Weak and strong constraint data assimilation in the inverse Regional Ocean Modeling System (ROMS): Development and application for a baroclinic coastal upwelling system

2007 ◽  
Vol 16 (3-4) ◽  
pp. 160-187 ◽  
Author(s):  
Emanuele Di Lorenzo ◽  
Andrew M. Moore ◽  
Hernan G. Arango ◽  
Bruce D. Cornuelle ◽  
Arthur J. Miller ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Coastal Upwelling ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
Strong Constraint ◽  
Upwelling System

scholarly journals Drivers and impact of the seasonal variability of the organic carbon offshore transport in the Canary Upwelling System

2020 ◽  
Author(s):  
Giulia Bonino ◽  
Elisa Lovecchio ◽  
Nicolas Gruber ◽  
Matthias Münnich ◽  
Simona Masina ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Temporal Variability ◽  
Seasonal Variability ◽  
Coastal Upwelling ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
Nearshore Processes ◽  
Upwelling System ◽  
Canary Upwelling ◽  
Offshore Transport

Abstract. The Canary Upwelling System (CanUS) is a productive coastal region characterized by strong seasonality and an intense offshore transport of organic carbon (Corg) to the adjacent oligotrophic offshore waters. There, the respiration of this Corg substantially modifies net community production (NCP). While this transport and the resulting coupling of the biogeochemistry between the coastal and open ocean has been well studied in the annual mean, the temporal variability, and especially its seasonality has not yet been investigated. Here, we fill this gap, and determine the seasonal variability of the offshore transport of Corg, its mesoscale component, latitudinal differences, and the underlying physical and biological drivers. To this end, we employ the Regional Ocean Modeling System (ROMS) coupled to a nutrient, phytoplankton, zooplankton, and detritus (NPZD) ecosystem model. Our results reveal the importance of the mesoscale fluxes and of the upwelling processes (coastal upwelling and Ekman pumping) in modulating the seasonal variation of the offshore Corg transport. We find that the region surrounding Cape Blanc (21° N) hosts the most intense Corg offshore flux in every season, linked to the persistent, and far reaching Cape Blanc filament. Coastal upwelling filaments dominate the seasonality of the total offshore flux up to 100 km from the coast, contributing in every season season at least 80 % to the total flux. The seasonality of the upwelling modulates the offshore Corg seasonality hundreds of km from the CanUS coast via lateral redistribution of nearshore production. North of 24.5° N, the sharp summer-fall peak of coastal upwelling results in an export of more than 30 % of the coastal Corg at the 100 km offshore due to a combination of intensified nearshore production and offshore fluxes. To the south, the less pronounced upwelling seasonality regulates an overall larger, but farther-reaching and less seasonally varying lateral flux, which exports between 60 and 90 % of the coastal production more than 100 km offshore. Overall, we show that the temporal variability of nearshore processes impacts the variability of Corg and NCP hundreds of km offshore from the CanUS coast via the offshore transport of the nearshore production.

scholarly journals Drivers and impact of the seasonal variability of the organic carbon offshore transport in the Canary upwelling system

2021 ◽  
Vol 18 (8) ◽  
pp. 2429-2448
Author(s):  
Giulia Bonino ◽  
Elisa Lovecchio ◽  
Nicolas Gruber ◽  
Matthias Münnich ◽  
Simona Masina ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Temporal Variability ◽  
Seasonal Variability ◽  
Coastal Upwelling ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
Nearshore Processes ◽  
Upwelling System ◽  
Canary Upwelling ◽  
Offshore Transport

