Articles | Volume 26, issue 1
https://doi.org/10.5194/npg-26-1-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-26-1-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Feb 2019
Research article |
| 18 Feb 2019
| 18 Feb 2019
Exploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical–dynamical atmospheric model
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, Potsdam, Germany
Department of Physics, University of Potsdam, Potsdam, Germany
Stefan Petri
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, Potsdam, Germany
Jascha Lehmann
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, Potsdam, Germany
Erik Peukert
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, Potsdam, Germany
Department of Physics, University of Potsdam, Potsdam, Germany
Dim Coumou
Potsdam Institute for Climate Impact Research (PIK), Leibniz Association, Potsdam, Germany
Institute for Environmental Studies (IVM), Vrije University Amsterdam, Amsterdam, the Netherlands
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Manuscript not accepted for further review
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The planetary boundary framework characterizes major risks of destabilization of the Earth system. We use the comprehensive Earth system model POEM to study the impact of the interacting boundaries for climate change and land system change. Our study shows the importance of long-term effects on carbon dynamics and climate, as well as the need to investigate both boundaries simultaneously and to generally keep both boundaries within acceptable ranges to avoid a catastrophic scenario for humanity.
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During at least two phases in its past, Earth was more or less covered in ice. These “snowball Earth” events probably started suddenly upon undercutting a certain threshold in the carbon-dioxide concentration. This threshold can vary considerably under different conditions. In our study, we find the thresholds for different distributions of continents, geometries of Earth’s orbit, and volcanic eruptions. The results show that the threshold might have varied by up to 46 %.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
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Georg Feulner, Mona Bukenberger, and Stefan Petri
Earth Syst. Dynam., 14, 533–547, https://doi.org/10.5194/esd-14-533-2023, https://doi.org/10.5194/esd-14-533-2023, 2023
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One limit of planetary habitability is defined by the threshold of global glaciation. If Earth cools, growing ice cover makes it brighter, leading to further cooling, since more sunlight is reflected, eventually leading to global ice cover (Snowball Earth). We study how much carbon dioxide is needed to prevent global glaciation in Earth's history given the slow increase in the Sun's brightness. We find an unexpected change in the characteristics of climate states close to the Snowball limit.
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In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
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We present the technical implementation of a coarse-resolution coupling between an ice sheet model and an ocean model that allows one to simulate ice–ocean interactions at timescales from centuries to millennia. As ice shelf cavities cannot be resolved in the ocean model at coarse resolution, we bridge the gap using an sub-shelf cavity module. It is shown that the framework is computationally efficient, conserves mass and energy, and can produce a stable coupled state under present-day forcing.
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Weather Clim. Dynam., 1, 519–539, https://doi.org/10.5194/wcd-1-519-2020, https://doi.org/10.5194/wcd-1-519-2020, 2020
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We study the interactions between the tropical convective activity and the mid-latitude circulation in the Northern Hemisphere during boreal summer. We identify two circumglobal wave patterns with phase shifts corresponding to the South Asian and the western North Pacific monsoon systems at an intra-seasonal timescale. These patterns show two-way interactions in a causal framework at a weekly timescale and assess how El Niño affects these interactions.
Giorgia Di Capua, Marlene Kretschmer, Reik V. Donner, Bart van den Hurk, Ramesh Vellore, Raghavan Krishnan, and Dim Coumou
Earth Syst. Dynam., 11, 17–34, https://doi.org/10.5194/esd-11-17-2020, https://doi.org/10.5194/esd-11-17-2020, 2020
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Drivers from both the mid-latitudes and the tropical regions have been proposed to influence the Indian summer monsoon (ISM) subseasonal variability. To understand the relative importance of tropical and mid-latitude drivers, we apply recently developed causal discovery techniques to disentangle the causal relationships among these processes. Our results show that there is indeed a two-way interaction between the mid-latitude circulation and ISM rainfall over central India.
Giorgia Di Capua, Marlene Kretschmer, Reik V. Donner, Bart van den Hurk, Ramesh Vellore, Raghavan Krishnan, and Dim Coumou
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-11, https://doi.org/10.5194/esd-2019-11, 2019
Manuscript not accepted for further review
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Both drivers from the mid-latitudes and from the tropical regions have been proposed to influence the Indian summer monsoon (ISM) subseasonal variability. To understand the relative importance of tropical and mid-latitude drivers, we apply recently developed causal discovery techniques to disentangle the causal relationships among these processes. Our results show that there is indeed a two-way interaction between the mid-latitude circulation and ISM rainfall over central India.
Julia Brugger, Matthias Hofmann, Stefan Petri, and Georg Feulner
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-36, https://doi.org/10.5194/cp-2018-36, 2018
Manuscript not accepted for further review
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To get a deeper understanding of the various evolutionary changes, which took place during the Devonian (419 to 359 Ma), we here use a coupled climate model to investigate the sensitivity of the Devonian climate to changes in orbital forcing, continental configuration and vegetation cover. Our results are summarised by best-guess simulations for the Early, Middle and Late Devonian showing a decreasing temperature trend in accordance with the reconstructed decreasing atmospheric CO2.
