scholarly journals Moderate runoff extremes in Swiss rivers and their seasonal occurrence in a changing climate

2021 ◽  
Author(s):  
Regula Muelchi ◽  
Ole Rössler ◽  
Jan Schwanbeck ◽  
Rolf Weingartner ◽  
Olivia Martius
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Models ◽  
Climate Model ◽  
Late Summer ◽  
Climate Change Scenarios ◽  
Low Flows ◽  
Glacier Melt ◽  
High Flows ◽  
Alpine Catchments

Abstract. Future changes in runoff impact many sectors such as agriculture, energy production, or ecosystems. Therefore, assessments of runoff characteristics under climate change are crucial for decision-makers and water management planners. We study changes in moderate runoff extremes, i.e. low and high flows that occur once every year or season in today's climate. Daily runoff is simulated for 93 Swiss catchments for the period 1981–2099 under the Representative Concentration Pathway 8.5 using 20 downscaled regional climate models from the newest transient Swiss climate change scenarios. The magnitude of moderate annual low flows is projected to decrease in lower lying catchments and to increase in Alpine catchments. Seasonal low flows in summer are projected to decrease and seasonal low flows in winter to increase. Moderate annual high flows are projected to slightly increase in most catchments but to decrease in high Alpine catchments. However, the climate model agreement on the sign of change in moderate high flows is not robust. The projected decrease in Alpine catchments contradicts results for extreme high flows from previous studies. This difference may be due to different indicators used (moderate extremes vs. extremes). The time of emergence indicates the timing of significant changes in the flow magnitudes. For low flows the time of emergence is early in 21st century in high Alpine catchments due to early changes in winter low flows. In lower lying catchments, significant changes in low flows emerge later in the century. For moderate high flows, only few catchments indicate a significant change. Shifts in the seasonality of moderate low flows due to climate change are found in many catchments. By end of the 21st century, low flows are projected to occur in late summer and early autumn in most catchments indicating that the lack of precipitation in summer and autumn exceeds the contributions from other processes such as snow and glacier melt contributions. For moderate high flows, changes in seasonality are found in Alpine catchments with a shift towards earlier occurrence in summer due to a reduced contribution of snow and glacier melt in summer. In the projections, low flows occur more frequently in lower lying catchments and less frequently in Alpine catchments. For high flows the frequency increases slightly in most catchments, but models often disagree on the sign of change. Changes in the annual co-occurrence of moderate low and high flows are mainly due to changes in the frequency of low flows that increases in lower lying catchments and decreases in Alpine catchments.

scholarly journals River runoff in Switzerland in a changing climate – changes in moderate extremes and their seasonality

2021 ◽  
Vol 25 (6) ◽  
pp. 3577-3594
Author(s):  
Regula Muelchi ◽  
Ole Rössler ◽  
Jan Schwanbeck ◽  
Rolf Weingartner ◽  
Olivia Martius
Keyword(s):  
Climate Change ◽  
21St Century ◽  
River Runoff ◽  
Climate Model ◽  
Low Flows ◽  
Glacier Melt ◽  
Winter Half ◽  
Summer Half ◽  
High Flows ◽  
Alpine Catchments

Abstract. Future changes in river runoff will impact many sectors such as agriculture, energy production, or ecosystems. Here, we study changes in the seasonality, frequency, and magnitude of moderate low and high flows and their time of emergence. The time of emergence indicates the timing of significant changes in the flow magnitudes. Daily runoff is simulated for 93 Swiss catchments for the period 1981–2099 under Representative Concentration Pathway 8.5 with 20 climate model chains from the most recent transient Swiss Climate Change Scenarios. In the present climate, annual low flows typically occur in the summer half-year in lower-lying catchments (<1500 m a.s.l.) and in the winter half-year in Alpine catchments (>1500 m a.s.l.). By the end of the 21st century, annual low flows are projected to occur in late summer and early autumn in most catchments. This indicates that decreasing precipitation and increasing evapotranspiration in summer and autumn exceed the water contributions from other processes such as snowmelt and glacier melt. In lower-lying catchments, the frequency of annual low flows increases, but their magnitude decreases and becomes more severe. In Alpine catchments, annual low flows occur less often and their magnitude increases. The magnitude of seasonal low flows is projected to decrease in the summer half-year in most catchments and to increase in the winter half-year in Alpine catchments. Early time of emergence is found for annual low flows in Alpine catchments in the 21st century due to early changes in low flows in the winter half-year. In lower-lying catchments, significant changes in low flows emerge later in the century. Annual high flows occur today in lower-lying catchments in the winter half-year and in Alpine catchments in the summer half-year. Climate change will change this seasonality mainly in Alpine catchments with a shift towards earlier seasonality in summer due to the reduced contribution of snowmelt and glacier melt in summer. Annual high flows tend to occur more frequent, and their magnitude increases in most catchments except some Alpine catchments. The magnitude of seasonal high flows in most catchments is projected to increase in the winter half-year and to decrease in the summer half-year. However, the climate model agreement on the sign of change in moderate high flows is weak.

