基于MODIS数据的陕西地表温度监测

地表温度是反映土壤—植被—大气系统能量流动与物质交换的重要参数,讨论了利用EO S/M OD IS资料反演地表温度的分裂窗方法各参数获取及其在陕西省的应用;建立了基于M OD IS遥感资料和地面自动气象站观测资料反演地表温度的统计模型。监测试验结果表明:利用分裂窗方法反演陕西地表温度,其中参数设定仍需要做大量工作;统计方法考虑季节差异,在地表状况不太复杂时也能取得较好的监测效果。     

基于MODIS数据的作物苗期干旱监测方法

针对苗期低植被覆盖情况,在原有的归一化植被指数基础上,增加了土壤调节植被指数,将其与条件温度指数结合,通过与地面实测土壤相对湿度进行相关分析,分别建立作物苗期的干旱监测模型,并与热惯量方法和供水植被指数方法进行对比分析,初步得出辽宁省范围内作物苗期进行大范围干旱遥感监测的最适宜模型为土壤调节植被指数一温度模型.     

基于MODIS数据的拉萨市地表温度变化研究

采用2000～2011年6月MODIS地表温度产品和拉萨市4个气象站6月平均地表温度对拉萨市地表温度的时空变化进行了分析.结果表明：拉萨市在近12年内地表温度呈明显上升趋势,2009年地表温度达到最高为28.49℃,最小值出现在2003年为14.12℃.在空间分布上高温区主要集中在城市中心和城市周边区域,并随着时间推移不断向外扩张,在2007年6月拉萨市地表温度高温区分布范围最大,其中纳木错东部和林周县的高温区增加最显著;在利用实测的地表温度与MO-DIS反演的地表温度做相关分析发现,两者的相关系数为0.64通过了0.001的显著性检验,两种地表温度的时间变化趋势也较为一致,因此MODIS地表温度反演产品适用于大范围地表温度和城市热环境监测是可行的.     

基于MODIS数据的金塔绿洲地表温度反演

地表温度(LST)是气象、水文、生态等研究领域中的一个重要参数.本文对MODIS数据的分裂窗算法进行了简要的介绍,并利用MODIS数据计算反演了地表温度所需的关键参数:大气透过率和地表比辐射率,然后运用分裂窗算法反演了金塔绿洲地区的地表温度,并与地面实测数据进行了对比分析.结果表明,这一方法能获得较合理的地表温度,符合金塔绿洲的实际地表状况.     

基于MODIS数据的乌昌地区地表温度反演

陆地表面温度是监测地球资源环境变化的重要指标之一,对于区域干旱预报、作物产量估算、数值天气预报等的研究都有重要意义。本文阐述了MODIS资料反演地表温度的原理,建立了基于MODIS资料、地理信息数据和地面气象站观测资料反演地表温度的统计模型。     

基于MODIS的温度植被干旱指数在四川盆地盛夏干旱监测中的适用性研究

基于卫星资料的温度植被干旱指数(TVDI)已被广泛应用于干旱监测,地表温度依赖于海拔高度,在地形复杂的四川省,如何将该指数更好的应用到业务干旱监测中,需进一步研究。本文利用MODIS数据,分析四川盆地2014年7月12～27日平均地表温度、植被指数、TVDI和100站土壤湿度的空间分布,并对比了它们之间的异同。研究结果表明,TVDI的空间分布主要由地表温度的空间分布决定,TVDI不仅可用于监测四川盆地较大范围的干旱状况,也可用于监测局地的干旱状况。当前自动站土壤湿度观测值与TVDI之间在有限点上不存在显著的线性相关,如何对TVDI进行干旱分级仍需深入研究。      

