Balanced subsampling of future regional climate ensembles of opportunity

2020 ◽  
Author(s):  
Jesús Fernández ◽  
María Dolores Frías
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Regional Climate ◽  
National Level ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Modelling ◽  
Model Intercomparison ◽  
Climate Change Projections ◽  
The Impact

<p>International model intercomparison initiatives, such as CORDEX or CMIP5, along with several relatively recent projects at international and national level, provide a wealth of model simulations of future regional climate. In a recent work, Fernandez et al (2019) collected 196 different future climate change projections over Spain, considering data from ENSEMBLES, ESCENA, EURO- and Med-CORDEX, along with their driving global climate projections from CMIP3 and CMIP5. This ensemble mixed different multi-model initiatives in an ensemble of opportunity, in the sense that it does not respond to any scientific design beyond the exploration of multi-model uncertainty. This ensemble of opportunity is not only the result of the mixture of different initiatives, but also responds to the lack of a balanced experimental design within most of the initiatives. Many of the initiatives -especially those unfunded, such as CORDEX- are carried out on a voluntary basis, with no strong constraint in the global climate models (GCMs) used as boundary conditions or in the number of contributing members per regional climate model (RCM).</p><p>Fernandez et al (2019) found in this ensemble a strong influence of the driving GCM on the regional climate change signal, along with favored GCMs, selected by many regional climate modelling groups to the detriment of GCMs publishing their output later or not at all. In this work, we quantitatively assess the impact of unbalanced GCM-RCM ensembles. For this purpose, we subsampled the ensemble of opportunity to obtain balanced sets of members according to different “what-if” situations: What if all RCMs had contributed a single member to the ensemble? What if each GCM had been dynamically downscaled only once? What if a given GCM/RCM had not contributed to the ensemble? For each hypothesis, there are a number of alternative sub-ensembles, which are used to evaluate uncertainty.</p><p><strong>Acknowledgement:</strong></p><p>This work is partially funded by the Spanish government through MINECO/FEDER co-funded projects INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R). </p><p><strong>References:</strong></p><p>Fernández, J., et al. (2019) Consistency of climate change projections from multiple global and regional model intercomparison projects. Clim Dyn 52:1139. https://doi.org/10.1007/s00382-018-4181-8</p>

Is Institutional Democracy a Good Proxy for Model Independence?

2016 ◽  
Vol 29 (23) ◽  
pp. 8301-8316 ◽  
Author(s):  
Martin Leduc ◽  
René Laprise ◽  
Ramón de Elía ◽  
Leo Šeparović
Keyword(s):  
Climate Change ◽  
Model Comparison ◽  
Climate Models ◽  
Regional Climate ◽  
Burden Of Proof ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Cross Model ◽  
Structural Differences ◽  
The Impact

Abstract Climate models developed within a given research group or institution are prone to share structural similarities, which may induce resembling features in their simulations of the earth’s climate. This assertion, known as the “same-center hypothesis,” is investigated here using a subsample of CMIP3 climate projections constructed by retaining only the models originating from institutions that provided more than one model (or model version). The contributions of individual modeling centers to this ensemble are first presented in terms of climate change projections. A metric for climate change disagreement is then defined to analyze the impact of typical structural differences (such as resolution, parameterizations, or even entire atmosphere and ocean components) on regional climate projections. This metric is compared to a present climate performance metric (correlation of error patterns) within a cross-model comparison framework in terms of their abilities to identify the same-center models. Overall, structural differences between the pairs of same-center models have a stronger impact on climate change projections than on how models reproduce the observed climate. The same-center criterion is used to detect agreements that might be attributable to model similarities and thus that should not be interpreted as implying greater confidence in a given result. It is proposed that such noninformative agreements should be discarded from the ensemble, unless evidence shows that these models can be assumed to be independent. Since this burden of proof is not generally met by the centers participating in a multimodel ensemble, the authors propose an ensemble-weighting scheme based on the assumption of institutional democracy to prevent overconfidence in climate change projections.

scholarly journals A regional climate modelling projection ensemble experiment – NARCliM

