scholarly journals Assimilation of SLA along track observations in the Mediterranean with an oceanographic model forced by atmospheric pressure

2012 ◽  
Vol 9 (2) ◽  
pp. 1577-1598 ◽  
Author(s):  
S. Dobricic ◽  
C. Dufau ◽  
P. Oddo ◽  
N. Pinardi ◽  
I. Pujol ◽  
...  

Abstract. A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently new higher frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments we show that in order to obtain the most accurate analyses the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure the high frequency filtering of SLA observations, however, improves the quality of the analyses. It is further shown that MFS analyses, produced by an assimilation system given by the numerical model and the high frequency SLA observations, have a correct power spectrum at high wave numbers and they filter efficiently the SLA assimilated observations which, on the other hand, are contaminated by high wavenumber noise.

Ocean Science ◽  
2012 ◽  
Vol 8 (5) ◽  
pp. 787-795 ◽  
Author(s):  
S. Dobricic ◽  
C. Dufau ◽  
P. Oddo ◽  
N. Pinardi ◽  
I. Pujol ◽  
...  

Abstract. A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently, new higher-frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments, we show that, in order to obtain the most accurate analyses, the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure, the high-frequency filtering of SLA observations, however, improves the quality of the SLA analyses. It is further shown by comparing the power density spectra of the model fields and observations that the model is able to extract the correct information from noisy observations even without their filtering during the pre-processing.


2006 ◽  
Vol 3 (5) ◽  
pp. 1609-1621 ◽  
Author(s):  
A. Russo ◽  
A. Coluccelli

Abstract. The MFS (Mediterranean Forecasting System) project and its follower MFSTEP (Mediterranean ocean Forecasting System–Towards Environmental Prediction) are being covering the Mediterranean Sea with operational Ocean General Circulation Models (OGCMs) at horizontal resolution varying from about 12 km till 2005 to 6.5 km in 2006 (reaching 3 km with some regional models and 1.5 km for few shelf models). Heat, water and momentum fluxes through the air-sea interface are derived from the European Center for Medium-range Weather Forecast (ECMWF) output at 0.5° horizontal resolution. Such horizontal resolutions could be not able to provide the needed forecast accuracy in some cases (localized emergencies at sea, e.g. oil spill; need for high resolution current forecasts, e.g. offshore works). A solution to this problem is represented by relocatable models able to be rapidly deployed and to produce forecasts starting from the MFS products. The Harvard Ocean Prediction System (HOPS) has been chosen as base of the relocatable model and it has been interfaced with the MFSTEP OGCM and one regional model. The relocatable model has demonstrated capability to produce forecasts within 2-3 days in many cases, and more rapid implementation may be obtained.


2014 ◽  
Vol 142 (10) ◽  
pp. 3756-3780 ◽  
Author(s):  
Yujie Pan ◽  
Kefeng Zhu ◽  
Ming Xue ◽  
Xuguang Wang ◽  
Ming Hu ◽  
...  

Abstract A coupled ensemble square root filter–three-dimensional ensemble-variational hybrid (EnSRF–En3DVar) data assimilation (DA) system is developed for the operational Rapid Refresh (RAP) forecasting system. The En3DVar hybrid system employs the extended control variable method, and is built on the NCEP operational gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVar) framework. It is coupled with an EnSRF system for RAP, which provides ensemble perturbations. Recursive filters (RF) are used to localize ensemble covariance in both horizontal and vertical within the En3DVar. The coupled En3DVar hybrid system is evaluated with 3-h cycles over a 9-day period with active convection. All conventional observations used by operational RAP are included. The En3DVar hybrid system is run at ⅓ of the operational RAP horizontal resolution or about 40-km grid spacing, and its performance is compared to parallel GSI 3DVar and EnSRF runs using the same datasets and resolution. Short-term forecasts initialized from the 3-hourly analyses are verified against sounding and surface observations. When using equally weighted static and ensemble background error covariances and 40 ensemble members, the En3DVar hybrid system outperforms the corresponding GSI 3DVar and EnSRF. When the recursive filter coefficients are tuned to achieve a similar height-dependent localization as in the EnSRF, the En3DVar results using pure ensemble covariance are close to EnSRF. Two-way coupling between EnSRF and En3DVar did not produce noticeable improvement over one-way coupling. Downscaled precipitation forecast skill on the 13-km RAP grid from the En3DVar hybrid is better than those from GSI 3DVar analyses.


