广西旅游气候舒适度分析

通过对广西各大旅游区历年的气候资料进行计算和分析，得出这些旅游区最适宜旅游期和不适宜期，为人们在广西旅游活动提供参考。     

气候变化对海南岛旅游气候舒适度及客流量可能影响的分析

选取温度、湿度、日照、降水、风速等相关的气象要素,建立表征海南岛旅游气候的舒适度的旅游气候指数计算模型,利用1981—2010年海南岛气候数据和RCP4.5情景下的预估数据,分析1981—2010年、2011—2040年、2041—2070年海南岛旅游气候指数的空间分布规律。结果表明:表征海南岛旅游气候舒适度的旅游气候指数在不同月份发生明显变化;2011—2040年、2041—2070年海南岛旅游气候指数在温度和降水增加的情况下,与1981—2010年平均水平相比,1月适合旅游活动的舒适水平提高,TCI指数大于70的分布范围增加;在4、7、10月,适合旅游活动的舒适水平降低,TCI指数小于59的分布范围增加。同时选取吸引指数和旅游气候指数,选择海南岛5个旅游客流量较大的海口、三亚、万宁、儋州、五指山,建立海南岛气候-旅游流模型;利用RCP4.5预估数据,在假定旅游吸引指数不改变的情况下,以海南岛的热点城市海口、三亚为例,分析了气候变化情景下旅游气候指数的变化对各月客流量的影响情况,结果表明:随着旅游气候指数的减小将导致该月接待过夜游客数量呈下降趋势。     

广西旅游气候舒适度分析

通过对广西各大旅游区历年的气候资料进行计算和分析,得出这些旅游区最适宜旅游期和不适宜期,为人们在广西旅游活动提供参考。     

长岛县旅游气候舒适度分析

气候舒适度是影响一个地区旅游资源开发和发展以及旅游季节游客数量的重要因素。利用长岛国家基本气象站1986—2015年的气温、降水、风速、相对湿度和日照时数等与旅游气候舒适度相关的气象观测资料,对山东省烟台市长岛县气候舒适度进行研究计算,划分出长岛适宜于旅游的季节分布;结合2011—2015年长岛县游客的月统计资料,分析研究长岛旅游气候舒适度与游客数量之间对应关系。结果表明:长岛县5—10月均较适宜旅游,其中最佳旅游时间段为6—9月,其他月份气候舒适度等级较低,基本不适合旅游。旅游游客数量与气候舒适度密切相关,综合气候舒适度指数每变化一个单位,长岛县游客数量月指数增加2.098个百分点。     

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。     

汉中地区旅游气候舒适度评价

利用1981—2010年汉中地区11县(区)气温、风速、相对湿度、日照时数等气象要素的月平均值资料,采用温湿指数、风效指数、着衣指数及由3指数组成的综合气候舒适度指数,对汉中各区县全年各月的旅游气候舒适度进行了分析评价,结果显示:留坝、佛坪等北部山区旅游舒适期在4—9月,宁强、镇巴及略阳等南部、西部山区全年旅游舒适期多在4—6月及9—10月,汉台、勉县、南郑、城固、洋县以及西乡等平川地区的旅游舒适期在4、5、9、10月,全年旅游不舒适期较短,留坝为2个月,佛坪仅1个月,其它区域无旅游不舒适期;汉中各地区旅游气候舒适度差异较明显,南部及西部山区气候舒适度较高,其余地区气候舒适性相对较低;汉中各地区四季的气候舒适度以春、秋季最高,而留坝和佛坪等北部山区则表现为夏季最高,冬季均表现为最低;汉中地区旅游气候舒适度划分为北部山区、平川区、南部及西部山区3个区域。     

