An update of IPCC climate reference regions for subcontinental analysis of climate model data: Definition and aggregated datasets

Iturbide, Maialen; Gutiérrez, José; Alves, Lincoln M.; Bedia, Joaquín; Cimadevilla, Ezequiel; Cofiño, Antonio S.; Cerezo‐Mota, Ruth; Luca, Alejandro Di; Faria, Sérgio H.; Gorodetskaya, Irina; Hauser, Mathias; Herrera, Sixto; Hewitt, Helene T.; Hennessy, Kevin; Jones, Richard G.; Krakovska, Svitlana; Martinez‐Castro, Daniel; Narisma, Gemma Teressa; Nurhati, Intan Suci; Pinto, Izidine; Seneviratne, Sonia I.; Hurk, Bart van den; Vera, Carolina

doi:10.5194/essd-2019-258

Cited by 27 publications

(44 citation statements)

References 15 publications

(19 reference statements)

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“…We first compute the forced response over the new IPCC-defined regions 46 for Europe, the Arctic, Australia and South-East Asia (Figs. 6 and 7 ) to determine whether there is model-to-model agreement.…”

Section: Resultsmentioning

confidence: 99%

More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century

2021

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Separating how model-to-model differences in the forced response (UMD) and internal variability (UIV) contribute to the uncertainty in climate projections is important, but challenging. Reducing UMD increases confidence in projections, while UIV characterises the range of possible futures that might occur purely by chance. Separating these uncertainties is limited in traditional multi-model ensembles because most models have only a small number of realisations; furthermore, some models are not independent. Here, we use six largely independent single model initial-condition large ensembles to separate the contributions of UMD and UIV in projecting 21st-century changes of temperature, precipitation, and their temporal variability under strong forcing (RCP8.5). We provide a method that produces similar results using traditional multi-model archives. While UMD is larger than UIV for both temperature and precipitation changes, UIV is larger than UMD for the changes in temporal variability of both temperature and precipitation, between 20° and 80° latitude in both hemispheres. Over large regions and for all variables considered here except temporal temperature variability, models agree on the sign of the forced response whereas they disagree widely on the magnitude. Our separation method can readily be extended to other climate variables.

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Section: Resultsmentioning

confidence: 99%

More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century

2021

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“…For the scaling plots, we follow a similar procedure as in Seneviratne et al (2016) and Wartenburger et al (2017), using ESRs (Seneviratne et al, 2018; IPCC, 2018). First, regional means are calculated for the 43 currently proposed AR6 regions (see Figure S1 Iturbide et al, 2020), the global ocean and the global land. Then, we calculate a centered 20‐year running mean for all available models for each year for Tglob and the extreme index.…”

Section: Methods and Datamentioning

confidence: 99%

Regional Climate Sensitivity of Climate Extremes in CMIP6 Versus CMIP5 Multimodel Ensembles

2020

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We analyze projected changes in climate extremes (extreme temperatures and heavy precipitation) in the multimodel ensembles of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). The results reveal close similarity between both ensembles in the regional climate sensitivity of the projected multimodel mean changes in climate extremes, that is, their projected changes as a function of global warming. This stands in contrast to widely reported divergences in global (transient and equilibrium) climate sensitivity in the two multimodel ensembles. Some exceptions include higher warming in the South America monsoon region, lower warming in Southern Asia and Central Africa, and higher increases in heavy precipitation in Western Africa and the Sahel region in the CMIP6 ensemble. The multimodel spread in regional climate sensitivity is found to be large in both ensembles. In particular, it contributes more to intermodel spread in projected regional climate extremes compared with the intermodel spread in global climate sensitivity in CMIP6. Our results highlight the need to consider regional climate sensitivity as a distinct feature of Earth system models and a key determinant of projected regional impacts, which is largely independent of the models' response in global climate sensitivity. Plain Language Summary Many articles analyze and compare global climate sensitivity in climate models, that is, how their global warming differs at a given level of CO 2 concentrations. However, global warming is only one quantity affecting impacts. To assess human-and ecosystem-relevant impacts, it is essential to evaluate the regional climate sensitivity of climate models, that is, how their regional climate features differ at a given level of global warming. We analyze here regional climate sensitivity in the new multimodel ensemble that will underlie the conclusions of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). This ensemble of model projections is called the "Sixth Coupled Model Intercomparison Project" or CMIP6. We find that differences in regional climate sensitivity between models in CMIP6 often contribute more to the uncertainty of regional extremes projections than the uncertainty in global mean warming between models. Overall, the regional climate sensitivity features in the CMIP6 models' projections ensemble are very similar to those of the prior ensemble (CMIP5), although the model ensembles have been highlighted to differ in their global climate sensitivity over the 21st century.

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“…The CORDEX domains are: North America (NAM-22), Central America (CAM-22), South America (SAM-22), Europe (EUR-11), Africa (AFR-22), South Asia (WAS-22), East Asia (EAS-22), Southeast Asia (SEA-22), and Australasia (AUS-22) (Iturbide et al 2020;Gutowski et al 2016) were alternatively driven by GFDL-ES2M, MPI-ESM-MR, and MIROC5 in selected domains, which are referred to as secondary CORDEX-CORE GCMs.…”

Section: Methodsmentioning

confidence: 99%

“…In the frame of this paper, we want to introduce and analyse the CORDEX-CORE ensemble of regional climate simulations. Mean climate changes in different areas of the world are investigated, based on the newly defined IPCC physical climate reference regions (Iturbide et al 2020). The analysis focuses on the mean climate change signals of the near-surface temperature and precipitation.…”

Section: Introductionmentioning

confidence: 99%

Assessing mean climate change signals in the global CORDEX-CORE ensemble

et al. 2020

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The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$ km (0.22$$^{\circ }$$ ∘ ) versus 50$$\,\mathrm {km}$$ km (0.44$$^{\circ }$$ ∘ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

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An update of IPCC climate reference regions for subcontinental analysis of climate model data: Definition and aggregated datasets

Cited by 27 publications

References 15 publications

More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century

More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century

Regional Climate Sensitivity of Climate Extremes in CMIP6 Versus CMIP5 Multimodel Ensembles

Assessing mean climate change signals in the global CORDEX-CORE ensemble

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