基于MODIS数据地表温度反演劈窗算法的比较研究

选取QIN和SOB两种代表性劈窗算法对辽宁地区地表温度进行反演,并分析二者的精度和误差分布。结果表明：QIN和SOB算法反演的地表温度（TS）与地面气象台站准同步观测的气温和地温的线性拟合显著,SOB算法线性拟合更好;从误差分布直方图上看,两种算法的反演结果与地温更接近,SOB算法与同步气温和地温在±2 ℃之间的误差比例略高于QIN算法;在野外开展与卫星遥感空间尺度一致的地表温度观测试验,QIN和SOB算法与实测值的平均绝对误差均为1.5 ℃;与NASA官网发布的地表温度产品对比发现,QIN和SOB算法的平均绝对误差分别为1.75 ℃、1.70 ℃;因此QIN、SOB算法在辽宁地区均适用,SOB算法误差更小。     

MODIS数据在福建省地表温度上的应用研究

利用MODIS卫星资料的宏观、实时等特点对福建省地表温度进行遥感反演,在对MODIS影像进行双眼皮校正、几何校正和辐射校正的基础上,建立以分裂窗法的福建省地表温度反演算法模型,并对两个时相的福建省地表温度结果进行动态分析。结果表明福建省地表热量分布存在着明显的北冷南暖、东高西低的特点,沿海地区由于经济发达和城市化进程的原因,城市聚落地明显要比中西部相对落后农村地区地表温度高,并有加剧的趋势,这对合理进行农作物合理区划和环境监测分析提供了重要的参照依据。     

MODIS数据在福建省地表温度上的应用研究

利用MODIS卫星资料的宏观、实时等特点对福建省地表温度进行遥感反演,在对MODIS影像进行双眼皮校正、几何校正和辐射校正的基础上,建立以分裂窗法的福建省地表温度反演算法模型,并对两个时相的福建省地表温度结果进行动态分析。结果表明福建省地表热量分布存在着明显的北冷南暖、东高西低的特点,沿海地区由于经济发达和城市化进程的原因,城市聚落地明显要比中西部相对落后农村地区地表温度高,并有加剧的趋势,这对合理进行农作物合理区划和环境监测分析提供了重要的参照依据。     

基于MODIS数据的近地表气温估算

气温是各种植物生理、水文、环境等模型中一个非常重要的近地表气象参数,多年来气温数据均以气象站点资料插值得到。近年来,卫星遥感数据被用于气温估算,且精度不断提高。为研究基于MODIS数据的近地表气温估算方法,以浙江省为研究区域,利用33个站点2011年逐日每10 min一次的自动气象站气温观测数据和MODIS地表温度产品及参数因子,建立了MODIS地表温度和地面观测的气温的线性关系,同时通过考虑归一化植被指数、水汽压、地表反照率、高程4个影响因子,得出了卫星过境时刻MODIS地表温度和气温的多因子估算模型;利用Zaksek等提出的基于能量平衡的遥感模型进行了气温估算,并采用多元回归分析法对该模型重新进行了拟合,得到近地表气温。结果表明:三种方法的决定系数R2分别为0.87、0.94、0.90,均方根误差RMSE分别为3.35℃、2.31℃、2.78℃,多因子估算模型得到的结果最好。同时对其分白天和夜间进行检验,二者的RMSE分别为2.27℃、1.93℃,夜间精度比白天高。对于季节的变化,秋季估算结果最好,春季次之,冬季稍差,夏季最差。     

气候变化背景下湖北省高温干旱复合灾害变化特征

利用湖北省76个国家气象站1961—2022年地面气象观测资料,基于气象干旱综合监测指数(Meteorological Drought Composite Index,MCI)和有效降水指数(Effective Precipitation,EP)识别湖北省历年干旱和洪涝过程,分析近62 a旱涝过程频次时空变化和旱涝年、旱涝转换特征以及2010年以来旱涝特点。结果表明：湖北省旱涝频发区总体呈东涝西旱、南涝北旱的片状分布。干旱和暴雨洪涝发生频次分别呈现波动式下降、上升趋势。干旱主要发生在春季和伏秋季,发生频次总体呈减少趋势,但夏秋干旱以及极端干旱有趋多增强的态势;暴雨洪涝主要集中在夏季,发生频次呈增多趋势。旱涝年年际间呈现连旱2~4 a、连涝2~3 a或旱涝交替的特征,部分年份年内旱涝并存、旱涝急转,2010年以来无旱涝并存年。旱涝转换站数年际间波动较大,呈现5个阶段性上升特征,各递增阶段最大站数呈递减趋势。2010年以来旱涝呈现极端性增强、骤发性增多及连旱连涝的特点。

