Results 1-20 of 133.
((author:Barth, author:Alexander)) AND NOT ((filter:prvw))

Bookmark and Share    
Full Text
See detailExperiences with using netCDF 4
Troupin, Charles ULiege; Watelet, Sylvain ULiege; Barth, Alexander ULiege et al

Conference (2017, October 05)

Detailed reference viewed: 13 (2 ULiège)
Full Text
See detailNotebooks for documenting work-flows
Troupin, Charles ULiege; Barth, Alexander ULiege; Muñoz, Cristian et al

Conference (2017, October 02)

Detailed reference viewed: 13 (1 ULiège)
Full Text
See detailSoftware citation and process traceability
Troupin, Charles ULiege; Muñoz, Cristian; Rújula, Miquel Angel et al

Conference (2017, October)

Detailed reference viewed: 23 (4 ULiège)
Full Text
See detailCharacteristics of surface chlorophyll-a concentrations in the South China Sea
Huynh, Thi Hong Ngu ULiege; Alvera Azcarate, Aida ULiege; Barth, Alexander ULiege et al

Poster (2017, April 25)

In this study, the spatial and temporal variability of surface chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is investigated, using the cloud-free MODISA Chl-a data set (2003-2016 ... [more ▼]

In this study, the spatial and temporal variability of surface chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is investigated, using the cloud-free MODISA Chl-a data set (2003-2016) reconstructed by the Data Interpolating Empirical Orthogonal Functions technique. EOF analysis on the reconstructed data set presents the characteristics of the surface Chl-a: (1) the first mode presents the high Chl-a concentrations in the coastal regions, except those of the Palawan and Philippines, generally with peaks in summer (June-July) and winter (November-December). (2) the second mode shows the seasonal variability of Chl-a in the whole basin, increasing in winter and decreasing in summer. (3) the third mode highlights the out-of-phase variability of the southern SCS Chl-a between the west and east coasts in winter and summer. The analysis also indicates that the variability of surface Chl-a is influenced by ENSO with a time lag of 5-9 months. [less ▲]

Detailed reference viewed: 31 (3 ULiège)
See detailThree-dimensional modelling of the Southern Bight of the North Sea: first results and perspectives
Ivanov, Evgeny ULiege; Capet, Arthur ULiege; Barth, Alexander ULiege et al

Poster (2017, March 03)

The impact of offshore wind farm installation and dredging activities on the spatial distribution and dynamics of sediment grain size, biogeochemistry and biodiversity will be estimated in the Southern ... [more ▼]

The impact of offshore wind farm installation and dredging activities on the spatial distribution and dynamics of sediment grain size, biogeochemistry and biodiversity will be estimated in the Southern Bight of the North Sea (SBNS) with a focus on the Belgian Coastal Zone (BCZ) in the frame of the FaCE-It research project (Functional biodiversity in a Changing sedimentary Environment: Implications for biogeochemistry and food webs in a managerial setting). The three-dimensional hydrodynamical model ROMS-COAWST was implemented for simulation of the complex hydrodynamics of SBNS and sediment transport. The first level of nesting with the resolution of 1 km was used in the area of Belgian Economical Zone. In order to reach a fine resolution of 250 m in the BCZ, the second level of nesting will be used. Six-hourly ECMWF ERA-interim meteorological data was used to force the model at the sea-air boundary and the coarse resolution model results available from Copernicus Marine Environment Monitoring Service were used to force the model at the open boundaries. Tides and rivers were also considered. Next types of long-run simulations have been conducted: a 10-years climatological simulation and an interannual simulation over 2004-2013 in order to investigate the interannual dynamics. The model accuracy was evaluated through validation of its outputs against observed salinity, temperature and currents data (remote sensing and in-situ). Results validation of currents and temperature and salinity horizontal fields and vertical profiles against available satellite fields and in-situ data, i.e. from the project field campaign, is conducted and discussed. Application of the nested grid and its benefits for results accuracy is also presented. [less ▲]

Detailed reference viewed: 21 (1 ULiège)
Full Text
See detailBlending of Radial HF Radar Surface Current and Model Using ETKF Scheme For The Sunda Strait
Subekti Mujiasih, ULiege; Riyadi, Mochammad; Wandono, Dr et al

Conference (2017)

Preliminary study of data blending of surface current for Sunda Strait-Indonesia has been done using the analysis scheme of the Ensemble Transform Kalman Filter (ETKF). The method is utilized to combine ... [more ▼]

