On the independence from the emission pathway of the projected changes of river runoff

2020 ◽  
Author(s):  
Lorenzo Mentaschi ◽  
Lorenzo Alfieri ◽  
Francesco Dottori ◽  
Carmelo Cammalleri ◽  
Berny Bisselink ◽  
...  
Keyword(s):  
Climate Model ◽  
Statistical Significance ◽  
Regional Climate ◽  
Time Frame ◽  
Climate Impact ◽  
The Other ◽  
Minor Role ◽  
Emission Pathway ◽  
Projected Change ◽  
Projected Changes

<p><span>After the Paris Agreement of 2015 many studies on climate impact assessment, e.g. of floods, water resources and droughts, focused on understanding the projected changes at the time frame when a specific warming level is reached. The results of these studies assume that the pathway to reach a certain greenhouse concentration and corresponding warming level plays a minor role in the change of the physical variables that define the hazard. However, this hypothesis should be verified for each variable, as the links between the timing of the warming levels and the projected changes of the geophysical variables are not yet fully understood. To address this gap, in this contribution we compared the projected changes of annual mean, extreme high and extreme low river discharges in Europe at 1.5°C and 2°C under scenarios RCP8.5 and RCP4.5 from an ensemble of Regional Climate Model simulations. The statistical significance of the difference between the two scenarios for both warming levels has been then evaluated versus the other sources of uncertainty, through an Analysis of Variance (ANOVA). The results show that in the majority of Europe (>95% of the surface area for the annual mean discharge, >98% for high and low extremes), the differences in the changes projected in the two pathways are statistically small. These results suggest that in studies of changes at specific warming levels the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the merged ensemble, findings show that the projected changes of annual mean, extreme high and extreme low river discharges are statistically significant in large portions of Europe. Merging the 2 pathways comes with a two-fold advantage with respect to the separate treatment of the 2 scenarios. On the one hand, it improves the estimation of the statistical significance of the projected change, by increasing its size and by better taking into account the pathway-related uncertainty (the emission pathways are set ex-ante as a hypothesis for the CMIP experiment, and the related uncertainty is usually neglected). On the other hand, a multi-pathway ensemble can simplify the discussion of the projected changes by removing from the analysis the dependency from the emission pathway, and making the results clearer and more understandable by a non-scientific public.</span></p>

scholarly journals Independence of Future Changes of River Runoff in Europe from the Pathway to Global Warming

2020 ◽  
Author(s):  
Lorenzo Mentaschi ◽  
Lorenzo Alfieri ◽  
Francesco Dottori ◽  
Carmelo Cammalleri ◽  
Berny Bisselink ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Statistical Significance ◽  
Regional Climate ◽  
Climate Impact ◽  
Major Loss ◽  
Floods And Droughts ◽  
The Difference ◽  
Projected Changes ◽  
Time Frames

The outcomes of the 2015 Paris Agreement triggered a number of climate impact assessments, such as for floods and droughts, to focus on future time frames corresponding to the years of reaching specific levels of global warming. Yet, the links between the timing of the warming levels and the corresponding greenhouse gas concentration pathways to reach them, remain poorly understood. To address this gap, we compare projected changes of annual mean, extreme high and extreme low river discharges in Europe at 1.5°C and 2°C under scenarios RCP8.5 and RCP4.5 from an ensemble of Regional Climate Model (RCM) simulations. The statistical significance of the difference between the two scenarios for both warming levels is then evaluated. Results show that in the majority of Europe (>95% of the surface area for the annual mean discharge, >98% for high and low extremes), the changes projected in the two pathways are statistically indistinguishable. These results suggest that in studies of changes at specific warming levels the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the unified ensemble, findings show that the projected changes of annual mean, extreme high and extreme low river discharge are statistically significant in large portions of Europe.

scholarly journals Independence of Future Changes of River Runoff in Europe from the Pathway to Global Warming

