Precipitation variability increases in a warmer climate
By A. Pendergrass, Reto Knutti, Flavio Lehner, C. Deser, B. Sanderson. Scientific Reports, 2017
602 citations recorded by the source corpus.
Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle’s response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21st century, we find that in the global, multi-model mean, precipitation variability increases 3–4% K−1 globally, 4–5% K−1 over land and 2–4% K−1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.
Subfields: Atmospheric Science, Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/f13c9825b80a78d3f7792971dae0151b174b77f7
How researchers see this paper
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In Atmospheric Science
- Reto Knutti
- L. Brunner
- Flavio Lehner
- Erich Fischer
- C. Tebaldi
- Ed Hawkins
- G. J. van Oldenborgh
- Jochem Marotzke
In Global and Planetary Change
- Reto Knutti
- L. Brunner
- Flavio Lehner
- Erich Fischer
- C. Tebaldi
- Ed Hawkins
- G. J. van Oldenborgh
- Jochem Marotzke
In Water Science and Technology
Citations in the corpus
- Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6 (2020, background): “…that, one can also assess the contribution of any forced change in internal variability by comparing the time-evolving variability across ensemble members with the constant variability from present-day or a control simulation (Pendergrass et al., 2017; Maher et al., 2018; Schlunegger et al., 2020).”
- Anthropogenic influence on the drivers of the Western Cape drought 2015–2017 (2018, background): “…southern South Africa is also among the few regions where precipitation variability on daily to interannual time scales is expected to decrease with warming (Pendergrass et al 2017) a decrease that has been in fact already detected in a broader defined South African region (Gergis andHenley 2017).”