Future Climate and Potential Impacts at the Study Sites

2017 ◽  
pp. 33-78
Author(s):  
Bob van Oort
Keyword(s):  
Statistical Downscaling ◽  
Local Level ◽  
Regional Climate ◽  
Climate Projections ◽  
Climate Modelling ◽  
Climate Scenarios ◽  
Climate Data ◽  
Local Conditions ◽  
Study Sites ◽  
Regional Climate Projections

The chapter opens with statements of uncertainties in climate modelling. Then, the most updated regional climate projections are downscaled by combining them with existing climate data on local level (statistical downscaling) and modified by local conditions (elevation, aspect). Climate scenarios are computed for 2030, 2050 and 2100 for all the six study sites (Chapters 4-9), using a 12 x 12 km grid.

Regional Climate Scenarios for use in Nordic Water Resources Studies

2003 ◽  
Vol 34 (5) ◽  
pp. 399-412 ◽  
Author(s):  
M. Rummukainen ◽  
J. Räisänen ◽  
D. Bjørge ◽  
J.H. Christensen ◽  
O.B. Christensen ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Soil Frost ◽  
Nordic Region ◽  
Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

Selecting climate projections for services: the DRIAS-2020 dataset

2021 ◽  
Author(s):  
Lola Corre ◽  
Samuel Somot ◽  
Jean-Michel Soubeyroux ◽  
Sébastien Bernus ◽  
Agathe Drouin ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Easy Access ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Climate Data ◽  
Quantile Mapping ◽  
The Past ◽  
Climate Service ◽  
Climatic Information

<p>The French National Climate Service “Drias, futures of climate” was launched in 2012, as a response of the French scientific community to society’s need for climatic information. It is mainly composed of a website that provides easy access to the best available climate data to characterize climate change over France. Latest advances developed in 2020 include the availability of a new set of regional climate scenarios corrected by a quantile-mapping based method with correction depending on the weather regime. As for the previous set, the climate projections are based on the EURO-CORDEX ensemble, whose contents have been greatly enriched over the past years. Singular effort was done to build a robust and synthetic set that well represents the uncertainties of climate change over France. The different criteria defined to select the simulations will be presented, and the range of the projected climate change will be examined, with respect to larger ensembles.</p><p> </p>

Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

scholarly journals Reassessing Model Uncertainty for Regional Projections of Precipitation with an Ensemble of Statistical Downscaling Methods

2017 ◽  
Vol 30 (1) ◽  
pp. 203-223 ◽  
Author(s):  
D. San-Martín ◽  
R. Manzanas ◽  
S. Brands ◽  
S. Herrera ◽  
J. M. Gutiérrez
Keyword(s):  
Statistical Downscaling ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Companion Paper ◽  
Climate Projections ◽  
Interaction Terms ◽  
Weather Typing ◽  
Ensembles Project ◽  
Families First

This is the second in a pair of papers in which the performance of statistical downscaling methods (SDMs) is critically reassessed with respect to their robust applicability in climate change studies. Whereas the companion paper focused on temperatures, the present manuscript deals with precipitation and considers an ensemble of 12 SDMs from the analog, weather typing, and regression families. First, the performance of the methods is cross-validated considering reanalysis predictors, screening different geographical domains and predictor sets. Standard accuracy and distributional similarity scores and a test for extrapolation capability are considered. The results are highly dependent on the predictor sets, with optimum configurations including information from midtropospheric humidity. Second, a reduced ensemble of well-performing SDMs is applied to four GCMs to properly assess the uncertainty of downscaled future climate projections. The results are compared with an ensemble of regional climate models (RCMs) produced in the ENSEMBLES project. Generally, the mean signal is similar with both methodologies (with the exception of summer, which is drier for the RCMs) but the uncertainty (spread) is larger for the SDM ensemble. Finally, the spread contribution of the GCM- and SDM-derived components is assessed using a simple analysis of variance previously applied to the RCMs, obtaining larger interaction terms. Results show that the main contributor to the spread is the choice of the GCM, although the SDM dominates the uncertainty in some cases during autumn and summer due to the diverging projections from different families.

Future circulation changes over the EURO-CORDEX domain

2020 ◽  
Author(s):  
Tugba Ozturk ◽  
Dominic Matte ◽  
Jens Hesselbjerg Christensen
Keyword(s):  
Regional Climate ◽  
Storm Track ◽  
Lower Troposphere ◽  
Climate Extremes ◽  
Extreme Weather Events ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Summer Circulation ◽  
Regional Climate Projections ◽  
Circulation Changes

<p><span lang="EN-US">The occurrence of extreme weather events and climate extremes over Europe and the Mediterranean region are believed to be associated with changes and variability in the mid-latitude atmospheric circulation. CMIP5 models exhibits a substantial decrease in mid-latitude mean storm track activity for summer under climate change for a variety of scenarios. In this work, we aim to investigate future change in summer circulation and its implication for summer temperature and precipitation extremes over Europe particularly focusing on the Southeastern Mediterranean. EURO-CORDEX regional climate projections at 0.11° grid-mesh are used to analyze future climate projections addressing climate warming targets of 1°C, 2°C and 3°C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for the variables in concern in order to provide robust signals not to be dependent on climate sensitivity. Our focus in this study is on monthly mean geopotential height, winds at mid- and lower-troposphere as indicators of the simulated circulation changes.</span></p>

Coordinated Global and Regional Climate Modeling*

2015 ◽  
Vol 29 (1) ◽  
pp. 17-35 ◽  
Author(s):  
J. F. Scinocca ◽  
V. V. Kharin ◽  
Y. Jiao ◽  
M. W. Qian ◽  
M. Lazare ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Value Added ◽  
Regional Climate Modeling ◽  
Climate Projections ◽  
Climate Modelling

Abstract A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

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