Nonlinear Processes in Geophysics

Syndicate content
Combined list of the recent articles of the journal Nonlinear Processes in Geophysics and the recent discussion forum Nonlinear Processes in Geophysics Discussions
Updated: 6 hours 12 min ago

Revising the stochastic iterative ensemble smoother

Fri, 03/15/2019 - 14:02
Revising the stochastic iterative ensemble smoother
Patrick N. Raanes, Andreas S. Stordal, and Geir Evensen
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2019-10,2019
Manuscript under review for NPG (discussion: open, 0 comments)
A popular (variational ensemble smoother) method of data assimilation is simplified. An exact relationship between ensemble linearizations (linear regression) and adjoints (analytic derivatives) is established.

Particle Clustering and Subclustering as a Proxy for Mixing in Geophysical Flows

Thu, 03/14/2019 - 14:02
Particle Clustering and Subclustering as a Proxy for Mixing in Geophysical Flows
Rishiraj Chakraborty, Aaron Coutino, and Marek Stastna
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2019-6,2019
Manuscript under review for NPG (discussion: open, 0 comments)
In this paper, we highlight a specific example of large scale flows. We talk about technical developments of how to extract regions of dense mixing in the flow using graph theoretic tools from discrete Mathematics.

Data assimilation using adaptive, non-conservative, moving mesh models

Mon, 03/11/2019 - 14:02
Data assimilation using adaptive, non-conservative, moving mesh models
Ali Aydoğdu, Alberto Carrassi, Colin T. Guider, Chris K. R. T. Jones, and Pierre Rampal
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2019-9,2019
Manuscript under review for NPG (discussion: open, 0 comments)
Computational models involving adaptive meshes can both evolve dynamically and be remeshed. The remeshing means that the state vector dimension changes in time and across ensemble members, making EnKF unsuitable for the assimilation of observational data. We develop a modification in which the analysis is performed on a fixed uniform grid onto which the ensemble is mapped, with resolution related to the remeshing criteria. The approach is tested on two 1D models proving success.

Denoising stacked autoencoders for transient electromagnetic signal denoising

Fri, 03/01/2019 - 14:02
Denoising stacked autoencoders for transient electromagnetic signal denoising
Fanqiang Lin, Kecheng Chen, Xuben Wang, Hui Cao, Danlei Chen, and Fanzeng Chen
Nonlin. Processes Geophys., 26, 13-23, https://doi.org/10.5194/npg-26-13-2019, 2019
The deep-seated information is reflected in the late-stage data of the second field. By introducing the deep learning algorithm integrated with the characteristics of the secondary field data, we can map the contaminated data in late track data to a high-probability position. By comparing several filtering algorithms, the SFSDSA method has better performance and the denoising signal is conducive to further improving the effective detection depth.

Data assimilation as a deep learning tool to infer ODE representations of dynamical models

Thu, 02/28/2019 - 14:02
Data assimilation as a deep learning tool to infer ODE representations of dynamical models
Marc Bocquet, Julien Brajard, Alberto Carrassi, and Laurent Bertino
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2019-7,2019
Manuscript under review for NPG (discussion: open, 0 comments)
This paper describes an innovative way to use data assimilation to infer the dynamics of a physical system from its observation only. The method can operate with noisy and partial observation of the physical system. It acts as a deep learning technique specialised to dynamical models without the need for machine learning tools. The method is successfully tested on chaotic dynamical systems: the Lorenz-63, Lorenz-96, Kuramoto-Sivashinski models and a two-scale Lorenz model.

Exploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical–dynamical atmospheric model

Mon, 02/18/2019 - 14:02
Exploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical–dynamical atmospheric model
Sonja Totz, Stefan Petri, Jascha Lehmann, Erik Peukert, and Dim Coumou
Nonlin. Processes Geophys., 26, 1-12, https://doi.org/10.5194/npg-26-1-2019, 2019

Climate and weather conditions in the mid-latitudes are strongly driven by the large-scale atmosphere circulation. Observational data indicate that important components of the large-scale circulation have changed in recent decades, including the strength and the width of the Hadley cell, jets, storm tracks and planetary waves.

