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  • 11
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    The Climate-system Historical Forecast Project: Do stratosphere-resolving models make better seasonal climate predictions in boreal winter? (2016)
    Royal Meteorological Society
    In:  Quarterly Journal of the Royal Meteorological Society, 142 (696). pp. 1413-1427.
    Details
    Publication Date: 2019-02-01
    Description: Using an international, multi-model suite of historical forecasts from the World Climate Research Programme (WCRP) Climate-system Historical Forecast Project (CHFP), we compare the seasonal prediction skill in boreal wintertime between models that resolve the stratosphere and its dynamics (“high-top”) and models that do not (“low-top”). We evaluate hindcasts that are initialized in November, and examine the model biases in the stratosphere and how they relate to boreal wintertime (Dec-Mar) seasonal forecast skill. We are unable to detect more skill in the high-top ensemble-mean than the low-top ensemble-mean in forecasting the wintertime North Atlantic Oscillation, but model performance varies widely. Increasing the ensemble size clearly increases the skill for a given model. We then examine two major processes involving stratosphere-troposphere interactions (the El Niño-Southern Oscillation/ENSO and the Quasi-biennial Oscillation/QBO) and how they relate to predictive skill on intra-seasonal to seasonal timescales, particularly over the North Atlantic and Eurasia regions. High-top models tend to have a more realistic stratospheric response to El Niño and the QBO compared to low-top models. Enhanced conditional wintertime skill over high-latitudes and the North Atlantic region during winters with El Niño conditions suggests a possible role for a stratospheric pathway.
    Type: Article , PeerReviewed
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  • 12
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    The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model (2015)
    Springer
    In:  Climate Dynamics, 44 (9-10). pp. 2723-2735.
    Details
    Publication Date: 2018-01-19
    Description: A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2–4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.
    Type: Article , PeerReviewed
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  • 13
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    Changes in the seasonal cycle of the Atlantic meridional heat transport in a RCP 8.5 climate projection in MPI-ESM (2017)
    Copernicus Publications (EGU)
    In:  Earth System Dynamics, 8 . pp. 129-146.
    Details
    Publication Date: 2020-02-06
    Description: We investigate changes in the seasonal cycle of the Atlantic Ocean meridional heat transport (OHT) in a climate projection experiment with the Max Planck Institute Earth System Model (MPI-ESM) performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Specifically, we compare a Representative Concentration Pathway (RCP) RCP 8.5 climate change scenario, covering the simulation period from 2005 to 2300, to a historical simulation, covering the simulation period from 1850 to 2005. In RCP 8.5, the OHT declines by 30–50 % in comparison to the historical simulation in the North Atlantic 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 OHT seasonal cycle, we find a northward shift of 5° and latitude-dependent shifts between 1 and 6 months that are mainly associated with changes in the meridional velocity field. We find that the changes in the OHT seasonal cycle predominantly result 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 in turn to latitude-dependent shifts between 1 and 6 months in the overturning component. In comparison to the historical simulation, in the subpolar North Atlantic, in RCP 8.5 we find a reduction of the North Atlantic Deep Water formation and changes in the gyre heat transport result in a strongly weakened seasonal cycle with a weakened amplitude by the end of the 23rd century.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 14
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    Nonlinear Stratospheric Variability: Multifractal De-trended Fluctuation Analysis and Singularity Spectra (2016)
    Royal Society London
    In:  Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 472 (2191). Art. no. 20150864.
    Details
    Publication Date: 2019-02-01
    Description: Characterizing the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study, the different scaling laws in the long-term stratospheric variability are studied using multifractal de-trended fluctuation analysis (MF-DFA). The analysis is performed comparing four re-analysis products and different realizations of an idealized numerical model, isolating the role of topographic forcing and seasonal variability, as well as the absence of climate teleconnections and small-scale forcing. The Northern Hemisphere (NH) shows a transition of scaling exponents for time scales shorter than about 1 year, for which the variability is multifractal and scales in time with a power law corresponding to a red spectrum, to longer time scales, for which the variability is monofractal and scales in time with a power law corresponding to white noise. Southern Hemisphere (SH) variability also shows a transition at annual scales. The SH also shows a narrower dynamical range in multifractality than the NH, as seen in the generalized Hurst exponent and in the singularity spectra. The numerical integrations show that the models are able to reproduce the lowfrequency variability but are not able to fully capture the shorter term variability of the stratosphere.
