A multiscale ocean data assimilation approach combining spatial and spectral localisation

Abstract. Ocean data assimilation systems encompass a wide range of scales that are difficult to control simultaneously using partial observation networks. All scales are not observable by all observation systems, which is not easily taken into account in current ocean operational systems. The main reason for this difficulty is that the error covariance matrices are usually assumed to be local (e.g. using a localisation algorithm in ensemble data assimilation systems), so that the large-scale patterns are removed from the error statistics. To better exploit the observational information available for all scales in the assimilation systems of the Copernicus Marine Environment Monitoring Service, we investigate a new method to introduce scale separation in the assimilation scheme. The method is based on a spectral transformation of the assimilation problem and consists in carrying out the analysis with spectral localisation for the large scales and spatial localisation for the residual scales. The target is to improve the observational update of the large-scale components of the signal by an explicit observational constraint applied directly on the large scales and to restrict the use of spatial localisation to the small-scale components of the signal. To evaluate our method, twin experiments are carried out with synthetic altimetry observations (simulating the Jason tracks), assimilated in a 1/4∘ model configuration of the North Atlantic and the Nordic Seas. Results show that the transformation to the spectral domain and the spectral localisation provides consistent ensemble estimates of the state of the system (in the spectral domain or after backward transformation to the spatial domain). Combined with spatial localisation for the residual scales, the new scheme is able to provide a reliable ensemble update for all scales, with improved accuracy for the large scale; and the performance of the system can be checked explicitly and separately for all scales in the assimilation system.

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A multiscale ocean data assimilation approach combining spatial and spectral localisation

10.5194/os-2018-132 ◽

2018 ◽

Author(s):

Ann-Sophie Tissier ◽

Jean-Michel Brankart ◽

Charles-Emmanuel Testut ◽

Giovanni Ruggiero ◽

Emmanuel Cosme ◽

...

Keyword(s):

Data Assimilation ◽

Large Scale ◽

Spectral Space ◽

Small Scale ◽

Localization Algorithm ◽

Error Statistics ◽

Ocean Data Assimilation ◽

Spectral Localization ◽

Wide Range ◽

Spatial Localisation

Abstract. Ocean data assimilation systems encompass a wide range of scales that are difficult to control simultaneously using partial observation networks. All scales are not observable by all observation systems which is not easily taken into account in current ocean operational systems. The main reason for this difficulty is that the error covariance matrices are usually assumed to be local (e.g. using a localization algorithm in ensemble data assimilation systems), so that the large scale patterns are removed from the error statistics. To better exploit the observational information available for all scales in CMEMS assimilation systems, we investigate a new method to introduce scale separation in the assimilation scheme. The method is based on a spectral transformation of the assimilation problem and consists in carrying out the analysis with spectral localisation for the large scales and spatial localisation for the residual scales. The target is to improve the observational update of the large scale components of the signal by an explicit observational constraint applied directly on the large scales, and to restrict the use of spatial localisation to the small scale components of the signal. To evaluate our method, twin experiments are carried out with synthetic altimetry observations (simulating the JASON tracks), assimilated in a 1/4° model configuration of the North Atlantic and the Nordic Seas. Results show that the transformation to the spectral space and the spectral localization provides consistent ensemble estimates of the state of the system (in the spectral space,or after backward transformation to the spatial space). Combined with spatial localisation for the residual scales, the new scheme is able to provide a reliable ensemble update for all scales, with improved accuracy for the large scale; and the performance of the system can be checked explicitly and separately for all scales in the assimilation system.

