Assessment of future changes in water availability and aridity

Greve, Peter; Seneviratne, Sonia I.

doi:10.1002/2015gl064127

Cited by 155 publications

(144 citation statements)

References 30 publications

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“…Although empirical studies suggest that the overall magnitude of PE using this Priestley-Taylor coefficient of α = 1.26 will bring estimates within closer proximity to models that include an aerodynamic component, spatial and temporal variability in estimates will only reflect variation in T a and R n . In forests, α must be modified [30,31], yet it is still a useful concept if it is recognized that there is no universal value of α. Lastly, other studies express PE based solely on a function of R n [32], or solely based on D a [33].…”

Section: Introductionmentioning

confidence: 99%

“…The Penman-Monteith model is widely applied [35][36][37][38]. Other studies represent potential evapotranspiraiton based on the Priestley-Taylor model [30,39], or close equivalents based on R n and T a [25,40], or R n alone [32], or D a alone [41,42]. Despite its importance in modelling the surface water balance and subsequent application in ecological research, differences in the variation of evaporative demand resulting from these approaches, including long-term trends at the regional scale, are not well documented.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and Temporal Variability of Potential Evaporation across North American Forests

2017

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Given the widespread ecological implications that would accompany any significant change in evaporative demand of the atmosphere, this study investigated spatial and temporal variation in several accepted expressions of potential evaporation (PE). The study focussed on forest regions of North America, with 1 km-resolution spatial coverage and a monthly time step, from 1951-2014. We considered Penman's model (E Pen ), the Priestley-Taylor model (E PT ), 'reference' rates based on the Penman-Monteith model for grasslands (E RG ), and reference rates for forests that are moderately coupled (E RFu ) and well coupled (E RFc ) to the atmosphere. To give context to the models, we also considered a statistical fit (E PanFit ) to measurements of pan evaporation (E Pan ). We documented how each model compared with E Pan , differences in attribution of variance in PE to specific driving factors, mean spatial patterns, and time trends from 1951-2014. The models did not agree strongly on the sensitivity to underlying drivers, zonal variation of PE, or on the magnitude of trends from 1951-2014. Sensitivity to vapour pressure deficit (D a ) differed among models, being absent from E PT and strongest in E RFc . Time trends in reference rates derived from the Penman-Monteith equation were highly sensitive to how aerodynamic conductance was set. To the extent that E PanFit accurately reflects the sensitivity of PE to D a over land surfaces, future trends in PE based on the Priestley-Taylor model may underestimate increasing evaporative demand, while reference rates for forests, that assume strong canopy-atmosphere coupling in the Penman-Monteith model, may overestimate increasing evaporative demand. The resulting historical database, covering the spectrum of different models of PE applied in modern studies, can serve to further investigate biosphere-hydroclimate relationships across North America.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variability of Potential Evaporation across North American Forests

2017

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“…In addition, we provide analyses for changes in precipitation minus evapotranspiration (P −E) as a further measure of changes in land water availability (e.g. Greve and Seneviratne, 2015).…”

Section: Climate and Extremes Indicesmentioning

confidence: 99%

Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

et al. 2017

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Abstract. This article extends a previous study (Seneviratne et al., 2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and watercycle indices and their changes as a function of global warming. These projections are based on simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global mean temperature targets, such as the 2 and 1.5 • limits agreed within the 2015 Paris Agreement.

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“…The models' simulation of global precipitation is generally less accurate than that of temperature [21,22]. At regional scales, the simulation of precipitation is even more problematic, very likely due to large uncertainties in the modeling of aerosol and cloud processes.…”

Section: Cmip5 Climate Models Simulationsmentioning

confidence: 99%

Observed and Projected Precipitation Changes over the Nine US Climate Regions

et al. 2017

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Abstract:We analyze the past temperature and precipitation changes in nine separate US climate regions. We find that the temperature increased in a statistically significant (95% confidence level equivalent to alpha level of 0.05) manner in all of these regions. However, the variability in the observed precipitation was much more complex. In the eastern US (east of Rocky Mountains), the precipitation increased in all five climate regions and the increase was statistically significant in three of them. In contract, in the western US, the precipitation increased in two regions and decreased in two with no statistical significance in any region. The CMIP5 climate models (an ensemble mean) were not able to capture properly either the large precipitation differences between the eastern and the western US, or the changes of precipitation between 1900 and 2015 in eastern US. The statistical regression model explains the differences between the eastern and western US precipitation as results of different significant predictors. The anthropogenic greenhouse gases and aerosol (GHGA) are the major forcing of the precipitation in the eastern part of US, while the Pacific Decadal Oscillation (PDO) has the major influence on precipitation in the western part of the US. Our analysis suggests that the precipitation over the eastern US increased at an approximate rate of 6.7%/K, in agreement with the Clausius-Clapeyron equation, while the precipitation of the western US was approximately constant, independent of the temperature. Future precipitation over the western part of the US will depend on the behavior of the PDO, and how it (PDO) may be affected by future warming. Low hydrological sensitivity (percent increase of precipitation per one K of warming) projected by the CMIP5 models for the eastern US suggests either an underestimate of future precipitation or an overestimate of future warming.

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Assessment of future changes in water availability and aridity

Cited by 155 publications

References 30 publications

Spatial and Temporal Variability of Potential Evaporation across North American Forests

Spatial and Temporal Variability of Potential Evaporation across North American Forests

Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

Observed and Projected Precipitation Changes over the Nine US Climate Regions

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