Here, we use a new statistical–dynamical atmosphere model (SDAM) to test the individual sensitivities of the large-scale atmospheric circulation to changes in the zonal temperature gradient, meridional temperature gradient and global-mean temperature. We analyze the Northern Hemisphere Hadley circulation, jet streams, storm tracks and planetary waves by systematically altering the zonal temperature asymmetry, the meridional temperature gradient and the global-mean temperature. Our results show that the strength of the Hadley cell, storm tracks and jet streams depend, in terms of relative changes, almost linearly on both the global-mean temperature and the meridional temperature gradient, whereas the zonal temperature asymmetry has little or no influence. The magnitude of planetary waves is affected by all three temperature components, as expected from theoretical dynamical considerations. The width of the Hadley cell behaves nonlinearly with respect to all three temperature components in the SDAM. Moreover, some of these observed large-scale atmospheric changes are expected from dynamical equations and are therefore an important part of model validation.

Precision Annealing Monte Carlo Methods for Statistical Data Assimilation: Metropolis-Hastings Procedures

Fri, 02/08/2019 - 14:02
Precision Annealing Monte Carlo Methods for Statistical Data Assimilation: Metropolis-Hastings Procedures
Adrian S. Wong, Kangbo Hao, Zheng Fang, and Henry D. I. Abarbanel
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2019-1,2019
Manuscript under review for NPG (discussion: open, 1 comment)
Our paper deals with data assimilation methods for chaotic systems and how one can make predictions from incomplete data of such systems. The method that we chose to explore in detail is a Monte Carlo method with an annealing heuristic. Our results show that Monte Carlo methods are a viable alternatives to the standard set of derivative-based methods. We verify the method using the Lorenz 96 system due to the simplicity of that system.

Mahalanobis distance based recognition of changes in the dynamics of seismic process

Tue, 02/05/2019 - 14:02
Mahalanobis distance based recognition of changes in the dynamics of seismic process
Teimuraz Matcharashvili, Zbigniew Czechowski, and Natalia Zhukova
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-57,2019
Manuscript under review for NPG (discussion: open, 1 comment)

In present work we aimed to analyze regularity of seismic process based on all its spatial, temporal and energetic characteristics. Increments of cumulative times, increments of cumulative distances and increments of cumulative seismic energies, have been calculated from southern California earthquake catalogue, 1975 to 2017.

Used method of analysis represented combination of multivariate Mahalanobis distance calculation with the surrogate data testing. Prior to proceed to the analysis of dynamical features of seismic process we have tested used approach for two different 3 dimensional models in which dynamical features were changed from more regular to the more randomized conditions by adding some extent of noises.

Analysis of variability in the extent of regularity of seismic process have been accomplished for different representative threshold values.

According to results of our analysis about third part of considered 50 data windows, the original seismic process is indistinguishable from random process by its features of temporal, spatial and energetic variability. It was shown that prior to strong earthquake occurrences, in periods of relatively small earthquakes generation, percentage of windows in which seismic process is indistinguishable from random process essentially increases (to 60–80 %). At the same time, in periods of aftershock activity in all considered windows the process of small earthquake generation become regular and thus is strongly different from randomized catalogues.

In some periods of catalogue time span seismic process looks closer to randomness while in other cases it becomes closer to regular behavior. Exactly, in periods of relatively decreased earthquake generation activity (at smaller energy release), seismic process looks random-like while in periods of occurrence of strong events, followed by series of aftershocks, it reveal significant deviation from randomness – the extent of regularity essentially increases. The period, for which such deviation from the random behavior can last, depends on the amount of seismic energy released by the strong earthquake.

Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to India Rainfall

Thu, 12/13/2018 - 14:02
Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to India Rainfall
Justin A. Schulte
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-55,2018
Manuscript under review for NPG (discussion: final response, 2 comments)
Statistical hypothesis tests in wavelet analysis are used to asses the likelihood that time series features are noise. The choice of test will determine what features emerge as a signal. Tests based on area do poorly at distinguishing abrupt fluctuations from periodic behavior unlike tests based on arc length that do better. The application of the tests suggests that there are features in India rainfall time series that emerge from background noise.