Abstract. The Canary upwelling system (CanUS) is a productive coastal region characterized by strong seasonality and an intense offshore transport of organic carbon (Corg) to the adjacent oligotrophic offshore waters. There, the respiration of this Corg substantially modifies net community production (NCP). While this transport and the resulting coupling of the biogeochemistry between the coastal and open ocean has been well studied in the annual mean, the temporal variability, and especially its seasonality, has not yet been investigated. Here, we determine the seasonal variability of the offshore transport of Corg, its mesoscale component, latitudinal differences, and the underlying physical and biological drivers. To this end, we employ the Regional Ocean Modeling System (ROMS) coupled to a nutrient–phytoplankton–zooplankton–detritus (NPZD) ecosystem model. Our results reveal the importance of the mesoscale fluxes and of the upwelling processes (coastal upwelling and Ekman pumping) in modulating the seasonal variation of the offshore Corg transport. We find that the region surrounding Cape Blanc (21∘ N) hosts the most intense Corg offshore flux in every season, linked to the persistent, and far reaching Cape Blanc filament and its interaction with the Cape Verde Front. Coastal upwelling filaments dominate the seasonality of the total offshore flux up to 100 km from the coast, contributing in every season at least 80 % to the total flux. The seasonality of the upwelling modulates the offshore Corg seasonality hundreds of kilometers from the CanUS coast via lateral redistribution of nearshore production. North of 24.5∘ N, the sharp summer–fall peak of coastal upwelling results in an export of more than 30 % of the coastal Corg at 100 km offshore due to a combination of intensified nearshore production and offshore fluxes. To the south, the less pronounced upwelling seasonality regulates an overall larger but farther-reaching and less seasonally varying lateral flux, which exports between 60 % and 90 % of the coastal production more than 100 km offshore. Overall, we show that the temporal variability of nearshore processes modulates the variability of Corg and NCP hundreds of kilometers offshore from the CanUS coast via the offshore transport of the nearshore production.

Predictability of Mesoscale Variability in the East Australian Current Given Strong-Constraint Data Assimilation

2012 ◽  
Vol 42 (9) ◽  
pp. 1402-1420 ◽  
Author(s):  
Javier Zavala-Garay ◽  
J. L. Wilkin ◽  
H. G. Arango
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Empirical Relationship ◽  
Ocean Modeling ◽  
Sea Surface ◽  
Initial Time ◽  
East Australian Current ◽  
Mesoscale Variability ◽  
Regional Ocean Modeling System ◽  
Strong Constraint

Abstract One of the many applications of data assimilation is the estimation of adequate initial conditions for model forecasts. In this work, the authors evaluate to what extent the incremental, strong-constraint, four-dimensional variational data assimilation (IS4DVAR) can improve prediction of mesoscale variability in the East Australian Current (EAC) using the Regional Ocean Modeling System (ROMS). The observations considered in the assimilation experiments are daily composites of satellite sea surface temperature (SST), 7-day average reanalysis of satellite altimeter sea level anomalies, and subsurface temperature profiles from high-resolution expendable bathythermograph (XBT). Considering all available observations for years 2001 and 2002, ROMS forecast initial conditions are generated every week by assimilating the available observations from the 7 days prior to the forecast initial time. It is shown that assimilation of surface information only [SST and sea surface height (SSH)] results in poor estimates of the true subsurface ocean state (as depicted by the XBTs) and therefore poor forecast skill of subsurface conditions. Including the XBTs in the assimilation experiments improves the ocean state estimation in the vicinity of the XBT transects. By introducing subsurface pseudo-observations (which are called synthetic CTD) based on an empirical relationship between satellite surface observations and subsurface variability, the authors find a significant improvement in ocean state estimates that leads to skillful forecasts for up to 2 weeks in the domain considered.

scholarly journals On the long-range offshore transport of organic carbon from the Canary Upwelling System to the open North Atlantic

2017 ◽  
Vol 14 (13) ◽  
pp. 3337-3369 ◽  
Author(s):  
Elisa Lovecchio ◽  
Nicolas Gruber ◽  
Matthias Münnich ◽  
Zouhair Lachkar
Keyword(s):  
Organic Carbon ◽  
North Atlantic ◽  
Ecosystem Model ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
Net Community Production ◽  
Upwelling System ◽  
Canary Upwelling ◽  
Vertical Export ◽  
Offshore Transport

