scholarly journals Calibrating large-ensemble European climate projections using observational data

2020 ◽  
Vol 11 (4) ◽  
pp. 1033-1049
Author(s):  
Christopher H. O'Reilly ◽  
Daniel J. Befort ◽  
Antje Weisheimer
Keyword(s):  
Observational Data ◽  
Regional Climate ◽  
Coupled Model ◽  
Calibration Method ◽  
Climate Projections ◽  
Max Planck ◽  
Large Ensemble ◽  
Calibration Methods ◽  
Projected Changes ◽  
Model Approach

Abstract. This study examines methods of calibrating projections of future regional climate for the next 40–50 years using large single-model ensembles (the Community Earth System Model (CESM) Large Ensemble and Max Planck Institute (MPI) Grand Ensemble), applied over Europe. The three calibration methods tested here are more commonly used for initialised forecasts from weeks up to seasonal timescales. The calibration techniques are applied to ensemble climate projections, fitting seasonal ensemble data to observations over a reference period (1920–2016). The calibration methods were tested and verified using an “imperfect model” approach using the historical/representative concentration pathway 8.5 (RCP8.5) simulations from the Coupled Model Intercomparison Project 5 (CMIP5) archive. All the calibration methods exhibit a similar performance, generally improving the out-of-sample projections in comparison to the uncalibrated (bias-corrected) ensemble. The calibration methods give results that are largely indistinguishable from one another, so the simplest of these methods, namely homogeneous Gaussian regression (HGR), is used for the subsequent analysis. As an extension to the HGR calibration method it is applied to dynamically decomposed data, in which the underlying data are separated into dynamical and residual components (HGR-decomp). Based on the verification results obtained using the imperfect model approach, the HGR-decomp method is found to produce more reliable and accurate projections than the uncalibrated ensemble for future climate over Europe. The calibrated projections for temperature demonstrate a particular improvement, whereas the projections for changes in precipitation generally remain fairly unreliable. When the two large ensembles are calibrated using observational data, the climate projections for Europe are far more consistent between the two ensembles, with both projecting a reduction in warming but a general increase in the uncertainty of the projected changes.

scholarly journals Calibrating large-ensemble European climate projections using observational data

2020 ◽  
Author(s):  
Christopher H. O'Reilly ◽  
Daniel J. Befort ◽  
Antje Weisheimer
Keyword(s):  
Observational Data ◽  
Regional Climate ◽  
Calibration Method ◽  
Climate Projections ◽  
Large Ensemble ◽  
Calibration Methods ◽  
Out Of Sample ◽  
Large Ensembles ◽  
Projected Changes ◽  
Gaussian Regression

Abstract. This study examines methods of calibrating projections of future regional climate using large single model ensembles (the CESM Large Ensemble and MPI Grand Ensemble), applied over Europe. The three calibration methods tested here are more commonly used for initialised forecasts from weeks up to seasonal timescales. The calibration techniques are applied to ensemble climate projections, fitting seasonal ensemble data to observations over a reference period (1920–2016). The calibration methods were tested and verified using an imperfect model approach using the historical/RCP 8.5 simulations from the CMIP5 archive. All the calibration methods exhibit a similar performance, generally improving the out-of-sample projections in comparison to the uncalibrated (bias-corrected) ensemble. The calibration methods give results that are largely indistinguishable from one another, so the simplest of these methods, namely Homogeneous Gaussian Regression, is used for the subsequent analysis. An extension to this method – applying it to dynamically decomposed data (in which the underlying data is separated into dynamical and residual components) – is also tested. The verification indicates that this calibration method produces more reliable and accurate projections than the uncalibrated ensemble for future climate over Europe. The calibrated projections for temperature demonstrate a particular improvement, whereas the projections for changes in precipitation generally remain fairly unreliable. When the two large ensembles are calibrated using observational data, the climate projections for Europe are far more consistent between the two ensembles, with both projecting a reduction in warming but a general increase in the uncertainty of the projected changes.

scholarly journals Calibrating large-ensemble European climate projections using observational data

2020 ◽  
Author(s):  
Christopher O'Reilly ◽  
Daniel Befort ◽  
Antje Weisheimer
Keyword(s):  
Observational Data ◽  
Climate Projections ◽  
Slight Reduction ◽  
Reference Period ◽  
Calibration Methods ◽  
Out Of Sample ◽  
Large Ensembles ◽  
Model Ensembles ◽  
Projected Changes ◽  
Gaussian Regression

