scholarly journals Understanding Interdependent Climate Change Risks Using a Serious Game

2020 ◽  
Vol 101 (8) ◽  
pp. E1279-E1300 ◽  
Author(s):  
Sabine Undorf ◽  
Simon F. B. Tett ◽  
Joseph Hagg ◽  
Marc J. Metzger ◽  
Chris Wilson ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Serious Game ◽  
Climate Projections ◽  
Civil Infrastructure ◽  
Climate Risks ◽  
Climate Change Risks ◽  
Climate Hazards ◽  
Interdependent Risks ◽  
Infrastructure Services

Abstract Anthropogenic climate change calls for rapid and enormous cuts in emissions of CO2 and other greenhouse gases to mitigate future impacts. Even with these, however, many changes will continue to occur over the next 20–30 years adding to those already observed. Adaptation is crucial and urgent, but identifying strategies is complex and requires dialogue and cooperation among stakeholders, especially for infrastructure that exhibits interdependent risks in that failure in one type may impact others. A serious game was codeveloped with infrastructure operators to communicate climate projections and climate hazards to them; identify potential interdependencies, cascading impacts, cumulative effects, and vulnerability hot spots; and engage them to improve cooperation and enable a shared understanding of cross-cutting climate risks and interdependencies. In the game, players provide present-day infrastructure services in the Inverclyde district, Scotland, as they experience a plausible decade of 2050s weather characterized by a sequence of hazard events. This sequence was extracted from climate model projections to ensure scientific plausibility. The infrastructure operators were responsible for drinking water and gas supplies, road and rail transport, wastewater treatment, and civil infrastructure. When playing the game the participating U.K. infrastructure providers felt that although there were challenges, they could cope with 2050s climate change. None of the projected hazard events were anticipated to cause catastrophic impact cascades on infrastructure. The game was positively received, and the study suggests it is a useful tool to both communicate climate hazards and explore potential interdependent risks by bringing together stakeholders’ individual expertise in an engaging way.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

scholarly journals Flood risk assessment methodology for planning under climate change scenarios and the corresponding change in land cover

2019 ◽  
Vol 11 (4) ◽  
pp. 1370-1382 ◽  
Author(s):  
Asma Hanif ◽  
Ashwin Dhanasekar ◽  
Anthony Keene ◽  
Huishu Li ◽  
Kenneth Carlson
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate Model ◽  
The United States ◽  
Army Corps ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Rcp Scenarios ◽  
Daily Precipitation Data ◽  
Time Frames

Abstract Projected climate change impacts on the hydrological regime and corresponding flood risks were examined for the years 2030 (near-term) and 2050 (long-term), under representative concentration pathways (RCP) 4.5 (moderate) and 8.5 (high) emission scenarios. The United States Army Corps of Engineers' (USACE) Hydrologic Engineering Center's Hydrologic Modeling System was used to simulate the complete hydrologic processes of the various dendritic watershed systems and USACEs' Hydrologic Engineering Center's River Analysis System hydraulic model was used for the two-dimensional unsteady flow flood calculations. Climate projections are based on recent global climate model simulations developed for the International Panel on Climate Change, Coupled Model Inter-comparison Project Phase 5. Hydrographs for frequent (high-recurrence interval) storms were derived from 30-year historical daily precipitation data and decadal projections for both time frames and RCP scenarios. Since the climate projections for each scenario only represented ten years of data, 100-year or 500-year storms cannot be derived. Hence, this novel approach of identifying frequent storms is used as an indicator to compare across the various time frames and climate scenarios. Hydrographs were used to generate inundation maps and results are used to identify vulnerabilities and formulate adaptation strategies to flooding at 43 locations worldwide.

scholarly journals A Conceptual Tool for Climate Change Risk Assessment

2014 ◽  
Vol 18 (21) ◽  
pp. 1-15 ◽  
Author(s):  
Paul A. T. Higgins ◽  
Jonah V. Steinbuck
Keyword(s):  
Climate Change ◽  
Social Institutions ◽  
Public Understanding ◽  
Management Decision ◽  
Contributing Factors ◽  
Conceptual Tool ◽  
Climate Risks ◽  
Wide Range ◽  
Climate Change Risks ◽  
Economic Analyses