2013 ◽  
Vol 6 (3) ◽  
pp. 5117-5139 ◽  
Author(s):  
J. P. Evans ◽  
F. Ji ◽  
C. Lee ◽  
P. Smith ◽  
D. Argüeso ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Planning Process ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Regional Climate Modelling ◽  
Climate Projections ◽  
Climate Modelling ◽  
User Engagement

Abstract. Including the impacts of climate change in decision making and planning processes is a challenge facing many regional governments including the New South Wales (NSW) and Australian Capital Territory (ACT) governments in Australia. NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modelling project that aims to provide a comprehensive and consistent set of climate projections that can be used by all relevant government departments when considering climate change. To maximise end user engagement and ensure outputs are relevant to the planning process, a series of stakeholder workshops were run to define key aspects of the model experiment including spatial resolution, time slices, and output variables. As with all such experiments, practical considerations limit the number of ensembles members that can be simulated such that choices must be made concerning which Global Climate Models (GCMs) to downscale from, and which Regional Climate Models (RCMs) to downscale with. Here a methodology for making these choices is proposed that aims to sample the uncertainty in both GCMs and RCMs, as well as spanning the range of future climate projections present in the full GCM ensemble. The created ensemble provides a more robust view of future regional climate changes.

scholarly journals Sensitivity of the Amazon biome to high resolution climate change projections

2016 ◽  
Vol 46 (2) ◽  
pp. 175-188 ◽  
Author(s):  
Andre de Arruda LYRA ◽  
Sin Chan CHOU ◽  
Gilvan de Oliveira SAMPAIO
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Forest Type ◽  
Regional Climate ◽  
Amazon Region ◽  
Future Climate Change ◽  
Eastern Region ◽  
Climate Change Scenarios ◽  
Climate Change Projections ◽  
The Impact

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

scholarly journals Assessing the Impact of Land Use and Climate Change on Surface Runoff Response Using Gridded Observations and SWAT+

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 48
Author(s):  
Paul Kiprotich ◽  
Xianhu Wei ◽  
Zongke Zhang ◽  
Thomas Ngigi ◽  
Fengting Qiu ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Surface Runoff ◽  
Regional Climate ◽  
Future Climate Change ◽  
Climate Projections ◽  
Gridded Data ◽  
Study Results ◽  
The Impact

The Anthropocene period is characterised by a general demographic shift from rural communities to urban centres that transform the predominantly wild global landscape into mostly cultivated land and cities. In addition to climate change, there are increased uncertainties in the water balance and these feedbacks cannot be modelled accurately due to scarce or incomplete in situ data. In African catchments with limited current and historical climate data, precise modelling of potential runoff regimes is difficult, but a growing number of model applications indicate that useful simulations are feasible. In this study, we used the new generation of soil and water assessment tool (SWAT) dubbed SWAT+ to assess the viability of using high resolution gridded data as an alternative to station observations to investigate surface runoff response to continuous land use change and future climate change. Simultaneously, under two representative concentration pathways (RCP4.5 and RCP8.5), six regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment Program (CORDEX) and their ensemble were evaluated for model skill and systematic biases and the best performing model was selected. The gridded data predicted streamflow accurately with a Nash–Sutcliffe efficiency greater than 0.89 in both calibration and validation phases. The analysis results show that further conversion of grasslands and forests to agriculture and urban areas doubled the runoff depth between 1984 and 2016. Climate projections predict a decline in March–May rainfall and an increase in the October–December season. Mean temperatures are expected to rise by about 1.3–1.5 °C under RCP4.5 and about 2.6–3.5 °C under RCP8.5 by 2100. Compared to the 2010–2016 period, simulated surface runoff response to climate change showed a decline under RCP4.5 and an increase under RCP8.5. In contrast, the combine effects of land use change and climate change simulated a steady increase in surface runoff under both scenarios. This suggests that the land use influence on the surface runoff response is more significant than that of climate change. The study results highlight the reliability of gridded data as an alternative to instrumental measurements in limited or missing data cases. More weight should be given to improving land management practices to counter the imminent increase in the surface runoff to avoid an increase in non-point source pollution, erosion, and flooding in the urban watersheds.

