4.8 Article

Patterns of the seasonal response of tropical rainfall to global warming

期刊

NATURE GEOSCIENCE
卷 6, 期 5, 页码 357-361

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NATURE PORTFOLIO
DOI: 10.1038/NGEO1792

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资金

  1. National Basic Research Program of China [2012CB955604, 2010CB950403]
  2. Natural Science Foundation of China [41105047, 41275083]
  3. US National Science Foundation
  4. Div Atmospheric & Geospace Sciences
  5. Directorate For Geosciences [1305719] Funding Source: National Science Foundation

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Tropical convection is an important factor in regional climate variability and change around the globe(1,2). The response of regional precipitation to global warming is spatially variable, and state-of-the-art model projections suffer large uncertainties in the geographic distribution of precipitation changes(3-5). Two views exist regarding tropical rainfall change: one predicts increased rainfall in presently rainy regions (wet-get-wetter)(6-8), and the other suggests increased rainfall where the rise in sea surface temperature exceeds the mean surface warming in the tropics (warmer-get-wetter)(9-12). Here we analyse simulations with 18 models from the Coupled Model Intercomparison Project (CMIP5), and present a unifying view for seasonal rainfall change. We find that the pattern of ocean warming induces ascending atmospheric flow at the Equator and subsidence on the flanks, anchoring a band of annual mean rainfall increase near the Equator that reflects the warmer-get-wetter view. However, this climatological ascending motion marches back and forth across the Equator with the Sun, pumping moisture upwards from the boundary layer and causing seasonal rainfall anomalies to follow a wet-get-wetter pattern. The seasonal mean rainfall, which is the sum of the annual mean and seasonal anomalies, thus combines the wet-get-wetter and warmer-get-wetter trends. Given that precipitation climatology is well observed whereas the pattern of ocean surface warming is poorly constrained(13,14), our results suggest that projections of tropical seasonal mean rainfall are more reliable than the annual mean.

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