scholarly journals Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin

2014 ◽  
Vol 14 (22) ◽  
pp. 12031-12053 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette ◽  
M. Sicard ◽  
...  
Keyword(s):  
Air Quality ◽  
Mediterranean Basin ◽  
Interpolation Method ◽  
Period Length ◽  
Research Network ◽  
Optimal Interpolation ◽  
Aerodynamic Diameter ◽  
Western Mediterranean Basin ◽  
Ground Based Lidar ◽  
The Impact

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the Polair3D chemistry transport model (CTM) of the Polyphemus air quality modelling platform. We assimilate hourly averaged normalised range-corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) network and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM10–2.5) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh = 100 km, an assimilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period) are evaluated using the level 2.0 (cloud-screened and quality-assured) aerosol optical depth (AOD) data from AERONET, and mass concentration measurements (PM10 or PM2.5) from the French air quality (BDQA) network and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one without DA for PM2.5, PM10and AOD. Additionally, the comparison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period.

scholarly journals Assimilation of lidar signals: application to aerosol forecasting in the Mediterranean Basin

2014 ◽  
Vol 14 (9) ◽  
pp. 13059-13107 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette ◽  
M. Sicard ◽  
...  
Keyword(s):  
Transport Model ◽  
Interpolation Method ◽  
Period Length ◽  
Research Network ◽  
Optimal Interpolation ◽  
Aerodynamic Diameter ◽  
Background Error ◽  
The Mediterranean ◽  
Ground Based Lidar ◽  
The Impact

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on analysis and short-term forecasts of aerosols through a case study in the Mediterranean. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the chemistry transport model (CTM) {Polair3D of the air quality modelling platform POLYPHEMUS. We assimilate hourly-averaged normalised range corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS) and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM2.5–10) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh

scholarly journals Implementation of dust emission and chemistry into the Community Multiscale Air Quality modeling system and initial application to an Asian dust storm episode

2012 ◽  
Vol 12 (21) ◽  
pp. 10209-10237 ◽  
Author(s):  
K. Wang ◽  
Y. Zhang ◽  
A. Nenes ◽  
C. Fountoukis
Keyword(s):  
Air Quality ◽  
Dust Storm ◽  
Dust Emission ◽  
Forecast Model ◽  
Heterogeneous Reactions ◽  
Dust Particles ◽  
Aerodynamic Diameter ◽  
Dust Emissions ◽  
New Model ◽  
The Impact

Abstract. The US Environmental Protection Agency's (EPA) Community Multiscale Air Quality (CMAQ) modeling system version 4.7 is further developed to enhance its capability in simulating the photochemical cycles in the presence of dust particles. The new model treatments implemented in CMAQ v4.7 in this work include two online dust emission schemes (i.e., the Zender and Westphal schemes), nine dust-related heterogeneous reactions, an updated aerosol inorganic thermodynamic module ISORROPIA II with an explicit treatment of crustal species, and the interface between ISORROPIA II and the new dust treatments. The resulting improved CMAQ (referred to as CMAQ-Dust), offline-coupled with the Weather Research and Forecast model (WRF), is applied to the April 2001 dust storm episode over the trans-Pacific domain to examine the impact of new model treatments and understand associated uncertainties. WRF/CMAQ-Dust produces reasonable spatial distribution of dust emissions and captures the dust outbreak events, with the total dust emissions of ~111 and 223 Tg when using the Zender scheme with an erodible fraction of 0.5 and 1.0, respectively. The model system can reproduce well observed meteorological and chemical concentrations, with significant improvements for suspended particulate matter (PM), PM with aerodynamic diameter of 10 μm, and aerosol optical depth than the default CMAQ v4.7. The sensitivity studies show that the inclusion of crustal species reduces the concentration of PM with aerodynamic diameter of 2.5 μm (PM2.5) over polluted areas. The heterogeneous chemistry occurring on dust particles acts as a sink for some species (e.g., as a lower limit estimate, reducing O3 by up to 3.8 ppb (~9%) and SO2 by up to 0.3 ppb (~27%)) and as a source for some others (e.g., increasing fine-mode SO42− by up to 1.1 μg m−3 (~12%) and PM2.5 by up to 1.4 μg m−3 (~3%)) over the domain. The long-range transport of Asian pollutants can enhance the surface concentrations of gases by up to 3% and aerosol species by up to 20% in the Western US.

scholarly journals Near-Real-Time Application of SEVIRI Aerosol Optical Depth Algorithm

