A data assimilative marine ecosystem model of the central equatorial Pacific: Numerical twin experiments

A five-component, data assimilative marine ecosystem model is developed for the high-nutrient low-chlorophyll region of the central equatorial Pacific (0N, 140W). Identical twin experiments, in which model-generated synthetic \u27data\u27 are assimilated into the model, are employed to determine the feasibility of improving simulation skill by assimilating in situ cruise data (plankton, nutrients and primary production) and remotely-sensed ocean color data. Simple data assimilative schemes such as data insertion or nudging may be insufficient for lower trophic level marine ecosystem models, since they require long time-series of daily to weekly plankton and nutrient data as well as adequate knowledge of the governing ecosystem parameters. In contrast, the variational adjoint technique, which minimizes model-data misfits by optimizing tunable ecosystem parameters, holds much promise for assimilating biological data into marine ecosystem models. Using sampling strategies typical of those employed during the U.S. Joint Global Flux Study (JGOFS) equatorial Pacific process study and the remotely-sensed ocean color data available from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), parameters that characterize processes such as growth, grazing, mortality, and recycling can be estimated. Simulation skill is improved even if synthetic data associated with 40% random noise are assimilated; however, the presence of biases of 10-20% proves to be more detrimental to the assimilation results. Although increasing the length of the assimilated time series improves simulation skill if random errors are present in the data, simulation skill may deteriorate as more biased data are assimilated. As biological data sets, including in situ, satellite and acoustic sources, continue to grow, data assimilative biological-physical models will play an increasingly crucial role in large interdisciplinary oceanographic observational programs

Meridional circulation in the tropical North Atlantic

A transatlantic CTD/ADCP section nominally located at 11°N was carried out in March 1989. In this paper relative geostrophic velocities are computed from these data via the thermal wind balance, with reference level choices based primarly on water mass distributions. A brief overview of the meridional circulation of the upper waters resulting from these analysis techniques is presented. Schematic circulation patterns of the NADW and AAW are also presented. In both the western and eastern basins these waters are characterized by cyclonic recirculation gyres. A paricularly notable result of the deep western basin analysis is the negligible net flow of middle NADW. Although the horizontal circulation patterns described in this study agree well with results from many previous studies, the meridional overturning cell and net heat flux are considerably lower, while the net freshwater flux is slightly higher than previous estimates. These discrepancies may be attbuted to: (1) differences in methodologies, (2) the increased resolution of this section, and (3) temporal (including decadal, synoptic, and most importantly, seasonal) variability.Funding was provided by the National Science Foundation through Grant Nos. OCE-8716314 and OCE-9101636 and the Office of Naval Research through the American Society for Engineering Education

Deep circulation in the tropical North Atlantic

A transatlantic CTD/ADCP (Conductivity, Temperature, Depth/Acoustic Doppler Current Profiler) section along 11N, taken in March 1989, has been used to compute geostrophic velocities; geostrophic transport is required to balance in situ values of the Ekman and shallow boundary current transports. The horizontal flow structure is described for eight layers, with particular emphasis on deep and bottom waters (four layers below = 4.7°C). In the shallow layers, total North Brazil Current (NBC) transport agrees with other observations previously made in the month of March, while net northward flow of these layers across the western basin is also consistent with recent observations to the north. For each of the four deep layers, circulation patterns are illustrated by means of schematic cartoons. Each of these layers flows southward in the Deep Western Boundary Current, which has a magnitude of 26.5 Sv. Roughly half of this flow returns northward to the west of the Mid-Atlantic Ridge, confirming the existence of a hypothesized cyclonic recirculation gyre in the western basin of the tropical Atlantic. To varying degrees the deep and bottom waters also circulate cyclonically in the eastern basin, with net northward flow across this basin. Partly as a result of the unusual appearance of the North Equatorial Countercurrent in March 1989, the in situ values of the meridional overturning cell (5.2 Sv), heat flux (3.0 × 1014 W), and freshwater flux (−0.65 Sv) computed from the 11N section depart significantly from estimates of these quantities in the literature. By forcing the 11N geostrophic velocities to balance annual average Ekman and NBC transports, annual average values of these fluxes (12 Sv; 11 × 1014 W; −0.6 Sv) are obtained, and are shown to agree well with historical estimates

Combining observations and numerical model results to improve estimates of hypoxic volume within the Chesapeake Bay, USA

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 4924–4944, doi:10.1002/jgrc.20331.The overall size of the “dead zone” within the main stem of the Chesapeake Bay and its tidal tributaries is quantified by the hypoxic volume (HV), the volume of water with dissolved oxygen (DO) less than 2 mg/L. To improve estimates of HV, DO was subsampled from the output of 3-D model hindcasts at times/locations matching the set of 2004–2005 stations monitored by the Chesapeake Bay Program. The resulting station profiles were interpolated to produce bay-wide estimates of HV in a manner consistent with nonsynoptic, cruise-based estimates. Interpolations of the same stations sampled synoptically, as well as multiple other combinations of station profiles, were examined in order to quantify uncertainties associated with interpolating HV from observed profiles. The potential uncertainty in summer HV estimates resulting from profiles being collected over 2 weeks rather than synoptically averaged ∼5 km3. This is larger than that due to sampling at discrete stations and interpolating/extrapolating to the entire Chesapeake Bay (2.4 km3). As a result, sampling fewer, selected stations over a shorter time period is likely to reduce uncertainties associated with interpolating HV from observed profiles. A function was derived that when applied to a subset of 13 stations, significantly improved estimates of HV. Finally, multiple metrics for quantifying bay-wide hypoxia were examined, and cumulative hypoxic volume was determined to be particularly useful, as a result of its insensitivity to temporal errors and climate change. A final product of this analysis is a nearly three-decade time series of improved estimates of HV for Chesapeake Bay.Funding for this study was provided by the IOOS COMT Program through NOAA grants NA10NOS0120063 and NA11NOS0120141. Additional funding was provided by NSF grant OCE-1061564

