Spatial and temporal change in landslide hazard by future climate change scenarios using probabilistic-based frequency ratio model

The aims of this study were to apply, verify and compare a frequency ratio model for landslide hazards, considering future climate change and using a geographic information system in Inje, Korea. Data for the future climate change scenario (A1B), topography, soil, forest, land cover and geology were collected, processed and compiled in a spatial database. The probability of landslides in the study area in target years in the future was then calculated assuming that landslides are triggered by a daily rainfall threshold. Landslide hazard maps were developed for the two study areas, and the frequency ratio for one area was applied to the other area as a cross-check of methodological validity. Verification results for the target years in the future were 82.32–84.69%. The study results, showing landslide hazards in future years, can be used to help develop landslide management plans.     

Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques

Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies.     

全球气候数据集生成及气候变化应用研究

科技部在"十三五"期间部署的国家重点研发计划"全球变化及应对"专项资助了"全球气候数据集生成及气候变化关键过程和要素监测"研究项目。项目围绕由全球气候观测系统提出的基本气候变量,完善地空天基观测体系,生成中国首套以遥感数据为主体的涵盖大气、海洋和陆表长时间序列、高精度、高时空一致性的产品,即气候数据集,动态监测全球变化关键过程和要素。     

A multi-scale spatiotemporal modeling approach to explore vegetation dynamics patterns under global climate change

Given the complexity of vegetation dynamic patterns under global climate change, multi-scale spatiotemporal explicit models are necessary in order to account for environmental heterogeneity. However, there is no efficient time-series tool to extract, reconstruct and analyze the multi-scale vegetation dynamic patterns under global climate change. To fill this gap, a Multi-Scale Spatio-Temporal Modeling (MSSTM) framework which can incorporate the pixel, scale, and time-specific heterogeneity was proposed. The MSSTM method was defined on proper time-series models for multi-temporal components through wavelet transforms. The proposed MSSTM approach was applied to a subtropical mountainous and hilly agro-forestry ecosystem in southeast China using the moderate resolution imaging spectroradiometer enhanced vegetation index (EVI) time-series data sets from 2001 to 2011. The MSSTM approach was proved to be efficient in characterizing and forecasting the complex vegetation dynamic patterns. It provided good estimates of the peaks and valleys of the observed EVI and its average percentages of relative absolute errors of reconstruction was low (6.65). The complexity of the relationship between vegetation dynamics and meteorological parameters was also revealed through the MSSTM method: (1) at seasonal level, vegetation dynamic patterns are strongly associated with climatic variables, primarily the temperature and then precipitation, with correlations slight decreasing (EVI–temperature)/increasing (EVI–precipitation) with altitudinal gradients. (2) At inter-annual scale, obvious positive correlations were primarily observed between EVI and temperature. (3) Despite very low-correlation coefficients observed at intra-seasonal scales, considerable proportions of EVI anomalies are associated with climatic variables, principally the precipitation and sunshine durations.     

辽宁省气候变化与厄尔尼诺相关性分析

为了探讨近50年来辽宁省气候变化特征及其与厄尔尼诺的关系,文章根据1965—2013年辽宁省23个气象站点的降水、年均气温数据与表征厄尔尼诺南方涛动(ENSO)事件的热带太平洋海表温度距平和南方涛动指数资料,利用气候倾向率、M-K突变检验以及反距离权重插值等方法进行分析研究,结果表明:1965—2013年辽宁省降水量由东南向西北逐渐减少,在多个时间段内发生突变现象;气温有显著的上升趋势,并在空间上呈现由东北向西南逐渐增加的趋势;降水变化与ENSO事件强度存在着一定的负相关性,而气温变化与ENSO事件强度没有显著的相关性。     

后疫情时代全球气候变化的应对与抉择

后疫情时代,全球气候变化影响和应对呈现新趋势,突发性、全球性和关联性成为鲜明的特征.当前,要着力解决应对气候变化的重大科学问题,就必须继续务实加强基础研究,妥善处理应对全球变化的挑战和可持续发展之间的关系;根据中国国情选择自己的气候变化应对之路;进一步处理好减排与增汇、减缓与适应的关系;设立国家碳中和重大专项;制定和实...     

Lake variations in response to climate change in the Tibetan Plateau in the past 40 years

The Qinghai-Tibetan Plateau plays an important role in global climate and environmental change and holds the largest lake area in China, with a total surface area of 36,900 km². The expansion and shrinkage of these lakes are critical to the water cycle and ecological and environmental systems across the plateau. In this paper, surface areas of major lakes within the plateau were extracted based on a topographic map from 1970, and Landsat MSS, TM and ETM+ satellite images from the 1970s to 2008. Then, a multivariate correlation analysis was conducted to examine the relationship between the changes in lake surface areas and the changes in climatic variables including temperature, precipitation, evaporation, and sunshine duration. Initial results suggest that the variations in lake surface areas within the plateau are closely related to the warming, humidified climate transition in recent years such as the rise of air temperature and the increase in precipitation. In particular, the rising temperature accelerates melting of glaciers and perennial snow cover and triggers permafrost degradation, and leads to the expansion of most lakes across the plateau. In addition, different distributions and types of permafrost may cause different lake variations in the southern Tibetan Plateau.     