2020 ◽  
Vol 12 (9) ◽  
pp. 1481
Author(s):  
Olga Zawadzka-Manko ◽  
Iwona S. Stachlewska ◽  
Krzysztof M. Markowicz
Keyword(s):  
Real Time ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Interpolation Method ◽  
Research Network ◽  
Optimal Interpolation ◽  
Infrared Imager ◽  
Uncertainty Calculation ◽  
Extended Area ◽  
Southern Norway

Within the framework of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project, the near-real-time (NRT) operation has been documented for an in-house developed algorithm used for the retrieval of aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG). With the frequency of 15 min at a spatial resolution of roughly 5.5 × 5.5 km the AOD maps are provided for the country domains of Poland, the Czech Republic, Romania, and Southern Norway. A significant improvement has been reported in terms of modification of the existing prototype algorithm that it suits the operational NRT AOD retrieval for an extended area. This is mainly due to the application of the optimal interpolation method for the AOD estimation on reference days with the use of ground-based measurements of the Aerosol Robotic Network (AERONET) and the Aerosol Research Network (PolandAOD-NET) as well as simulations of the Copernicus Atmosphere Monitoring Service (CAMS). The main issues that have been addressed regarding surface reflectance estimation, cloud screening and uncertainty calculation. Exemplary maps of the NRT retrieval have been presented.

scholarly journals Implementation of dust emission and chemistry into the Community Multiscale Air Quality modeling system and initial application to an Asian dust storm episode

2012 ◽  
Vol 12 (5) ◽  
pp. 13457-13514 ◽  
Author(s):  
K. Wang ◽  
Y. Zhang ◽  
A. Nenes ◽  
C. Fountoukis
Keyword(s):  
Air Quality ◽  
Dust Storm ◽  
Dust Emission ◽  
Heterogeneous Reactions ◽  
Dust Particles ◽  
Aerodynamic Diameter ◽  
Dust Emissions ◽  
New Model ◽  
The Us ◽  
The Impact

Abstract. The US Environmental Protection Agency (EPA)'s Community Multiscale Air Quality (CMAQ) modeling system version 4.7 is further developed to enhance its capability in simulating the photochemical cycles in the presence of dust particles. The new model treatments implemented in CMAQ v4.7 in this work include two online-dust emission schemes, nine dust-related heterogeneous reactions, an updated aerosol inorganic thermodynamic module ISORROPIA II with an explicit treatment of crustal species, and the interface between ISORROPIA II and the new dust treatments. The resulting improved CMAQ (referred to as CMAQ-Dust), offline-coupled with the Weather Research and Forecast model (WRF), are applied to the April 2001 dust storm episode over the trans-Pacific domain to examine the impact of new model treatments and understand associated uncertainties. WRF/CMAQ-Dust produces reasonable spatial distribution of dust emissions and captures the dust outbreak events, with the total dust emissions of ∼111 and 223 Tg when the erodible fraction is assumed to be 0.5 and 1.0, respectively, for the April 2001 episode. The model system can reproduce well observed meteorological and chemical concentrations, with significant improvements for suspended particulate matter (PM), PM with aerodynamic diameter of 10 μm and aerosol optical depth than default CMAQ v4.7. The sensitivity studies show that the inclusion of crustal species reduces the concentration of PM with aerodynamic diameter of 2.5 μm (PM2.5) over polluted areas. The heterogeneous chemistry occurring on dust particles acts as a sink for some species (e.g., as a lower limit estimate, O3 by up to 3.8 ppb (∼9%) and SO2 by up to 0.3 ppb (∼27%)) and as a source for some others (e.g., fine-mode SO42− by up to 1.1 μg m−3 (∼12%) and PM2.5 by up to 1.4 μg m−3 (∼3%) over the domain. The long-range transport of Asian pollutants can enhance the background concentrations of gases by up to 3% and aerosol species by up to 20% in the US.