The future of European floodplain wetlands under a changing climate

2011 ◽  
Vol 2 (2-3) ◽  
pp. 106-122 ◽  
Author(s):  
Christof Schneider ◽  
Martina Flörke ◽  
Gertjan Geerling ◽  
Harm Duel ◽  
Mateusz Grygoruk ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Scale ◽  
Future Climate Change ◽  
Anthropogenic Factors ◽  
Climate Modelling ◽  
Floodplain Wetlands ◽  
Potential Threat ◽  
Climate Change Projections ◽  
The Future ◽  
Floodplain Inundation

In the future, climate change may severely alter flood patterns over large regional scales. Consequently, besides other anthropogenic factors, climate change represents a potential threat to river ecosystems. The aim of this study is to evaluate the effect of climate change on floodplain inundation for important floodplain wetlands in Europe and to place these results in an ecological context. This work is performed within the Water Scenarios for Europe and Neighbouring States (SCENES) project considering three different climate change projections for the 2050s. The global scale hydrological model WaterGAP is applied to simulate current and future river discharges that are then used to: (i) estimate bankfull flow conditions, (ii) determine three different inundation parameters, and (iii) evaluate the hydrological consequences and their relation to ecology. Results of this study indicate that in snow-affected catchments (e.g. in Central and Eastern Europe) inundation may appear earlier in the year. Duration and volume of inundation are expected to decrease. This will lead to a reduction in habitat for fish, vertebrates, water birds and floodplain-specific vegetation causing a loss in biodiversity, floodplain productivity and fish production. Contradictory results occur in Spain, France, Southern England and the Benelux countries. This reflects the uncertainties of current climate modelling for specific seasons.

scholarly journals Climate Perspectives in the Intra–Americas Seas

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 959
Author(s):  
Ana María Durán-Quesada ◽  
Rogert Sorí ◽  
Paulina Ordoñez ◽  
Luis Gimeno
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Large Scale ◽  
Negative Impact ◽  
Current Knowledge ◽  
Regional Climate ◽  
Climate Projections ◽  
Economic Activities ◽  
Weather And Climate ◽  
The Impact

The Intra–Americas Seas region is known for its relevance to air–sea interaction processes, the contrast between large water masses and a relatively small continental area, and the occurrence of extreme events. The differing weather systems and the influence of variability at different spatio–temporal scales is a characteristic feature of the region. The impact of hydro–meteorological extreme events has played a huge importance for regional livelihood, having a mostly negative impact on socioeconomics. The frequency and intensity of heavy rainfall events and droughts are often discussed in terms of their impact on economic activities and access to water. Furthermore, future climate projections suggest that warming scenarios are likely to increase the frequency and intensity of extreme events, which poses a major threat to vulnerable communities. In a region where the economy is largely dependent on agriculture and the population is exposed to the impact of extremes, understanding the climate system is key to informed policymaking and management plans. A wealth of knowledge has been published on regional weather and climate, with a majority of studies focusing on specific components of the system. This study aims to provide an integral overview of regional weather and climate suitable for a wider community. Following the presentation of the general features of the region, a large scale is introduced outlining the main structures that affect regional climate. The most relevant climate features are briefly described, focusing on sea surface temperature, low–level circulation, and rainfall patterns. The impact of climate variability at the intra–seasonal, inter–annual, decadal, and multi–decadal scales is discussed. Climate change is considered in the regional context, based on current knowledge for natural and anthropogenic climate change. The present challenges in regional weather and climate studies have also been included in the concluding sections of this review. The overarching aim of this work is to leverage information that may be transferred efficiently to support decision–making processes and provide a solid foundation on regional weather and climate for professionals from different backgrounds.

