Towards predictive understanding of regional climate change

Xie, Shang‐Ping; Deser, Clara; Vecchi, Gabriel A.; Collins, Matthew; Delworth, Thomas L.; Hall, Alex; Hawkins, Ed; Johnson, Nathaniel C.; Cassou, Christophe; Giannini, Alessandra; Watanabe, Masahiro

doi:10.1038/nclimate2689

Cited by 295 publications

(235 citation statements)

References 99 publications

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“…Improved resolution of regional climate processes is a focal point of current climate research (Xie et al, 2015). Refined resolution in global climate models has allowed them to better resolve coastal processes and, in some cases, to reduce regional model biases (Saba et al, 2016).…”

Section: Improving Marine Mammal Distribution Projectionsmentioning

confidence: 99%

Projecting Marine Mammal Distribution in a Changing Climate

et al. 2017

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Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate Silber et al.Projecting Marine Mammal Distributions changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations.

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Section: Improving Marine Mammal Distribution Projectionsmentioning

confidence: 99%

Projecting Marine Mammal Distribution in a Changing Climate

et al. 2017

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“…A large ensemble of multiple climate models has contributed to addressing robust climate trends in the future projections (e.g. Xie et al, 2015). Model intercomparisons of the past climate changes and data-model comparisons are powerful frameworks for understanding physical processes responsible for climate change and variability and assessing reliability of the climate model projections (e.g.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Pliocene climate simulations in MRI-CGCM2.3 to respective boundary conditions

2016

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Abstract. Accumulations of global proxy data are essential steps for improving reliability of climate model simulations for the Pliocene warming climate. In the Pliocene Model Intercomparison Project phase 2 (PlioMIP2), a part project of the Paleoclimate Modelling Intercomparison Project phase 4, boundary forcing data have been updated from the PlioMIP phase 1 due to recent advances in understanding of oceanic, terrestrial and cryospheric aspects of the Pliocene palaeoenvironment. In this study, sensitivities of Pliocene climate simulations to the newly archived boundary conditions are evaluated by a set of simulations using an atmosphereocean coupled general circulation model, MRI-CGCM2.3. The simulated Pliocene climate is warmer than pre-industrial conditions for 2.4 • C in global mean, corresponding to 0.6 • C warmer than the PlioMIP1 simulation by the identical climate model. Revised orography, lakes, and shrunk ice sheets compared with the PlioMIP1 lead to local and remote influences including snow and sea ice albedo feedback, and poleward heat transport due to the atmosphere and ocean that result in additional warming over middle and high latitudes. The amplified higher-latitude warming is supported qualitatively by the proxy evidences, but is still underestimated quantitatively. Physical processes responsible for the global and regional climate changes should be further addressed in future studies under systematic intermodel and data-model comparison frameworks.

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“…One could argue that they have set themselves up for success by choosing a projection variable in which there are known model errors that are strongly related to the projection variable of interest. Much harder problems present themselves, notably when considering projection variables involving dynamical variations such as storms and more regional climate change [Shepherd, 2014;Xie et al, 2015]. Even for a basic but highly policy-relevant climate projection variable such as mean precipitation (Figure 1), there are multiple problems to be overcome.…”

Section: Reto Knutti and Colleagues Have Returned To This Issue In Thmentioning

confidence: 99%