近52年新疆主要旅游城市舒适度分析

本文选用新疆16座主要旅游城市1961—2012年的逐日平均气温和水汽压等资料,根据饱和水气压与温度的关系计算出在不同温度下的相对湿度,以学者特吉旺（W.H.Terjung ,1966）[1]提出的舒适度指数和四川省地方标准规定的9级等级划分方法为基础,根据新疆地区独特的的气候特点,对舒适度指数的区段进行重新划分,计算出各个地区的舒适度指数;其次,分析各个地区各年各月的舒适度变化规律,得出如下结果：（1）新疆主要城市的气候舒适度大小在25～75之间,与新疆的气候条件比较吻合;（2）乌鲁木齐1-3月和11-12月比较寒冷,基于温湿指数旅游舒适度指数较低,夏季5-9月凉爽舒适,适宜旅游;（3）吐鲁番以南的城市,适宜旅游的时间多出现在春季的4-5月以及秋季的9-10月,舒适度指数高,有利于发展旅游业;1-2月和12月天气冷或偏冷、6-8月天气炎热,旅游舒适度指数相对较低。吐鲁番5-8月舒适天数虽然相对较少,但是以酷热火焰山著称,也易发展旅游业。（4）南疆地区适宜旅游的时间是4-10月,1-2和12月天气寒冷又干燥,基于温度湿度的旅游舒适度指数较低。（5）16座城市的舒适度比较高的时间集中在4月、5月、9月、10月的春秋两季;（6）新疆的舒适天数正在逐年上升,不舒适天数正在逐年下降;（7）将16座城市舒适度指数的月变化用饼状图标注在新疆地图上,为希望到新疆游玩的旅客提供了时间和地点的选择依据。     

1971—2014年玉门市旅游气候舒适度评价分析

利用玉门市1971—2014年逐日气温、相对湿度、平均风速和日照时数等气象观测资料,运用温湿指数、风寒指数、着衣指数和人体舒适度指数4种旅游气候舒适度评价指数,计算玉门市旅游舒适度指数,确定了玉门市旅游气候舒适期及天数;构建综合舒适度指数模型,并对各指数进行了突变检验。结果表明,玉门市较舒适期为4月下旬中期至9月下旬末,约160 d;舒适期为5月中旬至9月中旬,约124 d。其中,5、6、8月最适宜旅游,7、9月为适宜旅游,11月—次年的3月,由于气候寒冷,不适宜旅游。玉门市的温湿指数舒适期天数从1983年开始明显增多;风寒指数舒适期天数从1990年开始明显增多;着衣指数舒适期天数从1991年开始明显增多;人体舒适度指数舒适期天数从1986年开始明显增多。     

西藏地区人体舒适度指数的变化特征

采用1980～2009年西藏地区38个气象站的观测资料,分析了该地区人体舒适度指数的时空分布特征。结果表明:(1)无论年或者季节变化,舒适度指数均呈现从东南向西北方向逐渐减少的分布规律,普遍舒适的区域主要位于西藏南部和东南部地区;近30a来西藏地区人体舒适度指数呈现显著增加的趋势;舒适度指数与海拔高度、纬度、温度和相对湿度密切相关;(2)从舒适日数来看,西藏地区基本处于冷或偏冷、凉或偏凉的舒适度状态,寒冷和普遍舒适的日数较少;近30a来西藏地区1级和2级不舒适天数呈现逐渐减少趋势,3级、4级不舒适天数和5级舒适天数呈现逐渐增加的趋势;(3)从适合旅游的舒适天数来看,西北部以6～9月为适宜旅游月份,中部以5～9月或10月为适宜旅游月份,过渡到东南部地区以5～9月或10月为适宜旅游月份,甚至可以提前到4月;旅游适宜月份数和天数由北向南呈逐渐增加的趋势。     

1971-2013年敦煌旅游气候舒适度分析与评价

旅游气候舒适度是评价和分析旅游资源的重要指标。为了科学合理评价和利用敦煌的旅游气候资源,本研究利用敦煌市1971 - 2013年逐年逐月逐日气温、相对湿度、平均风速和日照时数等气象观测资料,运用温湿指数(THI)、风寒指数(WCI)、着衣指数(ICL)和人体舒适度指数(K)等四种旅游气候舒适度评价指数,计算敦煌逐年逐月逐日旅游舒适指数,分析敦煌年内气候舒适期起止时间、期间天数;年际、月均变化特点以及各指数舒适期天数年际间是否存在突变等。通过构建综合舒适度指数,结果表明：较适宜旅游季节从4月中旬开始,10月上旬结束;5月、9月最适宜旅游,4月至10月较适宜旅游,这一结果反映了敦煌夏季干燥炎热的沙漠气候特点。四种指数模型计算出的指数年际和月均变化趋势不一致,计算出的较舒适期天数在年际间存在突变现象,敦煌旅游舒适日在年际间呈突变增多的趋势。研究结果为敦煌旅游发展规划和游客选择旅游时间提供了一定的科学依据。     