Abstract This study develops a new conceptual tool to explore the potential societal consequences of climate change. The conceptual tool delineates three quasi-independent factors that contribute to the societal consequences of climate change: how climate changes; the sensitivity of physical systems, biological resources, and social institutions to climate change; and the degree of human dependence on those systems, resources, and institutions. This conceptual tool, as currently developed, is not predictive, but it enables the exploration of the dependence of climate change risks on key contributing factors. In exploring a range of plausible behaviors for these factors and methods for their synthesis, the authors show that plausible assumptions lead to a wide range in potential societal consequences of climate change. This illustrates that the societal consequences of climate change are currently difficult to constrain and that high-consequence climate change outcomes are not necessarily low probability, as suggested by leading economic analyses. With careful implementation, this new conceptual tool has potential to increase public understanding of climate change risks, to support risk management decision making, or to facilitate communication of climate risks across disciplinary boundaries.

scholarly journals Evaluation of Long-Term SOC and Crop Productivity within Conservation Systems Using GFDL CM2.1 and EPIC

2018 ◽  
Vol 10 (8) ◽  
pp. 2665 ◽  
Author(s):  
Kieu N. Le ◽  
Manoj K. Jha ◽  
Jaehak Jeong ◽  
Philip W. Gassman ◽  
Manuel R. Reyes ◽  
...  
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Climate Model ◽  
Crop Yields ◽  
Upland Rice ◽  
Cropping Systems ◽  
Global Climate Model ◽  
Crop Productivity ◽  
Climate Projections ◽  
Epic Model

Will soil organic carbon (SOC) and yields increase for conservation management systems in tropical zones in response to the next 100 years? To answer the question, the Environmental Policy Integrated Climate (EPIC) model was used to study the effects of climate change, cropping systems, conservation agriculture (CA) and conservation tillage management practices on SOC and crop productivity in Kampong Cham, Cambodia. The EPIC model was successfully calibrated and validated for crop yields, biomass, SOC and nitrogen based on field data from a five-year field experiment. Historical weather (1994–2013) was used for baseline assessment versus mid-century (2046–2064) and late-century (2081–2100) climate projections generated by the Geophysical Fluids Dynamics Laboratory (GFDL) CM2.1 global climate model. The simulated results showed that upland rice yield would increase the most under the B1 scenario in mid-century for all treatments, followed by soybean and maize. Cassava yield only increased under CA treatment when cultivated as a continuous primary crop. Carbon sequestration was more sensitive to cropping systems and crop rotation than climate change. The results indicated that the rotated CA primary crop (maize) systems should be prioritized for SOC sequestration as well as for increasing crop productivity. In addition, rice systems may increase SOC compared to soybean and cassava.

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Control Period ◽  
Flood Frequency ◽  
Climate Projections ◽  
The Future ◽  
Flood Quantiles ◽  
The Impact

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

scholarly journals Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks

2019 ◽  
Vol 11 (17) ◽  
pp. 4764 ◽  
Author(s):  
Anna Sperotto ◽  
Josè Luis Molina ◽  
Silvia Torresan ◽  
Andrea Critto ◽  
Manuel Pulido-Velazquez ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bayesian Networks ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Large Variability ◽  
Nutrient Loadings

With increasing evidence of climate change affecting the quality of water resources, there is the need to assess the potential impacts of future climate change scenarios on water systems to ensure their long-term sustainability. The study assesses the uncertainty in the hydrological responses of the Zero river basin (northern Italy) generated by the adoption of an ensemble of climate projections from 10 different combinations of a global climate model (GCM)–regional climate model (RCM) under two emission scenarios (representative concentration pathways (RCPs) 4.5 and 8.5). Bayesian networks (BNs) are used to analyze the projected changes in nutrient loadings (NO3, NH4, PO4) in mid- (2041–2070) and long-term (2071–2100) periods with respect to the baseline (1983–2012). BN outputs show good confidence that, across considered scenarios and periods, nutrient loadings will increase, especially during autumn and winter seasons. Most models agree in projecting a high probability of an increase in nutrient loadings with respect to current conditions. In summer and spring, instead, the large variability between different GCM–RCM results makes it impossible to identify a univocal direction of change. Results suggest that adaptive water resource planning should be based on multi-model ensemble approaches as they are particularly useful for narrowing the spectrum of plausible impacts and uncertainties on water resources.

