Cluster analysis of the ensembles of EURO-CORDEX simulations

2021 ◽  
Author(s):  
Tímea Kalmár ◽  
Rita Pongrácz ◽  
Ildikó Pieczka
Keyword(s):  
Climate Change ◽  
Cluster Analysis ◽  
Climate Change Impact ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Change Research ◽  
Model Simulations ◽  
Climate Simulations ◽  
Change Impact ◽  
Precipitation And Temperature

<p>Climate models play an important role in global and regional climate change research, improving our understanding and predictability of climate behaviour. The CORDEX (Coordinated Regional Downscaling Experiment) program was established to provide a framework for the assessment of Regional Climate Models (RCMs) and to contribute to climate change impact assessment and adaptation processes. The climate simulations are based on multiple dynamical and empirical-statistical downscaling models forced by multiple global climate models (GCMs). The motivation behind the use of multiple models in climate change research is to cover different sources of uncertainties, that is why it is recommended to use all available simulations in climate change studies. However, many climate change impact studies face difficulties (e.g., limited computing resources or free access to climate data) using all the available simulations, and therefore it is quite often the case that only subsets of simulations are used. Another problem is that the ensembles of GCM-RCM simulations are too big to be handled by many impact modellers. The selection of model simulations is subjective in most cases, and it is often reduced by hand-picking climate simulations depending on the partners involved in the project. An objective method can be based on cluster analysis, which is a flexible and unsupervised numerical technique that involves the sorting of data into statistically similar groups. These groups can be either (i) determined entirely by the properties of the data themselves or (ii) guided by user constraints. In the present study, we focus on Central-Eastern Europe, because the model simulations are particularly uncertain in the precipitation and temperature distribution over this region. The aim of the study is to develop a method based on the precipitation and temperature values of 55 EURO-CORDEX simulations for a near-present historical period (1995–2014), which could help to select suitable subsets of ensembles of climate simulations tailored to the needs within climate change impact studies.</p><p> </p><p>Acknowledgement: This study is supported by the ÚNKP-20-3 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund.</p>

scholarly journals Accounting for global-mean warming and scaling uncertainties in climate change impact studies: application to a regulated lake system

2007 ◽  
Vol 11 (3) ◽  
pp. 1207-1226 ◽  
Author(s):  
B. Hingray ◽  
N. Mouhous ◽  
A. Mezghani ◽  
K. Bogner ◽  
B. Schaefli ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Climate Scenarios ◽  
Change Impact ◽  
Global Mean ◽  
Potential Climate Change

Abstract. A probabilistic assessment of climate change and related impacts should consider a large range of potential future climate scenarios. State-of-the-art climate models, especially coupled atmosphere-ocean general circulation models and Regional Climate Models (RCMs) cannot, however, be used to simulate such a large number of scenarios. This paper presents a methodology for obtaining future climate scenarios through a simple scaling methodology. The projections of several key meteorological variables obtained from a few regional climate model runs are scaled, based on different global-mean warming projections drawn in a probability distribution of future global-mean warming. The resulting climate change scenarios are used to drive a hydrological and a water management model to analyse the potential climate change impacts on a water resources system. This methodology enables a joint quantification of the climate change impact uncertainty induced by the global-mean warming scenarios and the regional climate response. It is applied to a case study in Switzerland, a water resources system formed by three interconnected lakes located in the Jura Mountains. The system behaviour is simulated for a control period (1961–1990) and a future period (2070–2099). The potential climate change impacts are assessed through a set of impact indices related to different fields of interest (hydrology, agriculture and ecology). The results obtained show that future climate conditions will have a significant influence on the performance of the system and that the uncertainty induced by the inter-RCM variability will contribute to much of the uncertainty of the prediction of the total impact. These CSRs cover the area considered in the 2001–2004 EU funded project SWURVE.

scholarly journals CHASE-PL Climate Projection dataset over Poland – Bias adjustment of EURO-CORDEX simulations

2017 ◽  
Author(s):  
Abdelkader Mezghani ◽  
Andreas Dobler ◽  
Jan Erik Haugen ◽  
Rasmus Eduard Benestad ◽  
Kajsa Maria Parding ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Change Impact ◽  
Climate Projections ◽  
Systematic Bias ◽  
Model Simulations ◽  
Change Impact ◽  
Annual Means ◽  
Projected Changes ◽  
Precipitation And Temperature