Sonja Totz, Alexey V. Eliseev, Stefan Petri, Michael Flechsig, Levke Caesar, Vladimir Petoukhov, and Dim Coumou
Geosci. Model Dev., 11, 665–679, https://doi.org/10.5194/gmd-11-665-2018, https://doi.org/10.5194/gmd-11-665-2018, 2018
Sonja Molnos, Stefan Petri, Jascha Lehmann, Erik Peukert, and Dim Coumou
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-65, https://doi.org/10.5194/esd-2017-65, 2017
Manuscript not accepted for further review
Sonja Molnos, Tarek Mamdouh, Stefan Petri, Thomas Nocke, Tino Weinkauf, and Dim Coumou
Earth Syst. Dynam., 8, 75–89, https://doi.org/10.5194/esd-8-75-2017, https://doi.org/10.5194/esd-8-75-2017, 2017
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A. V. Eliseev, D. Coumou, A. V. Chernokulsky, V. Petoukhov, and S. Petri
Geosci. Model Dev., 6, 1745–1765, https://doi.org/10.5194/gmd-6-1745-2013, https://doi.org/10.5194/gmd-6-1745-2013, 2013
A. Menon, A. Levermann, J. Schewe, J. Lehmann, and K. Frieler
Earth Syst. Dynam., 4, 287–300, https://doi.org/10.5194/esd-4-287-2013, https://doi.org/10.5194/esd-4-287-2013, 2013
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Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere
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Nonlin. Processes Geophys., 31, 303–317, https://doi.org/10.5194/npg-31-303-2024, https://doi.org/10.5194/npg-31-303-2024, 2024
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Nonlin. Processes Geophys., 31, 287–302, https://doi.org/10.5194/npg-31-287-2024, https://doi.org/10.5194/npg-31-287-2024, 2024
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Forecasts have uncertainties. It is thus essential to reduce these uncertainties. Such reduction requires uncertainty quantification, which often means running costly models multiple times. The cost limits the number of model runs and thus the quantification’s accuracy. This study proposes a technique that utilizes users’ knowledge of forecast uncertainties to improve uncertainty quantification. Tests show that this technique improves uncertainty reduction.
Loris Foresti, Bernat Puigdomènech Treserras, Daniele Nerini, Aitor Atencia, Marco Gabella, Ioannis V. Sideris, Urs Germann, and Isztar Zawadzki
Nonlin. Processes Geophys., 31, 259–286, https://doi.org/10.5194/npg-31-259-2024, https://doi.org/10.5194/npg-31-259-2024, 2024
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We compared two ways of defining the phase space of low-dimensional attractors describing the evolution of radar precipitation fields. The first defines the phase space by the domain-scale statistics of precipitation fields, such as their mean, spatial and temporal correlations. The second uses principal component analysis to account for the spatial distribution of precipitation. To represent different climates, radar archives over the United States and the Swiss Alpine region were used.
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Nonlin. Processes Geophys., 31, 237–245, https://doi.org/10.5194/npg-31-237-2024, https://doi.org/10.5194/npg-31-237-2024, 2024
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Nonlin. Processes Geophys., 31, 219–227, https://doi.org/10.5194/npg-31-219-2024, https://doi.org/10.5194/npg-31-219-2024, 2024
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The nonstationary kinetic model of turbulence is used to describe the evolution and structure of the upper turbulent layer with the parameters taken from in situ observations. As an example, we use a set of data for three cruises made in different areas of the world ocean. With the given profiles of current shear and buoyancy frequency, the theory yields results that satisfactorily agree with the measurements of the turbulent dissipation rate.
Vivian A. Montiforte, Hans E. Ngodock, and Innocent Souopgui
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2024-3, https://doi.org/10.5194/npg-2024-3, 2024
Revised manuscript accepted for NPG
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Advanced data assimilation methods are complex and computationally expensive. We compare two simpler methods, Diffusive Back and Forth Nudging and Concave-Convex Nonlinearity, that account for change over time with the potential of providing accurate results with a reduced computational cost. We evaluate the accuracy of the two methods by implementing them within simple chaotic models. We conclude that the length and frequency of observations impacts which method is better suited for a problem.
Thomas Muschinski, Georg J. Mayr, Achim Zeileis, and Thorsten Simon
Nonlin. Processes Geophys., 30, 503–514, https://doi.org/10.5194/npg-30-503-2023, https://doi.org/10.5194/npg-30-503-2023, 2023
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Statistical post-processing is necessary to generate probabilistic forecasts from physical numerical weather prediction models. To allow for more flexibility, there has been a shift in post-processing away from traditional parametric regression models towards modern machine learning methods. By fusing these two approaches, we developed model output statistics random forests, a new post-processing method that is highly flexible but at the same time also very robust and easy to interpret.
Kenta Kurosawa, Shunji Kotsuki, and Takemasa Miyoshi
Nonlin. Processes Geophys., 30, 457–479, https://doi.org/10.5194/npg-30-457-2023, https://doi.org/10.5194/npg-30-457-2023, 2023
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This study aimed to enhance weather and hydrological forecasts by integrating soil moisture data into a global weather model. By assimilating atmospheric observations and soil moisture data, the accuracy of forecasts was improved, and certain biases were reduced. The method was found to be particularly beneficial in areas like the Sahel and equatorial Africa, where precipitation patterns vary seasonally. This new approach has the potential to improve the precision of weather predictions.
Annika Vogel and Richard Ménard
Nonlin. Processes Geophys., 30, 375–398, https://doi.org/10.5194/npg-30-375-2023, https://doi.org/10.5194/npg-30-375-2023, 2023
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Accurate estimation of the error statistics required for data assimilation remains an ongoing challenge, as statistical assumptions are required to solve the estimation problem. This work provides a conceptual view of the statistical error estimation problem in light of the increasing number of available datasets. We found that the total number of required assumptions increases with the number of overlapping datasets, but the relative number of error statistics that can be estimated increases.
Yung-Yun Cheng, Shu-Chih Yang, Zhe-Hui Lin, and Yung-An Lee
Nonlin. Processes Geophys., 30, 289–297, https://doi.org/10.5194/npg-30-289-2023, https://doi.org/10.5194/npg-30-289-2023, 2023
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In the ensemble Kalman filter, the ensemble space may not fully capture the forecast errors due to the limited ensemble size and systematic model errors, which affect the accuracy of analysis and prediction. This study proposes a new algorithm to use cost-free pseudomembers to expand the ensemble space effectively and improve analysis accuracy during the analysis step, without increasing the ensemble size during forecasting.
