Skillful decadal prediction of unforced southern European summer temperature variations

We assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970-2014. Using a multi-model ensemble average from 8 decadal prediction systems, we show that European summer temperatures are highly predictable for up to 10 years in CMIP6. Much of this predictive capability, or skill, is related to the externally forced response. Prediction skill for the unforced signal of European summer temperature is low. A link between unforced Southern European summer temperature and preceding spring Eastern North Atlantic - Mediterranean sea surface temperature (SST) observed during the period 1900-1969 motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over Europe. This dynamical-statistical model uses dynamical spring SST predictions to predict European summer temperature. Our model significantly increases decadal prediction skill of unforced European summer temperature variations: Unlike purely dynamical predictions, the dynamical-statistical model shows significant prediction skill for unforced Southern European summer temperature 2-9 years ahead. Our results highlight that dynamical-statistical models can serve to benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over Europe.

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Skillful decadal prediction of unforced Southern European summer temperature variations

Environmental Research Letters ◽

10.1088/1748-9326/ac20f5 ◽

2021 ◽

Author(s):

Leonard Borchert ◽

Vimal Koul ◽

Matthew B. Menary ◽

Daniel J. Befort ◽

Didier Swingedouw ◽

...

Keyword(s):

Summer Temperature ◽

Decadal Prediction ◽

Temperature Variations

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ENSO asymmetry: the search for extreme El Niño events in HadGEM

10.5194/egusphere-egu21-9593 ◽

2021 ◽

Author(s):

Sarah Ineson ◽

Nick Dunstone ◽

Adam Scaife ◽

Kuniko Yamazaki

Keyword(s):

Coupled Model ◽

Control Model ◽

Decadal Prediction ◽

Enso Asymmetry ◽

Prediction Systems ◽

Hadley Centre ◽

Control Behaviour

Analysis of a long control run of the Hadley Centre coupled model shows that ENSO asymmetry is weak. We use the same model in our seasonal and decadal prediction systems, and while on seasonal timescales the initialised prediction realistically captures the amplitude of extreme El Ni&#241;o events, on longer timescales the predictions revert to the control behaviour i.e. there are no very large El Ni&#241;o events. This may impact on our ability evaluate the risk of extreme regional events. Here we show results exploring asymmetry in both the control model, and also from a number of perturbed parameter experiments, each a plausible realisation of the control.

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Prediction of Low Engine Order Inlet Distortion Driven Resonance in a Low Aspect Ratio Fan

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education ◽

10.1115/2000-gt-0374 ◽

2000 ◽

Cited By ~ 6

Author(s):

J. G. Marshall ◽

L. Xu ◽

J. Denton ◽

J. W. Chew

Keyword(s):

Aspect Ratio ◽

Three Dimensional ◽

Coupled Model ◽

Response Prediction ◽

Euler Method ◽

Forced Response ◽

Blade Vibration ◽

Inlet Distortion ◽

Low Aspect Ratio ◽

Engine Order

This paper presents a forced response prediction of 3 resonances in a low aspect ratio modern fan rotor and compares with other worker’s experimental data. The incoming disturbances are due to low engine-order inlet distortion from upstream screens. The resonances occur in the running range at 3 and 8 engine orders which cross low modes (flap, torsion and stripe) of the blade. The fan was tested with on-blade instrumentation at both on- and off-resonant conditions to establish the unsteady pressures due to known distortion patterns. The resulting steady and unsteady flow in the fan blade passages has been predicted by three methods, all three-dimensional. The first is a linearised unsteady Euler method; the second is a non-linear unsteady Navier-Stokes method; the third method uses a similar level of aerodynamic modelling as the second but also includes a coupled model of the structural dynamics. The predictions for the 3 methods are presented against the test data, and further insight into the problem is obtained through post-processing of the data. Predictions of the blade vibration response are also obtained. Overall the level of agreement between calculations and measurements is considered encouraging although further research is needed.

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Skillful Dynamical-Statistical Predictions of European Summer Temperature

10.5194/egusphere-egu21-10788 ◽

2021 ◽

Author(s):

Juliette Mignot ◽

Leonard Borchert ◽

Vimal Koul ◽

Björn Mayer ◽

Matthew Menary ◽

...