THE SCIENCE UNDERLYING THE ISSUE OF CLIMATE CHANGE AND PROSPECTS FOR ADAPTATION

2001 ◽  
Vol 41 (1) ◽  
pp. 689
Author(s):  
C.D. Mitchell ◽  
G.I. Pearman
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Greenhouse Gas ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Initial Response ◽  
Lower Atmosphere ◽  
Future Climate Change ◽  
Atmospheric Concentration

The prospect of global-scale changes in climate resulting from changes in atmospheric greenhouse gas concentrations has produced a complex set of public and private- sector responses. This paper reviews several elements of this issue that are likely to be most important to industry.Scientific research continues to provide evidence to suggest that global climate will change significantly over the coming decades due to increases in the atmospheric concentration of greenhouse gases. Nonetheless, there exists a debate over the difference between observations of temperature retrieved from satellite and temperature measurements taken from the surface. Recent research undertaken to inform the debate is discussed, with the conclusion that there are real differences in trend between the surface and the lower atmosphere that can be explained in physical terms. Attention is turning to developing an understanding as to why climate model results show apparently consistent trends between the surface and the lower atmosphere, in contrast to these observations.While such uncertainties in the underlying science have been used to question whether action on the greenhouse issues is necessary, the initial response, as evidenced by international negotiations, has been to start mitigating greenhouse gas emissions. Adaptation to future climate change has received less attention than mitigation. A number of reasons for this are discussed, including the fact that regional scenarios of climate change are uncertain.The principles of risk management may be one way to manage the uncertainties associated with projections of regional climate change. Although the application of risk management to the potential impacts of climate change requires further investigation, elements of such a framework are identified, and include:Identifying the critical climate-related thresholds that are important to industry and its operations (for example, a 1-in-100 year return tropical cyclone).Using this understanding to analyse, and where possible quantify, industry’s pre-existing or baseline adaptive state through the use of sensitivity surfaces and quantified thresholds (for example, were facilities designed for a 1-in-100 event or a 1-in-500 year event?)Establishing probabilistic statements or scenarios of climate that are relevant to industry practice (for example, risk of a storm surge may be more important to operations than elevated wind strength; if so, what is the probability that an event will exceed the design threshold during the lifetime of the facility?).Bringing information on existing adaptive mechanisms together with climate scenarios to produce a quantitative risk assessment.Deciding on risk treatment (additional adaptive measures).

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

Coordinated Global and Regional Climate Modeling*

2015 ◽  
Vol 29 (1) ◽  
pp. 17-35 ◽  
Author(s):  
J. F. Scinocca ◽  
V. V. Kharin ◽  
Y. Jiao ◽  
M. W. Qian ◽  
M. Lazare ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Value Added ◽  
Regional Climate Modeling ◽  
Climate Projections ◽  
Climate Modelling

Abstract A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

scholarly journals Assessment of the impacts of climate change on maize production in the Wami Ruvu basin of Tanzania

2016 ◽  
Vol 8 (1) ◽  
pp. 142-164 ◽  
Author(s):  
Philbert Luhunga ◽  
Ladslaus Chang'a ◽  
George Djolov
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Projections ◽  
Intergovernmental Panel ◽  
Lower Altitude ◽  
Rcp 8.5 ◽  
Maize Yields ◽  
The Impact ◽  
Impacts Of Climate Change

The IPCC (Intergovernmental Panel on Climate Change) assessment reports confirm that climate change will hit developing countries the hardest. Adaption is on the agenda of many countries around the world. However, before devising adaption strategies, it is crucial to assess and understand the impacts of climate change at regional and local scales. In this study, the impact of climate change on rain-fed maize (Zea mays) production in the Wami-Ruvu basin of Tanzania was evaluated using the Decision Support System for Agro-technological Transfer. The model was fed with daily minimum and maximum temperatures, rainfall and solar radiation for current climate conditions (1971–2000) as well as future climate projections (2010–2099) for two Representative Concentration Pathways: RCP 4.5 and RCP 8.5. These data were derived from three high-resolution regional climate models, used in the Coordinated Regional Climate Downscaling Experiment program. Results showed that due to climate change future maize yields over the Wami-Ruvu basin will slightly increase relative to the baseline during the current century under RCP 4.5 and RCP 8.5. However, maize yields will decline in the mid and end centuries. The spatial distribution showed that high decline in maize yields are projected over lower altitude regions due to projected increase in temperatures in those areas.

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