Eugenia Kalnay, Travis Sluka, Takuma Yoshida, Cheng Da, and Safa Mote
Nonlin. Processes Geophys., 30, 217–236, https://doi.org/10.5194/npg-30-217-2023, https://doi.org/10.5194/npg-30-217-2023, 2023
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Strongly coupled data assimilation (SCDA) generates coherent integrated Earth system analyses by assimilating the full Earth observation set into all Earth components. We describe SCDA based on the ensemble Kalman filter with a hierarchy of coupled models, from a coupled Lorenz to the Climate Forecast System v2. SCDA with a sufficiently large ensemble can provide more accurate coupled analyses compared to weakly coupled DA. The correlation-cutoff method can compensate for a small ensemble size.
Mao Ouyang, Keita Tokuda, and Shunji Kotsuki
Nonlin. Processes Geophys., 30, 183–193, https://doi.org/10.5194/npg-30-183-2023, https://doi.org/10.5194/npg-30-183-2023, 2023
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This research found that weather control would change the chaotic behavior of an atmospheric model. We proposed to introduce chaos theory in the weather control. Experimental results demonstrated that the proposed approach reduced the manipulations, including the control times and magnitudes, which throw light on the weather control in a real atmospheric model.
Qiwen Sun, Takemasa Miyoshi, and Serge Richard
Nonlin. Processes Geophys., 30, 117–128, https://doi.org/10.5194/npg-30-117-2023, https://doi.org/10.5194/npg-30-117-2023, 2023
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This paper is a follow-up of a work by Miyoshi and Sun which was published in NPG Letters in 2022. The control simulation experiment is applied to the Lorenz-96 model for avoiding extreme events. The results show that extreme events of this partially and imperfectly observed chaotic system can be avoided by applying pre-designed small perturbations. These investigations may be extended to more realistic numerical weather prediction models.
Antoine Perrot, Olivier Pannekoucke, and Vincent Guidard
Nonlin. Processes Geophys., 30, 139–166, https://doi.org/10.5194/npg-30-139-2023, https://doi.org/10.5194/npg-30-139-2023, 2023
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This work is a theoretical contribution that provides equations for understanding uncertainty prediction applied in air quality where multiple chemical species can interact. A simplified minimal test bed is introduced that shows the ability of our equations to reproduce the statistics estimated from an ensemble of forecasts. While the latter estimation is the state of the art, solving equations is numerically less costly, depending on the number of chemical species, and motivates this research.
Pierre Tandeo, Pierre Ailliot, and Florian Sévellec
Nonlin. Processes Geophys., 30, 129–137, https://doi.org/10.5194/npg-30-129-2023, https://doi.org/10.5194/npg-30-129-2023, 2023
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The goal of this paper is to obtain probabilistic predictions of a partially observed dynamical system without knowing the model equations. It is illustrated using the three-dimensional Lorenz system, where only two components are observed. The proposed data-driven procedure is low-cost, is easy to implement, uses linear and Gaussian assumptions and requires only a small amount of data. It is based on an iterative linear Kalman smoother with a state augmentation.
Clara Deser and Adam S. Phillips
Nonlin. Processes Geophys., 30, 63–84, https://doi.org/10.5194/npg-30-63-2023, https://doi.org/10.5194/npg-30-63-2023, 2023
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Past and future climate change at regional scales is a result of both human influences and natural (internal) variability. Here, we provide an overview of recent advances in climate modeling and physical understanding that has led to new insights into their respective roles, illustrated with original results for the European climate. Our findings highlight the confounding role of internal variability in attribution, climate model evaluation, and accuracy of future projections.
Elia Gorokhovsky and Jeffrey L. Anderson
Nonlin. Processes Geophys., 30, 37–47, https://doi.org/10.5194/npg-30-37-2023, https://doi.org/10.5194/npg-30-37-2023, 2023
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Older observations of the Earth system sometimes lack information about the time they were taken, posing problems for analyses of past climate. To begin to ameliorate this problem, we propose new methods of varying complexity, including methods to estimate the distribution of the offsets between true and reported observation times. The most successful method accounts for the nonlinearity in the system, but even the less expensive ones can improve data assimilation in the presence of time error.
Tobias Necker, David Hinger, Philipp Johannes Griewank, Takemasa Miyoshi, and Martin Weissmann
Nonlin. Processes Geophys., 30, 13–29, https://doi.org/10.5194/npg-30-13-2023, https://doi.org/10.5194/npg-30-13-2023, 2023
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This study investigates vertical localization based on a convection-permitting 1000-member ensemble simulation. We derive an empirical optimal localization (EOL) that minimizes sampling error in 40-member sub-sample correlations assuming 1000-member correlations as truth. The results will provide guidance for localization in convective-scale ensemble data assimilation systems.
Stéphane Vannitsem
Nonlin. Processes Geophys., 30, 1–12, https://doi.org/10.5194/npg-30-1-2023, https://doi.org/10.5194/npg-30-1-2023, 2023
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The impact of climate change on weather pattern dynamics over the North Atlantic is explored through the lens of information theory. These tools allow the predictability of the succession of weather patterns and the irreversible nature of the dynamics to be clarified. It is shown that the predictability is increasing in the observations, while the opposite trend is found in model projections. The irreversibility displays an overall increase in time in both the observations and the model runs.
Dikraa Khedhaouiria, Stéphane Bélair, Vincent Fortin, Guy Roy, and Franck Lespinas
Nonlin. Processes Geophys., 29, 329–344, https://doi.org/10.5194/npg-29-329-2022, https://doi.org/10.5194/npg-29-329-2022, 2022
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This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms that has not yet been explored for precipitation analyses. Our approach combined an ensemble-based DA approach with an existing deterministically based DA. Both DA scheme families have desirable aspects that can be leveraged if combined. The DA hybrid method showed better precipitation analyses in regions with a low rate of assimilated surface observations, which is typically the case in winter.