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Finescale Structure of the T–S Relation in the Eastern North Atlantic

Journal of Physical Oceanography ◽

10.1175/jpo2763.1 ◽

2005 ◽

Vol 35 (8) ◽

pp. 1437-1454 ◽

Cited By ~ 58

Author(s):

R. Ferrari ◽

K. L. Polzin

Keyword(s):

North Atlantic ◽

Large Scale ◽

Salinity Gradient ◽

Mesoscale Eddies ◽

Thermal Dissipation ◽

Small Scale ◽

The North ◽

Wide Range ◽

Using Data ◽

Gyre Circulation

Abstract Distributions of temperature (T) and salinity (S) and their relationship in the oceans are the result of a balance between T–S variability generated at the surface by air–sea fluxes and its removal by molecular dissipation. In this paper the role of different motions in setting the cascade of T–S variance to dissipation scales is quantified using data from the North Atlantic Tracer Release Experiment (NATRE). The NATRE observational programs include fine- and microscale measurements and provide a snapshot of T–S variability across a wide range of scales from basin to molecular. It is found that microscale turbulence controls the rate of thermal dissipation in the thermocline. At this level the T–S relation is established through a balance between large-scale advection by the gyre circulation and small-scale turbulence. Further down, at the level of intermediate and Mediterranean waters, mesoscale eddies are the rate-controlling process. The transition between the two regimes is related to the presence of a strong salinity gradient along density surfaces associated with the outflow of Mediterranean waters. Mesoscale eddies stir this gradient and produce a rich filamentation and salinity-compensated temperature inversions: isopycnal stirring and diapycnal mixing are both required to explain the T–S relation at depth.

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Coupled Thermo-Hydro-Geochemical Models of Engineered Barrier Systems: The Febex Project

MRS Proceedings ◽

10.1557/proc-663-561 ◽

2000 ◽

Vol 663 ◽

Cited By ~ 2

Author(s):

J. Samper ◽

R. Juncosa ◽

V. Navarro ◽

J. Delgado ◽

L. Montenegro ◽

...

Keyword(s):

Large Scale ◽

Reference Model ◽

Numerical Models ◽

Full Scale ◽

Small Scale ◽

Model Parameters ◽

In Situ Test ◽

Wide Range ◽

Engineered Barrier

ABSTRACTFEBEX (Full-scale Engineered Barrier EXperiment) is a demonstration and research project dealing with the bentonite engineered barrier designed for sealing and containment of waste in a high level radioactive waste repository (HLWR). It includes two main experiments: an situ full-scale test performed at Grimsel (GTS) and a mock-up test operating since February 1997 at CIEMAT facilities in Madrid (Spain) [1,2,3]. One of the objectives of FEBEX is the development and testing of conceptual and numerical models for the thermal, hydrodynamic, and geochemical (THG) processes expected to take place in engineered clay barriers. A significant improvement in coupled THG modeling of the clay barrier has been achieved both in terms of a better understanding of THG processes and more sophisticated THG computer codes. The ability of these models to reproduce the observed THG patterns in a wide range of THG conditions enhances the confidence in their prediction capabilities. Numerical THG models of heating and hydration experiments performed on small-scale lab cells provide excellent results for temperatures, water inflow and final water content in the cells [3]. Calculated concentrations at the end of the experiments reproduce most of the patterns of measured data. In general, the fit of concentrations of dissolved species is better than that of exchanged cations. These models were later used to simulate the evolution of the large-scale experiments (in situ and mock-up). Some thermo-hydrodynamic hypotheses and bentonite parameters were slightly revised during TH calibration of the mock-up test. The results of the reference model reproduce simultaneously the observed water inflows and bentonite temperatures and relative humidities. Although the model is highly sensitive to one-at-a-time variations in model parameters, the possibility of parameter combinations leading to similar fits cannot be precluded. The TH model of the “in situ” test is based on the same bentonite TH parameters and assumptions as for the “mock-up” test. Granite parameters were slightly modified during the calibration process in order to reproduce the observed thermal and hydrodynamic evolution. The reference model captures properly relative humidities and temperatures in the bentonite [3]. It also reproduces the observed spatial distribution of water pressures and temperatures in the granite. Once calibrated the TH aspects of the model, predictions of the THG evolution of both tests were performed. Data from the dismantling of the in situ test, which is planned for the summer of 2001, will provide a unique opportunity to test and validate current THG models of the EBS.