    Type: Article , PeerReviewed
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  • 15
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    How linear is the ENSO Teleconnection to the North Pacific? The Role of ENSO Atmospheric Feedbacks for Rainfall in California (2018)
    In:  [Talk] In: EGU General Assembly 2018, 08.-13.04.2018, Vienna, Austria .
    Details
    Publication Date: 2019-01-10
    Description: El Niño/Southern Oscillation has global teleconnections. Precipitation on the US East Coast, and in particular Southern California, is strongly dependent on ENSO variability in the tropical Pacific: More rainfall is expected during El Niño episodes, and reduced rainfall during La Niña. While this teleconnection is highly dependent on the location, timing, and strength of the sea surface temperature (SST) signal in the tropical Pacific, the associated nonlinearities are often not well represented in current climate models. Moreover, the location and strength of convection over the equatorial Pacific has been shown to be linked to the strength of atmospheric feedbacks in the tropical Pacific, i.e. the wind-SST feedback and the heat flux-SST feedback. The strength of the local atmospheric feedbacks is here shown to not only affecting tropical Pacific ENSO dynamics, but also the teleconnection to California: A strengthening of the atmospheric feedback tends to initiate a stronger wave train to California, bringing significantly higher rainfall. In addition to feedback strength, this study compares coupled and atmosphere-only models with observations in terms of the ENSO teleconnection to California.
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 16
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    How Predictable Are the Arctic and North Atlantic Oscillations? Exploring the Variability and Predictability of the Northern Hemisphere (2018)
    In:  [Poster] In: AGU Fall Meeting 2018, 10.-14.12.2018, Washington, D.C., USA .
    Details
    Publication Date: 2019-01-08
    Description: The North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) describe the dominant part of the variability in the Northern Hemisphere extratropical troposphere. Because of the strong connection of these patterns with surface climate, recent years have shown an increased interest and an increasing skill in forecasting them. However, it is unclear what the intrinsic limits of short-term predictability for the NAO and AO patterns are. This study compares the variability and predictability of both patterns, using a range of data and index computation methods for the daily NAO and AO indices. Small deviations from Gaussianity are found along with characteristic decorrelation time scales of around one week. In the analysis of the Lyapunov spectrum it is found that predictability is not significantly different between the AO and NAO or between reanalysis products. Differences exist, however, between the indices based on EOF analysis, which exhibit predictability time scales around 12–16 days, and the station-based indices, exhibiting a longer predictability of 18–20 days. Both of these time scales indicate predictability beyond that currently obtained in ensemble prediction models for short-term predictability. Additional longer-term predictability for these patterns may be gained through local feedbacks and remote forcing mechanisms for particular atmospheric conditions.
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 17
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    Seasonal Forecasting: Using global teleconnections to predict the weather in the North Atlantic / Europe region (2015)
    In:  [Invited talk] In: Oxford University, Atmospheric, Oceanic and Planetary Physics, 10.2015, Oxford, UK .
    Details
    Publication Date: 2016-11-18
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 18
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    An industry perspective on the use of seasonal forecasts and weather information for evaluating sensitivities in traded commodity supply chains (2015)
    In:  [Talk] In: EGU General Assembly 2015, 12.–17.04.2015 , Vienna, Austria .
    Details
    Publication Date: 2017-05-23
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 19
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    Seasonal Predictability over Europe arising from El Nino and Stratospheric Variability in the MPI-ESM Seasonal Prediction System (2015)
    In:  [Talk] In: EGU General Assembly 2015, 12.–17.04.2015 , Vienna, Austria .
    Details
    Publication Date: 2017-05-23
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 20
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    Using relaxation experiments to determine remote influences useful for seasonal prediction over Europe (2018)
    In:  [Invited talk] In: EGU General Assembly 2018, 08.-13.04.2018, Vienna, Austria .
    Details
    Publication Date: 2018-11-19
    Description: Experiments using atmosphere-only, as well as coupled forecast models, in which parts of the model atmosphere are constrained towards reanalysis products by relaxation are described. Such experiments have proved useful for determining remote influences, e.g. from the tropics or from the stratosphere, potentially useful for seasonal forecasting boreal winter over Europe. Such techniques can also be used for diagnosing remote influences important in the dynamics of a particular season, a good example being the extreme winter of 1962/63. An example is also given for the boreal summer East Atlantic pattern in which relaxation experiments fail to capture the appropriate influence from the tropics. Possible reasons for this will be given.
    Type: Conference or Workshop Item , NonPeerReviewed
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