Chu-Chun Chang and Eugenia Kalnay
Nonlin. Processes Geophys., 29, 317–327, https://doi.org/10.5194/npg-29-317-2022, https://doi.org/10.5194/npg-29-317-2022, 2022
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This study introduces a new approach for enhancing the ensemble data assimilation (DA), a technique that combines observations and forecasts to improve numerical weather predictions. Our method uses the prescribed correlations to suppress spurious errors, improving the accuracy of DA. The experiments on the simplified atmosphere model show that our method has comparable performance to the traditional method but is superior in the early stage and is more computationally efficient.
Andrey A. Popov, Amit N. Subrahmanya, and Adrian Sandu
Nonlin. Processes Geophys., 29, 241–253, https://doi.org/10.5194/npg-29-241-2022, https://doi.org/10.5194/npg-29-241-2022, 2022
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Numerical weather prediction requires the melding of both computational model and data obtained from sensors such as satellites. We focus on one algorithm to accomplish this. We aim to aid its use by additionally supplying it with data obtained from separate models that describe the average behavior of the computational model at any given time. We show that our approach outperforms the standard approaches to this problem.
Takemasa Miyoshi and Qiwen Sun
Nonlin. Processes Geophys., 29, 133–139, https://doi.org/10.5194/npg-29-133-2022, https://doi.org/10.5194/npg-29-133-2022, 2022
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The weather is chaotic and hard to predict, but the chaos implies an effective control where a small control signal grows rapidly to make a big difference. This study proposes a control simulation experiment where we apply a small signal to control
naturein a computational simulation. Idealized experiments with a low-order chaotic system show successful results by small control signals of only 3 % of the observation error. This is the first step toward realistic weather simulations.
Sagar K. Tamang, Ardeshir Ebtehaj, Peter Jan van Leeuwen, Gilad Lerman, and Efi Foufoula-Georgiou
Nonlin. Processes Geophys., 29, 77–92, https://doi.org/10.5194/npg-29-77-2022, https://doi.org/10.5194/npg-29-77-2022, 2022
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The outputs from Earth system models are optimally combined with satellite observations to produce accurate forecasts through a process called data assimilation. Many existing data assimilation methodologies have some assumptions regarding the shape of the probability distributions of model output and observations, which results in forecast inaccuracies. In this paper, we test the effectiveness of a newly proposed methodology that relaxes such assumptions about high-dimensional models.
Yumeng Chen, Alberto Carrassi, and Valerio Lucarini
Nonlin. Processes Geophys., 28, 633–649, https://doi.org/10.5194/npg-28-633-2021, https://doi.org/10.5194/npg-28-633-2021, 2021
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Chaotic dynamical systems are sensitive to the initial conditions, which are crucial for climate forecast. These properties are often used to inform the design of data assimilation (DA), a method used to estimate the exact initial conditions. However, obtaining the instability properties is burdensome for complex problems, both numerically and analytically. Here, we suggest a different viewpoint. We show that the skill of DA can be used to infer the instability properties of a dynamical system.
Juan Ruiz, Guo-Yuan Lien, Keiichi Kondo, Shigenori Otsuka, and Takemasa Miyoshi
Nonlin. Processes Geophys., 28, 615–626, https://doi.org/10.5194/npg-28-615-2021, https://doi.org/10.5194/npg-28-615-2021, 2021
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Effective use of observations with numerical weather prediction models, also known as data assimilation, is a key part of weather forecasting systems. For precise prediction at the scales of thunderstorms, fast nonlinear processes pose a grand challenge because most data assimilation systems are based on linear processes and normal distribution errors. We investigate how, every 30 s, weather radar observations can help reduce the effect of nonlinear processes and nonnormal distributions.
Zofia Stanley, Ian Grooms, and William Kleiber
Nonlin. Processes Geophys., 28, 565–583, https://doi.org/10.5194/npg-28-565-2021, https://doi.org/10.5194/npg-28-565-2021, 2021
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In weather forecasting, observations are incorporated into a model of the atmosphere through a process called data assimilation. Sometimes observations in one location may impact the weather forecast in another faraway location in undesirable ways. The impact of distant observations on the forecast is mitigated through a process called localization. We propose a new method for localization when a model has multiple length scales, as in a model spanning both the ocean and the atmosphere.
Zhao Liu, Shaoqing Zhang, Yang Shen, Yuping Guan, and Xiong Deng
Nonlin. Processes Geophys., 28, 481–500, https://doi.org/10.5194/npg-28-481-2021, https://doi.org/10.5194/npg-28-481-2021, 2021
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A general methodology is introduced to capture regime transitions of the Atlantic meridional overturning circulation (AMOC). The assimilation models with different parameters simulate different paths for the AMOC to switch between equilibrium states. Constraining model parameters with observations can significantly mitigate the model deviations, thus capturing AMOC regime transitions. This simple model study serves as a guideline for improving coupled general circulation models.
Guillaume Evin, Matthieu Lafaysse, Maxime Taillardat, and Michaël Zamo
Nonlin. Processes Geophys., 28, 467–480, https://doi.org/10.5194/npg-28-467-2021, https://doi.org/10.5194/npg-28-467-2021, 2021
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Forecasting the height of new snow is essential for avalanche hazard surveys, road and ski resort management, tourism attractiveness, etc. Météo-France operates a probabilistic forecasting system using a numerical weather prediction system and a snowpack model. It provides better forecasts than direct diagnostics but exhibits significant biases. Post-processing methods can be applied to provide automatic forecasting products from this system.
