Jerry D. Wiggert

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’ 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 onedimensional 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.

Ocean- Atmosphere Interactions During Cyclone Nargis

Cyclone Nargis (Figure 1a) made landfall in Myanmar (formerly Burma) on 2 May 2008 with sustained winds of approximately 210 kilometers per hour, equivalent to a category 3–4 hurricane. In addition, Nargis brought approximately 600 millimeters of rain and a storm surge of 3–4 meters to the low-lying and densely populated Irrawaddy River delta. In its wake, the storm left an estimated 130,000 dead or missing and more than

Processes controlling interannual variations in wintertime (Northeast Monsoon) primary productivity in the central Arabian Sea

10 billion in economic losses. It was the worst natural disaster to strike the Indian Ocean region since the 26 December 2004 tsunami and the worst recorded natural disaster ever to affect Myanmar.

Biophysical Processes in the Indian Ocean

Three years of ocean color observations obtained by SeaWiFS reveal significant interannual variation in surface chlorophyll a (Chl a) concentrations in the central Arabian Sea during the Northeast (winter) Monsoon (NEM). Consistent with previous findings in the literature, no obvious relation to sea-surface temperature is apparent. A strong relationship with interannual variability in thermocline depth has been established using an interannually forced ocean general circulation model (OGCM). This relationship consists of reduced Chl a concentration associated with a deeper thermocline. Deeper winter convection is generally associated with higher nutrient concentrations and therefore higher phytoplankton biomass. Both in situ observations from the US JGOFS Arabian Sea Expedition and net wintertime nutrient entrainment estimated with the OGCM simulation indicate that mixed-layer concentrations are always sufficiently high to be non-limiting for phytoplankton growth. This raises two questions. What process(es) check phytoplankton growth? What leads to the observed relationship between deeper thermocline and reduced chl a concentration? A prominent feature of the NEM is a large-amplitude diurnal cycle of the mixed layer that is evident in moored temperature time-series. We hypothesize that the night-time penetration of this diurnal mixing, which is defined by the interannually varying thermocline depth, determines the magnitude of phytoplankton biomass that will be retained in the euphotic zone for the following photoperiod. This daily dilution acts to check the accumulation of phytoplankton biomass and prevents a full phytoplankton bloom. A simple 1-D model has been developed to quantify this process. An excellent correspondence exists between model-predicted mixed-layer Chl a concentration as it varies with thermocline depth and the similarly represented SeaWiFS observations.

Climate Forcing and Salinity Variability in Chesapeake Bay, USA

Basic physical processes that impact biological activity in the Indian Ocean (IO), namely, near-surface processes (upwelling, entrainment, detrainment, and advection) and subsurface circulations (shallow overturning cells and subthermocline currents), are reviewed. In the Arabian Sea, there are upwelling blooms during the southwest monsoon (SWM) along Somalia, Oman, and the west coast of India. In the central Arabian Sea, the overall SWM (northeast monsoon; NEM) blooms appear to be a series of entrainment (detrainment) blooms forced by intraseasonal winds. In the western Bay of Bengal, a prominent NEM bloom results from the entrainment of a preexisting deep chlorophyll maximum (DCM). South of Sri Lanka, the SWM bloom is caused by coastal upwelling and Ekman suction, and is swept into the Bay of Bengal by the Southwest Monsoon Current. In the tropical, South IO (5―20°S), there is a weak, surface bloom during boreal summer when new production is enhanced by nutrient entrainment; the surface bloom is even weaker (or absent) during boreal winter because the mixed layer is thinner, the thermocline is deeper, and hence, nutrient entrainment weaker. At intraseasonal timescales, blooms are associated with wind events and Rossby waves/eddies, and they can be generated by both new production and entrainment of a preexisting DCM. During the 1997/1998 El Nino―Southern Oscillation/IO zonal dipole event, there was an upwelling bloom near Sumatra/Java in fall 1997, a much deeper DCM and weaker surface bloom along 5―10°S in spring 1998, and a weaker bloom in the Arabian Sea during the SWM of 1998.

The effect of temporal undersampling on primary production estimates

Salinity is a critical factor in understanding and predicting physical and biogeochemical processes in the coastal ocean where it varies considerably in time and space. In this paper, we introduce a Chesapeake Bay community implementation of the Regional Ocean Modeling System (ChesROMS) and use it to investigate the interannual variability of salinity in Chesapeake Bay. The ChesROMS implementation was evaluated by quantitatively comparing the model solutions with the observed variations in the Bay for a 15-year period (1991 to 2005). Temperature fields were most consistently well predicted, with a correlation of 0.99 and a root mean square error (RMSE) of 1.5°C for the period, with modeled salinity following closely with a correlation of 0.94 and RMSE of 2.5. Variability of salinity anomalies from climatology based on modeled salinity was examined using empirical orthogonal function analysis, which indicates the salinity distribution in the Bay is principally driven by river forcing. Wind forcing and tidal mixing were also important factors in determining the salinity stratification in the water column, especially during low flow conditions. The fairly strong correlation between river discharge anomaly in this region and the Pacific Decadal Oscillation suggests that the long-term salinity variability in the Bay is affected by large-scale climate patterns. The detailed analyses of the role and importance of different forcing, including river runoff, atmospheric fluxes, and open ocean boundary conditions, are discussed in the context of the observed and modeled interannual variability.