Keyword(s):

Surface Temperature ◽

North Atlantic ◽

Spectral Band ◽

Summer Temperature ◽

Statistical Prediction ◽

Climate Projections ◽

Decadal Prediction ◽

Data Set ◽

Temperature Variations ◽

Decadal Climate

While decadal North Atlantic sea surface temperature (SST) variations are generally predictable, prediction skill of surface temperature over Europe is much more limited. We invoke here observed links of decadal European summer temperature variations to North Atlantic SST changes in the preceding months to produce skillful decadal predictions of European summer temperature variations.We analyze the ERA5 reanalysis data set to re-assess the observed influence of North Atlantic SST on European summer temperature for the period 1960-2020. To facilitate possible merging activities of initialized decadal prediction simulations and climate projections in the future, we examine predictions for the target regions Northern Europe (NEU), Central Europe (CEU) and Mediterranean (MED) as are defined as the SREX regions for IPCC Assessment Report 5. Summer (June-July-August: JJA) temperature in NEU shows significant co-variability in a decadal spectral band with MAM SST in the Western North Atlantic (WNA), while JJA CEU temperature shows the same with JJA SST in that region. JJA temperature in the MED region shows significant decadal co-variability with the annual mean AMV index. SVD analysis illustrates that an atmospheric Rossby wave train connects North Atlantic SST to European summer temperature changes.Dynamical retrospective forecasts from a suite of decadal prediction systems from the Coupled Model Intercomparison Project Phase 6 Decadal Climate Prediction Project are tested for their agreement with observations for the period 1960-2020. Dynamical predictions of JJA temperature in NEU, CEU and MED are mostly not skillful at lead years 1-10 in the CMIP6 simulations. Most models do, however, show skill in the SST regions that are connected to these summer temperature variations, identified above. We use these SST predictions to drive a simple statistical model that rescales the variance of the SST predictions according to observed SAT variance in the target region. This dynamical-statistical prediction is shown to be skillful at lead years 1-10 for summer temperature in the SREX regions. This skill, however, relies on the skill of the models in predicting the respective SST index. Our work therefore indicates a promising avenue to produce skillful decadal climate predictions over land based on skillful predictions of the ocean.

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Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution

10.5194/egusphere-egu2020-5649 ◽

2020 ◽

Author(s):

Mareike Schuster ◽

Jens Grieger ◽

Andy Richling ◽

Thomas Schartner ◽

Sebastian Illing ◽

...

Keyword(s):

North Atlantic ◽

Storm Track ◽

Forecast Skill ◽

Prediction Skill ◽

Decadal Prediction ◽

The North ◽

The North Atlantic ◽

Prediction Systems ◽

The Impact ◽

Extratropical Circulation

As the scientific and societal interest in skillful decadal predictions grows, a lot of effort is currently put into the development and advancement of such prediction systems worldwide. Studies evaluating the skill of basic atmospheric quantities, such as e.g. surface temperatures, in those prediction systems are numerous. However, dynamical quantities are discussed only rarely. Also, there is a lack of investigations which assess the exclusive impact of the model&#8217;s resolution on the forecast skill.&#160;In this study, we address both these issues: we analyse a set of four quantities of the extratropical circulation (storm track, blocking frequencies, cyclone frequencies, windstorm frequencies) and compare the deterministic forecast skill for lead winters 2-5 within the German MiKlip prediction system of two different spatial resolutions. While the lower resolution (LR, atm: T63L47, ocean: 1.5&#176; L40) shows common deficits in the climatological representation, e.g. an overly zonal extratropical storm track and a deficit in blocking frequencies over the North Atlantic and Europe, the higher resolution version (HR, atm: T127L95, ocean: 0.4&#176; L40) counteracts these biases. In return, the deterministic decadal prediction skill, which is measured in terms of anomaly correlation, increases (statistically significant) with the increase in resolution for all four quantities.&#160;The improvements found in our study for the different metrics follow a physically consistent line of argument, and the areas of improved forecast skill are crucial regions for the genesis and intensification of synoptic weather systems over the North Atlantic and for their impact on Europe. Thus, we identified a significant improvement of the storm track skill along the North Atlantic Current (i.e., the source region of synoptic eddies), a downstream improvement of the cyclone frequency skill over the central North Atlantic (where the synoptic systems intensify), and finally improved skill of the cyclone, windstorm and blocking frequencies over the European continent (i.e., the impact area).Not only is the skill improved with the increase in resolution (HR vs. LR), but also the HR system itself offers significant deterministic decadal forecast skill for the extratropical circulation metrics in large regions over the North Atlantic and Europe (HR vs. ERA-Interim) for the considered lead time of two to five winters.&#160;Our results are encouraging for the advancement of decadal prediction systems as they document that even small improvements in the bias of the model, through an increased spatial resolution and possibly a better representation of smaller scales, can have a substantial effect on the representation of dynamical processes and can ultimately lead to a significant improvement of the decadal prediction skill for extratropical features and extreme events.

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Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

Monthly Weather Review ◽

10.1175/mwr-d-18-0199.1 ◽

2019 ◽

Vol 147 (5) ◽

pp. 1429-1445 ◽

Cited By ~ 3

Author(s):

Yuchu Zhao ◽

Zhengyu Liu ◽

Fei Zheng ◽

Yishuai Jin

Keyword(s):

Data Assimilation ◽

Parameter Optimization ◽

Real World ◽

Climate Models ◽

Coupled Model ◽

Prediction Skill ◽

Model Parameters ◽

Real World Data ◽

The Real ◽

Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

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