Davide Faranda, Mathieu Vrac, Pascal Yiou, Flavio Maria Emanuele Pons, Adnane Hamid, Giulia Carella, Cedric Ngoungue Langue, Soulivanh Thao, and Valerie Gautard
Nonlin. Processes Geophys., 28, 423–443, https://doi.org/10.5194/npg-28-423-2021, https://doi.org/10.5194/npg-28-423-2021, 2021
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Machine learning approaches are spreading rapidly in climate sciences. They are of great help in many practical situations where using the underlying equations is difficult because of the limitation in computational power. Here we use a systematic approach to investigate the limitations of the popular echo state network algorithms used to forecast the long-term behaviour of chaotic systems, such as the weather. Our results show that noise and intermittency greatly affect the performances.
Stephen Jewson, Giuliana Barbato, Paola Mercogliano, Jaroslav Mysiak, and Maximiliano Sassi
Nonlin. Processes Geophys., 28, 329–346, https://doi.org/10.5194/npg-28-329-2021, https://doi.org/10.5194/npg-28-329-2021, 2021
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Climate model simulations are uncertain. In some cases this makes it difficult to know how to use them. Significance testing is often used to deal with this issue but has various shortcomings. We describe two alternative ways to manage uncertainty in climate model simulations that avoid these shortcomings. We test them on simulations of future rainfall over Europe and show they produce more accurate projections than either using unadjusted climate model output or statistical testing.
Sagar K. Tamang, Ardeshir Ebtehaj, Peter J. van Leeuwen, Dongmian Zou, and Gilad Lerman
Nonlin. Processes Geophys., 28, 295–309, https://doi.org/10.5194/npg-28-295-2021, https://doi.org/10.5194/npg-28-295-2021, 2021
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Data assimilation aims to improve hydrologic and weather forecasts by combining available information from Earth system models and observations. The classical approaches to data assimilation usually proceed with some preconceived assumptions about the shape of their probability distributions. As a result, when such assumptions are invalid, the forecast accuracy suffers. In the proposed methodology, we relax such assumptions and demonstrate improved performance.
Abd AlRahman AlMomani and Erik Bollt
Nonlin. Processes Geophys., 28, 153–166, https://doi.org/10.5194/npg-28-153-2021, https://doi.org/10.5194/npg-28-153-2021, 2021
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This paper introduces a tool for data-driven discovery of early warning signs of critical transitions in ice shelves from remote sensing data. Our directed spectral clustering method considers an asymmetric affinity matrix along with the associated directed graph Laplacian. We applied our approach to reprocessing the ice velocity data and remote sensing satellite images of the Larsen C ice shelf.
Yvonne Ruckstuhl, Tijana Janjić, and Stephan Rasp
Nonlin. Processes Geophys., 28, 111–119, https://doi.org/10.5194/npg-28-111-2021, https://doi.org/10.5194/npg-28-111-2021, 2021
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The assimilation of observations using standard algorithms can lead to a violation of physical laws (e.g. mass conservation), which is shown to have a detrimental impact on the system's forecast. We use a neural network (NN) to correct this mass violation, using training data generated from expensive algorithms that can constrain such physical properties. We found that, in an idealized set-up, the NN can match the performance of these expensive algorithms at negligible computational costs.
Shin'ya Nakano
Nonlin. Processes Geophys., 28, 93–109, https://doi.org/10.5194/npg-28-93-2021, https://doi.org/10.5194/npg-28-93-2021, 2021
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The ensemble-based variational method is a method for solving nonlinear data assimilation problems by using an ensemble of multiple simulation results. Although this method is derived based on a linear approximation, highly uncertain problems, in which system nonlinearity is significant, can also be solved by applying this method iteratively. This paper reformulated this iterative algorithm to analyze its behavior in high-dimensional nonlinear problems and discuss the convergence.
Sangeetika Ruchi, Svetlana Dubinkina, and Jana de Wiljes
Nonlin. Processes Geophys., 28, 23–41, https://doi.org/10.5194/npg-28-23-2021, https://doi.org/10.5194/npg-28-23-2021, 2021
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To infer information of an unknown quantity that helps to understand an associated system better and to predict future outcomes, observations and a physical model that connects the data points to the unknown parameter are typically used as information sources. Yet this problem is often very challenging due to the fact that the unknown is generally high dimensional, the data are sparse and the model can be non-linear. We propose a novel approach to address these challenges.
Olivier Pannekoucke, Richard Ménard, Mohammad El Aabaribaoune, and Matthieu Plu
Nonlin. Processes Geophys., 28, 1–22, https://doi.org/10.5194/npg-28-1-2021, https://doi.org/10.5194/npg-28-1-2021, 2021
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Numerical weather prediction involves numerically solving the mathematical equations, which describe the geophysical flow, by transforming them so that they can be computed. Through this transformation, it appears that the equations actually solved by the machine are then a modified version of the original equations, introducing an error that contributes to the model error. This work helps to characterize the covariance of the model error that is due to this modification of the equations.
Pengcheng Yan, Guolin Feng, Wei Hou, and Ping Yang
Nonlin. Processes Geophys., 27, 489–500, https://doi.org/10.5194/npg-27-489-2020, https://doi.org/10.5194/npg-27-489-2020, 2020
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A system transiting from one stable state to another has to experience a period. Can we predict the end moment (state) if the process has not been completed? This paper presents a method to solve this problem. This method is based on the quantitative relationship among the parameters, which is used to describe the transition process of the abrupt change. By using the historical data, we extract some parameters for predicting the uncompleted climate transition process.
Reinhold Hess
Nonlin. Processes Geophys., 27, 473–487, https://doi.org/10.5194/npg-27-473-2020, https://doi.org/10.5194/npg-27-473-2020, 2020
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Forecasts of ensemble systems are statistically aligned to synoptic observations at DWD in order to provide support for warning decision management. Motivation and design consequences for extreme and rare meteorological events are presented. Especially for probabilities of severe wind gusts global logistic parameterisations are developed that generate robust statistical forecasts for extreme events, while local characteristics are preserved.