Preliminary study of data blending of surface current for Sunda Strait-Indonesia has been done using the analysis scheme of the Ensemble Transform Kalman Filter (ETKF). The method is utilized to combine radial velocity from HF Radar and u and v component of velocity from Global Copernicus - Marine environment monitoring service (CMEMS) model. The initial ensemble is based on the time variability of the CMEMS model result. Data tested are from 2 CODAR Seasonde radar sites in Sunda Strait and 2 dates such as 09 September 2013 and 08 February 2016 at 12.00 UTC. The radial HF Radar data has a hourly temporal resolution, 20-60 km of spatial range, 3 km of range resolution, 5 degree of angular resolution and spatial resolution and 11.5-14 MHz of frequency range. The u and v component of the model velocity represents a daily mean with 1/12 degree spatial resolution. The radial data from one HF radar site is analyzed and the result compared to the equivalent radial velocity from CMEMS for the second HF radar site. Error checking is calculated by root mean squared error (RMSE). Calculation of ensemble analysis and ensemble mean is using Sangoma software package. The tested R which represents observation error covariance matrix, is a diagonal matrix with diagonal elements equal 0.05, 0.5 or 1.0 m 2 /s 2 . The initial ensemble members comes from a model simulation spanning a month (September 2013 or February 2016), one year (2013) or 4 years (2013-2016). The spatial distribution of the radial current are analyzed and the RMSE values obtained from independent HF radar station are optimized. It was verified that the analysis reproduces well the structure included in the analyzed HF radar data. More importantly, the analysis was also improved relative to the second independent HF radar site. RMSE of the improved analysis is better than first HF Radar site Analysis. The best result of the blending exercise was obtained for observation error variance equal to 0.05 m 2 /s 2 . This study is still preliminary step, but it gives promising result for bigger size of data, combining other model and further development [less ▲]

Detailed reference viewed: 36 (3 ULiège)
See detailDeveloping a hydrodynamical model of the Southern Bight of the North Sea for impact studies
Ivanov, Evgeny ULiege; Capet, Arthur ULiege; Barth, Alexander ULiege et al

Poster (2016, November 08)

In the frame of the Brain FaCE-It project (Functional biodiversity in a Changing sedimentary Environment: Implications for biogeochemistry and food webs in a managerial setting), the impact of fining and ... [more ▼]

In the frame of the Brain FaCE-It project (Functional biodiversity in a Changing sedimentary Environment: Implications for biogeochemistry and food webs in a managerial setting), the impact of fining and hardening resulting from dredging and wind farms installation on the sediment grain size distribution has to be assessed at the scale of the Southern Bight of the North Sea (SBNS) with a particular focus on the Belgian Coastal Zone (BCZ). With this aim, the ROMS-COAWST tri-dimensional (3D) hydrodynamic model is implemented to simulate the hydrodynamics in the SBNS. At its open boundaries with the Atlantic Ocean and the North Sea, the model is forced with the results of a coarse resolution model available from Mercator. A high resolution of 250 m is used in the area of the BCZ where the accuracy of model predictions needs to be refined. Model currents, tides, temperature and salinity fields will be described and first validation exercises with satellite and local data will be presented and discussed in regards with the objectives of FaCE-It. In a next step, the model will be coupled with a sediment transport in order to describe the dynamics of suspended particulate materials (SPM) and the distribution of the seafloor sediment grain size. When finalized the hydrodynamic model will be coupled with a diagenetic model and will provide environmental conditions for scaling up local foodweb studies that are performed in the frame of FaCE-iT. The final aim is to assess the impact of substrate modifications due to aggregate extraction and wind farms on the biogeochemistry, benthic functionality and food webs at local (around the wind farm) and regional scales (SBNS). [less ▲]

Detailed reference viewed: 12 (1 ULiège)
Full Text
See detailOceanBrowser: on-line visualization of gridded ocean data and in situ observations
Barth, Alexander ULiege; Watelet, Sylvain ULiege; Troupin, Charles et al

Conference (2016, October)

Detailed reference viewed: 17 (4 ULiège)
See detailDINEOF analyses of Sea Surface Temperature data in the Black Sea
Alvera Azcarate, Aida ULiege; Vandenbulcke, Luc ULiege; Barth, Alexander ULiege et al

Scientific conference (2016, September 29)

Detailed reference viewed: 22 (5 ULiège)
Full Text
See detailData-Interpolating Variational Analysis (DIVA) software: recent development and application
Watelet, Sylvain ULiege; Back, Örjan; Barth, Alexander ULiege et al

Poster (2016, April 20)

Detailed reference viewed: 25 (4 ULiège)
Full Text
See detailCorrecting Biases in a lower resolution global circulation model with data assimilation
Canter, Martin ULiege; Barth, Alexander ULiege

Poster (2016)

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run ... [more ▼]

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we establish a forcing term which is directly added inside the model’s equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have currents perpendicular to the coast. The randomly generated stochastic forcing are then directly injected into the NEMO LIM model’s equations in order to force the model at each timestep, and not only during the assimilation step. Results from a twin experiment will be presented. This method is being applied to a real case, with observations on the sea surface height available from the mean dynamic topography of CNES (Centre national d’études spatiales). The model, the bias correction, and more extensive forcings, in particular with a three dimensional structure and a time-varying component, will also be presented. [less ▲]