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

scholarly journals Assessment of extreme flows and uncertainty under climate change: disentangling the uncertainty contribution of representative concentration pathways, global climate models and internal climate variability

2020 ◽  
Vol 24 (6) ◽  
pp. 3251-3269 ◽  
Author(s):  
Chao Gao ◽  
Martijn J. Booij ◽  
Yue-Ping Xu
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Internal Climate Variability ◽  
Low Flows ◽  
Uncertainty Sources ◽  
High Flows

Abstract. Projections of streamflow, particularly of extreme flows under climate change, are essential for future water resources management and the development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explored the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, eastern China. ANOVA (analysis of variance) was employed to quantify the contribution of different uncertainty sources from RCPs (representative concentration pathways), GCMs (global climate models) and internal climate variability, using an ensemble of 4 RCP scenarios, 9 GCMs and 1000 simulated realizations of each model–scenario combination by SDRM-MCREM (a stochastic daily rainfall model coupling a Markov chain model with a rainfall event model). The results show that annual mean flow and high flows are projected to increase and that low flows will probably decrease in 2041–2070 (2050s) and 2071–2100 (2080s) relative to the historical period of 1971–2000, suggesting a higher risk of floods and droughts in the future in the Qu River basin, especially for the late 21st century. Uncertainty in mean flows is mostly attributed to GCM uncertainty. For high flows and low flows, internal climate variability and GCM uncertainty are two major uncertainty sources for the 2050s and 2080s, while for the 2080s, the effect of RCP uncertainty becomes more pronounced, particularly for low flows. The findings in this study can help water managers to become more knowledgeable about and get a better understanding of streamflow projections and support decision making regarding adaptations to a changing climate under uncertainty in the Qu River basin.

scholarly journals Spectral representation of the annual cycle in the climate change signal

2011 ◽  
Vol 15 (9) ◽  
pp. 2777-2788 ◽  
Author(s):  
T. Bosshard ◽  
S. Kotlarski ◽  
T. Ewen ◽  
C. Schär
Keyword(s):  
Climate Change ◽  
Annual Cycle ◽  
Climate Models ◽  
Climate Model ◽  
Climate Impact ◽  
Climate Change Signal ◽  
Climate Change Scenarios ◽  
Regional Climate Model Output ◽  
Spectral Smoothing ◽  
Precipitation Changes

Abstract. The annual cycle of temperature and precipitation changes as projected by climate models is of fundamental interest in climate impact studies. Its estimation, however, is impaired by natural variability. Using a simple form of the delta change method, we show that on regional scales relevant for hydrological impact models, the projected changes in the annual cycle are prone to sampling artefacts. For precipitation at station locations, these artefacts may have amplitudes that are comparable to the climate change signal itself. Therefore, the annual cycle of the climate change signal should be filtered when generating climate change scenarios. We test a spectral smoothing method to remove the artificial fluctuations. Comparison against moving monthly averages shows that sampling artefacts in the climate change signal can successfully be removed by spectral smoothing. The method is tested at Swiss climate stations and applied to regional climate model output of the ENSEMBLES project. The spectral method performs well, except in cases with a strong annual cycle and large relative precipitation changes.

scholarly journals Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for regional climate scenarios: a case study for West-Central Europe