A Comparison of Global Estimates of Marine Primary Production From Ocean Color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chl m-3. Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate

Advancing Marine Biogeochemical and Ecosystem Reanalyses and Forecasts as Tools for Monitoring and Managing Ecosystem Health

Ocean ecosystems are subject to a multitude of stressors, including changes in ocean physics and biogeochemistry, and direct anthropogenic influences. Implementation of protective and adaptive measures for ocean ecosystems requires a combination of ocean observations with analysis and prediction tools. These can guide assessments of the current state of ocean ecosystems, elucidate ongoing trends and shifts, and anticipate impacts of climate change and management policies. Analysis and prediction tools are defined here as ocean circulation models that are coupled to biogeochemical or ecological models. The range of potential applications for these systems is broad, ranging from reanalyses for the assessment of past and current states, and short-term and seasonal forecasts, to scenario simulations including climate change projections. The objectives of this article are to illustrate current capabilities with regard to the three types of applications, and to discuss the challenges and opportunities. Representative examples of global and regional systems are described with particular emphasis on those in operational or pre-operational use. With regard to the benefits and challenges, similar considerations apply to biogeochemical and ecological prediction systems as do to physical systems. However, at present there are at least two major differences: (1) biogeochemical observation streams are much sparser than physical streams presenting a significant hinderance, and (2) biogeochemical and ecological models are largely unconstrained because of insufficient observations. Expansion of biogeochemical and ecological observation systems will allow for significant advances in the development and application of analysis and prediction tools for ocean biogeochemistry and ecosystems, with multiple societal benefits

Surface Ocean pCO2 Seasonality and Sea-Air CO2 Flux Estimates for the North American East Coast

Underway and in situ observations of surface ocean pCO2, combined with satellite data, were used to develop pCO2 regional algorithms to analyze the seasonal and interannual variability of surface ocean pCO2 and sea-air CO2 flux for five physically and biologically distinct regions of the eastern North American continental shelf: the South Atlantic Bight (SAB), the Mid-Atlantic Bight (MAB), the Gulf of Maine (GoM), Nantucket Shoals and Georges Bank (NS+GB), and the Scotian Shelf (SS). Temperature and dissolved inorganic carbon variability are the most influential factors driving the seasonality of pCO2. Estimates of the sea-air CO2 flux were derived from the available pCO2 data, as well as from the pCO2 reconstructed by the algorithm. Two different gas exchange parameterizations were used. The SS, GB+NS, MAB, and SAB regions are net sinks of atmospheric CO2 while the GoM is a weak source. The estimates vary depending on the use of surface ocean pCO2 from the data or algorithm, as well as with the use of the two different gas exchange parameterizations. Most of the regional estimates are in general agreement with previous studies when the range of uncertainty and interannual variability are taken into account. According to the algorithm, the average annual uptake of atmospheric CO2 by eastern North American continental shelf waters is found to be between 3.4 and 5.4 Tg C/yr (areal average of 0.7 to 1.0 mol CO2 /sq m/yr) over the period 2003-2010

Forecasting Prorocentrum minimum blooms in the Chesapeake Bay using empirical habitat models

Aquaculturists, local beach managers, and other stakeholders require forecasts of harmful biotic events, so they can assess and respond to health threats when harmful algal blooms (HABs) are present. Based on this need, we are developing empirical habitat suitability models for a variety of Chesapeake Bay HABs to forecast their occurrence based on a set of physical-biogeochemical environmental conditions, and start with the dinoflagellate Prorocentrum minimum (also known as P. cordatum).To identify an optimal set of environmental variables to forecast P. minimum blooms, we first assumed a linear relationship between the environmental variables and the inverse of the logistic function used to forecast the likelihood of bloom presence, and repeated the method using more than 16,000 combinations of variables. By comparing goodness-of-fit, we found water temperature, salinity, pH, solar irradiance, and total organic nitrogen represented the most suitable set of variables. The resulting algorithm forecasted P. minimum blooms with an overall accuracy of 78%, though with a significant variability ~ 30-90% depending on region and season. To understand this variability and improve model performance, we incorporated nonlinear effects into the model by implementing a generalized additive model. Even without considering interactions between the five variables used to train the model, this yielded an increase in overall model accuracy (~ 81%) due to the model’s ability to refine the regions in which P. minimum blooms occurred. Including nonlinear interactions increased the overall model accuracy even further (~ 85%) by accounting for seasonality in the interaction between solar irradiance and water temperature. Our findings suggest that the influence of predictors of these blooms change in time and space, and that model complexity impacts the model performance and our interpretation of the driving factors causing P. minimum blooms. Apart from their forecasting potential, our results may be particularly useful when constructing explicit relationships between environmental conditions and P. minimum presence in mechanistic models

Assessment of Skill and Portability in Regional Marine Biogeochemical Models: Role of Multiple Planktonic Groups

[1] Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models\u27 performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways

Carbon Budget of Tidal Wetlands, Estuaries, and Shelf Waters of Eastern North America

Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling