Comparison of univariate and multivariate bias-adjusting methods for hydrological impact assessment under climate change conditions

2020 ◽  
Author(s):  
Jorn Van de Velde ◽  
Bernard De Baets ◽  
Matthias Demuzere ◽  
Niko Verhoest
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
Climate Model ◽  
Temporal Structure ◽  
Regional Climate ◽  
Multivariate Methods ◽  
Rainfall Runoff ◽  
Early 21St Century ◽  
Hydrological Impact ◽  
Input Variables

<p>Climate change is one of the largest challenges currently faced by society, with an impact on many systems, such as hydrology. To locally assess this impact, Regional Climate Model (RCM) data are often used as an input for hydrological rainfall-runoff models. However, RCMs are still biased in comparison with the observations. Many methods have been developed to adjust this, but only during the last few years, methods to adjust biases in the variable correlation have become available. This is especially important for hydrological impact assessment, as the hydrological models often need multiple locally correct input variables. In contrast to univariate bias-adjusting methods, the multivariate methods have not yet been thoroughly compared. In this study, two univariate and three multivariate bias-adjusting methods are compared with respect to their performance under climate change conditions. To do this, the methods are calibrated in the late 20<sup>th</sup> century (1970-1989) and validated in the early 21st century (1998-2017), in which the effect of climate change is already visible. The variables adjusted are precipitation, evaporation and temperature, of which the resulting evaporation and precipitation are used as an input for a rainfall-runoff model, to allow for the validation of the methods on discharge. The methods are also evaluated using indices based on the calibrated variables, the temporal structure, and the multivariate correlation. For precipitation, all methods decrease the bias in a comparable manner. However, for many other indices the results differ considerable between the bias-adjusting methods. The multivariate methods often perform worse than the univariate methods, a result that is especially pronounced for temperature and evaporation.</p>

scholarly journals Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods

2020 ◽  
Author(s):  
Jorn Van de Velde ◽  
Matthias Demuzere ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Climate Change ◽  
Impact Analysis ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Temporal Structure ◽  
Regional Climate ◽  
Rainfall Runoff ◽  
Late 20Th Century ◽  
Climate Conditions ◽  
Early 21St Century

Abstract. Climate change is one of the biggest challenges currently faced by society, with an impact on many systems, such as the hydrological cycle. To locally assess this impact, Regional Climate Model (RCM) simulations are often used as input for hydrological rainfall-runoff models. However, RCM results are still biased with respect to the observations. Many methods have been developed to adjust these biases, but only during the last few years, methods to adjust biases that account for the correlation between the variables have been proposed. This correlation adjustment is especially important for compound event impact analysis. As a simple example of those compound events, hydrological impact assessment is used here, as hydrological models often need multiple locally unbiased input variables to ensure an unbiased output. However, it has been suggested that multivariate bias-adjusting methods may perform poorly under climate change conditions because of bias nonstationarity. In this study, two univariate and three multivariate bias-adjusting methods are compared with respect to their performance under climate change conditions. To this end, the methods are calibrated in the late 20th century (1970–1989) and validated in the early 21st century (1998–2017), in which the effect of climate change is already visible. The variables adjusted are precipitation, evaporation and temperature, of which the former two are used as input for a rainfall-runoff model, to allow for the validation of the methods on discharge. Although not used for discharge modelling, temperature is a commonly-adjusted variable in both uni- and multivariate settings and therefore important to take into account. The methods are also evaluated using indices based on the adjusted variables, the temporal structure, and the multivariate correlation. For precipitation, all methods decrease the bias in a comparable manner. However, for many other indices the results differ considerably between the bias-adjusting methods. The multivariate methods often perform worse than the univariate methods, a result that is especially notable for temperature and evaporation. As these variables have already changed the most under climate change conditions, this reinforces the opinion that the multivariate bias-adjusting methods are not yet fit to cope with nonstationary climate conditions. Although the effect is slightly dampened by the hydrological model, our analysis still reveals that, to date, the simpler univariate bias-adjusting methods are preferred for assessing climate change impact.

scholarly journals High-resolution Med-CORDEX regional climate model simulations for hydrological impact studies: a first evaluation in Morocco

2013 ◽  
Vol 10 (5) ◽  
pp. 5687-5737 ◽  
Author(s):  
Y. Tramblay ◽  
D. Ruelland ◽  
S. Somot ◽  
R. Bouaicha ◽  
E. Servat
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Regional Climate Model ◽  
Bias Correction ◽  
Hydrological Model ◽  
Climate Model ◽  
Regional Climate ◽  
Impact Studies ◽  
Hydrological Impact ◽  
Split Sample

