The Relationship between Statistically Linear and Nonlinear Feedbacks and Zonal-Mean Flow Variability in an Idealized Climate Model

2009 ◽  
Vol 66 (2) ◽  
pp. 353-372 ◽  
Author(s):  
Sergey Kravtsov ◽  
John E. Ten Hoeve ◽  
Steven B. Feldstein ◽  
Sukyoung Lee ◽  
Seok-Woo Son
Keyword(s):  
Phase Space ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Zonal Flow ◽  
Empirical Orthogonal Functions ◽  
Nonlinear Flow ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Flow Variability

Abstract Simulations using an idealized, atmospheric general circulation model (GCM) subjected to various thermal forcings are analyzed via a combination of probability density function (PDF) estimation and spectral analysis techniques. Seven different GCM runs are examined, each model run being characterized by different values in the strength of the tropical heating and high-latitude cooling. For each model run, it is shown that a linear stochastic model constructed in the phase space of the ten leading empirical orthogonal functions (EOFs) of the zonal-mean zonal flow provides an excellent statistical approximation to the simulated zonal flow variability, which includes zonal index fluctuations, and quasi-oscillatory, poleward, zonal-mean flow anomaly propagation. Statistically significant deviations from the above linear stochastic null hypothesis arise in the form of a few anomalously persistent, or statistically nonlinear, flow patterns, which occupy particular regions of the model’s phase space. Some of these nonlinear regimes occur during certain phases of the poleward propagation; however, such an association is, in general, weak. This indicates that the regimes and oscillations in the model may be governed by distinct dynamical mechanisms.

scholarly journals Producing realistic climate data with generative adversarial networks

2021 ◽  
Vol 28 (3) ◽  
pp. 347-370
Author(s):  
Camille Besombes ◽  
Olivier Pannekoucke ◽  
Corentin Lapeyre ◽  
Benjamin Sanderson ◽  
Olivier Thual
Keyword(s):  
Network Architecture ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Generative Adversarial Networks ◽  
Climate Data ◽  
Orthogonal Functions ◽  
Generative Adversarial Network ◽  
Latent Space

Abstract. This paper investigates the potential of a Wasserstein generative adversarial network to produce realistic weather situations when trained from the climate of a general circulation model (GCM). To do so, a convolutional neural network architecture is proposed for the generator and trained on a synthetic climate database, computed using a simple three dimensional climate model: PLASIM. The generator transforms a “latent space”, defined by a 64-dimensional Gaussian distribution, into spatially defined anomalies on the same output grid as PLASIM. The analysis of the statistics in the leading empirical orthogonal functions shows that the generator is able to reproduce many aspects of the multivariate distribution of the synthetic climate. Moreover, generated states reproduce the leading geostrophic balance present in the atmosphere. The ability to represent the climate state in a compact, dense and potentially nonlinear latent space opens new perspectives in the analysis and handling of the climate. This contribution discusses the exploration of the extremes close to a given state and how to connect two realistic weather situations with this approach.

scholarly journals Producing realistic climate data with GANs

2021 ◽  
Author(s):  
Camille Besombes ◽  
Olivier Pannekoucke ◽  
Corentin Lapeyre ◽  
Benjamin Sanderson ◽  
Olivier Thual
Keyword(s):  
Network Architecture ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Generative Adversarial Networks ◽  
Climate Data ◽  
Orthogonal Functions ◽  
Geostrophic Balance ◽  
Latent Space

Abstract. This paper investigates the potential of a Wasserstein Generative Adversarial Networks to produce realistic weather situations when trained from the climate of a general circulation model (GCM). To do so, a convolutional neural network architecture is proposed for the generator and trained on a synthetic climate database, computed using a simple 3 dimensional climate model: PLASIM. The generator transforms a latent space, defined by a 64 dimensional Gaussian distribution, into spatially defined anomalies on the same output grid as PLASIM. The analysis of the statistics in the leading empirical orthogonal functions shows that the generator is able to reproduce many aspects of the multivariate distribution of the synthetic climate. Moreover, generated states reproduce the leading geostrophic balance present in the atmosphere. The ability to represent the climate state in a compact, dense and potentially nonlinear latent space opens new perspectives in the analysis and the handling of the climate. This contribution discusses the exploration of the extremes close to a given state and how to connect two realistic weather situations with this approach.

scholarly journals Multiple Regimes and Low-Frequency Oscillations in the Northern Hemisphere’s Zonal-Mean Flow

