Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective

Xiong, Jinghua; Chen, Jie; Yin, Jiabo

doi:10.5194/hess-26-6457-2022

Cited by 20 publications

(4 citation statements)

References 127 publications

(141 reference statements)

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“…The spatial pattern of these changes in extreme precipitation closely follows the overall pattern of annual precipitation changes, as discussed in (IPCC, 2021). In essence, regions that were already dry are experiencing increased aridity, while areas with high climatological levels of precipitation are becoming even wetter (Feng and Zhang, 2015;Xiong et al, 2022). To provide a more detailed understanding of the total changes highlighted in Figure 3, one can decompose these changes into two components: changes in 155 variability (as shown in Figure 4) and changes in the mean state (as shown in Figure 5).…”

Section: Changes In Extreme Events Under Global Warmingmentioning

confidence: 99%

Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

Nordling,

Fahrenbach,

Samset

2024

Preprint

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Abstract. As global warming progresses, weather conditions like daily temperature and precipitation are changing due to changes in their means and distributions of day-to-day variability. In this study, we show that changes in variability have a stronger influence on the number of extreme precipitation days than the change in the mean state in many locations. We analyze daily precipitation and maximum temperatures at four levels of global warming and under different emission scenarios for the Northern Hemisphere (NH) summer (June – August). Our analysis is based on initial condition large ensemble simulations from three fully coupled Earth System Models (MPI-ESM1-2-LR, CanESM5, and ACCESS-ESM1-5) contributing to the Climate Model Inter-comparison Project phase 6 (CMIP6). We also use information from the Precipitation Driver Response Model Intercomparison Project (PDRMIP) to discern the influence of different climate drivers (notably aerosols and greenhouse gases). We decompose the total changes in daily NH summer precipitation and daily maximum temperature into mean and variability components (standard deviation and skewness). Our results show that in many locations, variability exerts a stronger influence than mean changes on daily precipitation. Changes in the widths and shapes of precipitation distributions are especially dominating over mean changes in Asia, the Arctic and Sub-Saharan Africa. In contrast, temperature changes are primarily driven by changes in the mean state. For the near future (2020–2040), we find that reductions in aerosol emissions would increase the likelihood of extreme summertime precipitation only over Asia. This study emphasizes the importance of incorporating daily variability changes into climate change impact assessments and advocates that future emulator and impact model development should focus on improving the representation of daily variability.

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Section: Changes In Extreme Events Under Global Warmingmentioning

confidence: 99%

Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

Nordling,

Fahrenbach,

Samset

2024

Preprint

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“…In particular, ET-WB is prone to overestimate the trends for regions with increasing ET, and the overestimations are larger if the trends are larger (based on other ET datasets), and vice versa. In a nutshell, unlike TWS/P -based evaluation (Held and Soden, 2006;Xiong et al, 2022b), the "dry gets drier and wet gets wetter" paradigm can be typically inferred from ET-WB on a basin scale, which generally exaggerates the prevailing increasing/decreasing ET tendencies in the basins (Yang et al, 2019). On a global scale, the median value of trend estimates from ET-WB ensemble members is 1 mm yr −2 , very close to the results from GLEAM (0.8 mm yr −2 ) and WGHM (0.8 mm yr −2 ).…”