     

Assessing the vulnerability of wind energy to climate change and extreme events

This article presents a review of the status and basis of wind-generated electricity production, the state of knowledge regarding possible changes in the spatio-temporal characteristics of the wind resource and wind turbine operating conditions, the principal extreme events that are of relevance to the wind energy industry, and the major potential vulnerabilities of the wind energy industry to climate change, with a specific focus on extreme events. Generally, the magnitude of projected changes over Europe and the contiguous USA are within the ‘conservative’ estimates embedded within the Wind Turbine Design Standards. However, more research is needed to quantify (i) how global climate evolution may influence the operation of wind turbines outside these regions, (ii) events causing coincident extreme wind speeds, gusts, and vertical wind shear, and (iii) combined wind-wave loading on offshore turbines.     

Indices for extreme events in projections of anthropogenic climate change

Indices for temperature and precipitation extremes are calculated on the basis of the global climate model ECHAM5/MPI-OM simulations of the twentieth century and SRES A1B and B1 emission scenarios for the twenty-first century. For model evaluation, the simulated indices representing the present climate were compared with indices based on observational data. This comparison shows that the model is able to realistically capture the observed climatological large-scale patterns of temperature and precipitation indices, although the quality of the simulations depends on the index and region under consideration. In the climate projections for the twenty-first century, all considered temperature-based indices, minimum Tmin, maximum Tmax, and the frequency of tropical nights, show a significant increase worldwide. Similarly, extreme precipitation, as represented by the maximum 5-day precipitation and the 95th percentile of precipitation, is projected to increase significantly in most regions of the world, especially in those that are relatively wet already under present climate conditions. Analogously, dry spells increase particularly in those regions that are characterized by dry conditions in present-day climate. Future changes in the indices exhibit distinct regional and seasonal patterns as identified exemplarily in three European regions.     

Vulnerability of the oil and gas sector to climate change and extreme weather events

A changing climate and more frequent extreme weather events pose challenges to the oil and gas sector. Identifying how these changes will affect oil and gas extraction, transportation, processing, and delivery, and how these industries can adapt to or mitigate any adverse impacts will be vital to this sector’s supply security. This work presents an overview of the sector’s vulnerability to a changing climate. It addresses the potential for Natech hazards and proposes risk reduction measures, including mitigation and adaptation options. Assessment frameworks to ensure the safety of people, the environment, and investments in the oil and gas sector in the face of climate change are presented and their limitations discussed. It is argued that a comprehensive and systemic analysis framework for risk assessment is needed. The paper concludes that climate change and extreme weather events represent a real physical threat to the oil and gas sector, particularly in low-lying coastal areas and areas exposed to extreme weather events. The sector needs to take climate change seriously, assess its own vulnerability, and take appropriate measures to prevent or mitigate any potentially negative effects.     