An overview of the EUCP project – towards improved European Climate Predictions and Projections

2020 ◽  
Author(s):  
Jason A. Lowe ◽  
Carol McSweeney ◽  
Chris Hewitt
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Projections ◽  
Public And Private ◽  
The People ◽  
Local Actors ◽  
Model Ensembles ◽  
Public And Private Sector

<p>There is clear evidence that, even with the most favourable emission pathways over coming decades, there will be a need for society to adapt to the impacts of climate variability and change. To do this regional, national and local actors need up-to-date information on the changing climate with clear accompanying detail on the robustness of the information. This needs to be communicated to both public and private sector organisations, ideally as part of a process of co-developing solutions.</p><p>EUCP is an H2020 programme that began in December 2017 with the aim of researching and testing the provision of improved climate predictions and projections for Europe for the next 40+ years, and drawing on the expertise of researchers from a number of major climate research institutes across Europe. It is also engaging with users of climate change information through a multiuser forum (MUF) to ensure that what we learn will match the needs of the people who need if for decision making and planning.</p><p>The first big issue that EUCP seeks to address is how better to use ensembles of climate model projections, moving beyond the one-model-one-vote philosophy. Here, the aim is to better understand how model ensembles might be constrained or sub-selected, and how multiple strands of information might be combined into improved climate change narratives or storylines. The second area where EUCP is making progress is in the use of very high-resolution regional climate simulations that are capable of resolving aspects of atmospheric convection. Present day and future simulations from a new generation of regional models ae being analysed in EUCP and will be used in a number of relevant case studies. The third issue that EUCP will consider is how to make future simulations more seamless across those time scales that are most relevant user decision making. This includes generating a better understanding of predictability over time and its sources in initialised forecasts, and also how to transition from the initialised forecasts to longer term boundary forced climate projections.</p><p>This presentation will provide an overview of the challenges being addressed by EUCP and the approaches the project is using.</p><p><br><br></p><p> </p>

scholarly journals Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?

2017 ◽  
Vol 98 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nikolina Ban ◽  
Nigel M. Roberts ◽  
Hayley J. Fowler ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Convective Storms ◽  
Wide Range

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.

scholarly journals Future runoff regime changes and their time of emergence for 93 catchments in Switzerland

2020 ◽  
Author(s):  
Regula Muelchi ◽  
Ole Rössler ◽  
Jan Schwanbeck ◽  
Rolf Weingartner ◽  
Olivia Martius
Keyword(s):  
Climate Change ◽  
Strong Influence ◽  
Climate Model ◽  
High Elevation ◽  
Snow Accumulation ◽  
Seasonal Patterns ◽  
Climate Projections ◽  
Local Climate ◽  
Runoff Change ◽  
Runoff Changes

Abstract. Assessments of climate change impacts on runoff regimes are essential for adaptation and mitigation planning. Changing runoff regimes and thus changing seasonal patterns of water availability have strong influence on various sectors such as agriculture, energy production or fishery. In this study, we use the most up to date local climate projections for Switzerland (CH2018) that were downscaled with a post-processing method (quantile mapping). This enables detailed information on changes in runoff regimes and their time of emergence for 93 rivers in Switzerland under three emission pathways RCP2.6, RCP4.5, and RCP8.5. Changes in seasonal patterns are projected with increasing winter runoff and decreasing summer and autumn runoff. Spring runoff is projected to increase in high elevation catchments and to decrease in lower lying catchments. Despite strong increases in winter and partly in spring, the yearly mean runoff is projected to decrease in most catchments. Results show a strong elevation dependence for the signal and magnitude of change. Compared to lower lying catchments, runoff changes in high elevation catchments (above 1500 masl) are larger in winter, spring, and summer due to the strong influence of reduced snow accumulation and earlier snow melt as well as glacier melt. Under RCP8.5 (RCP2.6) and for catchments with mean altitude below 1500 masl, average relative runoff change in winter is +27 % (+5 %), in spring −5 % (−6 %), in summer −31 % (−4 %), in autumn −21 % (−6 %), and −8 % (−4 %) throughout the year. For catchments with mean elevation above 1500 masl, runoff changes on average by +77 % (+24 %) in winter, by +28 % (+16 %) in spring, by −41 % (−9 %) in summer, by −15 % (−4 %) in autumn, and by −9 % (−0.6 %) in the yearly mean. The changes and the climate model agreement on the signal of change increase with increasing global mean temperatures or stronger emission scenarios. This amplification highlights the importance of climate change mitigation. Under RCP8.5, early times of emergence in winter (before 2065; period 2036–2065) and summer (before 2065) were found for catchments with mean altitudes above 1500 masl. Significant changes in catchments below 1500 masl emerge later in the century. However, not all catchments show a time of emergence in all seasons and in some catchments the detected significant changes are not persistent over time.

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