Ashesh Chattopadhyay, Pedram Hassanzadeh, and Devika Subramanian
Nonlin. Processes Geophys., 27, 373–389, https://doi.org/10.5194/npg-27-373-2020, https://doi.org/10.5194/npg-27-373-2020, 2020
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The performance of three machine-learning methods for data-driven modeling of a multiscale chaotic Lorenz 96 system is examined. One of the methods is found to be able to predict the future evolution of the chaotic system well from just knowing the past observations of the large-scale component of the multiscale state vector. Potential applications to data-driven and data-assisted surrogate modeling of complex dynamical systems such as weather and climate are discussed.
Maxime Taillardat and Olivier Mestre
Nonlin. Processes Geophys., 27, 329–347, https://doi.org/10.5194/npg-27-329-2020, https://doi.org/10.5194/npg-27-329-2020, 2020
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Statistical post-processing of ensemble forecasts is now a well-known procedure in order to correct biased and misdispersed ensemble weather predictions. But practical application in European national weather services is in its infancy. Different applications of ensemble post-processing using machine learning at an industrial scale are presented. Forecast quality and value are improved compared to the raw ensemble, but several facilities have to be made to adjust to operational constraints.
Jonathan Demaeyer and Stéphane Vannitsem
Nonlin. Processes Geophys., 27, 307–327, https://doi.org/10.5194/npg-27-307-2020, https://doi.org/10.5194/npg-27-307-2020, 2020
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Postprocessing schemes used to correct weather forecasts are no longer efficient when the model generating the forecasts changes. An approach based on response theory to take the change into account without having to recompute the parameters based on past forecasts is presented. It is tested on an analytical model and a simple model of atmospheric variability. We show that this approach is effective and discuss its potential application for an operational environment.
Carlos Osácar, Manuel Membrado, and Amalio Fernández-Pacheco
Nonlin. Processes Geophys., 27, 235–237, https://doi.org/10.5194/npg-27-235-2020, https://doi.org/10.5194/npg-27-235-2020, 2020
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We deduce that after a global thermal perturbation, the Earth's
atmosphere would need about a couple of months to come back to equilibrium.
Michiel Van Ginderachter, Daan Degrauwe, Stéphane Vannitsem, and Piet Termonia
Nonlin. Processes Geophys., 27, 187–207, https://doi.org/10.5194/npg-27-187-2020, https://doi.org/10.5194/npg-27-187-2020, 2020
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A generic methodology is developed to estimate the model error and simulate the model uncertainty related to a specific physical process. The method estimates the model error by comparing two different representations of the physical process in otherwise identical models. The found model error can then be used to perturb the model and simulate the model uncertainty. When applying this methodology to deep convection an improvement in the probabilistic skill of the ensemble forecast is found.
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020, https://doi.org/10.5194/npg-27-209-2020, 2020
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Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
André Düsterhus
Nonlin. Processes Geophys., 27, 121–131, https://doi.org/10.5194/npg-27-121-2020, https://doi.org/10.5194/npg-27-121-2020, 2020
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Seasonal prediction of the of the North Atlantic Oscillation (NAO) has been improved in recent years by improving dynamical models and ensemble predictions. One step therein was the so-called sub-sampling, which combines statistical and dynamical predictions. This study generalises this approach and makes it much more accessible. Furthermore, it presents a new verification approach for such predictions.
Courtney Quinn, Terence J. O'Kane, and Vassili Kitsios
Nonlin. Processes Geophys., 27, 51–74, https://doi.org/10.5194/npg-27-51-2020, https://doi.org/10.5194/npg-27-51-2020, 2020
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This study presents a novel method for reduced-rank data assimilation of multiscale highly nonlinear systems. Time-varying dynamical properties are used to determine the rank and projection of the system onto a reduced subspace. The variable reduced-rank method is shown to succeed over other fixed-rank methods. This work provides implications for performing strongly coupled data assimilation with a limited number of ensemble members on high-dimensional coupled climate models.
Cited articles
Adam, O., Schneider, T., and Harnik, N.: Role of changes in mean temperatures
versus temperature gradients in the recent widening of the Hadley
circulation, J. Climate, 27, 7450–7461, https://doi.org/10.1175/JCLI-D-14-00140.1,
2014.
Allen, R. J., Sherwood, S. C., Norris, J. R., and Zender, C. S.: Recent
Northern Hemisphere tropical expansion primarily driven by black carbon and
tropospheric ozone, Nature, 485, 350–354, https://doi.org/10.1038/nature11097,
2012.
Allen, R. J., Norris, J. R., and Kovilakam, M.: Influence of anthropogenic
aerosols and the Pacific Decadal Oscillation on tropical belt width, Nat.
Geosci., 7, 270–274, https://doi.org/10.1038/NGEO2091, 2014.
Archer, C. L. and Caldeira, K.: Historical trends in the jet streams,
Geophys. Res. Lett., 35, 1–6, https://doi.org/10.1029/2008GL033614, 2008.
Barnes, E. A. and Polvani, L. M.: Response of the midlatitude jets, and of
their variability, to increased greenhouse gases in the CMIP5 models, J.
Clim., 26, 7117–7135, https://doi.org/10.1175/JCLI-D-12-00536.1, 2013.
Branstator, G. W.: Organization of Storm Track Anomalies by Recuring
Low-Frequency Circulation Anomalies, J. Atmos. Sci., 52, 207–224, 1994.
Butler, A., Thompson, W. J., and Heikes, R.: The Steady-State Atmospheric
Circulation Response to Climate Change – like Thermal Forcings in a Simple
General Circulation Model, J. Climate, 23, 3474–3496,
https://doi.org/10.1175/2010JCLI3228.1, 2010.