Climate ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 22
Author(s):  
Lorenzo Mentaschi ◽  
Lorenzo Alfieri ◽  
Francesco Dottori ◽  
Carmelo Cammalleri ◽  
Berny Bisselink ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Statistical Significance ◽  
Regional Climate ◽  
Climate Impact ◽  
Major Loss ◽  
Floods And Droughts ◽  
The Difference ◽  
Projected Changes ◽  
Time Frames

The outcomes of the 2015 Paris Agreement triggered a number of climate impact assessments, such as for floods and droughts, to focus on future time frames corresponding to the years of reaching specific levels of global warming. Yet, the links between the timing of the warming levels and the corresponding greenhouse gas concentration pathways to reach them remain poorly understood. To address this gap, we compared projected changes of annual mean, extreme high, and extreme low river discharges in Europe at 1.5 °C and 2 °C under Representative Concentration Pathways RCP8.5 and RCP4.5 from an ensemble of regional climate model (RCM) simulations. The statistical significance of the difference between the two scenarios for both warming levels was then evaluated. The results show that in the majority of Europe (>95% of the surface area for the annual mean discharge, >98% for high and low extremes), the changes projected in the two pathways were statistically indistinguishable. These results suggest that in studies of changes at global warming levels, the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the unified ensemble, the findings show that the projected changes of annual mean, extreme high, and extreme low river discharge were statistically significant in large portions of Europe.

scholarly journals Independence of Future Changes of River Runoff in Europe from the Pathway to Global Warming

2019 ◽  
Author(s):  
Lorenzo Mentaschi ◽  
Lorenzo Alfieri ◽  
Francesco Dottori ◽  
Carmelo Cammalleri ◽  
Berny Bisselink ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Statistical Significance ◽  
Regional Climate ◽  
Climate Impact ◽  
Major Loss ◽  
Floods And Droughts ◽  
The Difference ◽  
Projected Changes ◽  
Time Frames

The outcomes of the 2015 Paris Agreement triggered a number of climate impact assessments, such as for floods and droughts, to focus on future time frames corresponding to the years of reaching specific levels of global warming. Yet, the links between the timing of the warming levels and the corresponding greenhouse gas concentration pathways to reach them, remain poorly understood. To address this gap, we compare projected changes of annual mean, extreme high and extreme low river discharges in Europe at 1.5° and 2° under scenarios RCP8.5 and RCP4.5 from an ensemble of Regional Climate Model (RCM) simulations. The statistical significance of the difference between the two scenarios for both warming levels is then evaluated. Results show that in the majority of Europe (>95% for the annual mean discharge, >98% for high and low extremes), the changes projected in the two pathways are statistically indistinguishable. These results suggest that in studies of changes at specific warming levels the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the unified ensemble, findings show that the projected changes of annual mean, extreme high and extreme low river discharge are statistically significant in large portions of Europe.

scholarly journals Hydrological Climate-Impact Projections for the Rhine River: GCM–RCM Uncertainty and Separate Temperature and Precipitation Effects*

2014 ◽  
Vol 15 (2) ◽  
pp. 697-713 ◽  
Author(s):  
Thomas Bosshard ◽  
Sven Kotlarski ◽  
Massimiliano Zappa ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Regional Climate ◽  
Climate Impact ◽  
Rhine River ◽  
Supply Source ◽  
Rhine Basin ◽  
Projected Changes ◽  
The Impact

Abstract Climate change is expected to affect the hydrological cycle, with considerable impacts on water resources. Climate-induced changes in the hydrology of the Rhine River (Europe) are of major importance for the riparian countries, as the Rhine River is the most important European waterway, serves as a freshwater supply source, and is prone to floods and droughts. Here regional climate model data from the Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project is used to drive the hydrological model Precipitation–Runoff–Evapotranspiration–Hydrotope (PREVAH) and to assess the impact of climate change on the hydrology in the Rhine basin. Results suggest increases in monthly mean runoff during winter and decreases in summer. At the gauge Cologne and for the period 2070–99 under the A1B scenario of the Special Report on Emissions Scenarios, projected decreases in summer vary between −9% and −40% depending on the climate model used, while increases in winter are in the range of +4% to +51%. These projected changes in mean runoff are generally consistent with earlier studies, but the derived spread in the runoff projections appears to be larger. It is demonstrated that temperature effects (e.g., through altered snow processes) dominate in the Alpine tributaries, while precipitation effects dominate in the lower portion of the Rhine basin. Analyses are also presented for selected extreme runoff indices.

