Dynamic adaptive pathways in downscaled climate change scenarios

The parallel scenario process enables characterization of climate-related risks and response options to climate change under different socio-economic futures and development prospects. The process is based on representative concentration pathways, shared socio-economic pathways, and shared policy assumptions. Although this scenario architecture is a powerful tool for evaluating the intersection of climate and society at the regional and global level, more specific context is needed to explore and understand risks, drivers, and enablers of change at the national and local level. We discuss the need for a stronger recognition of such national-scale characteristics to make climate change scenarios more relevant at the national and local scale, and propose ways to enrich the scenario architecture with locally relevant details that enhance salience, legitimacy, and credibility for stakeholders. Dynamic adaptive pathways are introduced as useful tools to draw out which elements of a potentially infinite scenario space connect with decision-relevant aspects of particular climate-related and non-climate-related risks and response options. Reviewing adaptation pathways for New Zealand case studies, we demonstrate how this approach could bring the global-scale scenario architecture within reach of local-scale decision-making. Such a process would enhance the utility of scenarios for mapping climate-related risks and adaptation options at the local scale, involving appropriate stakeholder involvement.     

Uncertainties linked to land-surface processes in climate change simulations

 The impact of climate change on the hydrology of continental surfaces is critical for human activities but the response of the surface to this perturbation may also affect the sensitivity of the climate. This complex feedback is simulated in general circulation models (GCMs) used for climate change predictions by their land-surface schemes. The present study attempts to quantify the uncertainty associated with these schemes and what impact it has on our confidence in the simulated climate anomalies. Four GCMs, each coupled to two different land-surface schemes, are used to explore the spectrum of uncertainties. It is shown that, in this sample, surface processes have a significant contribution to our ability to predict surface temperature changes and perturbations of the hydrological cycle in an environment with doubled greenhouse gas concentration. The results reveal that the uncertainty introduced by land-surface processes in the simulated climate is different from its impact on the sensitivity of GCMs to climate change, indeed an alteration of the surface parametrization with little impact on model climate can affect sensitivity significantly. This result leads us to believe that the validation of land-surface schemes should not be limited to the current climate but should also cover their sensitivity to variations in climatic forcing. Received: 24 June 1999 / Accepted: 20 April 2000     

Assessment of institutional capacity to adapt to climate change in transboundary river basins

Responses to climate change in transboundary river basins are believed to depend on national and sub-national capacities as well as the ability of co-riparian nations to communicate, coordinate, and cooperate across their international boundaries. We develop the first framework for assessing transboundary adaptive capacity. The framework considers six dimensions of transboundary river basins that influence planning and implementation of adaptation measures and represents those dimensions using twelve measurable indicators. These indicators are used to assess transboundary adaptive capacity of 42 basins in the Middle East, Mediterranean, and Sahel. We then conduct a cluster analysis of those basins to delineate a typology that includes six categories of basins: High Capacity, Mediated Cooperation, Good Neighbour, Dependent Instability, Self-Sufficient, and Low Capacity. We find large variation in adaptive capacity across the study area; basins in Western Europe generally have higher capacities to address the potential hazards of climate change. Our basin typology points to how climate change adaptation policy interventions would be best targeted across the different categories of basins.     

Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP

This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

The response of Lake Tahoe to climate change

Meteorology is the driving force for lake internal heating, cooling, mixing, and circulation. Thus continued global warming will affect the lake thermal properties, water level, internal nutrient loading, nutrient cycling, food-web characteristics, fish-habitat, aquatic ecosystem, and other important features of lake limnology. Using a 1-D numerical model—the Lake Clarity Model (LCM) —together with the down-scaled climatic data of the two emissions scenarios (B1 and A2) of the Geophysical Fluid Dynamics Laboratory (GFDL) Global Circulation Model, we found that Lake Tahoe will likely cease to mix to the bottom after about 2060 for A2 scenario, with an annual mixing depth of less than 200 m as the most common value. Deep mixing, which currently occurs on average every 3–4 years, will (under the GFDL B1 scenario) occur only four times during 2061 to 2098. When the lake fails to completely mix, the bottom waters are not replenished with dissolved oxygen and eventually dissolved oxygen at these depths will be depleted to zero. When this occurs, soluble reactive phosphorus (SRP) and ammonium-nitrogen (both biostimulatory) are released from the deep sediments and contribute approximately 51 % and 14 % of the total SRP and dissolved inorganic nitrogen load, respectively. The lake model suggests that climate change will drive the lake surface level down below the natural rim after 2085 for the GFDL A2 but not the GFDL B1 scenario. The results indicate that continued climate changes could pose serious threats to the characteristics of the Lake that are most highly valued. Future water quality planning must take these results into account.     

