| 1. |
- Li, Wantong, et al.
(författare)
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Contrasting Drought Propagation Into the Terrestrial Water Cycle Between Dry and Wet Regions
- 2023
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Ingår i: Earth's Future. - 2328-4277. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Drought's intensity and duration have increased in many regions over the last decades. However, the propagation of drought-induced water deficits through the terrestrial water cycle is not fully understood at a global scale. Here we study responses of monthly evaporation (ET) and runoff to soil moisture droughts occurring between 2001 and 2015 using independent gridded datasets based on machine learning-assisted upscaling of satellite and in-situ observations. We find that runoff and ET show generally contrasting drought responses across climate regimes. In wet regions, runoff is strongly reduced while ET is decoupled from soil moisture decreases and enhanced by sunny and warm weather typically accompanying soil moisture droughts. In drier regions, ET is reduced during droughts due to vegetation water stress, while runoff is largely unchanged as precipitation deficits are typically low in these regions and ET decreases are buffering runoff reductions. While these water flux drought responses are controlled by the large-scale climate regimes, they are additionally modulated by local vegetation characteristics. Land surface models capture the observed water cycle responses to drought in the case of runoff, but not for ET where the ET deficit (surplus) is overestimated (underestimated), related to a misrepresentation of the general soil moisture-evaporation interplay. In summary, our study illustrates how the joint analysis of machine learning-enhanced Earth observations can advance the understanding of global eco-hydrological processes, as well as the validation of land surface models.
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| 2. |
- Orth, Rene, et al.
(författare)
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Does model performance improve with complexity? : A case study with three hydrological models
- 2015
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Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694 .- 1879-2707. ; 523, s. 147-159
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Tidskriftsartikel (refereegranskat)abstract
- In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts). (C) 2015 The Authors. Published by Elsevier B.V.
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| 3. |
- Orth, René, et al.
(författare)
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Drought reduces blue-water fluxes more strongly than green-water fluxes in Europe
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Drought comprehensively affects different interlinked aspects of the terrestrial water cycle, which have so far been mostly investigated without direct comparison. Resolving the partitioning of water deficit during drought into blue-water runoff and green-water evapotranspiration fluxes is critical, as anomalies in these fluxes threaten different associated societal sectors and ecosystems. Here, we analyze the propagation of drought-inducing precipitation deficits through soil moisture reductions to their impacts on blue and green water fluxes by use of comprehensive multi-decadal data from > 400 near-natural catchments along a steep climate gradient across Europe. We show that soil-moisture drought reduces runoff stronger and faster than it reduces evapotranspiration over the entire continent. While runoff responds within weeks, evapotranspiration can be unaffected for months. Understanding these drought-impact pathways across blue and green-water fluxes and geospheres is essential for ensuring food and water security, and developing early-warning and adaptation systems in support of society and ecosystems.
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| 4. |
- Orth, René, et al.
(författare)
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Large-scale biospheric drought response intensifies linearly with drought duration in arid regions
- 2020
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 17:9, s. 2647-2656
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Tidskriftsartikel (refereegranskat)abstract
- Soil moisture droughts have comprehensive implications for terrestrial ecosystems. Here we study time-accumulated impacts of the strongest observed droughts on vegetation. The results show that drought duration, the time during which surface soil moisture is below seasonal average, is a key diagnostic variable for predicting drought-integrated changes in (i) gross primary productivity, (ii) evapotranspiration, (iii) vegetation greenness, and (iv) crop yields. Drought-integrated anomalies in these vegetation-related variables scale linearly with drought duration with a slope depending on climate. In arid regions, the slope is steep such that vegetation drought response intensifies with drought duration, whereas in humid regions, it is small such that drought impacts on vegetation are weak even for long droughts. These emergent large-scale linearities are not well captured by state-of-the-art hydrological, land surface, and vegetation models. Overall, the linear relationship of drought duration versus vegetation response and crop yield reductions can serve as a model benchmark and support drought impact interpretation and prediction.
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| 5. |
- Schewe, Jacob, et al.
(författare)
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State-of-the-art global models underestimate impacts from climate extremes
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
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| 6. |
- Wartenburger, Richard, et al.
(författare)
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Evapotranspiration simulations in ISIMIP2a-Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets
- 2018
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:7
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Tidskriftsartikel (refereegranskat)abstract
- Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%-40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.
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