幅度非常接近，但维持时间各季略有不同；80年代以来，最低和最高气温均在上升，但最低气温的增温率明显高于最高气温的增温率。     

西安市65年气温的变化分析

根据西安市1932～1996年的年、夏季（6～8）月、冬季（12～2月）平均气温资料以及1月和7月的历年逐日最高、最低气温资料,研究其总的气温变化趋势、冷暖阶段以及最高、最低气温的非对称变化和年际变化.结果表明：自本世纪30年代开始,西安气温呈上升趋势,至40年代前期达到最高,此后下降,50年代前期降至最低,80年代开始回升,1932～1949年为偏暖阶段,1950～1996年为偏冷阶段;1月的最低气温线性增长率为0.0471℃／a;7月的最高气温以-0.0219℃／a的递减率线性降低,增长率与递减率均低于全国水平,其结果导致西安冬季相对偏冷,夏季相对炎热,日较差呈明显下降趋势。     

宜君县1968—2017年气温变化趋势分析

采用宜君气象站1968—2017年地面观测资料,分析宜君县近50 a年平均气温、季平均气温、月平均气温及年极端最高气温、极端最低气温的气候变化特征。结果表明:宜君县近50 a年平均气温总体呈上升趋势,其线性变化趋势率为0.362℃/10 a,20世纪90年代末(1997年)之前为偏冷期,之后为偏暖期;冬季和春季气温变化显著,夏、秋季变化不明显;年平均最高气温和平均最低气温变化趋势与年平均气温变化趋势一致。     

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.     

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。     

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.     

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

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.     

Our Warmest Thanks to AAS Reviewers 2014

正The editorial office of Advances in Atmospheric Sciences(AAS),on behalf of all AAS editors,would like to publicly acknowledge the people listed below who served as reviewers for the journal daring 1 September 2013 to 24 August 2014.We recognize that the time and work of the reviewers is the most important resource in academic publishing.The quality of our journal depends in a crucial way upon the reviewing process and therefore all reviewers'time and efforts taken to sustain the quality of the journal are greatly appreciated.     

Data selection using support vector regression

Geophysical data sets are growing at an ever-increasing rate, requiring computationally efficient data selection(thinning)methods to preserve essential information. Satellites, such as Wind Sat, provide large data sets for assessing the accuracy and computational efficiency of data selection techniques. A new data thinning technique, based on support vector regression(SVR), is developed and tested. To manage large on-line satellite data streams, observations from Wind Sat are formed into subsets by Voronoi tessellation and then each is thinned by SVR(TSVR). Three experiments are performed. The first confirms the viability of TSVR for a relatively small sample, comparing it to several commonly used data thinning methods(random selection, averaging and Barnes filtering), producing a 10% thinning rate(90% data reduction), low mean absolute errors(MAE) and large correlations with the original data. A second experiment, using a larger dataset, shows TSVR retrievals with MAE < 1 m s-1and correlations 0.98. TSVR was an order of magnitude faster than the commonly used thinning methods. A third experiment applies a two-stage pipeline to TSVR, to accommodate online data. The pipeline subsets reconstruct the wind field with the same accuracy as the second experiment, is an order of magnitude faster than the nonpipeline TSVR. Therefore, pipeline TSVR is two orders of magnitude faster than commonly used thinning methods that ingest the entire data set. This study demonstrates that TSVR pipeline thinning is an accurate and computationally efficient alternative to commonly used data selection techniques.     

Temporal vulnerability in hazardscapes: Flood memory-networks and referentiality along the North Carolina Neuse River (USA)

Social models of population vulnerability to disasters increasingly include the notion that vulnerability has a strong temporal component. While this temporality is typically conceptualized as objective (making vulnerability “dynamic,” “multiscalar,” and/or “historical”), it consistently fails to acknowledge that among stakeholders managing hazardscapes temporality is also a social process in which subjective experience of time may play a role in creating situations of population vulnerability. This paper proposes that the temporal situatedness of a population relative to past hazard events and the quality with which stakeholders engage hazard memory-chains combine to significantly influences its vulnerability to natural hazards. It is proposed that this temporal vulnerability is characterized by shared, population level potential for surprise and can be evaluated by exploration of time-series depth and temporal reference points in historical ecological narratives and documents. Based on ethnohistoric research conducted from 2002 to 2006 in flood-prone eastern North Carolina (USA), it is illustrated how temporal vulnerability was relatively higher in the Neuse River watershed located at the City of Kinston than surrounding watersheds. Due to the combination of factors including the damming of the Neuse River in the 1980s, outdated official floodplain maps, relatively unmonitored floodplain development, the stochastic timing of flood events (placing the last major flood more than a generation away), technological optimism, and turnover of floodplain officials and residents, local stakeholders were seriously misinformed about the space-time risks involved both before and after the disaster of Hurricane Floyd (1999) happened. To deal with this inconsistency, the temporal rarity of Hurricane Floyd as a “500-year event” has been motivated and embraced by many in an effort to continue life-as-is. The paper proposes that the concept of temporal vulnerability is further explored and used as key dimension in the vulnerability sciences.     

An assessment of the predictability of the East Asian Subtropical Westerly Jet based on TIGGE data

The predictability of the position, spatial coverage and intensity of the East Asian subtropical westerly jet(EASWJ) in the summers of 2010 to 2012 was examined for ensemble prediction systems(EPSs) from four representative TIGGE centers,including the ECMWF, the NCEP, the CMA, and the JMA. Results showed that each EPS predicted all EASWJ properties well, while the levels of skill of all EPSs declined as the lead time extended. Overall, improvements from the control to the ensemble mean forecasts for predicting the EASWJ were apparent. For the deterministic forecasts of all EPSs, the prediction of the average axis was better than the prediction of the spatial coverage and intensity of the EASWJ. ECMWF performed best, with a lead of approximately 0.5–1 day in predictability over the second-best EPS for all EASWJ properties throughout the forecast range. For probabilistic forecasts, differences in skills among the different EPSs were more evident in the earlier part of the forecast for the EASWJ axis and spatial coverage, while they departed obviously throughout the forecast range for the intensity. ECMWF led JMA by about 0.5–1 day for the EASWJ axis, and by about 1–2 days for the spatial coverage and intensity at almost all lead times. The largest lead of ECMWF over the relatively worse EPSs, such as NCEP and CMA, was approximately 3–4 days for all EASWJ properties. In summary, ECMWF showed the highest level of skill for predicting the EASWJ, followed by JMA.