scholarly journals 2 °C vs. High Warming: Transitions to Flood-Generating Mechanisms across Canada

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1494
Author(s):  
Bernardo Teufel ◽  
Laxmi Sushama
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Regional Climate ◽  
Adaptation Measures ◽  
Relative Contribution ◽  
Late 21St Century ◽  
Transient Climate Change ◽  
Projected Changes ◽  
Change Mitigation

Fluvial flooding in Canada is often snowmelt-driven, thus occurs mostly in spring, and has caused billions of dollars in damage in the past decade alone. In a warmer climate, increasing rainfall and changing snowmelt rates could lead to significant shifts in flood-generating mechanisms. Here, projected changes to flood-generating mechanisms in terms of the relative contribution of snowmelt and rainfall are assessed across Canada, based on an ensemble of transient climate change simulations performed using a state-of-the-art regional climate model. Changes to flood-generating mechanisms are assessed for both a late 21st century, high warming (i.e., Representative Concentration Pathway 8.5) scenario, and in a 2 °C global warming context. Under 2 °C of global warming, the relative contribution of snowmelt and rainfall to streamflow peaks is projected to remain close to that of the current climate, despite slightly increased rainfall contribution. In contrast, a high warming scenario leads to widespread increases in rainfall contribution and the emergence of hotspots of change in currently snowmelt-dominated regions across Canada. In addition, several regions in southern Canada would be projected to become rainfall dominated. These contrasting projections highlight the importance of climate change mitigation, as remaining below the 2 °C global warming threshold can avoid large changes over most regions, implying a low likelihood that expensive flood adaptation measures would be necessary.

scholarly journals Projected Changes in Extreme Temperature and Precipitation Indices Over CORDEX-MENA Domain

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 622
Author(s):  
Tugba Ozturk ◽  
F. Sibel Saygili-Araci ◽  
M. Levent Kurnaz
Keyword(s):  
Regional Climate Model ◽  
Radiative Forcing ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Extreme ◽  
Pronounced Increase ◽  
Temperature And Precipitation ◽  
Projected Changes ◽  
Extreme Indices

In this study, projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices were investigated over Middle East and North Africa. Changes in the daily maximum and minimum temperature- and precipitation- based extreme indices were analyzed for the end of the 21st century compared to the reference period 1971–2000 using regional climate model simulations. Regional climate model, RegCM4.4 was used to downscale two different global climate model outputs to 50 km resolution under RCP4.5 and RCP8.5 scenarios. Results generally indicate an intensification of temperature- and precipitation- based extreme indices with increasing radiative forcing. In particular, an increase in annual minimum of daily minimum temperatures is more pronounced over the northern part of Mediterranean Basin and tropics. High increase in warm nights and warm spell duration all over the region with a pronounced increase in tropics are projected for the period of 2071–2100 together with decrease or no change in cold extremes. According to the results, a decrease in total wet-day precipitation and increase in dry spells are expected for the end of the century.

scholarly journals A novel bias correction methodology for climate impact simulations

2015 ◽  
Vol 6 (2) ◽  
pp. 1999-2042 ◽  
Author(s):  
S. Sippel ◽  
F. E. L. Otto ◽  
M. Forkel ◽  
M. R. Allen ◽  
B. P. Guillod ◽  
...  
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Terrestrial Ecosystem ◽  
Climate Impact ◽  
Correlation Structure ◽  
Terrestrial Biosphere ◽  
Terrestrial Ecosystem Model ◽  
Multivariate Correlation ◽  
Impact Simulations

