Watson W. Gregg

Atmospheric Iron Delivery and Surface Ocean Biological Activity in the Southern Ocean and Patagonian Region

[1] Iron is a limiting nutrient for biologic activity in much of the world ocean. We present a method to quantitatively address the response of surface ocean biology to inputs of atmospheric Fe associated with atmospheric dust. We merge two enabling technologies, global models of Earth system processes and satellite derived chlorophyll concentrations to assess the importance of Fe in oceanic biogeochemistry. We present an objective correlation analysis to elucidate the spatial response of chlorophyll to iron flux considering the ocean surface meridional center of mass in areas with high correlation. Several regions between 40� S and 60� S show correlations from 0.6 to 0.95, significant at the 0.05 level, particularly the Patagonian region. Surface chlorophyll and iron flux follow similar patterns, however chlorophyll may be displaced to different latitudes than where Fe input occurs due to meridional ocean transport. INDEX TERMS: 1615 Global Change: Biogeochemical processes (4805); 1640 Global Change: Remote sensing; 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0312 Atmospheric Composition and Structure: Air/sea constituent fluxes (3339, 4504); 0330 Atmospheric Composition and Structure: Geochemical cycles. Citation: Erickson, D. J., III, J. L. Hernandez, P. Ginoux, W. W. Gregg, C. McClain, and J. Christian, Atmospheric iron delivery and surface ocean biological activity in the Southern Ocean and Patagonian region, Geophys. Res. Lett., 30(12), 1609, doi:10.1029/2003GL017241, 2003.

Decadal trends in global pelagic ocean chlorophyll: A new assessment integrating multiple satellites, in situ data, and models

Quantifying change in ocean biology using satellites is a major scientific objective. We document trends globally for the period 1998–2012 by integrating three diverse methodologies: ocean color data from multiple satellites, bias correction methods based on in situ data, and data assimilation to provide a consistent and complete global representation free of sampling biases. The results indicated no significant trend in global pelagic ocean chlorophyll over the 15 year data record. These results were consistent with previous findings that were based on the first 6 years and first 10 years of the SeaWiFS mission. However, all of the Northern Hemisphere basins (north of 10° latitude), as well as the Equatorial Indian basin, exhibited significant declines in chlorophyll. Trend maps showed the local trends and their change in percent per year. These trend maps were compared with several other previous efforts using only a single sensor (SeaWiFS) and more limited time series, showing remarkable consistency. These results suggested the present effort provides a path forward to quantifying global ocean trends using multiple satellite missions, which is essential if we are to understand the state, variability, and possible changes in the global oceans over longer time scales.

Global seasonal climatologies of ocean chlorophyll: Blending in situ and satellite data for the Coastal Zone Color Scanner era

The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner (CZCS)) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: Global chlorophyll estimates increased 8–35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25–41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.

Tracking the SeaWiFS record with a coupled physical/biogeochemical/radiative model of the global oceans

Abstract The Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) has observed multiple years of routine global chlorophyll observations from space. The mission was launched into a record El Nino event, which eventually gave way to one of the most intense and longest-lasting La Nina events ever recorded. The SeaWiFS chlorophyll record captured the response of ocean phytoplankton to these significant events in the tropical Indo-Pacific basins, but also indicated significant interannual variability unrelated to the El Nino/La Nina events. This included large variability in the North Atlantic and Pacific basins, in the North Central and equatorial Atlantic, and milder patterns in the North Central Pacific. This SeaWiFS record was tracked with a coupled physical/biogeochemical/radiative model of the global oceans using near-real-time forcing data such as wind stresses, sea surface temperatures, and sea ice. This provided an opportunity to offer physically and biogeochemically meaningful explanations of the variability observed in the SeaWiFS data set, since the causal mechanisms and interrelationships of the model are completely understood. The coupled model was able to represent the seasonal distributions of chlorophyll during the SeaWiFS era, and was capable of differentiating among the widely different processes and dynamics occurring in the global oceans. The model was also reasonably successful in representing the interannual signal, especially when it was large, such as the El Nino and La Nina events in the tropical Pacific and Indian Oceans. The model provided different phytoplankton group responses for the different events in these regions: diatoms were predominant in the tropical Pacific during the La Nina, but other groups were predominant during El Nino. The opposite condition occurred in the tropical Indian Ocean. Both situations were due to the different responses of the basins to El Nino. Interannual variability in the North Pacific was exhibited as an increase in the spring bloom in 1999 and 2000 relative to 1998. This resulted in the model from a shallower and more rapidly shoaling mixed layer, producing more average irradiance in the water column and preventing herbivore populations to keep pace with increasing phytoplankton populations. However, several aspects of the interannual cycle were not well-represented by the model. Explanations range from inherent model deficiencies, to monthly averaging of forcing fields, to biases in SeaWiFS atmospheric correction procedures.

Coverage opportunities for global ocean color in a multimission era

The international community, recognizing the importance of global ocean color observations in the global carbon cycle, has proposed or flown six global ocean color missions over the next decade: the Ocean Color and Temperature Sensor (OCTS), Sea-viewing Wide Field-of-view Sensor (SeaWiFs), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. Each of these missions contains the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance). This paper assesses whether assembling and merging data from these missions can improve ocean coverage, since clouds and Sun glint prevent any single satellite from observing more than about 15% of the ocean surface in a single day, and whether new information about diel cycles of phytoplankton abundance is possible. Extensive numerical analysis, given the orbit and sensor characteristics of each mission, showed that merging data form three satellites can produce better ocean coverage in less time. Data from three satellites can improve coverage by 58% for a single day, including the obscuring effects of clouds and sun glint. Thus, observation of approximately 25% of the ocean can be provided, instead of only about 15-16% from a single satellite. After four days, approximately 62% of the ocean surface was observed, an increase from 43% observed by a single satellite. The addition of more satellites produced diminishing returns. Since the proposed missions have different orbits, the view the same location of the ocean at different times of day. This leads to the possibility of using data from the set of six missions to help understand diel phytoplankton dynamics.