固原地区旅游气候舒适度分析

利用固原地区6个县区站1986—2017年气温、湿度、云量、风速和降水等常规资料,采用人体舒适度气象指数(BCMI)和度假气候指数(HCI),对固原地区的旅游气候舒适度进行分析评价。结果表明:固原地区BCMI为4~6级的时期全年至少有5个月,总日数为153d,为2类气候适宜区。其中彭阳BCMI为4~6级的时期全年有6个月,总日数为183d,属于1类气候适宜区;西吉、泾源、隆德和原州区BCMI为4~6级的时期全年有5个月,总日数为153d,属于2类气候适宜区。从BCMI来看,在5—9月来固原地区旅游度假是最为舒适时期,且6—8月BCMI均在5级以下,说明固原地区盛夏舒适,适宜避暑。从HCI来看,固原地区全年适宜出行旅游,其中4—5月和9—10月属于"适宜"旅游,6—8月属于"很适宜"旅游;就固原地区而言,BCMI相对HCI能更好表征出固原地区的气候舒适度;5—9月是最适宜来固原地区度假旅游的时期。     

龙川县旅游气候舒适度分析

依据龙川县气象局1981～2010年的气象资料对龙川县的气候特征进行分析,利用舒适度公式得出龙川县人体舒适度气候指数,结合龙川县得天独厚的旅游资源,分析出龙川县各旅游区最适合旅游的时间。     

延安旅游气候舒适度和旅游前景分析

利用延安市12县区1981-2018年气象观测资料,计算温湿指数、风效指数和综合舒适指数,分析延安旅游气候舒适度,得出以下结论:延安市舒适旅游期持续时间较长,5-9月是延安市的最适宜旅游期,是开展乡村游、避暑游的最佳时期;4月和10月是较适宜旅游的时期。冬季室外环境温度低,湿度小,开展传统教育和红色旅游时要注重保暖。     

旅游气候舒适度指数比较分析

以贵阳市1961—2008年48 a气候统计资料,计算国内外常用的旅游气候舒适度指数,对各指数的评价结果进行比较分析。结果表明:各气候舒适度指数的评价结果差异很大,产生差异的原因是评价指数本身决定的。     

西江流域旅游气候舒适度的时空变化特征分析

采用人体舒适度指数分析方法,大样本利用西江流域13个主要旅游市（县）1961—2010年的气象站观测资料,统计分析了西江流域旅游气候舒适度的时空变化特征。结果表明：西江流域年舒适日数具有西部多于东部,山区多于河谷、平原的地域分布特点。西江流域北部多数市（县）适宜旅游的月份是3-5月、9-11月,南部多数市（县）适宜旅游的月份是3-5月、9-12月或10-12月。1961—2010年,西江流域冷不舒适日数均呈减少趋势,多数市（县）热不舒适日数呈增加趋势;北部多数市（县）年舒适日数呈显著增加趋势,南部部分市（县）,如靖西、梧州、大新等地年舒适日数呈现增加趋势,而桂平、南宁、上思等地则呈现减少趋势。     

A weather-resolving index for assessing the impact of climate change on tourism related climate resources

This study develops and tests a Modified Climate Index for Tourism (MCIT) utilizing more than 50 years of hourly temperature, wind and significant weather data from contrasting climatic regions, Florida and Alaska. The index measures climate as a tourism resource by combining several tourism-related climate elements. It improves previous methods by incorporating variables that are more relevant to tourism activities, by addressing the overriding nature of some conditions, and by incorporating hourly observations rather than simple daily averages. The MCIT was tested using hourly weather observations from King Salmon, Alaska and Orlando, Florida. The results show that average temperature alone is not sufficient to represent tourism climate resources. For example, at both the Florida and Alaskan sites, showers and thunderstorms are more limiting factors than temperature during much of the year. When applied to past climate data, the proposed MCIT generates meaningful results that capture tourism-related climate variations and trends, including (a) the increasingly favorable tourism conditions in Alaska due to a lengthening of the warm season and (b) a decrease of ideal climatic conditions in central Florida due to the increased summer temperatures. Thus, the index has the potential to become a useful quantitative tool to be used in conjunction with climate models to predict the nature and magnitude of the impact of anticipated climate changes on tourism.     