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Editorial

Widening Participation and Lifelong Learning ◽

10.5456/wpll.23.1.1 ◽

2021 ◽

Vol 23 (1) ◽

pp. 1-4

Author(s):

Eva Cendon ◽

John Butcher

Keyword(s):

Further Education ◽

University Education ◽

Small Scale ◽

Widening Participation ◽

The North ◽

Research Activities ◽

International Perspectives ◽

Wide Range ◽

International Sector ◽

The Uk

This general edition of the journal provides insights and results of research employing a wide range of approaches and perspectives on widening participation and lifelong learning. Studies from across the UK and international sector utilise different methodological approaches, and as such are particularly interesting, with diverse methods and ways of analysis, including phenomenographic, narrative, and thematic analysis. Overall, the articles range from exploratory case studies and small-scale research to wider range and broad scale studies, highlighting different facets and perspectives. Furthermore, the articles in this volume cover a broad spectrum of institutions and places involved in widening participation, with an emphasis on the (higher) education sector in the UK balanced by international perspectives. The first seven empirical articles are based on research activities in a secondary school, a youth centre, in further education colleges (usually focusing on post-compulsory secondary or pre-university education), in so-called post-92 universities (new(er) universities, formerly Polytechnics and teacher training colleges), and last but not least in a research intensive Russell Group university. They reported challenges from the specific local contexts of different regions in England, from the South (Chichester) to London to the North (Carlisle), and can usefully be framed in the context of international discussions appearing later in the journal.

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A Scale-Selective Data Assimilation Approach to Improving Tropical Cyclone Track and Intensity Forecasts in a Limited-Area Model: A Case Study of Hurricane Felix (2007)

Weather and Forecasting ◽

10.1175/waf-d-10-05033.1 ◽

2012 ◽

Vol 27 (1) ◽

pp. 124-140 ◽

Cited By ~ 11

Author(s):

Bin Liu ◽

Lian Xie

Keyword(s):

Data Assimilation ◽

Large Scale ◽

Dynamical Downscaling ◽

Weather Forecasting ◽

Forecast Error ◽

Regional Model ◽

Small Scale ◽

Limited Area ◽

Track Forecast ◽

Global Models

Abstract Accurately forecasting a tropical cyclone’s (TC) track and intensity remains one of the top priorities in weather forecasting. A dynamical downscaling approach based on the scale-selective data assimilation (SSDA) method is applied to demonstrate its effectiveness in TC track and intensity forecasting. The SSDA approach retains the merits of global models in representing large-scale environmental flows and regional models in describing small-scale characteristics. The regional model is driven from the model domain interior by assimilating large-scale flows from global models, as well as from the model lateral boundaries by the conventional sponge zone relaxation. By using Hurricane Felix (2007) as a demonstration case, it is shown that, by assimilating large-scale flows from the Global Forecast System (GFS) forecasts into the regional model, the SSDA experiments perform better than both the original GFS forecasts and the control experiments, in which the regional model is only driven by lateral boundary conditions. The overall mean track forecast error for the SSDA experiments is reduced by over 40% relative to the control experiments, and by about 30% relative to the GFS forecasts, respectively. In terms of TC intensity, benefiting from higher grid resolution that better represents regional and small-scale processes, both the control and SSDA runs outperform the GFS forecasts. The SSDA runs show approximately 14% less overall mean intensity forecast error than do the control runs. It should be noted that, for the Felix case, the advantage of SSDA becomes more evident for forecasts with a lead time longer than 48 h.