Modeling the biogeochemical cycle of dimethylsulfide in the upper ocean: a review

An important focus of climate-change research is the understanding of the role of ecosystems in shaping climate. Central to this aim is the identification of any feedbacks by which ecosystems may moderate anthropogenic forcing of climate. One possible ecosystem feedback involves the marine food-web and the biogenic sulfur compound dimethylsulfide (DMS). DMS is produced by algae containing the precursor compound dimethylsulfoniopropionate (DMSP), and once ventilated to the atmosphere can be transformed to sulfate aerosols and global climate. It was hypothesized that an increase in biogenically produced sulfate aerosols leading to formation of more cloud condensation nuclei (CCN), and brighter clouds, could stabilize the climate against perturbations due to greenhouse warming. Although a large database of DMS seawater measurements exist, attempts to statistically correlate DMS concentrations with other biological parameters, such as chlorophyll a or nutrients, have failed. This underscores the complex and dynamic nature of the DMS cycle, and means that simple regression-type predictive models are unlikely to be useful, except at local scales. Regional-scale simulations of the DMS cycle have involved multi-parameter, deterministic formulations based on ecological food-web approaches but with the added challenge of properly simulating the behavior of coupled sulfur and nitrogen (or carbon) cycles. Here we review the current DMS modeling approaches, outline the parameterization of key processes, and identify areas where our knowledge is poor and improvements should be made. Model skill can only be assessed against detailed regional and global data sets, however data have not always been collected in a form suitable for model parameter estimation or model calibration/validation. DMS time series, which are essential for calibration of seasonal or multi-annual simulations, are rare. We discuss the minimum requirements for a successful future integration of observational and theoretical efforts.

Interannual Variation in Phytoplankton Primary Production at a Global Scale

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998–2011. Globally, diatoms contributed the most to the total phytoplankton production (~50%, the equivalent of ~20 PgC∙y−1). Coccolithophores and chlorophytes each contributed ~20% (~7 PgC∙y−1) of the total primary production and cyanobacteria represented about 10% (~4 PgC∙y−1) of the total primary production. Primary production by diatoms was highest in the high latitudes (>40°) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998–2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1–2 PgC∙y−1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Nino Index, MEI) and “regional” climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p < 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

NOAA-NASA Coastal Zone Color Scanner Reanalysis Effort

Satellite observations of global ocean chlorophyll span more than two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration (NOAA-NASA) CZCS reanalysis (NCR) effort. NCR consisted of (1) algorithm improvement (AI), where CZCS processing algorithms were improved with modernized atmospheric correction and bio-optical algorithms and (2) blending where in situ data were incorporated into the CZCS AI to minimize residual errors. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.

Recent decadal trends in global phytoplankton composition

Identifying major trends in biogeochemical composition of the oceans is essential to improve our understanding of biological responses to climate forcing. Using the NASA Ocean Biogeochemical Model combined with ocean color remote sensing data assimilation, we assessed the trends in phytoplankton composition (diatoms, cyanobacteria, coccolithophores, and chlorophytes) at a global scale for the period 1998–2012. We related these trends in phytoplankton to physical conditions (surface temperature, surface photosynthetically available radiation (PAR), and mixed layer depth (MLD)) and nutrients (iron, silicate, and nitrate). We found a significant global decline in diatoms (−1.22% yr−1, p < 0.05). This trend was associated with a significant (p < 0.05) shallowing of the MLD (−0.20% yr−1), a significant increase in PAR (0.09% yr−1), and a significant decline in nitrate (−0.38% yr−1). The global decline in diatoms was mostly attributed to their decline in the North Pacific (−1.00% yr−1, p < 0.05), where the MLD shallowed significantly and resulted in a decline in all three nutrients (p < 0.05). None of the other phytoplankton groups exhibited a significant change globally, but regionally there were considerable significant trends. A decline in nutrients in the northernmost latitudes coincided with a significant decline in diatoms (North Pacific, −1.00% yr−1) and chlorophytes (North Atlantic, −9.70% yr−1). In the northern midlatitudes (North Central Pacific and Atlantic) where nutrients were more scarce, a decline in nutrients was associated with a decline in smaller phytoplankton: cyanobacteria declined significantly in the North Central Pacific (−0.72% yr−1) and Atlantic (−1.56% yr−1), and coccolithophores declined significantly in the North Central Atlantic (−2.06% yr−1). These trends represent the diversity and complexity of mechanisms that drives phytoplankton communities to adapt to variable conditions of nutrients, light, and mixed layer depth. These results provide a first insight into the existence of trends in phytoplankton composition over the maturing satellite ocean color era and illustrate how changes in the conditions of the oceans in the last ~15 years may have affected them.

Improvements in coverage frequency of ocean color: combining data from SeaWiFS and MODIS

Large improvements in coverage frequency (daily to four-day) can be expected by combining ocean color data from the Sea-Viewing Wide Field Of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectrometer (MODIS) missions. Results indicated 40-47% increases in global coverage over SeaWiFS alone in one day and >100% in low latitudes. The missions are highly complementary for observation of short-term processes.