Managing the inconceivable: participatory assessments of impacts and responses to extreme climate change

A comprehensive understanding of the implications of extreme climate change requires an in-depth exploration of the perceptions and reactions of the affected stakeholder groups and the lay public. The project on “Atlantic sea level rise: Adaptation to imaginable worst-case climate change” (Atlantis) has studied one such case, the collapse of the West Antarctic Ice Sheet and a subsequent 5–6 m sea-level rise. Possible methods are presented for assessing the societal consequences of impacts and adaptation options in selected European regions by involving representatives of pertinent stakeholders. Results of a comprehensive review of participatory integrated assessment methods with a view to their applicability in climate impact studies are summarized including Simulation-Gaming techniques, the Policy Exercise method, and the Focus Group technique. Succinct presentations of these three methods are provided together with short summaries of relevant earlier applications to gain insights into the possible design options. Building on these insights, four basic versions of design procedures suitable for use in the Atlantis project are presented. They draw on design elements of several methods and combine them to fit the characteristics and fulfill the needs of addressing the problem of extreme sea-level rise. The selected participatory techniques and the procedure designs might well be useful in other studies assessing climate change impacts and exploring adaptation options.     

Spatiotemporal variability of extreme precipitation in Shaanxi province under climate change

Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide a more comprehensively the changes in extreme precipitation between the periods of 1954–1983 and 1984–2013 in Shaanxi province under climate change, which will hopefully provide a scientific understanding of the precipitation-related natural hazards such as flood and drought. Daily precipitation from 34 surface meteorological stations were used to calculated 13 extreme precipitation indices (EPIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) expect Team on climate change Detection, Monitoring and Indices (ETCCDMI). Two periods including 1954–1983 and 1984–2013 were selected and five types of precipitation days (R10mm-R100mm) were defined, to provide more evidences of climate change impacts on the extreme precipitation events, and specially, to investigate the changes in different types of precipitation days. The EPIs were generated using RClimRex software, and the trends were analyzed using Mann-Kendall nonparametric test and Sen’s slope estimator. The relationships between the EPIs and the impacts of climate anomalies on typical EPIs were investigated using correlation and composite analysis. The mainly results include: 1) Thirteen EPIs, except consecutive dry day (CDD), were positive trends dominated for the period of 1984–2013, but the trends were not obvious for the period of 1954–1983. Most of the trends were not statistically significant at 5 % significance level. 2) The spatial distributions of stations that exhibited positive and negative trends were scattered. However, the stations that had negative trends mainly distributed in the north of Shaanxi province, and the stations that had positive trends mainly located in the south. 3) The percentage of stations that had positive trends had increased from the period of 1954–1983 to 1984–2013 for all the 13 EPIs except CDD, indicating the possible climate change impacts on extreme precipitation events. 4) The correlations between annual total wet-day precipitation (PRCPTOT) and other 12 EPIs varied for different indices and stations. The composite analysis found that El Niño Southern Oscillation (ENSO) exerted greater impacts on PRCPTOT than other EPIs and greater in the Guanzhong Plain (GZP) than Qinling-Dabashan Mountains (QDM) and Shanbei Plateau (SBP) of Shaanxi province.     

Characterising climate change discourse on social media during extreme weather events

When extreme weather events occur, people often turn to social media platforms to share information, opinions and experiences. One of the topics commonly discussed is the role climate change may or may not have played in influencing an event. Here, we examine Twitter posts that mentioned climate change in the context of three high-magnitude extreme weather events – Hurricane Irene, Hurricane Sandy and Snowstorm Jonas – in order to assess how the framing of the topic and the attention paid to it can vary between events. We also examine the role that contextual factors can play in shaping climate change coverage on the platform. We find that criticism of climate change denial dominated during Irene, while political and ideological struggle frames dominated during Sandy. Discourse during Jonas was, in contrast, more divided between posts about the scientific links between climate change and the events, and posts contesting climate science in general. The focus on political and ideological struggle frames during Sandy reflects the event’s occurrence at a time when the Occupy movement was active and the 2012 US Presidential Election was nearing. These factors, we suggest, could also contribute to climate change being a more prominent discussion point during Sandy than during Irene or Jonas. The Jonas frames, meanwhile, hint at lesser public understanding of how climate change may influence cold weather events when compared with tropical storms. Overall, our findings demonstrate how event characteristics and short-term socio-political context can play a critical role in determining the lenses through which climate change is viewed.