2005 ◽  
Vol 5 (4) ◽  
pp. 7415-7455 ◽  
Author(s):  
A. P. van Ulden ◽  
G. J. van Oldenborgh
Keyword(s):  
Climate Change ◽  
20Th Century ◽  
Central Europe ◽  
21St Century ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Scenarios ◽  
Model Simulations ◽  
Circulation Changes

Abstract. The credibility of regional climate change predictions for the 21st century depends on the ability of climate models to simulate global and regional circulations in a realistic manner. To investigate this issue, a large set of global coupled climate model experiments prepared for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change has been studied. First we compared 20th century model simulations of longterm mean monthly sea level pressure patterns with ERA-40. We found a wide range in performance. Many models performed well on a global scale. For northern midlatitudes and Europe many models showed large errors, while other models simulated realistic pressure fields. Next we focused on the monthly mean climate of West-Central Europe in the 20th century. In this region the climate depends strongly on the circulation. Westerlies bring temperate weather from the Atlantic Ocean, while easterlies bring cold spells in winter and hot weather in summer. In order to be credible for this region, a climate model has to show realistic circulation statistics in the current climate, and a response of temperature and precipitation variations to circulation variations that agrees with observations. We found that even models with a realistic mean pressure pattern over Europe still showed pronounced deviations from the observed circulation distributions. In particular, the frequency distributions of the strength of westerlies appears to be difficult to simulate well. This contributes substantially to biases in simulated temperatures and precipitation, which have to be accounted for when comparing model simulations with observations. Finally we considered changes in climate simulations between the end of the 20th century and the end of the 21st century. Here we found that changes in simulated circulation statistics play an important role in climate scenarios. For temperature, the warm extremes in summer and cold extremes in winter are most sensitive to changes in circulation, because these extremes depend strongly on the simulated frequency of eastery flow. For precipitation, we found that circulation changes have a substantial influence, both on mean changes and on changes in the probability of wet extremes and of long dry spells. Because we do not know how reliable climate models are in their predictions of circulation changes, climate change predictions for Europe are as yet uncertain in many aspects.

scholarly journals New Zealand River Hydrology under Late 21st Century Climate Change

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2175
Author(s):  
Daniel B. G. Collins
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
21St Century ◽  
Climate Model ◽  
Water Cycle ◽  
Well Being ◽  
Cultural Economic ◽  
Low Flows ◽  
Late 21St Century ◽  
The Mean

Climate change is increasingly affecting the water cycle and as freshwater plays a vital role in countries’ societal and environmental well-being it is important to develop national assessments of potential climate change impacts. Focussing on New Zealand, a climate-hydrology model cascade is used to project hydrological impacts of late 21st century climate change at 43,862 river locations across the country for seven hydrological metrics. Mean annual and seasonal river flows validate well across the whole model cascade, and the mean annual floods to a lesser extent, while low flows exhibit a large positive bias. Model projections show large swathes of non-significant effects across the country due to interannual variability and climate model uncertainty. Where changes are significant, mean annual, autumn, and spring flows increase along the west and south and decrease in the north and east. The largest and most extensive increases occur during winter, while during summer decreasing flows outnumber increasing. The mean annual flood increases more in the south, while mean annual low flows show both increases and decreases. These hydrological changes are likely to have important long-term implications for New Zealand’s societal, cultural, economic, and environmental well-being.

scholarly journals Permafrost Degradation within Eastern Chukotka CALM Sites in the 21st Century Based on CMIP5 Climate Models

Geosciences ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 232 ◽  
Author(s):  
Alexey Maslakov ◽  
Natalia Shabanova ◽  
Dmitry Zamolodchikov ◽  
Vasili Volobuev ◽  
Gleb Kraev
Keyword(s):  
Climate Change ◽  
Layer Thickness ◽  
Active Layer ◽  
21St Century ◽  
Climate Models ◽  
Climate Scenario ◽  
Active Layer Thickness ◽  
Climate Change Scenarios ◽  
Permafrost Degradation ◽  
Degradation Rates