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Buoyancy effects on large-scale motions in convective atmospheric boundary layers: implications for modulation of near-wall processes

Journal of Fluid Mechanics ◽

10.1017/jfm.2018.711 ◽

2018 ◽

Vol 856 ◽

pp. 135-168 ◽

Cited By ~ 19

Author(s):

S. T. Salesky ◽

W. Anderson

Keyword(s):

Boundary Layer ◽

Velocity Field ◽

Boundary Layers ◽

Vertical Velocity ◽

Amplitude Modulation ◽

Large Scale ◽

Streamwise Velocity ◽

Small Scale ◽

Convective Conditions ◽

Wide Range

A number of recent studies have demonstrated the existence of so-called large- and very-large-scale motions (LSM, VLSM) that occur in the logarithmic region of inertia-dominated wall-bounded turbulent flows. These regions exhibit significant streamwise coherence, and have been shown to modulate the amplitude and frequency of small-scale inner-layer fluctuations in smooth-wall turbulent boundary layers. In contrast, the extent to which analogous modulation occurs in inertia-dominated flows subjected to convective thermal stratification (low Richardson number) and Coriolis forcing (low Rossby number), has not been considered. And yet, these parameter values encompass a wide range of important environmental flows. In this article, we present evidence of amplitude modulation (AM) phenomena in the unstably stratified (i.e. convective) atmospheric boundary layer, and link changes in AM to changes in the topology of coherent structures with increasing instability. We perform a suite of large eddy simulations spanning weakly ($-z_{i}/L=3.1$) to highly convective ($-z_{i}/L=1082$) conditions (where$-z_{i}/L$is the bulk stability parameter formed from the boundary-layer depth$z_{i}$and the Obukhov length $L$) to investigate how AM is affected by buoyancy. Results demonstrate that as unstable stratification increases, the inclination angle of surface layer structures (as determined from the two-point correlation of streamwise velocity) increases from$\unicode[STIX]{x1D6FE}\approx 15^{\circ }$for weakly convective conditions to nearly vertical for highly convective conditions. As$-z_{i}/L$increases, LSMs in the streamwise velocity field transition from long, linear updrafts (or horizontal convective rolls) to open cellular patterns, analogous to turbulent Rayleigh–Bénard convection. These changes in the instantaneous velocity field are accompanied by a shift in the outer peak in the streamwise and vertical velocity spectra to smaller dimensionless wavelengths until the energy is concentrated at a single peak. The decoupling procedure proposed by Mathiset al.(J. Fluid Mech., vol. 628, 2009a, pp. 311–337) is used to investigate the extent to which amplitude modulation of small-scale turbulence occurs due to large-scale streamwise and vertical velocity fluctuations. As the spatial attributes of flow structures change from streamwise to vertically dominated, modulation by the large-scale streamwise velocity decreases monotonically. However, the modulating influence of the large-scale vertical velocity remains significant across the stability range considered. We report, finally, that amplitude modulation correlations are insensitive to the computational mesh resolution for flows forced by shear, buoyancy and Coriolis accelerations.

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Variational data assimilation with superparameterization

Nonlinear Processes in Geophysics Discussions ◽

10.5194/npgd-2-513-2015 ◽

2015 ◽

Vol 2 (2) ◽

pp. 513-536 ◽

Cited By ~ 1

Author(s):

I. Grooms ◽

Y. Lee

Keyword(s):

Data Assimilation ◽

Large Scale ◽

Climate Models ◽

Low Cost ◽

Ocean Model ◽

Variational Data Assimilation ◽

Scale Model ◽

Small Scale ◽

New Applications ◽

Lorenz 96

Abstract. Superparameterization (SP) is a multiscale computational approach wherein a large scale atmosphere or ocean model is coupled to an array of simulations of small scale dynamics on periodic domains embedded into the computational grid of the large scale model. SP has been successfully developed in global atmosphere and climate models, and is a promising approach for new applications. The authors develop a 3D-Var variational data assimilation framework for use with SP; the relatively low cost and simplicity of 3D-Var in comparison with ensemble approaches makes it a natural fit for relatively expensive multiscale SP models. To demonstrate the assimilation framework in a simple model, the authors develop a new system of ordinary differential equations similar to the two-scale Lorenz-'96 model. The system has one set of variables denoted {Yi}, with large and small scale parts, and the SP approximation to the system is straightforward. With the new assimilation framework the SP model approximates the large scale dynamics of the true system accurately.