Recent intense hurricane response to global climate change

An Anthropogenic Climate Change Index (ACCI) is developed and used to investigate the potential global warming contribution to current tropical cyclone activity. The ACCI is defined as the difference between the means of ensembles of climate simulations with and without anthropogenic gases and aerosols. This index indicates that the bulk of the current anthropogenic warming has occurred in the past four decades, which enables improved confidence in assessing hurricane changes as it removes many of the data issues from previous eras. We find no anthropogenic signal in annual global tropical cyclone or hurricane frequencies. But a strong signal is found in proportions of both weaker and stronger hurricanes: the proportion of Category 4 and 5 hurricanes has increased at a rate of ~25–30 % per °C of global warming after accounting for analysis and observing system changes. This has been balanced by a similar decrease in Category 1 and 2 hurricane proportions, leading to development of a distinctly bimodal intensity distribution, with the secondary maximum at Category 4 hurricanes. This global signal is reproduced in all ocean basins. The observed increase in Category 4–5 hurricanes may not continue at the same rate with future global warming. The analysis suggests that following an initial climate increase in intense hurricane proportions a saturation level will be reached beyond which any further global warming will have little effect.     

Temperature response to future urbanization and climate change

This study examines the impact of future urban expansion on local near-surface temperature for Sydney (Australia) using a future climate scenario (A2). The Weather Research and Forecasting model was used to simulate the present (1990–2009) and future (2040–2059) climates of the region at 2-km spatial resolution. The standard land use of the model was replaced with a more accurate dataset that covers the Sydney area. The future simulation incorporates the projected changes in the urban area of Sydney to account for the expected urban expansion. A comparison between areas with projected land use changes and their surroundings was conducted to evaluate how urbanization and global warming will act together and to ascertain their combined effect on the local climate. The analysis of the temperature changes revealed that future urbanization will strongly affect minimum temperature, whereas little impact was detected for maximum temperature. The minimum temperature changes will be noticeable throughout the year. However, during winter and spring these differences will be particularly large and the increases could be double the increase due to global warming alone at 2050. Results indicated that the changes were mostly due to increased heat capacity of urban structures and reduced evaporation in the city environment.     

企业气候变化意识及应对措施调查研究

基于2012—2015年在华北、珠三角和湖南湖北地区对企业管理人员进行的气候变化意识的问卷调查,构建了气候变化意识和企业应对气候变化措施两个一级指数。通过对调查结果交叉列联表分析,得出以下结论：企业管理人员的气候变化意识指数处于一般水平,并且受年龄、产业类型、企业类型的影响显著;企业应对气候变化措施指数也处于一般水平且不同企业水平差距较大,企业管理人员气候变化意识水平、未来预期和自主知识产权拥有量对其影响显著。     

Potential for added value to downscaled climate extremes over Korea by increased resolution of a regional climate model

This study estimates the potential for added value in dynamical downscaling by increasing the spatial resolution of the regional climate model (RCM) over Korea. The Global/Regional Integrated Model System—Regional Model Program with two different resolutions is employed as the RCM. Large-scale forcing is given by a historical simulation of a global climate model, namely the Hadley Center Global Environmental Model version 2. As a standard procedure, the reproducibility of the RCM results for the present climate is evaluated against the reanalysis and observation datasets. It is confirmed that the RCM adequately reproduces the major characteristics of the observed atmospheric conditions and the increased resolution of the RCM contributes to the improvement of simulated surface variables including precipitation and temperature. For the added-value assessment, the interannual and daily variabilities of precipitation, temperature are compared between the different resolution RCM experiments. It is distinctly shown that variabilities are additionally described as the spatial resolution becomes higher. The increased resolution also contributes to capture the extreme weather conditions, such as heavy rainfall events and sweltering days. The enhanced added value is more evident for the precipitation than for the temperature, which stands for a usefulness of the high-resolution RCM especially for diagnosing potential hazard related to heavy rainfall. The results of this study assure the effectiveness of increasing spatial resolution of the RCM for detecting climate extremes and also provide credibility to the current climate simulation for future projection studies.     

Statistical Downscaling Based on Dynamically DownscaledPredictors： Application to Monthly Precipitation in Sweden

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.     

Unpacking governance: Building adaptive capacity to climate change of river basins in Brazil

Governance and institutions are critical determinants of adaptive capacity and resilience. Yet the make-up and relationships between governance components and mechanisms that may or may not contribute to adaptive capacity remain relatively unexplored empirically. This paper builds on previous research focusing on integrated water resources management in Brazil to ‘unpack’ water governance mechanisms that may shape the adaptive capacity of water systems to climatic change. We construct a river basin index to characterize governance approaches in 18 Brazilian river basins, apply a reliability test to assess the validity of these governance indicators, and use in-depth qualitative data collected in a subsample of the basins to explore the relationship between the governance indicators and adaptive capacity. The analysis suggests a positive relationship between integrated water governance mechanisms and adaptive capacity. In addition, we carry out a cluster analysis to group the basins into types of governance approaches and further unveil potential relationships between the governance variables and overall adaptive capacities. The cluster analysis indicates that tensions and tradeoffs may exist between some of the variables, especially with equality of decision making and knowledge availability; a finding that has implications for decision makers aiming to build adaptive capacity and resilience through governance and institutional means.     