ASSIMILATION OF SEA SURFACE HEIGHT ANOMALIES INTO HYCOM WITH AN OPTIMAL INTERPOLATION SCHEME OVER THE ATLANTIC OCEAN METAREA V

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Clemente Augusto Souza Tanajura ◽  
Filipe Bitencourt Costa ◽  
Renato Ramos da Silva ◽  
Giovanni Abdelnur Ruggiero ◽  
Victor Bastos Daher
Keyword(s):  
Interpolation Method ◽  
Maximum Error ◽  
Sea Surface Height ◽  
Volume Transport ◽  
Ocean Model ◽  
Sea Surface ◽  
Height Anomaly ◽  
Optimal Interpolation ◽  
Sea Surface Height Anomaly ◽  
The Impact

Along-track sea surface height anomaly (SSHA) data from the Jason-1 and Jason-2 satellites were assimilated into the ocean model HYCOM from July 1, 2009 until December 31, 2009. A new and simple approach to overcome the bias between the model and observed SSHA was proposed. It focuses on the meso-scale differences between the data and the model along each satellite track. An optimal interpolation method and the Cooper and Haines (1996) scheme (C&H) were employed to produce a SSHA analysis field and to adjust model layer thicknesses over the Atlantic METAREA V. The corrected model state was used as initial condition for the next assimilation cycle. SSHA data with a 7-day window were assimilated in 3-day intervals centered in the SSHA data window and the C&H scheme was applied taking the SSHA analysis. A control run without assimilation was also performed. The results showed that the model SSHA was completely reorganized by the end of the experiment. The modifications of SSHA were compared to the American Navy HYCOM+NCODA system and AVISO data. Maximum error was reduced from 0.7 m to 0.2 m by assimilation. Comparisons were also made with the Argo temperature and salinity vertical profiles. Improvements in the currents and volume transport were also produced by assimilation. The impact in temperature was in general positive, but there was no substantial modification in salinity.

scholarly journals Modelling and assimilation of lidar signals over Greater Paris during the MEGAPOLI summer campaign

2014 ◽  
Vol 14 (7) ◽  
pp. 3511-3532 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Interpolation Method ◽  
Optimal Interpolation ◽  
Atmospheric Conditions ◽  
Model Aerosol ◽  
Paris Area ◽  
Lidar Observations

Abstract. In this study, we investigate the ability of the chemistry transport model (CTM) Polair3D of the air quality modelling platform Polyphemus to simulate lidar backscattered profiles from model aerosol concentration outputs. This investigation is an important preprocessing stage of data assimilation (validation of the observation operator). To do so, simulated lidar signals are compared to hourly lidar observations performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009, when a ground-based mobile lidar was deployed around Paris on-board a van. The comparison is performed for six different measurement days, 1, 4, 16, 21, 26 and 29 July 2009, corresponding to different levels of pollution and different atmospheric conditions. Overall, Polyphemus well reproduces the vertical distribution of lidar signals and their temporal variability, especially for 1, 16, 26 and 29 July 2009. Discrepancies on 4 and 21 July 2009 are due to high-altitude aerosol layers, which are not well modelled. In the second part of this study, two new algorithms for assimilating lidar observations based on the optimal interpolation method are presented. One algorithm analyses PM10 (particulate matter with diameter less than 10 μm) concentrations. Another analyses PM2.5 (particulate matter with diameter less than 2.5 μm) and PM2.5–10 (particulate matter with a diameter higher than 2.5 μm and lower than 10 μm) concentrations separately. The aerosol simulations without and with lidar data assimilation (DA) are evaluated using the Airparif (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and usefulness of assimilating lidar profiles for aerosol forecasts. The evaluation shows that lidar DA is more efficient at correcting PM10 than PM2.5, probably because PM2.5 is better modelled than PM10. Furthermore, the algorithm which analyses both PM2.5and PM2.5–10 provides the best scores for PM10. The averaged root-mean-square error (RMSE) of PM10 is 11.63 μg m−3 with DA (PM2.5 and PM2.5–10), compared to 13.69 μg m−3 with DA (PM10) and 17.74 μg m−3 without DA on 1 July 2009. The averaged RMSE of PM10 is 4.73 μg m−3 with DA (PM2.5 and PM2.5–10), against 6.08 μg m−3 with DA (PM10) and 6.67 μg m−3 without DA on 26 July 2009.

scholarly journals Mapping altimetry in the forthcoming SWOT era by back-and-forth nudging a one-layer quasi-geostrophic model

2020 ◽  
Author(s):  
Florian Le Guillou ◽  
Sammy Metref ◽  
Emmanuel Cosme ◽  
Julien Le Sommer ◽  
Clément Ubelmann ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
Model Simulation ◽  
Interpolation Method ◽  
Ocean Dynamics ◽  
Optimal Interpolation ◽  
Small Scale ◽  
Altimetric Data ◽  
The Impact ◽  
Mean Square Errors