贵州山地高分辨旅游气象舒适度时空分布特征

采用空间曲面插值方法,对省内气象台站相关气象数据进行空间插值,得到高分辨的气候要素空间分布栅格数据。然后以贵州省旅游气象舒适度标准(DB52/T556-2009)作为区划标准,对上述栅格数据进行空间分析计算,得到贵州全省四个季节1.0×1.0Km的气象舒适度时空分布。分析表明:贵州省大部分地区的最大气象优势为夏季避暑旅游,此外,还具备了将适宜旅游季节向春季和秋季延伸的有利条件,使贵州的旅游气候资源得到科学准确的定位,为贵州进行"避暑旅游气候品牌"打造提供了科技支撑。     

Counteracting urban climate change: adaptation measures and their effect on thermal comfort

Cities represent thermal load areas compared with their surrounding environments. Due to climate change, summer heat events will increase. Therefore, mitigation and adaptation are needed. In this study, meteorological measurements in various local climate zones were performed to demonstrate the influence of evaporation surfaces and other factors on thermal comfort, as determined by the physiologically equivalent temperature (PET). Furthermore, a quantification of the thermal effects of several adaptation measures and varying meteorological parameters was made using model simulations (ENVI-met) in an inner-city neighborhood (Oberhausen, Germany). The results show that the most effective adaptation measure was increased wind speed (maximal 15 K PET reduction). Moreover, vegetation areas show greater PET reductions by the combination of shading and evapotranspiration than water surfaces. The creation of park areas with sufficient water supply and tall, isolated, shade-providing trees that allow for adequate ventilation can be recommended for planning.     

气候变化对宁波四明山人体舒适度的影响

利用宁波四明山区域气象观测站逐日和逐小时气象要素观测资料,分析该区域气候条件,并以舒适度指标等评估其气候生态。结果表明,1961—2017年四明山区域气温持续上升,降水增多,日降水峰值集中在16—18时且未出现明显变化,小风日数增多,气候适宜日数明显增加。气温是影响该区域人体舒适度的主因,其次是相对湿度和风;春秋舒适日数多,气候温润,日晴夜雨特征明显;夏季凉爽,是理想的避暑休闲胜地;年舒适时数高山与平原相近,但季节差异明显,夏季高山地区非常舒适,其他三季平原更舒适。区域气候模式结果显示,未来四明山区域气温继续维持升高趋势,降水有所增加,极端高温事件增多,极端低温事件减少,人体舒适日数呈减少趋势,春、秋季略增加,夏季减少明显。     

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.     

Costing the impact of climate change on tourism in Europe: results of the PESETA project

Climate change might lead to large shifts in tourist flows, with large economic implications. This article simulates the effect of future climate change by the 2080s on outdoor international tourism expenditure within Europe. The assessment is based on the statistical relationship between bed nights and a climate-related index of human comfort, after accounting for other determinants of bed nights such as income and prices. It is concluded that climate change could have significant impacts on the regional distribution of the physical resources supporting tourism in Europe. For example, in summer, Southern Europe could experience climate conditions that are less favourable to tourism than the current climate, while countries in the North could enjoy better conditions. The economic effects of these changes are likely to be sizeable, albeit difficult to assess. Crucially, they are shown to depend on tourists’ temporal flexibility with respect to holiday planning. The greater the prominence of institutional rigidities such as school holidays, the larger the differences between winning and losing regions in terms of economic impact.     

Determinants of corporate adaptation to climate change in winter tourism: An econometric analysis

While corporate adaptation strategies in response to climate change have been characterized, the determinants of adaptation have not been comprehensively analyzed. Knowledge of these determinants is particularly useful for policy makers to provide favorable conditions in support of corporate adaptation measures. Based on unique data from a survey of Swiss ski lift operators, this paper empirically examines such determinants at the business level. Our econometric analysis with linear regression and count data models finds a positive influence of the awareness of possible climate change effects on the scope of corporate adaptation. Surprisingly, no significant influence of the vulnerability to climate change effects on the scope of adaptation could be found. Finally, the dependency on the affected business and the ability to adapt influence the specific strategic directions of corporate adaptation.