Abstract. The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Climate Projections – Bias Corrected Daily Precipitation and Temperature dataset 5 km (CPLCP-GDPT5) consists of projected daily minimum and maximum air temperatures and precipitation totals of nine EURO-CORDEX regional climate model outputs bias corrected and downscaled to 5 × 5 km grid. Simulations of one historical period (1971–2000) and two future horizons (2021–2050 and 2071–2100) assuming two Representative Concentration Pathways (RCP4.5 and RCP8.5) were produced. We used the quantile mapping method and corrected any systematic bias in these simulations before assessing the changes in annual and seasonal means of precipitation and temperature over Poland. Projected changes estimated from the multi-model ensemble mean showed that annual means of temperature are expected to increase constantly by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5, which is accelerating assuming the RCP8.5 scenario and can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 % to 10 % and by 8 % to 16 % for the two future horizons and RCPs, respectively. Similarly, individual model simulations also exhibited warmer and wetter conditions on an annual scale, showing an intensification of the magnitude of the change at the end of the 21st century. The same applied for projected changes in seasonal means of temperature showing a higher winter warming rate by up to 0.5 °C compared to the other seasons. However, projected changes in seasonal means of precipitation by the individual models largely differ and are sometimes inconsistent exhibiting spatial variations which depends on the selected season, location, future horizon and RCP. The overall range of the 90 % confidence interval predicted by the ensemble of multi-model simulations was found to likely vary between −7 % and +40 %, expected to occur in summer assuming the RCP4.5 scenarios and in winter assuming the RCP8.5 scenario, respectively, at the end of the 21st century. Finally, this high-resolution bias-corrected product can serve as a basis for climate change impact and adaptation studies for many sectors over Poland. CPLCP-GDPT5 dataset is publicly available at​ ​http://dx.doi.org/10.4121/uuid:e940ec1a-71a0-449e-bbe3-29217f2ba31d.

scholarly journals Assessing the climate change impact on the North African offshore surface wind and coastal low-level jet using coupled and uncoupled regional climate simulations

2018 ◽  
Vol 52 (11) ◽  
pp. 7111-7132 ◽  
Author(s):  
Pedro M. M. Soares ◽  
Daniela C. A. Lima ◽  
Alvaro Semedo ◽  
Rita M. Cardoso ◽  
William Cabos ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Regional Climate ◽  
Surface Wind ◽  
North African ◽  
Low Level ◽  
The North ◽  
Climate Simulations ◽  
Change Impact ◽  
Low Level Jet

scholarly journals CHASE-PL Climate Projection dataset over Poland – bias adjustment of EURO-CORDEX simulations

2017 ◽  
Vol 9 (2) ◽  
pp. 905-925 ◽  
Author(s):  
Abdelkader Mezghani ◽  
Andreas Dobler ◽  
Jan Erik Haugen ◽  
Rasmus E. Benestad ◽  
Kajsa M. Parding ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Change Impact ◽  
Emission Scenario ◽  
Climate Projections ◽  
Model Simulations ◽  
Change Impact ◽  
Annual Means ◽  
Projected Changes ◽  
Precipitation And Temperature

Abstract. The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Climate Projections – Gridded Daily Precipitation and Temperature dataset 5 km (CPLCP-GDPT5) consists of projected daily minimum and maximum air temperatures and precipitation totals of nine EURO-CORDEX regional climate model outputs bias corrected and downscaled to a 5 km  ×  5 km grid. Simulations of one historical period (1971–2000) and two future horizons (2021–2050 and 2071–2100) assuming two representative concentration pathways (RCP4.5 and RCP8.5) were produced. We used the quantile mapping method and corrected any systematic seasonal bias in these simulations before assessing the changes in annual and seasonal means of precipitation and temperature over Poland. Projected changes estimated from the multi-model ensemble mean showed that annual means of temperature are expected to increase steadily by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5 emission scenario. Assuming the RCP8.5 emission scenario, this can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 to 10 % and by 8 to 16 % for the two future horizons and RCPs, respectively. Similarly, individual model simulations also exhibited warmer and wetter conditions on an annual scale, showing an intensification of the magnitude of the change at the end of the 21st century. The same applied for projected changes in seasonal means of temperature showing a higher winter warming rate by up to 0.5 °C compared to the other seasons. However, projected changes in seasonal means of precipitation by the individual models largely differ and are sometimes inconsistent, exhibiting spatial variations which depend on the selected season, location, future horizon, and RCP. The overall range of the 90 % confidence interval predicted by the ensemble of multi-model simulations was found to likely vary between −7 % (projected for summer assuming the RCP4.5 emission scenario) and +40 % (projected for winter assuming the RCP8.5 emission scenario) by the end of the 21st century. Finally, this high-resolution bias-corrected product can serve as a basis for climate change impact and adaptation studies for many sectors over Poland. The CPLCP-GDPT5 dataset is publicly available at http://dx.doi.org/10.4121/uuid:e940ec1a-71a0-449e-bbe3-29217f2ba31d.

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