Communicating climate change: spatial analog versus color-banded isoline maps with and without accompanying text

People discount projected impacts of climate change that they see as spatially or temporally remote. To overcome this, climate change outreach must communicate impacts as local, concrete, immediate, and situated in a well-understood frame of reference. Spatial-analog mapping may meet this challenge: by drawing on people’s experience of existing climates, this technique matches a locality’s projected climates with present-day climates of other localities. However, analog maps’ effect on climate impact perceptions has not been compared with the effect on climate impact perceptions elicited by standard climate change mapping techniques. Accordingly, this study considers whether residents of Centre Region, Pennsylvania, who are shown spatial-analog maps for future Centre Region temperatures, perceive impacts as more salient than do residents shown the same temperature-change information directly using color-banded isallotherm maps. It also considers how responses differ when this information is presented using only text, only maps, or both maps and text. An online survey of 3094 members of 11 Centre Region organizations presents the maps and/or text and then assesses respondents’ impact perceptions. Based on 444 valid responses, the study finds that respondents, using spatial-analog survey forms, generally expect impacts to be less severe and disruptive than respondents using temperature-change forms. It also finds that respondents using survey forms with maps generally expect impacts to be more severe and disruptive than respondents using text-only forms. Climate change communicators who wish to improve understanding and engagement should therefore strongly consider using maps where possible, but should exercise caution before using spatial-analog approaches.     

Detecting patterns of climate change in long-term forecasts of marine environmental parameters

ABSTRACT

Forecasting environmental parameters in the distant future requires complex modelling and large computational resources. Due to the sensitivity and complexity of forecast models, long-term parameter forecasts (e.g. up to 2100) are uncommon and only produced by a few organisations, in heterogeneous formats and based on different assumptions of greenhouse gases emissions. However, data mining techniques can be used to coerce the data to a uniform time and spatial representation, which facilitates their use in many applications. In this paper, streams of big data coming from AquaMaps and NASA collections of 126 long-term forecasts of nine types of environmental parameters are processed through a cloud computing platform in order to (i) standardise and harmonise the data representations, (ii) produce intermediate scenarios and new informative parameters, and (iii) align all sets on a common time and spatial resolution. Time series cross-correlation applied to these aligned datasets reveals patterns of climate change and similarities between parameter trends in 10 marine areas. Our results highlight that (i) the Mediterranean Sea may have a standalone ‘response’ to climate change with respect to other areas, (ii) the Poles are most representative of global forecasted change, and (iii) the trends are generally alarming for most oceans.     

气候变化与国家安全风险分析关键技术探索

如何量化与认知气候变化对国家安全产生的巨大风险已经成为国内外首脑高峰会议的热点之一。IPCC的报告综合了千余名科学家与专家对气候变化包括气象灾害、粮食安全、生态系统、水资源等多个领域在内的风险评估的整理、分类和分析,但大多尚处于单项领域的研究,亟须进行系统的建模和全面的风险分析。该文提出了CyberGIS模型方法,探讨对国家安全风险问题的参数化建模和形式化表达。     

Spatiotemporal analysis of vegetation variability and its relationship with climate change in China

This paper investigated spatiotemporal dynamic pattern of vegetation, climate factor, and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets. First, most vegetation canopies demonstrated obvious seasonality, increasing with latitudinal gradient. Second, obvious dynamic trends were observed in both vegetation and climate change, especially the positive trends. Over 70% areas were observed with obvious vegetation greening up, with vegetation degradation principally in the Pearl River Delta, Yangtze River Delta, and desert. Overall warming trend was observed across the whole country (>98% area), stronger in Northern China. Although over half of area (58.2%) obtained increasing rainfall trend, around a quarter of area (24.5%), especially the Central China and most northern portion of China, exhibited significantly negative rainfall trend. Third, significantly positive normalized difference vegetation index (NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions, corresponding to their synchronous stronger seasonal pattern. Finally, at inter-annual level, the NDVI–climate relationship differed with climatic regions and their long-term trends: in humid regions, positive coefficients were observed except in regions with vegetation degradation; in arid, semiarid, and semihumid regions, positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature. This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process.     