AbstractDuring the past 25 years, altimetric observations of the ocean surface from space have been mapped to provide two dimensional sea surface height (SSH) fields which are crucial for scientific research and operational applications. The SSH fields can be reconstructed from conventional altimetric data using temporal and spatial interpolation. For instance, the standardDUACS products are created with an optimal interpolation method which is effective for both low temporal and low spatial resolution. However, the upcoming next-generation SWOT mission will provide very high spatial resolution but with low temporal resolution.The present paper makes the case that this temporal-spatial discrepancy induces the need for new advanced mapping techniques involving information on the ocean dynamics. An algorithm is introduced, dubbed the BFN-QG, that uses a simple data assimilation method, the back-and-forth nudging, to interpolate altimetric data while respecting quasigeostrophic dynamics. The BFN-QG is tested in an observing system simulation experiments and compared to the DUACS products. The experiments consider as reference the high-resolution numerical model simulation NATL60 from which are produced realistic data: four conventional altimetric nadirs and SWOT data. In a combined nadirs and SWOT scenario, the BFN-QG substantially improves the mapping by reducing the root-mean-square errors and increasing the spectral effective resolution by 40km. Also, the BFN-QG method can be adapted to combine large-scale corrections from nadirs data and small-scale corrections from SWOT data so as to reduce the impact of SWOT correlated noises and still provide accurate SSH maps.

Multiplatform analysis of a large anticyclonic eddy in the Algero-Provencal basin in 2019

2020 ◽  
Author(s):  
Aida Alvera-Azcárate ◽  
Alexander Barth ◽  
Charles Troupin ◽  
Jean-Marie Beckers ◽  
Hayley Evers-King ◽  
...  
Keyword(s):  
Mediterranean Basin ◽  
Cold Water ◽  
Remote Sensing Data ◽  
Western Mediterranean ◽  
Anticyclonic Eddy ◽  
Model Data ◽  
Multiple Sources ◽  
In Situ Data ◽  
Western Mediterranean Basin ◽  
The Impact

<p>A large anticyclonic eddy formed in April 2019 in the Algero-Provencal basin between Mallorca and Sardinia, and lasted until November 2019. While mesoscale activity is usually high in this part of the Mediterranean basin, the formation of such large (about 150 km in diameter) and long-lived eddies is not common. The eddy formed from a filament originated in the Algerian coast and was visible in multiple sources of satellite data, including sea surface temperature and ocean colour from Sentinel-3, until summer. Because of the warming of the surface layer, during summer months the eddy remained as a subsurface structure, evidenced by the sea level anomaly derived from altimetry data. A surface signal developed again in November, and the eddy finally dissipated in December 2019. According to CMEMS model data, in its strongest period the eddy reached about 300 m in depth, and during its sub-surface period the center was located at about 100 m depth. While at the surface the temperature signal was very clear, model data suggest the salinity anomaly was stronger than temperature, especially at depth. Such large and long-lived eddies have an impact in the basin currents, specifically in the transport of cold water from the northern to the southern part of the western Mediterranean basin, influencing the ecosystem there. The impact of the presence of this eddy, its long duration and the additional mesoscale and submesoscale activity that originated in its surroundings are investigated using a combination of remote sensing data, in situ data and model data.</p>

scholarly journals African dust outbreaks over the western Mediterranean basin: 11 year characterization of atmospheric circulation patterns and dust source areas

2014 ◽  
Vol 14 (5) ◽  
pp. 5495-5533 ◽  
Author(s):  
P. Salvador ◽  
S. Alonso ◽  
J. Pey ◽  
B. Artíñano ◽  
J. J. de Bustos ◽  
...  
Keyword(s):  
Atmospheric Circulation ◽  
Mediterranean Basin ◽  
Circulation Pattern ◽  
Western Mediterranean ◽  
Atmospheric Circulation Patterns ◽  
African Dust ◽  
Western Mediterranean Basin ◽  
Circulation Patterns ◽  
Impact Index ◽  
The Impact