<p>In this study methods of calibrating the output of large single model ensembles are examined. The methods broadly involve fitting seasonal ensemble data to observations over a reference period and scaling the ensemble signal and spread so as to optimize the fit over the reference period. These calibration methods are then applied to the future (or out-of-sample) projections. The calibration methods are tested and give indistinguishable results so the simplest of these methods, namely Homogenous Gaussian Regression, is selected. An extension to this method, applying it to dynamically decomposed data (in which the underlying data is separated into dynamical and residual components), is found to improve the reliability of the calibrated projections. The calibration methods were tested and verified using an “imperfect model” approach using the historical/RCP8.5 simulations from the CMIP5 archive. The verification indicates that this relatively straight-forward calibration produces more reliable and accurate projections than the uncalibrated (bias-corrected) ensemble for projections of future climate over Europe. When the two large ensembles are applied to observational data, the 2041-2060 climate projections for Europe for the RCP 8.5 scenario are more consistent between the two ensembles, with a slight reduction in warming but an increase in the uncertainty of the projected changes. </p>

scholarly journals Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

2017 ◽  
Author(s):  
Richard Wartenburger ◽  
Martin Hirschi ◽  
Markus G. Donat ◽  
Peter Greve ◽  
Andy J. Pitman ◽  
...  
Keyword(s):  
Water Cycle ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Projected Changes ◽  
Regional Analyses ◽  
Global Mean

Abstract. This article extends a previous study (Seneviratne et al., 2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global temperature targets, such as the 2 degree and 1.5 degree limits agreed within the 2015 Paris Agreement.

scholarly journals Projected changes in the seasonal cycle of the Atlantic meridional heat transport in MPI-ESM

2016 ◽  
Author(s):  
Matthias Fischer ◽  
Daniela I. V. Domeisen ◽  
Wolfgang A. Müller ◽  
Johanna Baehr
Keyword(s):  
Heat Transport ◽  
North Atlantic ◽  
Seasonal Cycle ◽  
Coupled Model ◽  
Change Scenario ◽  
Max Planck ◽  
Meridional Heat Transport ◽  
The North ◽  
The North Atlantic ◽  
Projected Changes

Abstract. We investigate the effect of a projected reduction in the Atlantic Ocean meridional heat transport (OHT) on changes in its seasonal cycle. We analyze a climate projection experiment with the Max-Planck Institute Earth System Model (MPI-ESM) performed for the Coupled Model Intercomparison Project phase 5 (CMIP5). In the RCP8.5 climate change scenario, the OHT declines in MPI-ESM in the North Atlantic by 30–50 % by the end of the 23rd century. The decline in the OHT is accompanied by a change in the seasonal cycle of the total OHT and its components. We decompose the OHT into overturning and gyre component. For the total OHT seasonal cycle, we find a northward shift of 5 degrees and latitude dependent temporal shifts of 1 to 6 months that are mainly associated with changes in the meridional velocity field. We find that the shift in the OHT seasonal cycle predominantly results from changes in the wind-driven surface circulation which projects onto the overturning component of the OHT in the tropical and subtropical North Atlantic. This leads to latitude dependent shifts of 1 to 6 months in the overturning component. In the subpolar North Atlantic, we find that the reduction of the North Atlantic Deep Water formation in RCP8.5 and changes in the gyre heat transport result in a strongly weakened seasonal cycle with a weakened seasonal amplitude by the end of the 23rd century and thus changes the OHT seasonal cycle in the SPG.

scholarly journals Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

2017 ◽  
Vol 10 (9) ◽  
pp. 3609-3634 ◽  
Author(s):  
Richard Wartenburger ◽  
Martin Hirschi ◽  
Markus G. Donat ◽  
Peter Greve ◽  
Andy J. Pitman ◽  
...  
Keyword(s):  
Water Cycle ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Projected Changes ◽  
Regional Analyses ◽  
Global Mean

Abstract. This article extends a previous study Seneviratne et al. (2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global mean temperature targets, such as the 2 and 1.5° limits agreed within the 2015 Paris Agreement.

scholarly journals Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

2017 ◽  
Vol 30 (21) ◽  
pp. 8517-8537 ◽  
Author(s):  
Fuyao Wang ◽  
Yan Yu ◽  
Michael Notaro ◽  
Jiafu Mao ◽  
Xiaoying Shi ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Statistical Method ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Ocean Basin ◽  
Climate Projections ◽  
Atmospheric Response ◽  
Statistical Assessment