Butler, A. H., Thompson, D. W. J., and Birner, T.: Isentropic Slopes,
Downgradient Eddy Fluxes, and the Extratropical Atmospheric Circulation
Response to Tropical Tropospheric Heating, J. Atmos. Sci., 68,
2292–2305, https://doi.org/10.1175/JAS-D-10-05025.1, 2011.
Chang, E. K. M., Guo, Y., and Xia, X.: CMIP5 multimodel ensemble projection of
storm track change under global warming, J. Geophys. Res.-Atmos., 117,
1–19, https://doi.org/10.1029/2012JD018578, 2012.
Chen, S., Wei, K., Chen, W., and Song, L.: Regional changes in the annual mean
Hadley circulation in recent decades, J. Geophys. Res.-Atmos., 119,
7815–7832, https://doi.org/10.1002/2014JD021540, 2014.
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre, M.
F., Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R., Ganopolski,
A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov, V., Stone,
P., and Wang, Z.: Earth system models of intermediate complexity: Closing the
gap in the spectrum of climate system models, Clim. Dynam., 18, 579–586,
https://doi.org/10.1007/s00382-001-0200-1, 2002.
Coumou, D., Petoukhov, V., and Eliseev, A. V.: Three-dimensional
parameterizations of the synoptic scale kinetic energy and momentum flux in
the Earth's atmosphere, Nonlin. Processes Geophys., 18, 807–827,
https://doi.org/10.5194/npg-18-807-2011, 2011.
Coumou, D., Lehmann, J., and Beckmann, J.: The weakening summer circulation
in the Northern Hemisphere mid-latitudes, Science, 348, 324–327, 2015.
D'Agostino, R. and Lionello, P.: Evidence of global warming impact on the
evolution of the Hadley Circulation in ECMWF centennial reanalyses, Clim.
Dynam., 48, 1–14, https://doi.org/10.1007/s00382-016-3250-0, 2016.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J.,
Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and
Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the
data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011.
Egger, J., Weickmann, K., and Hoinka, K. P.: Angular momentum in the global
atmospheric circulation, Rev. Geophys., 45, 1–25, https://doi.org/10.1029/2006RG000213,
2007.
Eliseev, A. V., Coumou, D., Chernokulsky, A. V., Petoukhov, V., and Petri,
S.: Scheme for calculation of multi-layer cloudiness and precipitation for
climate models of intermediate complexity, Geosci. Model Dev., 6, 1745–1765,
https://doi.org/10.5194/gmd-6-1745-2013, 2013.
Flechsig, M., Böhm, U., Nocke, T., and Rachimow, C.: The Multi-Run
Simulation Environment SimEnv, available at:
https://www.pik-potsdam.de/research/transdisciplinary-concepts-and-methods/tools/simenv/
(last access: 27 January 2019), 2013.
Frierson, D. M. W., Lu, J., and Chen, G.: Width of the Hadley cell in simple
and comprehensive general circulation models, Geophys. Res. Lett., 34, 1–5,
https://doi.org/10.1029/2007GL031115, 2007.
Haigh, J. D., Blackburn, M., and Day, R.: The Response of Tropospheric
Circulation to Perturbations in Lower-Stratospheric Temperature, J. Climate,
18, 3672–3685, 2005.
Harvey, B. J., Shaffrey, L. C., and Woollings, T. J.: Equator-to-pole
temperature differences and the extra-tropical storm track responses of the
CMIP5 climate models, Clim. Dynam., 43, 1171–1182, 2013.
Hawcroft, M. K., Shaffrey, L. C., Hodges, K. I., and Dacre, H. F.: How much
Northern Hemisphere precipitation is associated with extratropical cyclones?,
Geophys. Res. Lett., 39, 1–7, https://doi.org/10.1029/2012GL053866, 2012.
Hill, S. A., Ming, Y., and Held, I. M.: Mechanisms of forced tropical
meridional energy flux change, J. Climate, 28, 1725–1742,
https://doi.org/10.1175/JCLI-D-14-00165.1, 2015.
Hoskins, B. J. and Valdes, P. J.: On the Existence of Storm-Tracks, J. Atmos.
Sci., 47, 1854–1864, 1990.
Kang, S. M., Polvani, L. M., Fyfe, J. C., and Sigmond, M.: Impact of polar
ozone depletion on subtropical precipitation, Science, 332, 951–954,
https://doi.org/10.1126/science.1202131, 2011.
Lehmann, J. and Coumou, D.: The influence of mid-latitude storm tracks on
hot, cold, dry and wet extremes, Sci. Rep., 5, 17491, https://doi.org/10.1038/srep17491,
2015.
Lehmann, J., Coumou, D., Frieler, K., Eliseev, A. V., and Levermann, A.:
Future changes in extratropical storm tracks and baroclinicity under climate
change, Environ. Res. Lett., 9, 084002, https://doi.org/10.1088/1748-9326/9/8/084002,
2014.
Levine, X. J. and Schneider, T.: Baroclinic Eddies and the Extent of the
Hadley Circulation?: An Idealized GCM Study, J. Atmos. Sci., 72, 2744–2761,
https://doi.org/10.1175/JAS-D-14-0152.1, 2015.
Lu, J., Vecchi, G. A., and Reichler, T.: Expansion of the Hadley cell under
global warming, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL030931,
2007.
Lu, J., Chen, G., and Frierson, D. M. W.: Response of the Zonal Mean
Atmospheric Circulation to El Niño versus Global Warming, J. Climate, 21,
5835–5851, https://doi.org/10.1175/2008JCLI2200.1, 2008.
McCabe, G. J., Clark, M. P., and Serreze, M. C.: Trends in Northern
Hemisphere surface cyclone frequency and intensity, J. Climate, 14,
2763–2768, https://doi.org/10.1175/1520-0442(2001)014<2763:TINHSC>2.0.CO;2, 2001.