Permafrost degradation caused by contemporary climate change significantly affects arctic regions. Active layer thickening combined with the thaw subsidence of ice-rich sediments leads to irreversible transformation of permafrost conditions and activation of exogenous processes, such as active layer detachment, thermokarst and thermal erosion. Climatic and permafrost models combined with a field monitoring dataset enable the provision of predicted estimations of the active layer and permafrost characteristics. In this paper, we present the projections of active layer thickness and thaw subsidence values for two Circumpolar Active Layer Monitoring (CALM) sites of Eastern Chukotka coastal plains. The calculated parameters were used for estimation of permafrost degradation rates in this region for the 21st century under various IPCC climate change scenarios. According to the studies, by the end of the century, the active layer will be 6–13% thicker than current values under the RCP (Representative Concentration Pathway) 2.6 climate scenario and 43–87% under RCP 8.5. This process will be accompanied by thaw subsidence with the rates of 0.4–3.7 cm∙a−1. Summarized surface level lowering will have reached up to 5 times more than current active layer thickness. Total permafrost table lowering by the end of the century will be from 150 to 310 cm; however, it will not lead to non-merging permafrost formation.

scholarly journals Spectral representation of the annual cycle in the climate change signal

2011 ◽  
Vol 8 (1) ◽  
pp. 1161-1192 ◽  
Author(s):  
T. Bosshard ◽  
S. Kotlarski ◽  
T. Ewen ◽  
C. Schär
Keyword(s):  
Climate Change ◽  
Annual Cycle ◽  
Climate Models ◽  
Climate Model ◽  
Climate Impact ◽  
Climate Change Signal ◽  
Climate Change Scenarios ◽  
Regional Climate Model Output ◽  
Spectral Smoothing ◽  
Precipitation Changes

Abstract. The annual cycle of temperature and precipitation changes as projected by climate models is of fundamental interest in climate impact studies. Its estimation, however, is impaired by natural variability. Using a simple form of the delta change method, we show that on regional scales relevant for hydrological impact models, the projected changes in the annual cycle are prone to sampling artefacts. For precipitation at station locations, these artefacts may have amplitudes that are comparable to the climate change signal itself. Therefore, the annual cycle of the climate change signal should be filtered when generating climate change scenarios. We test a spectral smoothing method to remove the artificial fluctuations. Comparison against moving monthly averages shows that sampling artefacts in the climate change signal can successfully be removed by spectral smoothing. The method is tested at Swiss climate stations and applied to regional climate model output of the ENSEMBLES project. The spectral method performs well, except in cases with a strong annual cycle and large relative precipitation changes.

scholarly journals A new dataset for systematic assessments of climate change impacts as a function of global warming

2012 ◽  
Vol 5 (4) ◽  
pp. 3533-3572 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Political Debate ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalized patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilize a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

scholarly journals Antarctic precipitation and climate-change predictions: horizontal resolution and margin vs plateau issues

2009 ◽  
Vol 50 (50) ◽  
pp. 55-60 ◽  
Author(s):  
C. Genthon ◽  
G. Krinner ◽  
H. Castebrunet
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Models ◽  
Prediction Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Horizontal Resolution ◽  
Intergovernmental Panel ◽  
Precipitation Increase ◽  
Antarctic Precipitation

AbstractAll climate models participating in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, as made available by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) as the Coupled Model Intercomparison Project 3 (CMIP3) archive, predict a significant surface warming of Antarctica by the end of the 21st century under a moderate (SRESA1B) greenhouse-gas scenario. All models but one predict a concurrent precipitation increase but with a large scatter of results. The models with finer horizontal resolution tend to predict a larger precipitation increase. Because modeled Antarctic surface mass balance is known to be sensitive to horizontal resolution, extrapolating predictions from the different models with respect to model resolution may provide simple yet better multi-model estimates of Antarctic precipitation change than mere averaging or even more complex approaches. Using such extrapolation, a conservative estimate of the predicted precipitation increase at the end of the 21st century is +30 kg m–2 a–1 on the grounded ice sheet, corresponding to a >1m ma–1 sea-level rise. About three-quarters of this rise originates from the marginal regions of the Antarctic ice sheet with surface elevation below 2250 m. This is where field programs are most urgently needed to better understand and monitor accumulation at the surface of Antarctica, and to improve and verify prediction models.

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