4.8 Review

Towards predictive understanding of regional climate change

Journal

NATURE CLIMATE CHANGE
Volume 5, Issue 10, Pages 921-930

Publisher

NATURE PORTFOLIO
DOI: 10.1038/NCLIMATE2689

Keywords

-

Funding

  1. National Science Foundation (NSF)
  2. National Oceanic and Atmospheric Administration (NOAA)
  3. NERC [NE/I022841/1]
  4. NSF
  5. Directorate For Geosciences
  6. Div Atmospheric & Geospace Sciences [0955372] Funding Source: National Science Foundation
  7. Natural Environment Research Council [NE/I022841/1, ncas10009, NE/I020792/1] Funding Source: researchfish
  8. NERC [NE/I020792/1, NE/I022841/1] Funding Source: UKRI

Ask authors/readers for more resources

Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available