operational modeling over the southwestern atlantic · operational modeling over the southwestern...

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Operational Modeling over the Southwestern Atlantic Wlademir J. de Santis Junior , Edmo J. D. Campos, Fabio C. Cabral Instituto Oceanogr´ afico da Universidade de S˜ ao Paulo. Pra¸ ca do Oceanogr´afico,191,S˜aoPaulo,S.P, Brasil ([email protected]; [email protected]; [email protected]) Abstract An operational system for oceanic forecast with data assimilation was implemented using the Hy- brid Coordinate Ocean Model (HYCOM), fo- cused off the western South Atlantic basin. Two different grids were set with horizontal resolution of 1/4 and 1/24 degree. The coarser grid extends from 98 W to 114 E and 70 S to 60 N (Figure 1), and is responsible to create the large scale circulation over the Atlˆantic basing and pro- vide its information to the high resolution grid, which extends from 60 W to 20 W and 45 S to 10 N (Figure 2). Both grids are forced by the 0.5 degree GFS every 3 hours, but only on the finest grid the data assimilation was set. Specif- ically, anomalies on the sea surface heigh from AVISO were assimilated by an optimal interpo- lation method, which occurs with a six-day-delay to the operating day. Moreover, the assimilative process were modified to account the tide in the model integration. This poster intends to expose the operational procedure. Low Resolution Grid (ATIb0.25) The ATIb0.25 spin-up (named ATIa0.25) started with a 3-year-integration using climatological monthly averaged forcing from the Interna- tional Comprehensive Ocean-Atmosphere Data Set (COADS), followed by a 60-year-integration with NCEP/NCAR (National Centers for En- vironmental Prediction/National Center for At- mospheric Research) dated reanalysis, reaching the year of 2010, when the forcing was switched to the 0.5 degrees resolution model from Navy Operational Global Atmospheric Prediction Sys- tem (NOGAPS). Finally, on the operational mode (starting at 2013), the meteorological forc- ing was set to the Global Forecast System from NCEP. At the boundaries, the model was later- ally relaxed to the Levitus climatology over all integrations. Figure 1: Low resolution grid domain (ATLb0.25). High Resolution Grid (BRAm0.04) The second grid, with 1/24 degree of horizon- tal resolution and 22 hybrids vertical levels, was nested at the ATIb0.25 over the Southwestern Atlˆantic. Its spin-up started with a field ex- tracted from ATIb0.25 at 2010, when the forcing was switched to NOGAPS. At 2013, the opera- tional mode started, forced by GFS. The data assimilation of SSH anomalies from AVISO was performed since the spin-up integration started, and was done every 5 days, with a 6-day-delay to the operational day. Additionally, the tide was introduced by adding tidal flux over the bound- aries. In order to have the data assimilation and the tide signal on the operational mode, it was necessary to calculate the amplitudes and phase of the tide constituents at every grid point, which required a separate integration without data as- similation. With the tide constituents calcu- lated, the tide signal was predicted and added to the model surface elevation after data assimi- lation. This step was necessary since the assim- ilation method erases the tidal signal from the SSH model. Figure 2: High resolution grid domain (BRAm0.04). SSH Anomalies from AVISO and Assimilation Figure 3: Instantaneous anomalies of SSH AVISO. The Sea Surface High anomaly from AVISO is a combination of different altimetric satellites measurements. Since january 2012, they count with Jason-2, Envisat and Criosat-2, what pro- vides a robust sampling for real time applica- tions. The data assimilation was performed us- ing an optimal interpolation method that rear- range the vertical water mass distribution, con- serving its vertical integrated properties. How does it Works Every day, the meteorological forcing and the SSH anomalies from AVISO are downloaded and the integration starts with the previous restart file. Nevertheless, due to the 6-day-delay on the AVISO’s SSH gridded field, the BRAb0.04 integration starts seven days on the past. Af- ter one-day-integration, the SSH anomalies are assimilated, and the rest of integration (hind- cast/forecast) continue. Results and Conclusions Besides the operational system is up to date, its only reliable after a detailed validation of both grids, which has already started. However, its not the intention of this poster presents such val- idation. Anyway, on the context of the ATLAS- B Guariroba Buoy deployment, its convenient to inter-compare the results. The best fit compar- ison wasn’t from the same geographical point, but displaced of about 50 km southwest. De- spite the differences between the absolute value, there is a good accordance on its variability. Figure 4: Temperature comparison between BRAm0.04 and ATLAS-B Guariroba buoy. Figure 5: Salinity comparison between BRAm0.04 and ATLAS-B Guariroba buoy. Second Meeting of INCLINE Project 07–08/October/2013 LABMON – Laborat´ orio de Modelagem de Processos Oceˆ anicos. Instituto Oceanogr´afico – Universidade de S˜ao Paulo (www.labmon.usp.br)

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Page 1: Operational Modeling over the Southwestern Atlantic · Operational Modeling over the Southwestern Atlantic Wlademir J. de Santis Junior,EdmoJ.D.Campos,FabioC.Cabral ... ATLAS-B Guariroba