Abstract. The occurrence of African dust outbreaks over the western Mediterranean basin were identified on an 11 year period (2001–2011). PM10 daily data from nine regional background air quality monitoring sites across the study area were compiled and the net dust load transported during each event was estimated. Then, the main atmospheric circulation patterns causing the transport of African air masses, were characterized by mean of an objective classification methodology of atmospheric variables fields. Next, the potential source areas of mineral dust, associated to each circulation pattern were identified by trajectory statistical methods. Finally, an impact index was calculated to estimate the incidence of the African dust outbreaks produced during each circulation pattern, on the levels of dust load in PM10 concentrations recorded in the different regions. Our results indicate that the values of the impact index and the areas affected by African dust, strongly depended on the atmospheric circulation pattern. Four circulation types were obtained by the classification procedure. Two of them (CT-1 and CT-4) occurred predominantly during the warm season, bringing dust from areas of Algeria, Tunisia, Western Sahara, western Libya and Mauritania. African dust outbreaks produced during the CT-4 were the most frequent across the period of study, generating the highest impact index over southern, central and eastern regions of the Iberian Peninsula as well as over the Balearic Islands. Conversely, the events caused by the CT-1 encompassed the highest impact index over the western areas of the Iberian Peninsula. The two remaining circulation types (CT-2 and CT-3) were more frequently observed during the spring season. The prevailing flows generated by these two atmospheric circulation patterns, carried mineral dust from areas of Algeria, Tunisia and Western Sahara, giving rise to higher values of the impact index from eastern to western areas of the western Mediterranean basin.

scholarly journals ASSIMILATION OF SEA SURFACE HEIGHT ANOMALIES INTO HYCOM WITH AN OPTIMAL INTERPOLATION SCHEME OVER THE ATLANTIC OCEAN METAREA V

2013 ◽  
Vol 31 (2) ◽  
pp. 257 ◽  
Author(s):  
Clemente Augusto Souza Tanajura ◽  
Filipe Bitencourt Costa ◽  
Renato Ramos da Silva ◽  
Giovanni Abdelnur Ruggiero ◽  
Victor Bastos Daher
Keyword(s):  
Interpolation Method ◽  
Maximum Error ◽  
Sea Surface Height ◽  
Volume Transport ◽  
Ocean Model ◽  
Sea Surface ◽  
Height Anomaly ◽  
Optimal Interpolation ◽  
Ocean Data Assimilation ◽  
The Impact

ABSTRACT. Along-track sea surface height anomaly (SSHA) data from the Jason-1 and Jason-2 satellites were assimilated into the ocean model HYCOM from July 1, 2009 until December 31, 2009. A new and simple approach to overcome the bias between the model and observed SSHA was proposed. It focuses on the meso-scale differences between the data and the model along each satellite track. An optimal interpolation method and the Cooper & Haines (1996) scheme (C&H) were employed to produce a SSHA analysis field and to adjust model layer thicknesses over the Atlantic METAREA V. The corrected model state was used as initial condition for the next assimilation cycle. SSHA data with a 7-day window were assimilated in 3-day intervals centered in the SSHA data window and the C&H scheme was applied taking the SSHA analysis. A control run without assimilation was also performed. The results showed that the model SSHA was completely reorganized by the end of the experiment. The modifications of SSHA were compared to the American Navy HYCOM+NCODA system and AVISO data. Maximum error was reduced from 0.7 m to 0.2 m by assimilation. Comparisons were also made with the Argo temperature and salinity vertical profiles. Improvements in the currents and volume transport were also produced by assimilation. The impact in temperature was in general positive, but there was no substantial modification in salinity.   Keywords: ocean data assimilation, Jason-1 and Jason-2 satellites, Argo. RESUMO. Dados de anomalia da altura da superfície do mar (AASM) dos satellites Jason-1 e Jason-2 foram assimilados no modelo oceânico HYCOM de 1 de julho de 2009 a 31 de dezembro de 2009. Um nova e simples abordagem foi proposta para superar o viés entre os dados observados de AASM e o campo do modelo. Ela enfoca as diferenças entre o modelo e as observações na mesoescala ao longo de cada trilha dos satélites. Um método de interpolação estatística e o esquema de Cooper & Haines (1996) (C&H) foram empregados para produzir um campo de análise de AASM e ajustes nas espessuras das camadas do modelo sobre a METAREA V do Atlântico. O estado corrigido do modelo foi usado como condição inicial para o próximo ciclo de assimilação. Dados de AASM em uma janela de 7 dias foram assimilados a cada 3 dias em data centrada na janela de dados e o método de C&H foi aplicado com a análise de AASM. Os resultados mostraram que a AASM do modelo foi completamente reorganizada no final do experimento. As modificações de AASM foram comparadas com análises globais do sistema Americano HYCOM+NCODA e com dados do AVISO. Erros máximos foram reduzidos de 0,7 m para 0,2 m com a assimilação. Comparações foram também feitas com perfis verticais de temperatura e salinidade do Argo. Melhorias nas correntes e no transporte de volume foram produzidas em relação à rodada de controle. O impacto na temperatura foi em geral positivo, mas não houve modificação substancial na salinidade.   Palavras-chave: assimilação de dados oceanográficos, satélites Jason-1 e Jason-2, Argo.

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