Abstract. Understanding, quantifying and attributing the impacts of extreme weather and climate events in the terrestrial biosphere is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. In this study, we introduce a novel, resampling-based bias correction scheme that fully preserves the physical consistency and multivariate correlation structure of the model output. This procedure strongly improves the representation of climatic extremes and variability in a large regional climate model ensemble (HadRM3P, climateprediction.net/weatherathome), which is illustrated for summer extremes in temperature and rainfall over Central Europe. Moreover, we simulate biosphere–atmosphere fluxes of carbon and water using a terrestrial ecosystem model (LPJmL) driven by the bias corrected climate forcing. The resampling-based bias correction yields strongly improved statistical distributions of carbon and water fluxes, including the extremes. Our results thus highlight the importance to carefully consider statistical moments beyond the mean for climate impact simulations. In conclusion, the present study introduces an approach to alleviate climate model biases in a physically consistent way and demonstrates that this yields strongly improved simulations of climate extremes and associated impacts in the terrestrial biosphere. A wider uptake of our methodology by the climate and impact modelling community therefore seems desirable for accurately quantifying past, current and future extremes.

scholarly journals An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets

2020 ◽  
Vol 12 (4) ◽  
pp. 2959-2970
Author(s):  
Maialen Iturbide ◽  
José M. Gutiérrez ◽  
Lincoln M. Alves ◽  
Joaquín Bedia ◽  
Ruth Cerezo-Mota ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Atmospheric Model ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Scatter Plots ◽  
Projected Changes

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

scholarly journals Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

2018 ◽  
Vol 22 (4) ◽  
pp. 2163-2185 ◽  
Author(s):  
Stefan Liersch ◽  
Julia Tecklenburg ◽  
Henning Rust ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
...  
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Model Performance ◽  
Climate Impact ◽  
Hydrological Models ◽  
Blue Nile ◽  
Projected Change ◽  
Model Ensembles

Abstract. Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970–1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

scholarly journals Projected Changes of Precipitation IDF Curves for Short Duration under Climate Change in Central Vietnam

Hydrology ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 33 ◽  
Author(s):  
Nguyen Tien Thanh ◽  
Luca Dutto Aldo Remo
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Extreme Weather Events ◽  
Climate Data ◽  
Rcp Scenarios ◽  
Central Vietnam ◽  
Idf Curves ◽  
Projected Changes

In future years, extreme weather events are expected to frequently increase due to climate change, especially in the combination of climate change and events of El Niño–Southern Oscillation. This pays special attention to the construction of intensity–duration–frequency (IDF) curves at a tempo-spatial scale of sub-daily and sub-grid under a context of climate change. The reason for this is that IDF curves represent essential means to study effects on the performance of drainage systems, damps, dikes and reservoirs. Therefore, the objective of this study is to present an approach to construct future IDF curves with high temporo-spatial resolutions under climate change in central Vietnam, using the case of VuGia-ThuBon. The climate data of historical and future from a regional climate model RegCM4 forced by three global models MPI-ESM-MR, IPSL-CM5A-LR and ICHEC-EC-EARTH are used to re-grid the resolution of 10 km × 10 km grid spacing from 25 km × 25 km on the base of bilinear interpolation. A bias correction method is then applied to the finest resolution of a hydrostatic climate model for an ensemble of simulations. Furthermore, the IDF curves for short durations of precipitation are constructed for the historical climate and future climates under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, based on terms of correlation factors. The major findings show that the projected precipitation changes are expected to significantly increase by about 10 to 30% under the scenarios of RCP4.5 and RCP8.5. The projected changes of a maximum of 1-, 2-, and 3-days precipitation are expected to increase by about 30–300 mm/day. More importantly, for all return periods (i.e., 10, 20, 50, 100, and 200 years), IDF curves completely constructed for short durations of precipitation at sub-daily show an increase in intensities for the RCP4.5 and RCP8.5 scenarios.

Sign in / Sign up

Export Citation Format

Share Document