Section: Spatiotemporal Variation Of Et-wbmentioning

confidence: 99%

ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins

Xiong,

Xu,

Chandanpurkar

et al. 2023

Earth Syst. Sci. Data

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Abstract. Evaporation (ET) is one of the crucial components of the water cycle, which serves as the nexus between global water, energy, and carbon cycles. Accurate quantification of ET is, therefore, pivotal in understanding various earth system processes and subsequent societal applications. The prevailing approaches for ET retrievals are either limited in spatiotemporal coverage or largely influenced by the choice of input data or simplified model physics, or a combination thereof. Here, using an independent mass conservation approach, we develop water-balance-based ET datasets (ET-WB) for the global land and the selected 168 major river basins. We generate 4669 probabilistic unique combinations of the ET-WB leveraging multi-source datasets (23 precipitation, 29 runoff, and 7 storage change datasets) from satellite products, in situ measurements, reanalysis, and hydrological simulations. We compare our results with the four auxiliary global ET datasets and previous regional studies, followed by a rigorous discussion of the uncertainties, their possible sources, and potential ways to constrain them. The seasonal cycle of global ET-WB possesses a unimodal distribution with the highest (median value: 65.61 mm per month) and lowest (median value: 36.11 mm per month) values in July and January, respectively, with the spread range of roughly ±10 mm per month from different subsets of the ensemble. Auxiliary ET products illustrate similar intra-annual characteristics with some over- or underestimation, which are completely within the range of the ET-WB ensemble. We found a gradual increase in global ET-WB from 2003 to 2010 and a subsequent decrease during 2010–2015, followed by a sharper reduction in the remaining years primarily attributed to the varying precipitation. Multiple statistical metrics show reasonably good accuracy of monthly ET-WB (e.g., a relative bias of ±20 %) in most river basins, which ameliorates at annual scales. The long-term mean annual ET-WB varies within 500–600 mm yr−1 and is consistent with the four auxiliary ET products (543–569 mm yr−1). Observed trend estimates, though regionally divergent, are evidence of the increasing ET in a warming climate. The current dataset will likely be useful for several scientific assessments centering around water resources management to benefit society at large. The dataset is publicly available in various formats (NetCDF, Mat, and Shapefile) at https://doi.org/10.5281/zenodo.8339655 (Xiong et al., 2023).

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“…The global hydrological cycle has experienced considerable changes due to climate change and anthropogenic interventions, exerting a tremendous impact on agriculture, ecological environment, and freshwater availability globally (Shugar et al, 2020;Perera et al, 2020;Gampe et al, 2021). Assessing the variations of constituent components of the water cycle, namely, precipitation (P ), evapotranspiration (E), runoff (R), and storage change, is therefore crucial in understanding the systematic hydrological response and dealing with water-related issues in the context of global change (Moreno-Jimenez et al, 2019;Zhao et al, 2021;Yin et al, 2022). Under these circumstances, the "dry gets drier, and wet gets wetter" (DDWW) paradigm, firstly introduced by Held and Soden (2006), has become one of the most widely used hypotheses to summarize the long-term trends in the global hydrological cycle (Roderick et al, 2014;Yang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

A re-examination of the dry gets drier and wet gets wetter paradigm over global land: insight from terrestrial water storage changes

Xiong

Guo

Chen

et al. 2022

Preprint

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Abstract. The “dry gets drier and wet gets wetter” (DDWW) paradigm has been widely used to summarise the expected trends of the global hydrologic cycle under climate change. However, the paradigm is challenged over land due to the choice of different metrics and datasets used and is still unexplored from the perspective of terrestrial water storage anomaly (TWSA). Considering the essential role of TWSA in wetting and drying of the land system, here we built upon a large ensemble of TWSA datasets, including satellite-based products, global hydrological models, land surface models, and global climate models to evaluate the DDWW hypothesis during the historical (1985–2014) and future (2071–2100) periods under various scenarios with a 0.05 significance level. We find that 28.1 % of global land confirms the DDWW paradigm, while 23.3 % of the area shows the opposite pattern during the historical period. In the future, the DDWW paradigm is still challenged with the percentage supporting the pattern lower than 20 %, and both the DDWW-validated and DDWW-opposed proportion increase along with the intensification of emission scenarios. The different choices of data sources and varying significance levels (0.01–0.1) have subtle influences on the evaluation results of the DDWW paradigm. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWSA under climate change.

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Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective

Cited by 20 publications

References 127 publications

Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins

A re-examination of the dry gets drier and wet gets wetter paradigm over global land: insight from terrestrial water storage changes

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