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.

scholarly journals The future climate characteristics of the Carpathian Basin based on a regional climate model mini-ensemble

2011 ◽  
Vol 6 (1) ◽  
pp. 69-73 ◽  
Author(s):  
I. Krüzselyi ◽  
J. Bartholy ◽  
A. Horányi ◽  
I. Pieczka ◽  
R. Pongrácz ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Statistical Significance ◽  
Regional Climate ◽  
Carpathian Basin ◽  
Climate Projections ◽  
Target Area ◽  
Max Planck ◽  
The Future

Abstract. Four regional climate models (RCMs) were adapted in Hungary for the dynamical downscaling of the global climate projections over the Carpathian Basin: (i) the ALADIN-Climate model developed by Météo France on the basis of the ALADIN short-range modelling system; (ii) the PRECIS model available from the UK Met Office Hadley Centre; (iii) the RegCM model originally developed at the US National Center for Atmospheric Research, is maintained at the International Centre for Theoretical Physics in Trieste; and (iv) the REMO model developed by the Max Planck Institute for Meteorology in Hamburg. The RCMs are different in terms of dynamical model formulation, physical parameterisations; moreover, in the completed simulations they use different spatial resolutions, integration domains and lateral boundary conditions for the scenario experiments. Therefore, the results of the four RCMs can be considered as a small ensemble providing information about various kinds of uncertainties in the future projections over the target area, i.e., Hungary. After the validation of the temperature and precipitation patterns against measurements, mean changes and some extreme characteristics of these patterns (including their statistical significance) have been assessed focusing on the periods of 2021–2050 and 2071–2100 relative to the 1961–1990 model reference period. The ensemble evaluation indicates that the temperature-related changes of the different RCMs are in good agreement over the Carpathian Basin and these tendencies manifest in the general warming conditions. The precipitation changes cannot be identified so clearly: seasonally large differences can be recognised among the projections and between the two periods. An overview is given about the results of the mini-ensemble and special emphasis is put on estimating the uncertainties in the simulations for Hungary.

scholarly journals A Technique for Dynamically Downscaling Daily-Averaged GCM Datasets Using the Conformal Cubic Atmospheric Model

2011 ◽  
Vol 139 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Marcus Thatcher ◽  
John L. McGregor
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Coupled Model ◽  
Circulation Model ◽  
Interpolation Formula ◽  
Atmospheric Model ◽  
Order Estimate ◽  
Climate Projections ◽  
Coupled Models ◽  
Selective Filter

Abstract In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.

scholarly journals A multi-model, multi-scenario, and multi-domain analysis of regional climate projections for the Mediterranean

2019 ◽  
Vol 19 (8) ◽  
pp. 2621-2635 ◽  
Author(s):  
George Zittis ◽  
Panos Hadjinicolaou ◽  
Marina Klangidou ◽  
Yiannis Proestos ◽  
Jos Lelieveld
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Mediterranean Region ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Temperature And Precipitation ◽  
The Mediterranean ◽  
Projected Changes

AbstractObservation and model-based studies have identified the Mediterranean region as one of the most prominent climate change “hot-spots.” Parts of this distinctive region are included in several Coordinated Regional Downscaling Experiment (CORDEX) domains such as those for Europe, Africa, the Mediterranean, and the Middle East/North Africa. In this study, we compile and analyze monthly temperature and precipitation fields derived from regional climate model simulations performed over different CORDEX domains at a spatial resolution of 50 km. This unique multi-model, multi-scenario, and multi-domain “super-ensemble” is used to update projected changes for the Mediterranean region. The statistical robustness and significance of the climate change signal is assessed. By considering information from more than one CORDEX domains, our analysis addresses an additional type of uncertainty that is often neglected and is related to the positioning of the regional climate model domain. CORDEX simulations suggest a general warming by the end of the century (between 1 and 5 °C with respect to the 1986–2005 reference period), which is expected to be strongest during summer (up to 7 °C). A general drying (between 10 and 40%) is also inferred for the Mediterranean. However, the projected precipitation change signal is less significant and less robust. The CORDEX ensemble corroborates the fact that the Mediterranean is already entering the 1.5 °C climate warming era. It is expected to reach 2 °C warming well within two decades, unless strong greenhouse gas concentration reductions are implemented. The southern part of the Mediterranean is expected to be impacted most strongly since the CORDEX ensemble suggests substantial combined warming and drying, particularly for pathways RCP4.5 and RCP8.5.

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