Projected Changes of Extremely Cool Summer Days over Northeastern Japan Simulated by 20 km-mesh Large Ensemble Experiment

Projected changes in the midlatitude atmospheric circulation at the end of the twenty-first century are investigated using coupled ocean–atmosphere simulations from the Community Earth System Model Large Ensemble (CESM-LENS). Different metrics are used to describe the response of the midlatitude atmospheric dynamics in 40 ensemble members covering the 1920–2100 period. Contrasted responses are identified depending on the season and longitudinal sector that are considered. In winter, a slowdown of the zonal flow and an increase in waviness is found over North America, while the European sector exhibits a reinforced westerly flow and decreased waviness. Extreme temperature events in midlatitudes are more sensitive to thermodynamical than dynamical changes, and a general decrease in the intensity of wintertime cold spells is found. Analyses of individual ensemble members reveal a large spread in circulation changes due to internal variability. Causes for this spread are found to be tied to the Arctic amplification in the Pacific–North American sector and to the polar stratosphere in the North Atlantic. A competition mechanism is also discussed between the midlatitude response to polar versus tropical changes. While the upper-tropospheric tropical warming pushes the jet stream poleward, in winter, Arctic amplification and the weaker polar vortex exert an opposite effect. This competition results in a narrowing of the jet path in the midlatitudes, leading to decreased/unchanged waviness/blockings. This interpretation somewhat reconciles conflicting results between the hypothesized effect of Arctic amplification and projected changes in midlatitude flow characteristics. This study also illustrates that further understanding of regional processes is critical for anticipating changes in the midlatitude dynamics.

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Changes in Frequency of Large Precipitation Accumulations over Land in a Warming Climate from the CESM Large Ensemble: The Roles of Moisture, Circulation, and Duration

Journal of Climate ◽

10.1175/jcli-d-18-0600.1 ◽

2019 ◽

Vol 32 (17) ◽

pp. 5397-5416 ◽

Cited By ~ 9

Author(s):

Jesse Norris ◽

Gang Chen ◽

J. David Neelin

Keyword(s):

First Century ◽

Minor Effect ◽

Large Ensemble ◽

Almost Everywhere ◽

Community Earth System Model ◽

Twenty First Century ◽

Projected Changes ◽

The Tropics ◽

The Given ◽

Local Average

ABSTRACT Projected changes in the frequency of major precipitation accumulations (hundreds of millimeters), integrated over rainfall events, over land in the late twenty-first century are analyzed in the Community Earth System Model (CESM) Large Ensemble, based on the RCP8.5 scenario. Accumulation sizes are sorted by the local average recurrence interval (ARI), ranging from 0.1 to 100 years, for the current and projected late-twenty-first-century climates separately. For all ARIs, the frequency of exceedance of the given accumulation size increases in the future climate almost everywhere, especially for the largest accumulations, with the 100-yr accumulation becoming about 3 times more frequent, averaged over the global land area. The moisture budget allows the impacts of individual factors—moisture, circulation, and event duration—to be isolated. In the tropics, both moisture and circulation cause large future increases, enhancing the 100-yr accumulation by 23% and 13% (average over tropical land), and are individually responsible for making the current-climate 100-yr accumulation 2.7 times and 1.8 times more frequent, but effects of shorter durations slightly offset these effects. In the midlatitudes, large accumulations become about 5% longer in duration, but are predominantly controlled by enhanced moisture, with the 100-yr accumulation (land average) becoming 2.4 times more frequent, and 2.2 times more frequent due to moisture increases alone. In some monsoon-affected regions, the 100-yr accumulation becomes more than 5 times as frequent, where circulation changes are the most impactful factor. These projections indicate that changing duration of events is a relatively minor effect on changing accumulations, their future enhancement being dominated by enhanced intensity (the combination of moisture and circulation).

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Calibrating large-ensemble European climate projections using observational data

Earth System Dynamics ◽

10.5194/esd-11-1033-2020 ◽

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.

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Projected Changes in Extreme Precipitation in a 60‐km AGCM Large Ensemble and Their Dependence on Return Periods

Geophysical Research Letters ◽

10.1029/2019gl086855 ◽

2020 ◽

Vol 47 (13) ◽

Author(s):

Ryo Mizuta ◽

Hirokazu Endo

Keyword(s):

Extreme Precipitation ◽

Return Periods ◽

Large Ensemble ◽

Projected Changes

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Calibrating large-ensemble European climate projections using observational data

10.5194/esd-2020-6 ◽

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.

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