2006 ◽  
Vol 63 (3) ◽  
pp. 840-860 ◽  
Author(s):  
S. Kravtsov ◽  
A. W. Robertson ◽  
M. Ghil
Keyword(s):  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Zonal Flow ◽  
Empirical Orthogonal Functions ◽  
Mean Flow ◽  
Orthogonal Functions ◽  
Atlantic Sector ◽  
Low Frequency Oscillations ◽  
Multiple Regimes ◽  
Flow States

Abstract This paper studies multiple regimes and low-frequency oscillations in the Northern Hemisphere zonal-mean zonal flow in winter, using 55 yr of daily observational data. The probability density function estimated in the phase space spanned by the two leading empirical orthogonal functions exhibits two distinct, statistically significant maxima. The two regimes associated with these maxima describe persistent zonal-flow states that are characterized by meridional displacements of the midlatitude jet, poleward and equatorward of its time-mean position. The geopotential height anomalies of either regime have a pronounced zonally symmetric component, but largest-amplitude anomalies are located over the Atlantic and Pacific Oceans. High-frequency synoptic transients participate in the maintenance of and transitions between these regimes. Significant oscillatory components with periods of 147 and 72 days are identified by spectral analysis of the zonal-flow time series. These oscillations are described by singular spectrum analysis and the multitaper method. The 147-day oscillation involves zonal-flow anomalies that propagate poleward, while the 72-day oscillation only manifests northward propagation in the Atlantic sector. Both modes mainly describe changes in the midlatitude jet position and intensity. In the horizontal plane though, the two modes exhibit synchronous centers of action located over the Atlantic and Pacific Oceans. The two persistent flow regimes are associated with slow phases of either oscillation.

scholarly journals Zonal Flow Regime Changes in a GCM and in a Simple Quasigeostrophic Model: The Role of Stratospheric Dynamics

2009 ◽  
Vol 66 (5) ◽  
pp. 1366-1383 ◽  
Author(s):  
Isabella Bordi ◽  
Klaus Fraedrich ◽  
Michael Ghil ◽  
Alfonso Sutera
Keyword(s):  
General Circulation ◽  
Baroclinic Instability ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
Circulation Model ◽  
Zonal Flow ◽  
Heat Fluxes ◽  
Mean Flow ◽  
Single Wave

Abstract The atmospheric general circulation is characterized by both single- and double-jet patterns. The double-jet structure of the zonal mean zonal wind is analyzed in Southern Hemisphere observations for the two calendar months of November and April. The observed features are studied further in an idealized quasigeostrophic and a simplified general circulation model (GCM). Results suggest that capturing the bimodality of the zonal mean flow requires the parameterization of momentum and heat fluxes associated with baroclinic instability of the three-dimensional fields. The role of eddy heat fluxes in generating the observed double-jet pattern is ascertained by using an analytical Eady model with stratospheric easterlies, in which a single wave disturbance interacts with the mean flow. In this model, the dual jets are generated by the zonal mean flow correction. Sensitivity of the results to the tropospheric vertical wind shear (or, equivalently, the meridional temperature gradient in the basic state’s troposphere) is also studied in the Eady model and compared to related experiments using the simplified GCM.

Linear and Nonlinear Signatures in the Planetary Wave Dynamics of an AGCM: Phase Space Tendencies

2005 ◽  
Vol 62 (6) ◽  
pp. 1792-1811 ◽  
Author(s):  
Grant Branstator ◽  
Judith Berner
Keyword(s):  
Phase Space ◽  
General Circulation ◽  
Planetary Wave ◽  
Gaussian White Noise ◽  
Circulation Model ◽  
Lag Time ◽  
Empirical Orthogonal Functions ◽  
Linear Component ◽  
Least Squares Fit ◽  
Linear And Nonlinear