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Self-Supervised Pre-Training of Transformers for Satellite Image Time Series Classification

10.36227/techrxiv.13025039.v1 ◽

2020 ◽

Author(s):

Yuan Yuan ◽

Lei Lin

Keyword(s):

Time Series ◽

Deep Learning ◽

Large Scale ◽

Temporal Structure ◽

Satellite Image ◽

Fine Tuning ◽

Small Scale ◽

Model Parameters ◽

Learning Approaches ◽

Wide Range

Satellite image time series (SITS) classification is a major research topic in remote sensing and is relevant for a wide range of applications. Deep learning approaches have been commonly employed for SITS classification and have provided state-of-the-art performance. However, deep learning methods suffer from overfitting when labeled data is scarce. To address this problem, we propose a novel self-supervised pre-training scheme to initialize a Transformer-based network by utilizing large-scale unlabeled data. In detail, the model is asked to predict randomly contaminated observations given an entire time series of a pixel. The main idea of our proposal is to leverage the inherent temporal structure of satellite time series to learn general-purpose spectral-temporal representations related to land cover semantics. Once pre-training is completed, the pre-trained network can be further adapted to various SITS classification tasks by fine-tuning all the model parameters on small-scale task-related labeled data. In this way, the general knowledge and representations about SITS can be transferred to a label-scarce task, thereby improving the generalization performance of the model as well as reducing the risk of overfitting. Comprehensive experiments have been carried out on three benchmark datasets over large study areas. Experimental results demonstrate the effectiveness of the proposed method, leading to a classification accuracy increment up to 1.91% to 6.69%. <div><b>This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.</b></div>

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Physical Transport Processes that Affect the Distribution of Oil in the Gulf of Mexico: Observations and Modeling

Oceanography ◽

10.5670/oceanog.2021.117 ◽

2021 ◽

Vol 34 (1) ◽

pp. 58-75

Author(s):

Michel Boufadel ◽

◽

Annalisa Bracco ◽

Eric Chassignet ◽

Shuyi Chen ◽

...

Keyword(s):

Gulf Of Mexico ◽

Physical Environment ◽

Large Scale ◽

Transport Processes ◽

Small Scale ◽

Surface Mixed Layer ◽

Physical Processes ◽

Mixing Processes ◽

Near Surface ◽

Wide Range

Physical transport processes such as the circulation and mixing of waters largely determine the spatial distribution of materials in the ocean. They also establish the physical environment within which biogeochemical and other processes transform materials, including naturally occurring nutrients and human-made contaminants that may sustain or harm the region’s living resources. Thus, understanding and modeling the transport and distribution of materials provides a crucial substrate for determining the effects of biological, geological, and chemical processes. The wide range of scales in which these physical processes operate includes microscale droplets and bubbles; small-scale turbulence in buoyant plumes and the near-surface “mixed” layer; submesoscale fronts, convergent and divergent flows, and small eddies; larger mesoscale quasi-geostrophic eddies; and the overall large-scale circulation of the Gulf of Mexico and its interaction with the Atlantic Ocean and the Caribbean Sea; along with air-sea interaction on longer timescales. The circulation and mixing processes that operate near the Gulf of Mexico coasts, where most human activities occur, are strongly affected by wind- and river-induced currents and are further modified by the area’s complex topography. Gulf of Mexico physical processes are also characterized by strong linkages between coastal/shelf and deeper offshore waters that determine connectivity to the basin’s interior. This physical connectivity influences the transport of materials among different coastal areas within the Gulf of Mexico and can extend to adjacent basins. Major advances enabled by the Gulf of Mexico Research Initiative in the observation, understanding, and modeling of all of these aspects of the Gulf’s physical environment are summarized in this article, and key priorities for future work are also identified.

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