Detailed reference viewed: 16 (3 ULiège)
Full Text
See detailDeriving ocean climatologies with multivariate coupling
Barth, Alexander ULiege; Alvera Azcarate, Aida ULiege; Beckers, Jean-Marie ULiege

Conference (2016)

In situ measurements of ocean properties are generally sparsely distributed and thus undersample the ocean variability. Deriving ocean climatologies is a challenging task especially for biological and ... [more ▼]

In situ measurements of ocean properties are generally sparsely distributed and thus undersample the ocean variability. Deriving ocean climatologies is a challenging task especially for biological and chemical parameters where the number of data is, by an order of magnitude, smaller than for physical parameters. However, physical and biogeochemical parameters are related through the ocean dynamics. In particular fronts visible in physical parameters are often related to gradients in biogeochemical parameters. Ocean climatologies are generally derived for different variables independently. For biogeochemical parameters, only the very large-scale variability can be derived for poorly sampled areas. Here we present a method to derive multivariate analysis taking the relationship between physical and biogeochemical variables into account. The benefit of this procedure is showed by using model data for salinity, nitrate and phosphate of the Mediterranean Sea. The model fields are sampled at the locations of true observations (extracted from the World Ocean Database 2013) and the analysed fields are compared to the original model fields. The multivariate analysis result in a reduction of the RMS error and to a better representation of the gradients [less ▲]

Detailed reference viewed: 16 (2 ULiège)
Full Text
See detailComparison of different assimilation schemes in an operational assimilation system with Ensemble Kalman Filter
Yan, Yajing; Barth, Alexander ULiege; Beckers, Jean-Marie ULiege et al

Poster (2016)

In this paper, four assimilation schemes, including an intermittent assimilation scheme (INT) and three incremental assimilation schemes (IAU 0, IAU 50 and IAU 100), are compared in the same assimilation ... [more ▼]

In this paper, four assimilation schemes, including an intermittent assimilation scheme (INT) and three incremental assimilation schemes (IAU 0, IAU 50 and IAU 100), are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The three IAU schemes differ from each other in the position of the increment update window that has the same size as the assimilation window. 0, 50 and 100 correspond to the degree of superposition of the increment update window on the current assimilation window. Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/observation difference, as well as by rank histogram before the assimilation experiments The relevance of each assimilation scheme is evaluated through analyses on thermohaline variables and the current velocities. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semi-independent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system. [less ▲]

Detailed reference viewed: 14 (1 ULiège)
Full Text
See detailAnalysis of ocean in situ observations and web-based visualization
Barth, Alexander ULiege; Watelet, Sylvain ULiege; Troupin, Charles ULiege et al

Conference (2016)

The sparsity of observations poses a challenge common to various ocean science disciplines. Even for physical parameters where the spatial and temporal coverage is higher, current observational networks ... [more ▼]

The sparsity of observations poses a challenge common to various ocean science disciplines. Even for physical parameters where the spatial and temporal coverage is higher, current observational networks undersample a broad spectrum of scales. The situation is generally more severe for chemical and biological parameters because related sensors are less widely deployed. The analysis tool DIVA (Data-Interpolating Variational Analysis) is designed to generate gridded fields from in situ observations. DIVA has been applied to various physical (temperature and salinity), chemical (concentration of nitrate, nitrite and phosphate) and biological parameters (abundance of a species) in the context of different European projects (SeaDataNet, EMODnet Chemistry and EMODnet Biology). We show the technologies used to visualize the gridded fields based on the Web Map Services standard. Visualization of analyses from in situ observations provides a unique set of challenges since the accuracy of the analysed field is not spatially uniform as it strongly depends on the observations location. In addition, an adequate handling of depth and time dimensions is essential. Beside visualizing the gridded fields, access is also given to the underlying observations. It is thus also possible to view more detailed information about the variability of the observations. The in situ observation visualization service allows one to display vertical profiles and time series and it is built upon OGC standards (the Web Feature Service and Web Processing Services) and following recommendation from the INSPIRE directive. [less ▲]

Detailed reference viewed: 19 (0 ULiège)
Full Text
See detailOcean Modeling: Bias correction through stochastic forcing.
Canter, Martin ULiege; Barth, Alexander ULiege

Conference (2015, April 14)

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run ... [more ▼]

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we es- tablish a forcing term which is directly added inside the model’s equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. Indeed, we were able to estimate and recover an artificial bias that had been added into the model. This bias had a spatial structure and was constant through time. The mean and behaviour of the corrected model corresponded to those the reference model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have currents perpendicular to the coast. The randomly generated stochastic forcing are then directly injected into the NEMO LIM model’s equa- tions in order to force the model at each timestep, and not only during the assimilation step. The first results on a twin experiment with the NEMO LIM model will be presented. [less ▲]

Detailed reference viewed: 15 (0 ULiège)