Abstract To identify and quantify indications of linear and nonlinear planetary wave behavior, characteristics of a very long integration of an atmospheric general circulation model in a four-dimensional phase space are examined. The phase space is defined by the leading four empirical orthogonal functions of 500-hPa geopotential heights, and the primary investigated characteristic is the state dependence of mean phase space tendencies. Defining the linear component of planetary wave tendencies as that part which can be captured by a least squares fit linear operator driven by additive Gaussian white noise, the study finds that there are distinct linear and nonlinear signatures. These signatures are especially easy to see in plots of mean tendencies projected onto phase space planes. For some planes the mean tendencies are highly linear, while for others there are strong departures from linearity. The results of the analysis are found to depend strongly on the lag time used to estimate tendencies with the linear component monotonically increasing with lag time. This is shown to result from the ergodicity of the system. Using the theory of Markov models it is possible to remove the lag-dependent component of the tendencies from the results. When this is done the projected mean dynamics in some planes is found to be almost exclusively nonlinear, while in others it is nearly linear. In the four-dimensional space the linear component of the dynamics is largely a reflection of a westward propagating Northern Hemisphere pattern concentrated over the Pacific and North America. The nonlinear signature can be approximated by two linear functions, each operating in a different region of phase space. One region is centered around a Pacific blocking pattern while the other is centered on a state with enhanced zonal symmetry. It is concluded that reduced models of the planetary waves should strive to include these state-dependent dynamics.

scholarly journals Impact of a simple parameterization of convective gravity-wave drag in a stratosphere-troposphere general circulation model and its sensitivity to vertical resolution

1998 ◽  
Vol 16 (2) ◽  
pp. 238-249 ◽  
Author(s):  
C. Bossuet ◽  
M. Déqué ◽  
D. Cariolle
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Positive Impact ◽  
Deep Convection ◽  
Circulation Model ◽  
Wave Drag ◽  
Horizontal Resolution ◽  
Vertical Resolution ◽  
Mean Flow ◽  
The Impact

Abstract. Systematic westerly biases in the southern hemisphere wintertime flow and easterly equatorial biases are experienced in the Météo-France climate model. These biases are found to be much reduced when a simple parameterization is introduced to take into account the vertical momentum transfer through the gravity waves excited by deep convection. These waves are quasi-stationary in the frame of reference moving with convection and they propagate vertically to higher levels in the atmosphere, where they may exert a significant deceleration of the mean flow at levels where dissipation occurs. Sixty-day experiments have been performed from a multiyear simulation with the standard 31 levels for a summer and a winter month, and with a T42 horizontal resolution. The impact of this parameterization on the integration of the model is found to be generally positive, with a significant deceleration in the westerly stratospheric jet and with a reduction of the easterly equatorial bias. The sensitivity of the Météo-France climate model to vertical resolution is also investigated by increasing the number of vertical levels, without moving the top of the model. The vertical resolution is increased up to 41 levels, using two kinds of level distribution. For the first, the increase in vertical resolution concerns especially the troposphere (with 22 levels in the troposphere), and the second treats the whole atmosphere in a homogeneous way (with 15 levels in the troposphere); the standard version of 31 levels has 10 levels in the troposphere. A comparison is made between the dynamical aspects of the simulations. The zonal wind and precipitation are presented and compared for each resolution. A positive impact is found with the finer tropospheric resolution on the precipitation in the mid-latitudes and on the westerly stratospheric jet, but the general impact on the model climate is weak, the physical parameterizations used appear to be mostly independent to the vertical resolution.Key words. Meteorology and atmospheric dynamics · Convective processes · Waves and tides

scholarly journals Transient teleconnection event at the onset of a planet-encircling dust storm on Mars

2009 ◽  
Vol 27 (9) ◽  
pp. 3663-3676 ◽  
Author(s):  
O. Martínez-Alvarado ◽  
L. Montabone ◽  
S. R. Lewis ◽  
I. M. Moroz ◽  
P. L. Read
Keyword(s):  
Dust Storm ◽  
General Circulation ◽  
Thermal Emission ◽  
Three Dimensional ◽  
Circulation Model ◽  
Empirical Orthogonal Functions ◽  
State Variables ◽  
Orthogonal Functions ◽  
Teleconnection Patterns ◽  
Pressure Surface

Abstract. We use proper orthogonal decomposition (POD) to study a transient teleconnection event at the onset of the 2001 planet-encircling dust storm on Mars, in terms of empirical orthogonal functions (EOFs). There are several differences between this and previous studies of atmospheric events using EOFs. First, instead of using a single variable such as surface pressure or geopotential height on a given pressure surface, we use a dataset describing the evolution in time of global and fully three-dimensional atmospheric fields such as horizontal velocity and temperature. These fields are produced by assimilating Thermal Emission Spectrometer observations from NASA's Mars Global Surveyor spacecraft into a Mars general circulation model. We use total atmospheric energy (TE) as a physically meaningful quantity which weights the state variables. Second, instead of adopting the EOFs to define teleconnection patterns as planetary-scale correlations that explain a large portion of long time-scale variability, we use EOFs to understand transient processes due to localised heating perturbations that have implications for the atmospheric circulation over distant regions. The localised perturbation is given by anomalous heating due to the enhanced presence of dust around the northern edge of the Hellas Planitia basin on Mars. We show that the localised disturbance is seemingly restricted to a small number (a few tens) of EOFs. These can be classified as low-order, transitional, or high-order EOFs according to the TE amount they explain throughout the event. Despite the global character of the EOFs, they show the capability of accounting for the localised effects of the perturbation via the presence of specific centres of action. We finally discuss possible applications for the study of terrestrial phenomena with similar characteristics.