Abstract. In the framework of the international CORDEX program, new regional climate model (RCM) simulations at high spatial resolutions are becoming available for the Mediterranean region (Med-CORDEX initiative). This study provides the first evaluation for hydrological impact studies of these high-resolution simulations. Different approaches are compared to analyze the climate change impacts on the hydrology of a catchment located in North Morocco, using a high-resolution RCM (ALADIN-Climate) from the Med-CORDEX initiative at two different spatial resolutions (50 km and 12 km) and for two different Radiative Concentration Pathway scenarios (RCP4.5 and RCP8.5). The main issues addressed in the present study are: (i) what is the impact of increased RCM resolution on present-climate hydrological simulations and on future projections? (ii) Are the bias-correction of the RCM model and the parameters of the hydrological model stationary and transferable to different climatic conditions? (iii) What is the climate and hydrological change signal based on the new Radiative Concentration Pathways scenarios (RCP4.5 and RCP8.5)? Results indicate that high resolution simulations at 12 km better reproduce the seasonal patterns, the seasonal distributions and the extreme events of precipitation. The parameters of the hydrological model, calibrated to reproduce runoff at the monthly time step over the 1984–2010 period, do not show a strong variability between dry and wet calibration periods in a differential split-sample test. However the bias correction of precipitation by quantile-matching does not give satisfactory results in validation using the same differential split-sample testing method. Therefore a quantile-perturbation method that does not rely on any stationarity assumption and produces ensembles of perturbed series of precipitation was introduced. The climate change signal under scenarios 4.5 and 8.5 indicates a decrease of respectively −30% to −57% in surface runoff for the mid-term (2041–2062), when for the same period the projections for precipitation are ranging between −15% and −19% and for temperature between +1.28°C and +1.87°C.

scholarly journals High-resolution Med-CORDEX regional climate model simulations for hydrological impact studies: a first evaluation of the ALADIN-Climate model in Morocco

2013 ◽  
Vol 17 (10) ◽  
pp. 3721-3739 ◽  
Author(s):  
Y. Tramblay ◽  
D. Ruelland ◽  
S. Somot ◽  
R. Bouaicha ◽  
E. Servat
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Regional Climate Model ◽  
Bias Correction ◽  
Hydrological Model ◽  
Climate Model ◽  
Regional Climate ◽  
Impact Studies ◽  
Hydrological Impact ◽  
Split Sample

Abstract. In the framework of the international CORDEX program, new regional climate model (RCM) simulations at high spatial resolutions are becoming available for the Mediterranean region (Med-CORDEX initiative). This study provides the first evaluation for hydrological impact studies of one of these high-resolution simulations in a 1800 km2 catchment located in North Morocco. Different approaches are compared to analyze the climate change impacts on the hydrology of this catchment using a high-resolution RCM (ALADIN-Climate) from the Med-CORDEX initiative at two different spatial resolutions (50 and 12 km) and for two different Radiative Concentration Pathway scenarios (RCP4.5 and RCP8.5). The main issues addressed in the present study are: (i) what is the impact of increased RCM resolution on present-climate hydrological simulations and on future projections? (ii) Are the bias-correction of the RCM model and the parameters of the hydrological model stationary and transferable to different climatic conditions? (iii) What is the climate and hydrological change signal based on the new Radiative Concentration Pathways scenarios (RCP4.5 and RCP8.5)? Results indicate that high resolution simulations at 12 km better reproduce the seasonal patterns, the seasonal distributions and the extreme events of precipitation. The parameters of the hydrological model, calibrated to reproduce runoff at the monthly time step over the 1984–2010 period, do not show a strong variability between dry and wet calibration periods in a differential split-sample test. However the bias correction of precipitation by quantile-matching does not give satisfactory results in validation using the same differential split-sample testing method. Therefore a quantile-perturbation method that does not rely on any stationarity assumption and produces ensembles of perturbed series of precipitation was introduced. The climate change signal under scenarios 4.5 and 8.5 indicates a decrease of respectively −30 to −57% in surface runoff for the mid-term (2041–2062), when for the same period the projections for precipitation are ranging between −15 and −19% and for temperature between +1.3 and +1.9 °C.

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

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.

Sign in / Sign up

Export Citation Format

Share Document