中国北方地区生态环境质量时空变化及其对气候变化与人类活动的响应

中国北方地区地域辽阔,干旱面积分布较广,风沙危害、水土流失等问题严重,是典型的气候敏感区及生态环境脆弱区。然而,该区域近几十年来生态环境质量演变及其对气候变化与人类活动响应的规律还不清晰,研究这些规律对加强北方地区生态文明建设及维护生物多样性具有重要意义。本文基于中国历史高分辨率生态环境质量数据(CHEQ),以及气候指标、夜间灯光等遥感数据,利用趋势分析、变异系数、偏相关分析、多元回归分析、重标极差分析等方法,探究了北方地区2001—2018年生态环境质量时空变化特征及其对气候变化与人类活动的响应。结果表明：(1)2001—2018年CHEQ指数总体呈小幅下降趋势,空间上呈东高西低、南北高中部低的分布特征;(2)近18年来,北方地区生态环境质量改善的区域仅为18.66%,而退化面积比例为40%;(3)生态环境质量与气温和人类活动呈显著负相关关系(P<0.05),而与降水呈显著正相关关系(P<0.05);(4)气候变化对生态环境质量变化起主导作用的区域占研究区面积的90%。本文在弥补现有研究不足的同时,可以为快速掌握北方地区绿色经济发展下生态环境质量的变化规律和提高生态文明建...     

青藏高原地表冻融循环与植被返青期的变化趋势及其气候响应特征

青藏高原特殊的地理环境使其对全球气候变化十分敏感,所以研究其地表冻融循环和植被返青期的时空动态对于回顾和预测青藏高原对全球气候变化的响应具有重要意义。本文通过利用双指标地表冻融状态识别算法和被动微波亮温数据(SMMR、SSMI和SSMIS)来获取青藏高原长时间序列(1982年—2013年)逐日地表冻融状态,通过对GIMMS全球植被指数数据产品进行NDVI的滤波重建和返青期提取来获取青藏高原植被长时间序列(年份)的返青期;并且分析了地表冻融循环和植被返青期的变化趋势、相互关系及对青藏高原气候变化的响应特征。总体来看,在空间上,青藏高原的地表冻结集中发生在10月30日至次年4月2日,平均地表融化首日集中在5月12—27日,平均植被返青期集中在5月19—29日。植被返青期平均发生在地表融化首日后的3.94±5.58日,两者具有显著的相关关系(R=0.51,P=0.003)。青藏高原的地表融化首日和植被返青期在1982年—2013年间经历了推迟、提前再推迟的3个过程,融化时间和返青期在1982年—1987年分别以1.93±1.81 d/a和0.28±1.01 d/a的速度推迟;在1987年—2006年分别以0.67±0.20 d/a和0.13±0.16 d/a的速度提前;在2006年—2013年分别以0.97±0.84 d/a和1.04±0.52 d/a的速度推迟。中国气象局布设在青藏高原的CMA气象站的温度数据表明,高原的春季地表0 cm土壤温度呈持续上升的趋势,而植被返青期和地表融化首日并未持续提前,这可能是由几十年来高原不同地区降水等其他环境因素变化的差异造成。同时在气温持续升高期间,植被返青期的返青温度阈值也不断具有上升的趋势(R=0.72,P0.001),这可能与植被适应气候变化的自身调节能力有关。     

Coupling the 4M crop model with national geo-databases for assessing the effects of climate change on agro-ecological characteristics of Hungary

The 4M crop model was used to investigate the prospective effects of climate change on the agro-ecological characteristics of Hungary. The model was coupled with a detailed meteorological database and spatial soil information systems covering the whole territory of Hungary. Plant-specific model parameters were determined by inverse modeling. Future meteorological data were produced from the present meteorological data by combining a climate change scenario and a stochastic weather generator. Using the available and the generated data, the present and the prospective agro-ecological characteristics of Hungary were determined. According to the simulation results, average yields will decrease considerably (~30%) due to climate change. The rate of nitrate leaching will prospectively decrease as well. The fluctuations of both the yields and the annual nitrate leaching rates will most likely increase approaching the end of the twenty-first century. On the basis of the simulation results, the role of autumn crops is likely to become more significant in Hungary. The achieved results can be generalized for more extended regions based on the concept of spatial (geographical) analogy.     

Illegal land use change assessment using GIS and remote sensing to support sustainable land management strategies in Taiwan

Land use is changing at accelerated rates in Taiwan, and illegal land use change practices (ILP) are regularly observed within conservation areas. For this reason, we map high-potential areas of ILP within the Soil and water conservation zone (SWCZ) as an aid for effective land management and conducted an exploratory analysis of explanatory variables to evaluate their variability within ILP hot spots. We used variables relevant to hot spots to develop a logistic regression model and identified seven statistically significant variables. We re-applied the logistic regression approach to produce spatially explicit predictions of ILP. High probability areas are distributed along the coastal regions, covering 26% of the SWCZ, and their major drivers are related to accessibility and topography. The results from this research provide relevant information on the major drivers of ILP and high-potential areas, which can support officials in monitoring efforts for better planning and governance within the SWCZ.