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@ARTICLE{Shaw:1033581,
author = {Shaw, Tiffany A. and Arias, Paola A. and Collins, Mat and
Coumou, Dim and Diedhiou, Arona and Garfinkel, Chaim I. and
Jain, Shipra and Roxy, Mathew Koll and Kretschmer, Marlene
and Leung, L. Ruby and Narsey, Sugata and Martius, Olivia
and Seager, Richard and Shepherd, Theodore G. and
Sörensson, Anna A. and Stephenson, Tannecia and Taylor,
Michael and Wang, Lin},
title = {{R}egional climate change: consensus, discrepancies, and
ways forward},
journal = {Frontiers in climate},
volume = {6},
issn = {2624-9553},
address = {Lausanne},
publisher = {Frontiers Media},
reportid = {FZJ-2024-06461},
pages = {1391634},
year = {2024},
abstract = {Climate 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.},
cin = {JSC / ICE-4},
ddc = {333.7},
cid = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)ICE-4-20101013},
pnm = {2112 - Climate Feedbacks (POF4-211) / 5111 -
Domain-Specific Simulation $\&$ Data Life Cycle Labs (SDLs)
and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-2112 / G:(DE-HGF)POF4-5111},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001224218200001},
doi = {10.3389/fclim.2024.1391634},
url = {https://juser.fz-juelich.de/record/1033581},
}