2019 ◽  
Vol 36 (8) ◽  
pp. 1547-1561
Author(s):  
Elizabeth M. Douglass ◽  
Andrea C. Mask

AbstractAs numerical modeling advances, quantitative metrics are necessary to determine whether the model output accurately represents the observed ocean. Here, a metric is developed based on whether a model places oceanic fronts in the proper location. Fronts are observed and assessed directly from along-track satellite altimetry. Numerical model output is then interpolated to the locations of the along-track data, and fronts are detected in the model output. Scores are determined from the percentage of observed fronts correctly simulated in the model and from the percentage of modeled fronts confirmed by observations. These scores depend on certain parameters such as the minimum size of a front, which will be shown to be geographically dependent. An analysis of two models, the Hybrid Coordinate Ocean Model (HYCOM) and the Navy Coastal Ocean Model (NCOM), is presented as an example of how this metric might be applied and interpreted. In this example, scores are found to be relatively stable in time, but strongly dependent on the mesoscale variability in the region of interest. In all cases, the metric indicates that there are more observed fronts not found in the models than there are modeled fronts missing from observations. In addition to the score itself, the analysis demonstrates that modeled fronts have smaller amplitude and are less steep than observed fronts.


2007 ◽  
Vol 7 (3) ◽  
pp. 8309-8332 ◽  
Author(s):  
T. Niu ◽  
S. L. Gong ◽  
G. F. Zhu ◽  
H. L. Liu ◽  
X. Q. Hu ◽  
...  

Abstract. A data assimilation system (DAS) was developed for the Chinese Unified Atmospheric Chemistry Environment – Dust (CUACE/Dust) forecast system and applied in the operational forecasts of sand and dust storm (SDS) in spring 2006. The system is based on a three dimensional variational method (3D-Var) and uses extensively the measurements of surface visibility and dust loading retrieval from the Chinese geostationary satellite FY-2C. The results show that a major improvement to the capability of CUACE/Dust in forecasting the short-term variability in the spatial distribution and intensity of dust concentrations has been achieved, especially in those areas far from the source regions. The seasonal mean Threat Score (TS) over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the data assimilation system, a 41% enhancement. The assimilation results usually agree with the dust loading retrieved from FY-2C and visibility distribution from surface meteorological stations, which indicates that the 3D-Var method is very powerful for the unification of observation and numerical modeling results.


2013 ◽  
Vol 31 (2) ◽  
pp. 271 ◽  
Author(s):  
Leonardo Nascimento Lima ◽  
Clemente Augusto Souza Tanajura

ABSTRACT. In this study, assimilation of Jason-1 and Jason-2 along-track sea level anomaly (SLA) data was conducted in a region of the tropical and South Atlantic (7◦N-36◦S, 20◦W up to the Brazilian coast) using an optimal interpolation method and the HYCOM (Hybrid Coordinate Ocean Model). Four 24 h-forecast experiments were performed daily from January 1 until March 31, 2011 considering different SLA assimilation data windows (1 day and 2 days) and different coefficients in the parameterization of the SLA covariance matrix model. The model horizontal resolution was 1/12◦ and the number of vertical layers was 21. The SLA analyses added to the mean sea surface height were projected to the subsurface with the Cooper & Haines (1996) scheme. The results showed that the experiment with 2-day window of along-track data and with specific parameterizations of the model SLA covariance error for sub-regions of the METAREA V was the most accurate. It completely reconstructed the model sea surface height and important improvements in the circulation were produced. For instance, there was a substantial improvement in the representation of the Brazil Current and North Brazil Undercurrent. However, since no assimilation of vertical profiles of temperature and salinity and of sea surface temperature was performed, the methodology employed here should be considered only as a step towards a high quality analysis for operational forecasting systems.   Keywords: data assimilation, optimal interpolation, Cooper & Haines scheme, altimetry data.   RESUMO. Neste estudo, a assimilação de dados de anomalia da altura da superfície do mar (AASM) ao longo da trilha dos satélites Jason-1 e Jason-2 foi conduzida em uma região do Atlântico tropical e Sul (7◦N-36◦S, 20◦W até a costa do Brasil) com o método de interpolação ótima e o modelo oceânico HYCOM (Hybrid Coordinate Ocean Model). Foram realizados quatro experimentos de previsão de 24 h entre 1 de janeiro e 31 de março de 2011, considerando diferentes janelas de assimilação de AASM (1 dia e 2 dias) e diferentes coeficientes na parametrização da matriz de covariância dos erros de AASM do modelo. A resolução horizontal empregada no HYCOM foi 1/12◦ para 21 camadas verticais. As correções de altura da superfície do mar devido à assimilação de AASM foram projetadas abaixo da camada de mistura através da técnica de Cooper & Haines (1996). Os resultados mostraram que o experimento com assimilação de dados ao longo da trilha dos satélites com a janela de 2 dias e com parametrizações da matriz de covariância específicas para sub-regiões da METAREA V foi o mais acurado. Ele reconstruiu completamente a altura da superfície do mar e também proporcionou melhorias na circulação oceânica reproduzida pelo modelo. Por exemplo, houve substancial melhoria da representação nos campos da Corrente do Brasil e Subcorrente Norte do Brasil. Entretanto, tendo em vista que não foi realizada a assimilação de perfis verticais de temperatura e de salinidade e da temperatura da superfície do mar, a metodologia apresentada deve ser considerada apenas como um passo na conquista de uma análise oceânica e de um sistema previsor de qualidade para fins operacionais.   Palavras-chave: assimilação de dados, interpolação ótima, técnica de Cooper & Haines, dados de altimetria.


