Abstract

All currently available climate models predict a near-surface warming trend under the influence of rising levels of greenhouse gases in the atmosphere. In addition to the direct effects on climate--for example, on the frequency of heatwaves--this increase in surface temperatures has important consequences for the hydrological cycle, particularly in regions where water supply is currently dominated by melting snow or ice. In a warmer world, less winter precipitation falls as snow and the melting of winter snow occurs earlier in spring. Even without any changes in precipitation intensity, both of these effects lead to a shift in peak river runoff to winter and early spring, away from summer and autumn when demand is highest. Where storage capacities are not sufficient, much of the winter runoff will immediately be lost to the oceans. With more than one-sixth of the Earth's population relying on glaciers and seasonal snow packs for their water supply, the consequences of these hydrological changes for future water availability--predicted with high confidence and already diagnosed in some regions--are likely to be severe.

Keywords

SnowEnvironmental sciencePrecipitationSurface runoffGlacierSnowmeltClimate changeWater cycleSpring (device)Global warmingGreenhouse gasCryosphereClimatologyPopulationAtmospheric sciencesPhysical geographyGeographyGeologyMeteorologyEcologySea iceOceanography

MeSH Terms

AerosolsAnimalsGeographyGreenhouse EffectHumansIce CoverModelsTheoreticalRainSalmonSeasonsSnowWater Supply

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Publication Info

Year
2005
Type
article
Volume
438
Issue
7066
Pages
303-309
Citations
4708
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

4708
OpenAlex
207
Influential
3746
CrossRef

Cite This

T. P. Barnett, J. C. Adam, Dennis P. Lettenmaier (2005). Potential impacts of a warming climate on water availability in snow-dominated regions. Nature , 438 (7066) , 303-309. https://doi.org/10.1038/nature04141

Identifiers

DOI
10.1038/nature04141
PMID
16292301

Data Quality

Data completeness: 86%