Estimating vertically averaged energy dissipation rate

Mon, 12/10/2018 - 14:02
Estimating vertically averaged energy dissipation rate
Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, and Ichiro Yasuda
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-48,2018
Manuscript under review for NPG (discussion: final response, 3 comments)
The observed profiles of the turbulent energy dissipation rate look so erratic that we can hardly identify them as continuous curves. However, we found that each sequence has the striking feature of self-similarity. Using this, we can efficiently take ensemble statistics of the vertically averaged energy dissipation rate from a single observation profile, by scaling up and promoting the observed value at each depth to one that corresponds to the whole profile.

On the localization in strongly coupled ensemble data assimilation using a two-scale Lorenz model

Wed, 12/05/2018 - 14:02
On the localization in strongly coupled ensemble data assimilation using a two-scale Lorenz model
Zheqi Shen, Youmin Tang, Xiaojing Li, Yanqiu Gao, and Junde Li
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-50,2018
Revised manuscript under review for NPG (discussion: final response, 5 comments)
In this work, we conduct the strongly coupled data assimilation (SCDA) experiments using a two-scale Lorenz '96 model with the ensemble adjustment Kalman filter. This is a coupled system composed by two models with different scales. We have developed a new localization strategy for the cross-domain error covariances, which is crucial for the quality of SCDA. The results show that the SCDA with localization could provide much more accurate estimation of the states than the WCDA.

Can the Nucleation Phase be Generated on a Sub-fault Linked to the Main Fault of an Earthquake?

Wed, 12/05/2018 - 14:02
Can the Nucleation Phase be Generated on a Sub-fault Linked to the Main Fault of an Earthquake?
Jeen-Hwa Wang
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-49,2018
Manuscript under review for NPG (discussion: open, 4 comments)

We study the effects of seismic coupling, friction, viscous, and inertia on earthquake nucleation based on a two-body spring-slider model in the presence of thermal-pressurized slip-dependent friction and viscosity. The stiffness ratio of the system to represent seismic coupling is the ratio of coil spring K between two sliders and the leaf spring L between a slider and the background plate and denoted by s = K/L. The s is not a significant factor in generating the nucleation phase. The masses of the two sliders are m1 and m2, respectively. The frictional and viscous effects are specified by the static friction force, fo, the characteristic displacement, Uc, and viscosity coefficient, h, respectively. Numerical simulations show that friction and viscosity can both lengthen the natural period of the system and viscosity increases the duration time of motion of the slider. Higher viscosity causes lower particle velocities than lower viscosity. The ratios γ = h2/h1, φ = fo2/fo1, ψ = Uc2/Ucl, and μ = m2/m1 are four important factors in influencing the generation of a nucleation phase. When s > 0.17, γ > 1, 1.15 > φ > 1, ψ < 1, and μ < 30, simulation results exhibit the generation of nucleation phase on slider 1 and the formation of P wave on slider 2. The results are consistent with the observations and suggest the possibility of generation of nucleation phase on a sub-fault.

Competition between Chaotic Advection and Diffusion: Stirring and Mixing in a 3D Eddy Model

Tue, 12/04/2018 - 14:02
Competition between Chaotic Advection and Diffusion: Stirring and Mixing in a 3D Eddy Model
Genevieve Jay Brett, Larry Pratt, Irina Rypina, and Peng Wang
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-54,2018
Revised manuscript accepted for NPG (discussion: closed, 5 comments)
The relative importance of chaotic stirring and smaller-scale turbulent mixing for the distribution of dye in an idealized ocean flow feature is quantified using three different methods. We find that stirring is the dominant process in large areas with fast stirring, while mixing dominates in small fast-stirring regions and all slow-stirring regions. This quantification of process dominance can help oceanographers think about when to model stirring accurately, which can be costly.

Characterization of the South Atlantic Anomaly

Mon, 12/03/2018 - 14:02
Characterization of the South Atlantic Anomaly
Khairul Afifi Nasuddin, Mardina Abdullah, and Nurul Shazana Abdul Hamid
Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2018-51,2018
Revised manuscript accepted for NPG (discussion: closed, 4 comments)
This research intends to characterize the South Atlantic Anomaly (SAA) by applying power spectrum analysis approach. The outcomes of the research revealed that the SAA region had a tendency to be persistent during active period and normal periods. It can be said, it experiences this characteristic because of the Earth’s magnetic field strength. It is very important for spacecraft when entering the SAA take safety precaution in order to minimize the damage.

Theme by Danetsoft and Danang Probo Sayekti inspired by Maksimer