龙门县旅游气候舒适度分析

根据龙门县国家气象观测站1985—2014年逐月平均气温、相对湿度、风速等资料,以人体舒适度指数为指标,对龙门县旅游气候舒适度进行了分析和评价。结果表明,龙门县适宜旅游的时间集中于1—6月和9—12月,占总数的80%,其中最舒适月份为4和10月,凉舒适为1—3月和11—12月,暧舒适为5—6月和9月;不适宜旅游时间集中于7—8月,占总数的20%。龙门县适宜旅游时间较长。     

丽水市旅游气候舒适度分析

采用人体舒适度气象指数（BCMI）、寒冷指数（CI）、温湿指数（THI）和度假气候指数（HCI）等4个综合性的气候指标,对丽水市的旅游气候舒适度进行了分析评价,并着重对比分析了BCMI和HCI对旅游气候适宜性的表征能力。结果表明：丽水市全年有8个月BCMI处在4～6级之间,属一类气候适宜区;冬季CI值较低,无严寒现象,夏季低海拔地区THI值偏高,但海拔600 m以上地区（约占市域面积6成）THI值较低,适宜“避暑纳凉”;HCI比传统的BCMI表现的更客观、更全面,它不仅考虑了气候的热舒适性影响,还考虑了降水和云量对旅游出行及观光的影响,且就时间尺度而言,HCI更适合旅游舒适度逐日预报的开展。     

宜君县旅游度假气候舒适性分析

基于1956—2020年宜君县地面气象观测站逐日气温、降水、风速、相对湿度、总云量等资料,采用温湿指数、寒冷指数和气候度假指数以及人体舒适度指数,对宜君县的旅游气候舒适性进行定量评估。结果表明：宜君旅游适宜期在3—11月,尤其是5—9月更适宜旅游度假;与省内城市相比,宜君全年舒适及非常舒适的月份有5个月,特别是夏季6月,温湿指数等级为“非常舒适”,夏季月平均舒适日数达304 d,且7—8月月舒适日数均为31 d,多于西安和汉中,优势显著。从旅游气候风险来看,宜君强对流天气、沙尘天气以及霾日数逐年减少,风险低,适宜旅游。     

濮阳市旅游气候舒适度评价

对濮阳市的旅游气候舒适度分析后认为:濮阳市一年中4、5、9、10月的舒适指数在 1～-1(暖-凉)之间,风效指数在-a～-b(暖风-舒适风)之间,这4个月是濮阳市适于旅游的季节,其中10月是最佳旅游季节.旅游优势在于春、秋两季;夏季炎热、冬季寒冷,可充分利用农业生态园区景观和自然生态旅游资源,开展避暑和室内生态旅游等活动.     

甘肃平凉市的旅游气候舒适度评价

利用甘肃省平凉市7县（区）气象观测站1961—2010年50a气象资料,采用温湿指数、风寒指数和着衣指数指标,对平凉7县（区）各月旅游气候舒适度进行了分析。结果显示,平凉市7县（区）旅游气候最舒适期为每年的5～9月,较舒适期在4月和10月,不舒适期静宁、庄浪、华亭为4个月,主要分布在冬季及秋末（1～2月、11—12月）,崆峒、灵台、泾川、崇信为3个月,分布在冬季的1、2、12月。由于地理位置和海拔高度的不同,平凉旅游气候在东西南北方向上有着一定差异,在东西方向上差异尤其明显,一年中舒适度年指数自西向东呈升高趋势。     

1966—2018年秦皇岛气候舒适度时空变化特征

利用1966—2018年气象资料,采用气候舒适度评价及趋势分析方法,对秦皇岛地区近53 a气候舒适度变化进行分析。结果表明：秦皇岛北部山区、中部平原和东南沿海三个区域的气候舒适度变化趋势一致,存在空间差异性。整体上,秦皇岛气候舒适度以舒适至冷凉特征为主,各区域舒适和较舒适等级占47%—49%,冷不舒适等级占34%—37%,炎热及更热不舒适等级极少。近53 a,夏季、冬季气候舒适度均呈增暖趋势,冬季增暖幅度大于夏季。热不舒适日数自20世纪90年代开始激增且持续偏多,寒冷不舒适日数呈逐年代减少态势;在空间上,热不舒适日数随着测站高程和纬度的降低而增多,寒冷不舒适日数与之相反。5—10月气候舒适或较舒适,秦皇岛全域皆为旅游、疗养适宜期;7—8月无酷暑,“微热”的天气为人们提供畅游大海的有利气象条件;3月、4月和11月气候偏冷凉,是户外登山的大好时机;12月至翌年2月寒冷不舒适,不适宜大众旅游疗养,适宜开展冰雪旅游活动。因此,可以认为秦皇岛全域、全季皆适宜旅游,由此为秦皇岛市旅游开发与规划及研究气候变化对旅游业的影响提供依据,为来到“秦皇山海、康养福地”的康养群体提供生活和出游气象服务指导。     

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.