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How to avoid the risk of maladaptation? From a conceptual understanding to a systematic approach for analyzing potential adverse effects in adaptation actions
Get PDFClimate change is already affecting and altering natural and human systems, and its effects are expected to intensify over the coming decades. Adaptation is therefore imperative for future development. However, like any other anthropogenic intervention, adaptation measures can have unintended detrimental impacts and adverse effects on human and natural systems, known as maladaptation. With growing evidence of maladaptation, practitioners in the fields of resilience and climate change adaptation increasingly focus on avoiding maladaptation risks in their projects. Yet, there is still no clear understanding of how to comprehensively and systematically analyze adverse effects in adaptation actions. To address this gap, this article advances the conceptual understanding of maladaptation and elaborates a pragmatic approach for examining, identifying, and diagnosing maladaptation risks in adaptation measures. Starting by breaking down the concept of maladaptation into analytical components (i.e., drivers, mechanisms, dimensions, attributes, forms, and outputs of maladaptation) based on the relevant literature, we propose a new harmonized and actionable definition. Based on this new understanding, we propose a practical and systematic approach to analyze maladaptation risks at the early stages of adaptation planning. Through the proposed definition, conceptual disaggregation, and practical framework, this paper contributes to a better understanding of maladaptation and provides practitioners with means to improve the design of future adaptation measures
Evaluation of CanCM3 and CanCM4 models from the North American Multi-Model Ensemble (NMME) for drought prediction in arid and semi-arid basins of Iran
Get PDFABSTRACT
This study evaluates the potential of two models within the North American Multi-Model Ensemble (NMME) system, i.e., CanCM3 and CanCM4, for improving drought risk management through reliable prediction. By employing the Standardized Precipitation Evapotranspiration Index (SPEI) and gridded datasets (GPCC and CRU), this study assesses their drought forecast capabilities across four semi-arid to arid basins in Iran. The results reveal that both models effectively capture drought events at short lead times (0.5 months), achieving correlation coefficients exceeding 0.93. The performance decline at longer lead times (3.5 months) is less severe in spring and autumn, maintaining correlations of >0.6 compared to summer. A Critical Success Index (CSI) analysis further highlights the models' skill in detecting summer drought events at a 1.5-month lead time (CSI >0.94), underscoring their utility for critical agricultural and water resource planning. Seasonal analysis shows CanCM4 outperforming CanCM3, particularly regarding CSI and correlation stability. These findings offer a novel contribution to understanding the applicability of CanCM3 and CanCM4 for drought forecast purposes in arid and semi-arid basins and underline their value for enhancing drought early warning systems and supporting efficient resource allocation to mitigate drought impacts
Reflections on the large-scale application of a community resilience measurement framework across the globe
Get PDFThis paper reflects on learnings and analysis from an extensively globally applied, standardized community disaster resilience measurement framework that utilises bottom-up (locally collected) data. These lessons, from over a decade of on-the-ground work and analysis, are based on empirical evidence and have salience for scholars, policy-makers and practitioners aiming to strengthen community disaster resilience and apply bottom-up community disaster resilience measurement approaches. The Flood Resilience Measurement for Communities approach was co-designed and implemented by the Zurich Flood Resilience Alliance: a transdisciplinary science-policy-practice collaboration including scientists, practitioners and private business. It has been applied globally in approximately 400 communities worldwide, demonstrating the real-world impact of scalable community disaster resilience measurement initiatives. Findings provide evidence for the impacts and good practices of applying bottom-up community disaster resilience measurement approaches. Quantitative analysis on this unique dataset provides new entry points for research on typologies and dynamics of resilience, based on empirical evidence on human, social, physical, natural and financial dimensions. Based on our analysis, we find that the use of bottom-up, multidimensional, standardized community disaster resilience measurement approaches is a worthwhile endeavour to support community disaster resilience strengthening
High-income groups disproportionately contribute to climate extremes worldwide
Get PDFClimate injustice persists as those least responsible often bear the greatest impacts, both between and within countries. Here we show how GHG emissions from consumption and investments attributable to the wealthiest population groups have disproportionately influenced present-day climate change. We link emissions inequality over the period 1990–2020 to regional climate extremes using an emulator-based framework. We find that two-thirds (one-fifth) of warming is attributable to the wealthiest 10% (1%), meaning that individual contributions are 6.5 (20) times the average per capita contribution. For extreme events, the top 10% (1%) contributed 7 (26) times the average to increases in monthly 1-in-100-year heat extremes globally and 6 (17) times more to Amazon droughts. Emissions from the wealthiest 10% in the United States and China led to a two- to threefold increase in heat extremes across vulnerable regions. Quantifying the link between wealth disparities and climate impacts can assist in the discourse on climate equity and justice
Interactions between climate warming and management actions determining bird community change in protected areas
Get PDFBiodiversity is increasingly negatively affected by climate warming, making this issue a major conservation concern. Many bird species respond to warming temperatures by shifting distribution ranges, but these shifts often lag behind temperature changes. Protected areas (PAs) can facilitate such shifts, but a growing body of literature suggests that not all PAs facilitate climate warming responses equally, as realized management actions can differ. Here, we study waterbird community change as a response to climate warming in relation to targets of conservation projects implemented in Natura 2000 protected areas across the EU. We combine long-term waterbird survey data (i.e. International Waterbird Census) with data on conservation funded by the EU LIFE program, the main EU instrument for conservation. We used the community temperature index to measure thermal community changes over 28 years. We found community adjustment to climate warming lagged behind temperature. However, community change was twice as fast in sites were conservation was targeting wetland habitats compared with sites without habitat conservation. Targeting waterbirds directly did not lead to variation in community change compared with other types of species conservation. Our results imply that on the management level conservation targeting a community's habitat (rather than targeting the species group directly) is more likely to provide benefits for community adjustment to climate warming. This study demonstrates that management actions currently not targeting climate warming impacts on biodiversity, have the potential to support species responding to climate warming. However, conservation strategies need to be adapted to the challenges arising with climate warming