Operational Modeling over the SouthwesternAtlantic

Wlademir J. de Santis Junior, Edmo J. D. Campos, Fabio C. Cabral

Instituto Oceanografico da Universidade de Sao Paulo. Praca do Oceanografico, 191, Sao Paulo, S.P,

Brasil([email protected]; [email protected]; [email protected])

Abstract

An operational system for oceanic forecast withdata assimilation was implemented using the Hy-brid Coordinate Ocean Model (HYCOM), fo-cused o! the western South Atlantic basin. Twodi!erent grids were set with horizontal resolutionof 1/4 and 1/24 degree. The coarser grid extendsfrom 98!W to 114!E and 70!S to 60!N (Figure1), and is responsible to create the large scalecirculation over the Atlantic basing and pro-vide its information to the high resolution grid,which extends from 60!W to 20!W and 45!S to10!N (Figure 2). Both grids are forced by the0.5 degree GFS every 3 hours, but only on thefinest grid the data assimilation was set. Specif-ically, anomalies on the sea surface heigh fromAVISO were assimilated by an optimal interpo-lation method, which occurs with a six-day-delayto the operating day. Moreover, the assimilativeprocess were modified to account the tide in themodel integration. This poster intends to exposethe operational procedure.

Low Resolution Grid

(ATIb0.25)

The ATIb0.25 spin-up (named ATIa0.25) startedwith a 3-year-integration using climatologicalmonthly averaged forcing from the Interna-tional Comprehensive Ocean-Atmosphere DataSet (COADS), followed by a 60-year-integrationwith NCEP/NCAR (National Centers for En-vironmental Prediction/National Center for At-mospheric Research) dated reanalysis, reachingthe year of 2010, when the forcing was switchedto the 0.5 degrees resolution model from NavyOperational Global Atmospheric Prediction Sys-tem (NOGAPS). Finally, on the operationalmode (starting at 2013), the meteorological forc-ing was set to the Global Forecast System fromNCEP. At the boundaries, the model was later-ally relaxed to the Levitus climatology over allintegrations.

Figure 1: Low resolution grid domain (ATLb0.25).

High Resolution Grid

(BRAm0.04)

The second grid, with 1/24 degree of horizon-tal resolution and 22 hybrids vertical levels, wasnested at the ATIb0.25 over the SouthwesternAtlantic. Its spin-up started with a field ex-tracted from ATIb0.25 at 2010, when the forcingwas switched to NOGAPS. At 2013, the opera-tional mode started, forced by GFS. The dataassimilation of SSH anomalies from AVISO wasperformed since the spin-up integration started,and was done every 5 days, with a 6-day-delay tothe operational day. Additionally, the tide wasintroduced by adding tidal flux over the bound-aries. In order to have the data assimilation andthe tide signal on the operational mode, it wasnecessary to calculate the amplitudes and phaseof the tide constituents at every grid point, whichrequired a separate integration without data as-similation. With the tide constituents calcu-lated, the tide signal was predicted and addedto the model surface elevation after data assimi-lation. This step was necessary since the assim-ilation method erases the tidal signal from theSSH model.

Figure 2: High resolution grid domain (BRAm0.04).

SSH Anomalies from

AVISO and Assimilation

Figure 3: Instantaneous anomalies of SSH AVISO.

The Sea Surface High anomaly from AVISO isa combination of di!erent altimetric satellitesmeasurements. Since january 2012, they countwith Jason-2, Envisat and Criosat-2, what pro-

vides a robust sampling for real time applica-tions. The data assimilation was performed us-ing an optimal interpolation method that rear-range the vertical water mass distribution, con-serving its vertical integrated properties.

How does it Works

Every day, the meteorological forcing and theSSH anomalies from AVISO are downloaded andthe integration starts with the previous restartfile. Nevertheless, due to the 6-day-delay onthe AVISO’s SSH gridded field, the BRAb0.04integration starts seven days on the past. Af-ter one-day-integration, the SSH anomalies areassimilated, and the rest of integration (hind-cast/forecast) continue.

Results and Conclusions

Besides the operational system is up to date, itsonly reliable after a detailed validation of bothgrids, which has already started. However, itsnot the intention of this poster presents such val-idation. Anyway, on the context of the ATLAS-B Guariroba Buoy deployment, its convenient tointer-compare the results. The best fit compar-ison wasn’t from the same geographical point,but displaced of about 50 km southwest. De-spite the di!erences between the absolute value,there is a good accordance on its variability.

Figure 4: Temperature comparison between BRAm0.04 and

ATLAS-B Guariroba buoy.

Figure 5: Salinity comparison between BRAm0.04 and

ATLAS-B Guariroba buoy.

Second Meeting of INCLINE Project 07–08/October/2013

LABMON – Laboratorio de Modelagem de Processos Oceanicos. Instituto Oceanografico – Universidade de Sao Paulo (www.labmon.usp.br)