Linear and Nonlinear Signatures in the Planetary Wave Dynamics of an AGCM: Probability Density Functions

2007 ◽  
Vol 64 (1) ◽  
pp. 117-136 ◽  
Author(s):  
Judith Berner ◽  
Grant Branstator
Keyword(s):  
Phase Space ◽  
Probability Density ◽  
General Circulation ◽  
Planetary Wave ◽  
Circulation Model ◽  
Gaussian Mixture ◽  
Empirical Orthogonal Functions ◽  
Planetary Waves ◽  
Linear And Nonlinear ◽  
Non Gaussian

Abstract To identify and quantify indications of linear and nonlinear planetary wave behavior and their impact on the distribution of atmospheric states, characteristics of a very long integration of an atmospheric general circulation model (GCM) in a four-dimensional phase space are examined. The phase space is defined by the leading four empirical orthogonal functions of 500-hPa geopotential heights. First it is established that nonlinear tendencies similar to those reported in an earlier study of the phase space behavior in this GCM have the potential to lead to non-Gaussian features in the probability density function (PDF) of planetary waves. Then using objective measures it is demonstrated that the model’s distribution of states has distinctive non-Gaussian features. These features are characterized in various subspaces of dimension as high as four. A key feature is the presence of three radial ridges of enhanced probability emanating from the mode, which is shifted away from the climatological mean. There is no evidence of multiple maxima in the full PDF, but the radial ridges lead to three distinct modes in the distribution of circulation patterns. It is demonstrated that these key aspects of non-Gaussianity are captured by a two-Gaussian mixture model fitted in four dimensions. The two circulation states at the centroids of the component Gaussians are very similar to those associated with two nonlinear features identified by Branstator and Berner in their analysis of the trajectories of the GCM. These two dynamical features are locally linear, so it is concluded that the behavior of planetary waves can be conceptualized as being approximately piecewise-linear, leading to a two-Gaussian mixture with three preferred patterns.

scholarly journals A Dynamically Consistent Reconstruction of Ocean Temperature

2017 ◽  
Vol 34 (5) ◽  
pp. 1061-1082 ◽  
Author(s):  
Samuel S. P. Shen ◽  
Gregory P. Behm ◽  
Y. Tony Song ◽  
Tangdong Qu
Keyword(s):  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Global Ocean ◽  
Reconstruction Method ◽  
Ocean Temperature ◽  
Orthogonal Functions

AbstractThis paper provides a spectral optimal gridding (SOG) method to make a dynamically consistent reconstruction of water temperature for the global ocean at different depth levels. The dynamical consistency is achieved by using the basis of empirical orthogonal functions (EOFs) derived from NASA Jet Propulsion Laboratory (JPL) non-Boussinesq ocean general circulation model (OGCM) output at ¼° resolution from 1958 to 2013. A convenient singular value decomposition (SVD) method is used to calculate the EOFs, in order to enable efficient computing for a fine spatial grid globally. These EOFs are used as explainable variables and are regressed against the sparsely distributed in situ ocean temperature data at 33 standard depth levels. The observed data are aggregated onto a 1° latitude–longitude grid at each level from the surface to the 5500-m layer for the period 1950–2014. Three representative temperature reconstruction examples are presented and validated: two 10-m-layer (i.e., the second layer from the surface) reconstructions for January 2008 and January 1998, which are compared with independent sea surface temperature (SST) observations; and one 100-m-layer reconstruction for January 1998, which shows a strong cold anomaly El Niño signal in the western tropical Pacific up to −5°C from 150°E to 140°W. The SOG reconstruction can accurately locate the El Niño signal region in different ocean layers. The SOG reconstruction method is shown reliable and yields satisfactory accuracy even with sparse data. Validation and error analysis indicate that no systematic biases exist in the observed and reconstructed data.

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