Mitas, C. M. and Clement, A.: Has the Hadley cell been strengthening in
recent decades?, Geophys. Res. Lett., 32, L03809, https://doi.org/10.1029/2004GL021765,
2005.
Molnos, S., Mamdouh, T., Petri, S., Nocke, T., Weinkauf, T., and Coumou, D.:
A network-based detection scheme for the jet stream core, Earth Syst. Dynam.,
8, 75–89, https://doi.org/10.5194/esd-8-75-2017, 2017.
Nguyen, H., Evans, A., Lucas, C., Smith, I., and Timbal, B.: The hadley
circulation in reanalyses: Climatology, variability, and Change, J. Climate,
26, 3357–3376, https://doi.org/10.1175/JCLI-D-12-00224.1, 2013.
O'Gorman, P. A.: Understanding the varied response of the extratropical storm
tracks to climate change, P. Natl. Acad. Sci. USA, 107, 19176–19180,
https://doi.org/10.1073/pnas.1011547107, 2010.
O'Gorman, P. A. and Schneider, T.: Energy of Midlatitude Transient Eddies in
Idealized Simulations of Changed Climates, J. Climate, 21, 5797–5806,
https://doi.org/10.1175/2008JCLI2099.1, 2008.
Peixoto, J. and Oort, A. H.: Physics of Climate, 1st edn., American Institute
of Physics, New York, 1992.
Pena-Ortiz, C., Gallego, D., Ribera, P., Ordonez, P., and Del Carmen
Alvarez-Castro, M.: Observed trends in the global jet stream characteristics
during the second half of the 20th century, J. Geophys. Res.-Atmos., 118,
2702–2713, https://doi.org/10.1002/jgrd.50305, 2013.
Petoukhov, V., Ganopolski, A., Brovkin, V., Claussen, M., Eliseev, A. V.,
Kubatzki, C., and Rahmstorf, S.: CLIMBER 2: a climate system model of
intermediate complexity. Part I: model description and performance for
present climate, Clim. Dynam., 16, 1–17, https://doi.org/10.1007/PL00007919, 2000.
Pfahl, S., O'Gorman, P. A., and Singh, M. S.: Extratropical Cyclones in
Idealized Simulations of Changed Climates, J. Climate, 28, 9373–9392,
https://doi.org/10.1175/JCLI-D-14-00816.1, 2015.
Polvani, L. M. and Kushner, P. J.: Tropospheric Response to Stratospheric
Perturbations in a Relatively Simple General Circulation Model, Geophys. Res.
Lett., 29, 40–43, https://doi.org/10.1175/1520-0469(2003)060<1835:TRTSDI>2.0.CO;2,
2002.
Raible, C. C., Yoshimori, M., Stocker, T. F., and Casty, C.: Extreme
midlatitude cyclones and their implications for precipitation and wind speed
extremes in simulations of the Maunder Minimum versus present day conditions,
Clim. Dynam., 28, 409–423, https://doi.org/10.1007/s00382-006-0188-7, 2007.
Rikus, L.: A simple climatology of westerly jet streams in global reanalysis
datasets part 1: mid–latitude upper tropospheric jets, Clim. Dynam., 50,
2285–2310, https://doi.org/10.1007/s00382-015-2560-y, 2015.
Salby, M. L.: Physics of the atmosphere and climate, Cambridge University
Press, Cambridge, 2012.
Saltzman, B.: A Survey of Statistical-Dynamical Models of the Terrestrial
Climate, Adv. Geophys., 20, 183–304, https://doi.org/10.1016/S0065-2687(08)60324-6,
1978.
Schneider, T. and Bordoni, S.: Eddy-Mediated Regime Transitions in the
Seasonal Cycle of a Hadley Circulation and Implications for Monsoon Dynamics,
J. Atmos. Sci., 65, 915–934, https://doi.org/10.1175/2007JAS2415.1, 2008.
Schneidereit, A., Blender, R., Fraedrich, K., and Lunkeit, F.: Icelandic
climate and North Atlantic cyclones in ERA-40 reanalyses, Meteorol. Z., 16,
17–23, https://doi.org/10.1127/0941-2948/2007/0187, 2007.
Seo, K., Frierson, D. M. W., and Son, J.: A mechanism for future changes in
Hadley circulation strength in CMIP5 climate change simulations, Geophys.
Res. Lett., 40, 5251–5258, https://doi.org/10.1002/2014GL060868, 2014.
Son, S. W., Tandon, N. F., Polvani, L. M., and Waugh, D. W.: Ozone hole and
Southern Hemisphere climate change, Geophys. Res. Lett., 36, 3–7,
https://doi.org/10.1029/2009GL038671, 2009.
Totz, S., Eliseev, A. V., Petri, S., Flechsig, M., Caesar, L., Petoukhov, V.,
and Coumou, D.: The dynamical core of the Aeolus 1.0 statistical–dynamical
atmosphere model: validation and parameter optimization, Geosci. Model Dev.,
11, 665–679, https://doi.org/10.5194/gmd-11-665-2018, 2018.
Wang, X. L., Swail, V. R., and Zwiers, F. W.: Climatology and Changes of
Extratropical Cyclone Activity?: Comparison of ERA-40 with NCEP – NCAR
Reanalysis for 1958–2001, J. Climate, 19, 3145–3167,
https://doi.org/10.1175/JCLI3781.1, 2006.
Woollings, T.: Dynamical influences on European climate: an uncertain
future., Philos. Trans. A. Math. Phys. Eng. Sci., 368, 3733–3756,
https://doi.org/10.1098/rsta.2010.0040, 2010.
Yin, J. H.: A consistent poleward shift of the storm tracks in simulations of
21st century climate, Geophys. Res. Lett., 32, 1–4,
https://doi.org/10.1029/2005GL023684, 2005.