Abstract. A compilation of measurements of net community production (NCP) in the upper waters of the eastern subtropical North Atlantic had suggested net heterotrophic conditions, purportedly supported by the lateral export of organic carbon from the adjacent, highly productive Canary Upwelling System (CanUS). Here, we quantify and assess this lateral export using the Regional Ocean Modeling System (ROMS) coupled to a nutrient, phytoplankton, zooplankton, and detritus (NPZD) ecosystem model. We employ a new Atlantic telescopic grid with a strong refinement towards the northwestern African shelf to combine an eddy-resolving resolution in the CanUS with a full Atlantic basin perspective. Our climatologically forced simulation reveals an intense offshore flux of organic carbon that transports about 19 Tg C yr−1 away from the nearshore 100 km over the whole CanUS, amounting to more than a third of the NCP in this region. The offshore transport extends beyond 1500 km into the subtropical North Atlantic, adding organic carbon along the way to the upper 100 m at rates of between 8 and 34 % of the alongshore average NCP as a function of offshore distance. Although the divergence of this lateral export of organic carbon enhances local respiration, the upper 100 m layer in our model remains net autotrophic in the entire eastern subtropical North Atlantic. However, the vertical export of this organic carbon and its subsequent remineralization at depth makes the vertically integrated NCP strongly negative throughout this region, with the exception of a narrow band along the northwestern African shelf. The magnitude and efficiency of the lateral export varies substantially between the different subregions. In particular, the central coast near Cape Blanc is particularly efficient in collecting organic carbon on the shelf and subsequently transporting it offshore. In this central subregion, the offshore transport adds as much organic carbon as nearly 60 % of the local NCP to the upper 100 m, giving rise to a sharp peak of offshore respiration that extends to the middle of the gyre. Our modeled offshore transport of organic carbon is likely a lower-bound estimate due to our lack of full consideration of the contribution of dissolved organic carbon and that of particulate organic carbon stemming from the resuspension of sediments. But even in the absence of these contributions, our results emphasize the fundamental role of the lateral redistribution of the organic carbon for the maintenance of the heterotrophic activity in the open sea.

4DVAR data assimilation in the Intra-Americas Sea with the Regional Ocean Modeling System (ROMS)

2008 ◽  
Vol 23 (3-4) ◽  
pp. 130-145 ◽  
Author(s):  
B.S. Powell ◽  
H.G. Arango ◽  
A.M. Moore ◽  
E. Di Lorenzo ◽  
R.F. Milliff ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System

scholarly journals Reanalysis of the PacIOOS Hawaiian Island Ocean Forecast System, an implementation of the Regional Ocean Modeling System v3.6

2019 ◽  
Vol 12 (1) ◽  
pp. 195-213
Author(s):  
Dale Partridge ◽  
Tobias Friedrich ◽  
Brian S. Powell
Keyword(s):  
Initial Conditions ◽  
Hawaiian Island ◽  
The State ◽  
Ocean Modeling ◽  
Surface Velocity ◽  
Regional Ocean Modeling System ◽  
Forecast System ◽  
Strong Constraint ◽  
State Estimate ◽  
High Frequency Radar

Abstract. A 10-year reanalysis of the PacIOOS Hawaiian Island Ocean Forecast System was produced using an incremental strong-constraint 4-D variational data assimilation with the Regional Ocean Modeling System (ROMS v3.6). Observations were assimilated from a range of sources: satellite-derived sea surface temperature (SST), salinity (SSS), and height anomalies (SSHAs); depth profiles of temperature and salinity from Argo floats, autonomous Seagliders, and shipboard conductivity–temperature–depth (CTD); and surface velocity measurements from high-frequency radar (HFR). The performance of the state estimate is examined against a forecast showing an improved representation of the observations, especially the realization of HFR surface currents. EOFs of the increments made during the assimilation to the initial conditions and atmospheric forcing components are computed, revealing the variables that are influential in producing the state-estimate solution and the spatial structure the increments form.