Chesapeake Bay nitrogen fluxes derived from a land‐estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets

Annual primary production estimates for specific oceanic regions have typically been made using a variety of measures of productivity spaced, at best, several weeks apart Primary productivity in the oceans is known to be extremely episodic. It is hypothesized here that primary production data with a temporal resolution of several weeks have a high potential for error due to undersampling. In the present analysis, time series of gross primary productivity were calculated using time series of photosynthetically available radiation and chlorophyll a concentration as input to an optical production model. The input data are of minute scale resolution and were gathered during a number of moored experiments. These took place over the past 5 years at several oceanic sites. The minute scale productivity time series were integrated to form time series of daily estimates of gross production. These range in duration from 40 to 260 days. The time series exhibit several regimes characteristic of oceanic primary productivity, such as phytoplankton blooms, productivity pulses associated with advected water masses, steady state growth, and development of a subsurface productivity maximum. The presence of these features makes our time series ideal for investigating (1) the sensitivity of annual production estimates to the timing of the sample set and (2) the error introduced by undersampling inherent in coarser sampling methods. It was found that distinct pulses of productivity generate the greatest error and that high variability leads to large errors, even for well-resolved sampling intervals. The maximum percent error due to undersampling was found to be 85%. Additionally, up to a fourfold range between the maximum and minimum estimates of average daily production was found over all sampling intervals. Finally, the maximum expected range (300 g C m−2 yr1) and the expected standard deviation (±42 g C m−2 yr1) for annual water column production were determined at a Sargasso Sea site for which long-term productivity time series were available at four depths within the euphotic zone.

Basin‐Wide Modification of Dynamical and Biogeochemical Processes by the Positive Phase of the Indian Ocean Dipole During the SeaWiFS Era

Abstract The Chesapeake Bay plays an important role in transforming riverine nutrients before they are exported to the adjacent continental shelf. Although the mean nitrogen budget of the Chesapeake Bay has been previously estimated from observations, uncertainties associated with interannually varying hydrological conditions remain. In this study, a land‐estuarine‐ocean biogeochemical modeling system is developed to quantify Chesapeake riverine nitrogen inputs, within‐estuary nitrogen transformation processes and the ultimate export of nitrogen to the coastal ocean. Model skill was evaluated using extensive in situ and satellite‐derived data, and a simulation using environmental conditions for 2001–2005 was conducted to quantify the Chesapeake Bay nitrogen budget. The 5 year simulation was characterized by large riverine inputs of nitrogen (154 × 109 g N yr−1) split roughly 60:40 between inorganic:organic components. Much of this was denitrified (34 × 109 g N yr−1) and buried (46 × 109 g N yr−1) within the estuarine system. A positive net annual ecosystem production for the bay further contributed to a large advective export of organic nitrogen to the shelf (91 × 109 g N yr−1) and negligible inorganic nitrogen export. Interannual variability was strong, particularly for the riverine nitrogen fluxes. In years with higher than average riverine nitrogen inputs, most of this excess nitrogen (50–60%) was exported from the bay as organic nitrogen, with the remaining split between burial, denitrification, and inorganic export to the coastal ocean. In comparison to previous simulations using generic shelf biogeochemical model formulations inside the estuary, the estuarine biogeochemical model described here produced more realistic and significantly greater exports of organic nitrogen and lower exports of inorganic nitrogen to the shelf.

Research Opportunities and Challenges in the Indian Ocean

Characterizing how the Indian Ocean dipole (IOD) modifies typical basin-wide dynamical variability has been vigorously pursued over the past decade. Along with this dynamic response, a clear biological impact has been revealed in the ocean color data acquired by remote sensing platforms such as Sea-viewing Wide Field-of-View Sensor (SeaWiFS). The signature feature illustrating IOD alteration of typical spatiotemporal chlorophyll variability is the phytoplankton bloom that first appears in September along the eastern boundary of the IO in tropical waters that are normally highly oligotrophic. Positive chlorophyll anomalies (CLa) are also apparent in the southeastern Bay of Bengal, while negative anomalies are observed over much of the Arabian Sea. Moreover, in situ measurements obtained by the R/V Suroit as part of the Cirene cruise during the 2006/2007 IOD reveal anomalous subsurface biochemical distributions in the southern tropical IO that are not reflected in SeaWiFS data. Despite the clear basin-wide influence of IOD events on biological variability, the accompanying influence on biogeochemical cycling that must occur has received little attention. Here, the dynamical signatures apparent in remote sensing fields for the two positive-phase IODs of the SeaWiFS era are used to illuminate how these events are similar or distinct. A corresponding comparison of IOD-engendered surface CLa is performed, with the dynamical fields providing the framework for interpreting the mechanisms underlying the biological response. Then, results from a newly developed net primary production algorithm are presented that provide the first characterization of how biogeochemical fluxes throughout the IO are altered by IOD occurrence.

Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

The Indian Ocean is a dynamically complex and highly variable system, with circulation features and biogeochemical properties that are unusual in many respects. Yet the Indian Ocean (IO) remains one of the most undersampled and least understood of the worlds ocean basins. In this article, we define several outstanding research questions that need to be addressed in the IO related to ocean currents and variability, the controls and fate of primary production, global change and anthropogenic impacts, and the role of higher trophic levels in ecological processes and biogeochemical cycles. We also discuss a unique opportunity that has recently arisen for staging research in the IO.