Ocean Science ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 207-216 ◽  
Author(s):  
A. S. Lanotte ◽  
R. Corrado ◽  
L. Palatella ◽  
C. Pizzigalli ◽  
I. Schipa ◽  
...  

Abstract. The effect of vertical shear on the horizontal dispersion properties of passive tracer particles on the continental shelf of the South Mediterranean is investigated by means of observation and model data. In situ current measurements reveal that vertical gradients of horizontal velocities in the upper mixing layer decorrelate quite fast ( ∼  1 day), whereas an eddy-permitting ocean model, such as the Mediterranean Forecasting System, tends to overestimate such decorrelation time because of finite resolution effects. Horizontal dispersion, simulated by the Mediterranean sea Forecasting System, is mostly affected by: (1) unresolved scale motions, and mesoscale motions that are largely smoothed out at scales close to the grid spacing; (2) poorly resolved time variability in the profiles of the horizontal velocities in the upper layer. For the case study we have analysed, we show that a suitable use of deterministic kinematic parametrizations is helpful to implement realistic statistical features of tracer dispersion in two and three dimensions. The approach here suggested provides a functional tool to control the horizontal spreading of small organisms or substance concentrations, and is thus relevant for marine biology, pollutant dispersion as well as oil spill applications.


2021 ◽  
Author(s):  
Emanuela Clementi ◽  
Anna Chiara Goglio ◽  
Ali Aydogdu ◽  
Jenny Pistoia ◽  
Romain Escudier ◽  
...  

<p>The Mediterranean Analysis and Forecasting System operationally produces analyses and 10 days forecasts of the main physical parameters for the entire Mediterranean Sea and its Atlantic Ocean adjacent areas in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS).</p><p>The system is composed by the hydrodynamic model NEMO (Nucleus for European Modelling of the Ocean) 2-way coupled with the third-generation wave model WW3 (WaveWatchIII) and forced by ECMWF (European Centre for Medium-range Weather Forecasts) atmospheric fields. The forecast initial conditions are produced by the OceanVar, a 3D variational data assimilation system which daily assimilates Sea Level Anomaly, vertical profiles of Temperature and Salinity from ARGO and XBT (upon availbility) observations. Moreover a heat flux correction using satellite SST is imposed.</p><p>The system has been recently upgraded by including tidal waves, so that the tidal potential is calculated across the domain for the Mediterranean Sea 8 major constituents: M2, S2, N2, K2, K1, O1, P1, Q1. In addition, tidal forcing is applied along the lateral boundaries in the Atlantic Ocean by means of tidal elevation estimated using the FES2014 global tidal model and tidal currents evaluated using TUGO (Toulouse Unstructured Grid Ocean) model. Moreover the data assimilation scheme now accounts for the tidal signal in the altimeter tracks.</p><p>The system has been validated comparing model results with satellite and in situ observations. A specific harmonic analysis has been performed comparing model sea level amplitudes and phases with respect to: tide gauges, TPXO global tidal model and literature, showing an overall good skill of all the considered tidal constituents. Moreover the ability of the system to predict sea level has been evaluated comparing the model solutions with respect to tide gauges in areas where recent extreme events occurred such as Venice Lagoon “Acqua Alta” in November 2019, Western Mediterranean Sea during Gloria storm in January 2020, Ionian Sea during Medicane Ianos in September 2020.</p>


2008 ◽  
Vol 8 (13) ◽  
pp. 3473-3482 ◽  
Author(s):  
T. Niu ◽  
S. L. Gong ◽  
G. F. Zhu ◽  
H. L. Liu ◽  
X. Q. Hu ◽  
...  

Abstract. A data assimilation system (DAS) was developed for the Chinese Unified Atmospheric Chemistry Environment – Dust (CUACE/Dust) forecast system and applied in the operational forecasts of sand and dust storm (SDS) in spring 2006. The system is based on a three dimensional variational method (3D-Var) and uses extensively the measurements of surface visibility (phenomena) and dust loading retrieval from the Chinese geostationary satellite FY-2C. By a number of case studies, the DAS was found to provide corrections to both under- and over-estimates of SDS, presenting a major improvement to the forecasting capability of CUACE/Dust in the short-term variability in the spatial distribution and intensity of dust concentrations in both source regions and downwind areas. The seasonal mean Threat Score (TS) over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the data assimilation system, a 41% enhancement. The forecast results with DAS usually agree with the dust loading retrieved from FY-2C and visibility distribution from surface meteorological stations, which indicates that the 3D-Var method is very powerful by the unification of observation and numerical model to improve the performance of forecast model.


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