The impact of ocean data assimilation on the simulation of mesoscale eddies at São Paulo plateau (Brazil) using the regional ocean modeling system

2021 ◽  
pp. 101889
Author(s):  
Thiago Pires de Paula ◽  
Jose Antonio Moreira Lima ◽  
Clemente Augusto Souza Tanajura ◽  
Marcelo Andrioni ◽  
Renato Parkinson Martins ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Mesoscale Eddies ◽  
Sao Paulo ◽  
Ocean Modeling ◽  
São Paulo ◽  
Regional Ocean Modeling System ◽  
Ocean Data Assimilation ◽  
The Impact

scholarly journals High-Resolution Operational Ocean Forecast and Reanalysis System for the Indian Ocean

2020 ◽  
Vol 101 (8) ◽  
pp. E1340-E1356 ◽  
Author(s):  
P. A. Francis ◽  
A. K. Jithin ◽  
J. B. Effy ◽  
A. Chatterjee ◽  
K. Chakraborty ◽  
...  
Keyword(s):  
High Resolution ◽  
Indian Ocean ◽  
Data Assimilation ◽  
Coastal Waters ◽  
General Circulation ◽  
High Performance ◽  
Coast Guard ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
The Indian Ocean

Abstract A good understanding of the general circulation features of the oceans, particularly of the coastal waters, and ability to predict the key oceanographic parameters with good accuracy and sufficient lead time are necessary for the safe conduct of maritime activities such as fishing, shipping, and offshore industries. Considering these requirements and buoyed by the advancements in the field of ocean modeling, data assimilation, and ocean observation networks along with the availability of the high-performance computational facility in India, Indian National Centre for Ocean Information Services has set up a “High-Resolution Operational Ocean Forecast and Reanalysis System” (HOOFS) with an aim to provide accurate ocean analysis and forecasts for the public, researchers, and other types of users like navigators and the Indian Coast Guard. Major components of HOOFS are (i) a suite of numerical ocean models configured for the Indian Ocean and the coastal waters using the Regional Ocean Modeling System (ROMS) for forecasting physical and biogeochemical state of the ocean and (ii) the data assimilation based on local ensemble transform Kalman filter that assimilates in situ and satellite observations in ROMS. Apart from the routine forecasts of key oceanographic parameters, a few important applications such as (i) Potential Fishing Zone forecasting system and (ii) Search and Rescue Aid Tool are also developed as part of the HOOFS project. The architecture of HOOFS, an account of the quality of ocean analysis and forecasts produced by it and important applications developed based on HOOFS are briefly discussed in this article.

scholarly journals An Advanced Data Assimilation System for the Chesapeake Bay: Performance Evaluation

2012 ◽  
Vol 29 (10) ◽  
pp. 1542-1557 ◽  
Author(s):  
Matthew J. Hoffman ◽  
Takemasa Miyoshi ◽  
Thomas W. N. Haine ◽  
Kayo Ide ◽  
Christopher W. Brown ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Chesapeake Bay ◽  
Nonlinear Dynamical Systems ◽  
Initial Conditions ◽  
Real Data ◽  
Ocean Modeling ◽  
Forecast Errors ◽  
Regional Ocean Modeling System ◽  
Data Assimilation System ◽  
Assimilation System

Abstract An advanced data assimilation system, the local ensemble transform Kalman filter (LETKF), has been interfaced with a Regional Ocean Modeling System (ROMS) implementation on the Chesapeake Bay (ChesROMS) as a first step toward a reanalysis and improved forecast system for the Chesapeake Bay. The LETKF is among the most advanced data assimilation methods and is very effective for large, nonlinear dynamical systems with sparse data coverage. Errors in the Chesapeake Bay system are due more to errors in forcing than errors in initial conditions. To account for forcing errors, a forcing ensemble is used to drive the ensemble states for the year 2003. In the observing system simulation experiments (OSSEs) using the ChesROMS-LETKF system presented here, the filter converges quickly and greatly reduces the analysis and subsequent forecast errors in the temperature, salinity, and current fields in the presence of errors in wind forcing. Most of the improvement in temperature and currents comes from satellite sea surface temperature (SST), while in situ salinity profiles provide improvement to salinity. Corrections permeate through all vertical levels and some correction to stratification is seen in the analysis. In the upper Bay where the nature-run summer stratification is −0.2 salinity units per meter, stratification is improved from −0.01 per meter in the unassimilated model to −0.16 per meter in the assimilation. Improvements are seen in other parts of the Bay as well. The results from the OSSEs are promising for assimilating real data in the future.

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