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001033581 1001_ $$0P:(DE-HGF)0$$aShaw, Tiffany A.$$b0$$eCorresponding author
001033581 245__ $$aRegional climate change: consensus, discrepancies, and ways forward
001033581 260__ $$aLausanne$$bFrontiers Media$$c2024
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001033581 520__ $$aClimate change has emerged across many regions. Some observed regionalclimate changes, such as amplified Arctic warming and land-sea warmingcontrasts have been predicted by climate models. However, many otherobserved regional changes, such as changes in tropical sea surface temperatureand monsoon rainfall are not well simulated by climate model ensembles evenwhen taking into account natural internal variability and structural uncertaintiesin the response of models to anthropogenic radiative forcing. This suggestsclimate model predictions may not fully reflect what our future will look like.The discrepancies between models and observations are not well understooddue to several real and apparent puzzles and limitations such as the “signal-tonoiseparadox” and real-world record-shattering extremes falling outside of thepossible range predicted by models. Addressing these discrepancies, puzzlesand limitations is essential, because understanding and reliably predictingregional climate change is necessary in order to communicate effectively aboutthe underlying drivers of change, provide reliable information to stakeholders,enable societies to adapt, and increase resilience and reduce vulnerability.The challenges of achieving this are greater in the Global South, especiallybecause of the lack of observational data over long time periods and a lackof scientific focus on Global South climate change. To address discrepanciesbetween observations and models, it is important to prioritize resources forunderstanding regional climate predictions and analyzing where and whymodels and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.
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001033581 7001_ $$0P:(DE-HGF)0$$aArias, Paola A.$$b1
001033581 7001_ $$0P:(DE-HGF)0$$aCollins, Mat$$b2
001033581 7001_ $$0P:(DE-HGF)0$$aCoumou, Dim$$b3
001033581 7001_ $$0P:(DE-HGF)0$$aDiedhiou, Arona$$b4
001033581 7001_ $$0P:(DE-HGF)0$$aGarfinkel, Chaim I.$$b5
001033581 7001_ $$0P:(DE-HGF)0$$aJain, Shipra$$b6
001033581 7001_ $$0P:(DE-HGF)0$$aRoxy, Mathew Koll$$b7
001033581 7001_ $$0P:(DE-HGF)0$$aKretschmer, Marlene$$b8
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001033581 7001_ $$0P:(DE-HGF)0$$aNarsey, Sugata$$b10
001033581 7001_ $$0P:(DE-HGF)0$$aMartius, Olivia$$b11
001033581 7001_ $$0P:(DE-HGF)0$$aSeager, Richard$$b12
001033581 7001_ $$0P:(DE-Juel1)192332$$aShepherd, Theodore G.$$b13
001033581 7001_ $$0P:(DE-HGF)0$$aSörensson, Anna A.$$b14
001033581 7001_ $$0P:(DE-HGF)0$$aStephenson, Tannecia$$b15
001033581 7001_ $$0P:(DE-HGF)0$$aTaylor, Michael$$b16
001033581 7001_ $$0P:(DE-HGF)0$$aWang, Lin$$b17
001033581 773__ $$0PERI:(DE-600)2986708-3$$a10.3389/fclim.2024.1391634$$gVol. 6, p. 1391634$$p1391634$$tFrontiers in climate$$v6$$x2624-9553$$y2024
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