Societal response to CO2-induced climate change: Opportunities for research

How might a climate change, induced by increased CO₂ in the atmosphere, affect societies? What is the range of existing and potential mechanisms for societal response? And how might research contribute to a reduction of the adverse impact (or enhancement of the unique opportunities) of a climate change by providing greater understanding of the processes involved in climate and society interaction? This paper reflects an initial effort to shed light on these questions. It offers first a framework for identifying key issues in climate-society interaction; eight major questions are suggested by the framework. A discussion of each major question is then presented with the purpose of reviewing the current state of knowledge, identifying the gaps in understanding, and offering opportunities for research to fill those gaps. In all, twenty-two research needs are outlined and are summarized at the conclusion of the paper. The perspective is inter-disciplinary, but the review draws heavily from the geographic literature, reflecting the disciplinary bias of the authors.     

An analogue model to derive additional climate change scenarios from existing GCM simulations

 Changes in land surface driving variables, predicted by GCM transient climate change experiments, are confirmed to exhibit linearity in the global mean land temperature anomaly, ΔT _l . The associated constants of proportionality retain spatial and seasonal characteristics of the GCM output, whilst ΔT _l is related to radiative forcing anomalies. The resultant analogue model is shown to be robust between GCM runs and as such provides a computationally efficient technique of extending existing GCM experiments to a large range of climate change scenarios. As an example impacts study, the analogue model is used to drive a terrestrial ecosystem model, and predicted changes in terrestrial carbon are found to be similar to those when using GCM anomalies directly. Received: 4 January 1999 / Accepted: 11 December 1999     

Reconceptualising adaptation to climate change as part of pathways of change and response

The need to adapt to climate change is now widely recognised as evidence of its impacts on social and natural systems grows and greenhouse gas emissions continue unabated. Yet efforts to adapt to climate change, as reported in the literature over the last decade and in selected case studies, have not led to substantial rates of implementation of adaptation actions despite substantial investments in adaptation science. Moreover, implemented actions have been mostly incremental and focused on proximate causes; there are far fewer reports of more systemic or transformative actions. We found that the nature and effectiveness of responses was strongly influenced by framing. Recent decision-oriented approaches that aim to overcome this situation are framed within a “pathways” metaphor to emphasise the need for robust decision making within adaptive processes in the face of uncertainty and inter-temporal complexity. However, to date, such “adaptation pathways” approaches have mostly focused on contexts with clearly identified decision-makers and unambiguous goals; as a result, they generally assume prevailing governance regimes are conducive for adaptation and hence constrain responses to proximate causes of vulnerability. In this paper, we explore a broader conceptualisation of “adaptation pathways” that draws on ‘pathways thinking’ in the sustainable development domain to consider the implications of path dependency, interactions between adaptation plans, vested interests and global change, and situations where values, interests, or institutions constrain societal responses to change. This re-conceptualisation of adaptation pathways aims to inform decision makers about integrating incremental actions on proximate causes with the transformative aspects of societal change. Case studies illustrate what this might entail. The paper ends with a call for further exploration of theory, methods and procedures to operationalise this broader conceptualisation of adaptation.     

Projected shifts of wine regions in response to climate change

This research simulates the impact of climate change on the distribution of the most important European wine regions using a comprehensive suite of spatially informative layers, including bioclimatic indices and water deficit, as predictor variables. More specifically, a machine learning approach (Random Forest, RF) was first calibrated for the present period and applied to future climate conditions as simulated by HadCM3 General Circulation Model (GCM) to predict the possible spatial expansion and/or shift in potential grapevine cultivated area in 2020 and 2050 under A2 and B2 SRES scenarios. Projected changes in climate depicted by the GCM and SRES scenarios results in a progressive warming in all bioclimatic indices as well as increasing water deficit over the European domain, altering the climatic profile of each of the grapevine cultivated areas. The two main responses to these warmer and drier conditions are 1) progressive shifts of existing grapevine cultivated area to the north–northwest of their original ranges, and 2) expansion or contraction of the wine regions due to changes in within region suitability for grapevine cultivation. Wine regions with climatic conditions from the Mediterranean basin today (e.g., the Languedoc, Provence, Côtes Rhône Méridionales, etc.) were shown to potentially shift the most over time. Overall the results show the potential for a dramatic change in the landscape for winegrape production in Europe due to changes in climate.     

对基于土地应对气候变化的新认知

2019年8月7日IPCC《气候变化与土地特别报告》决策者摘要获得通过,报告涉及对基于土地应对气候变化不同措施的评估,取得一些新的认知,包括定量评估基于土地的40种综合措施对提高气候变化减缓和适应能力、防治荒漠化和土地退化、增强粮食安全、保护生物多样性和水资源及促进可持续发展的效益,提出在防治荒漠化和土地退化及保障粮食安全过程中提高气候变化适应和减缓能力的措施,评估了实施不同措施的风险、限制、障碍和保障政策等。在措施的分类、气候变化适应的主体对象,以及风险和政策分析等方面还存在一些不足。评估报告结论将对我国建立基于土地的应对气候变化的对策,促进把应对气候变化与防治荒漠化和土地退化、保护生态环境与增强粮食安全工作结合,制定相关政策等方面都具有重要的启示意义。