Closing decent living gaps in energy and emissions scenarios: introducing DESIRE
Get PDFSocial and environmental agendas are intricately connected and shape the international policy discourse. To support these discussions, we present a framework for interpreting global scenario outcomes on energy demand and supply-side transitions through the lens of societal well-being and minimum resource requirements. We develop and apply a new model called Decent living standards and the Environment in Scenarios considering Inequality and Resource Efficiency (DESIRE) to fill a critical gap in modelling inequality-growth-efficiency interactions. Utilising bottom–up literature on energy inequality and minimum energy requirements, we analyse system-wide changes from integrated assessment models to assess whether levels of energy consumption in pathways can be consistent with providing decent living standards (DLS) for all, covering three sectors in 173 countries. We apply DESIRE to multiple new sustainable development pathways (SDPs). By 2040, the combination of ambitious inequality reductions, service provisioning efficiency, and higher energy services in the SDPs reduces the global residential and commercial energy deprivation—currently over 5 billion people—by at least 90%. Industry energy gaps are closed, but transport gaps remain. In the SDPs, more than half of the global population—including in low-income countries—achieve living standards more than twice as high as the DLS benchmark for the residential and commercial sector. Energy use beyond DLS across all sectors accounts for about two-thirds of total energy use globally. Efficiency improvements reduce global energy requirements 30%–46% by 2040 in the SDPs (across countries from 17–35 GJ cap −1 in 2020 to 9–23 GJ cap −1 ), while climate policies reduce CO 2 emissions related to energy for DLS to almost zero in 2050, keeping cumulative emissions for DLS for all until 2050 close to the size of the remaining carbon budget to 1.5 °C (at 50% probability). This work illustrates the possibility of pathways that deliver DLS for all while meeting the Paris Agreement
Similarities and divergent patterns in hydrologic fluxes and storages simulated by global water models
No full textGlobal water models (GWMs) are critical tools for understanding the Earth’s water cycle and water resource management under a changing climate and accelerating human interventions. Although GWMs have been evaluated for hydrologic fluxes (for example, river discharge) and the role of representing human activities, there is a persistent gap in understanding models’ ability to simultaneously reproduce fluxes and storages (for example, terrestrial water storage (TWS)). Here we show that eight state-of-the-art GWMs do not consistently reproduce discharge and TWS with the same efficacy across varied geographic and climatic regions. Furthermore, model performance for discharge deteriorates as human impacts intensify. While a general agreement between simulated and observed TWS trends is found in two-thirds of major global river basins, models tend to underestimate the trends in both directions. Likewise, no single model simulates TWS trends and seasonality accurately and uniformly across major global river basins. Although improvements in capturing basin-averaged TWS trends, spatial distributions and seasonal fluctuations have been achieved compared with previous reports, challenges remain in accurately reproducing both fluxes and storages, owing primarily to inadequate representation of human activities in heavily managed regions. This study underscores critical disparities in GWM performance, emphasizing the need for further model enhancements, which is crucial for improved and more robust hydrologic assessments and predictions under climate change
Past socio-political transitions away from coal and gas show challenges and opportunities ahead
Get PDFTransitioning away from fossil fuels presents substantial challenges, given the growing mismatch between pledges submitted to international climate negotiations and the mitigation strategies that limit warming to below 1.5 °C or 2 °C presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report. The scientific case for phasing out coal-fired electricity is clear, and many countries are progressing towards this. However, despite widespread concerns about risks and trade-offs, natural gas is often considered a bridge fuel, and there is currently no progress towards phasing down its capacity. Previous work on the political feasibility of coal phase-out only considered limited socio-political factors, missing the importance of governance quality and policies supporting the energy transition. There is even more limited understanding of factors associated with gas phase-down, while Europe and North America fall behind trajectories required to limit warming below 1.5 °C. We use multivariate regression and clustering analyses on over four decades of data to investigate the drivers and synergies of coal and gas transitions. This reveals opportunities to overcome fossil fuel lock-in through renewable energy expansion, energy policy reforms, and power market restructuring. Countries with greater reliance on fossil fuel infrastructure and workforce face additional difficulties in phase out. Social factors such as higher belief in climate change are positively linked with more ambitious coal phase-out efforts. However, disentangling these links for gas remains difficult given the limited historical evidence of phase-down progress. We identify four archetypes (Coal Reliance, Gas Reliance, Limited Policy, and Transition Underway) that illustrate different ways countries have transitioned from coal and gas over time. These provide blueprints for potential future transitions in other countries. Recognizing the diverse social, political, and institutional factors that shape transitions can inform the design of politically relevant future scenarios
The DSK stock-flow consistent agent-based integrated assessment model
Get PDFWe present an updated, stock-flow consistent version of the ‘Dystopian Schumpeter meeting Keynes’ agent-based integrated assessment model. By embedding the model in a fully specified accounting system, all balance sheet items and financial flows can be explicitly and consistently tracked throughout a simulation. This allows for improved analysis of climate change and climate policy scenarios in terms of their systemic implications for agent and sector-level balance sheet dynamics and financial stability. We provide an extensive description of the updated model, representing the most detailed outline of a model from the well-established ‘Keynes + Schumpeter’ family available to date. Following a discussion of calibration and validation, we present a range of example scenarios