A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT)

A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

Ocean acidification shows negligible impacts on high-latitude bacterial community structure in coastal pelagic mesocosms

The impact of ocean acidification and carbonation on microbial community structure was assessed during a large-scale in situ costal pelagic mesocosm study, included as part of the EPOCA 2010 Arctic campaign. The mesocosm experiment included ambient conditions (fjord) and nine mesocosms with pCO(2) levels ranging from similar to 145 to similar to 1420 mu atm. Samples for the present study were collected at ten time points (t-1, t1, t5, t7, t12, t14, t18, t22, t26 to t28) in seven treatments (ambient fjord (similar to 145), 2x similar to 185, similar to 270, similar to 685, similar to 820, similar to 1050 mu atm) and were analysed for "small" and "large" size fraction microbial community composition using 16S rRNA (ribosomal ribonucleic acid) amplicon sequencing. This high-throughput sequencing analysis produced similar to 20 000 000 16S rRNA V4 reads, which comprised 7000OTUs. The main variables structuring these communities were sample origins (fjord or mesocosms) and the community size fraction (small or large size fraction). The community was significantly different between the unenclosed fjord water and enclosed mesocosms (both control and elevated CO2 treatments) after nutrients were added to the mesocosms, suggesting that the addition of nutrients is the primary driver of the change in mesocosm community structure. The relative importance of each structuring variable depended greatly on the time at which the community was sampled in relation to the phytoplankton bloom. The sampling strategy of separating the small and large size fraction was the second most important factor for community structure. When the small and large size fraction bacteria were analysed separately at different time points, the only taxon pCO(2) was found to significantly affect were the Gammaproteobacteria after nutrient addition. Finally, pCO(2) treatment was found to be significantly correlated (non-linear) with 15 rare taxa, most of which increased in abundance with higher CO2.

Surface Ocean CO2 Atlas (SOCAT) gridded data products

As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions).

Minor impact of ocean acidification to the composition of the active microbial community in an Arctic sediment

Effects of ocean acidification on the composition of the active bacterial and archaeal community within Arctic surface sediment was analysed in detail using 16S rRNA 454 pyrosequencing. Intact sediment cores were collected and exposed to one of five different pCO(2) concentrations [380 (present day), 540, 750, 1120 and 3000 atm] and RNA extracted after a period of 14 days exposure. Measurements of diversity and multivariate similarity indicated very little difference between pCO(2) treatments. Only when the highest and lowest pCO(2) treatments were compared were significant differences evident, namely increases in the abundance of operational taxonomic units most closely related to the Halobacteria and differences to the presence/absence structure of the Planctomycetes. The relative abundance of members of the classes Planctomycetacia and Nitrospira increased with increasing pCO(2) concentration, indicating that these groups may be able to take advantage of changing pH or pCO(2) conditions. The modest response of the active microbial communities associated with these sediments may be due to the low and fluctuating pore-water pH already experienced by sediment microbes, a result of the pH buffering capacity of marine sediments, or due to currently unknown factors. Further research is required to fully understand the impact of elevated CO2 on sediment physicochemical parameters, biogeochemistry and microbial community dynamics.

Variation in ocean colour may help predict cod and haddock recruitment

Characteristics of the spring and fall phytoplankton blooms in spawning areas on the Scotian Shelf, Canada, were estimated from remote sensing data. These blooms, along with anomalies in the North Atlantic Oscillation, were used to explain variation in the recruitment of 4 populations of cod and haddock. We tested the effects of the timing of the bloom using the chlorophyll a (chl a) signal, the maximum amount of chl a, the timing of the diatom bloom, and the maximum relative dominance of diatoms on the recruitment (to Age 1) of cod and haddock on the Scotian Shelf. Models were run separately for the effects of the spring and fall blooms. Only 3 of 10 models tested (0-lag) explained significant (80 to 92%) variation in recruitment. However, the performance of these models was not consistent across populations or species, suggesting that generalities about how spring and fall phytoplankton blooms affect recruitment cannot yet be made. The differences among models suggest that fish larvae are probably adapted locally to food production and thus indirectly to the characteristics of the phytoplankton bloom, which in turn are influenced by regional (meso-scale) oceanographic conditions.

Generalized ocean color inversion model for retrieving marine inherent optical properties

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Real-time sea surface air temperature retrieval over Southern Ocean using AMSR-E data

The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24~(th) -26~(th) Chinese Antarctic Expeditions during 2008-2010. First, Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively.

Atmospheric deposition of methanol over the Atlantic Ocean

In the troposphere, methanol (CH3OH) is present ubiquitously and second in abundance among organic gases after methane. In the surface ocean, methanol represents a supply of energy and carbon for marine microbes. Here we report direct measurements of air-sea methanol transfer along a similar to 10,000-km north-south transect of the Atlantic. The flux of methanol was consistently from the atmosphere to the ocean. Constrained by the aerodynamic limit and measured rate of air-sea sensible heat exchange, methanol transfer resembles a one-way depositional process, which suggests dissolved methanol concentrations near the water surface that are lower than what were measured at similar to 5 m depth, for reasons currently unknown. We estimate the global oceanic uptake of methanol and examine the lifetimes of this compound in the lower atmosphere and upper ocean with respect to gas exchange. We also constrain the molecular diffusional resistance above the ocean surface-an important term for improving air-sea gas exchange models.

Radiolaria: Major exporters of organic carbon to the deep ocean

Very large pulses of particulate organic matter intermittently sink to the deep waters of the open ocean in the Northeast Atlantic. These pulses, measured by moored sediment traps since 1989, can contribute up to 60% of the organic flux to 3000 m in a particular year and are thus a major cause of the variability in carbon sequestration from the atmosphere in the region. Pulses occur in the late summer and are characterized by material that is very rich in organic carbon but with low concentrations of the biominerals opal and calcite. A number of independent lines of evidence have been examined to determine the causes of these pulses: (1) Data from the Continuous Plankton Recorder (CPR) survey show that in this region, radiolarian protozoans intermittently reach high abundances in the late summer just preceding organic pulses to depth. (2) CPR data also show that the interannual variability in radiolarian abundance since 1997 mirrors very closely the variability of deep ocean organic deposition. (3) The settling material collected in the traps displays a strong correlation between fecal pellets produced by radiolaria and the measured organic carbon flux. These all suggest that the pulses are mediated by radiolarians, a group of protozoans found throughout the world’s oceans and which are widely used by paleontologists to determine past climate conditions. Changes in the upper ocean community structure (between years and on longer timescales) may have profound effects on the ability of the oceans to sequester carbon dioxide from the atmosphere.

Estimation of atmospheric nutrient inputs to the Atlantic Ocean from 50°N to 50°S based on large-scale field sampling: Iron and other dust-associated elements

Atmospheric inputs of mineral dust supply iron and other trace metals to the remote ocean and can influence the marine carbon cycle due to iron's role as a potentially limiting micronutrient. Dust generation, transport, and deposition are highly heterogeneous, and there are very few remote marine locations where dust concentrations and chemistry (e.g., iron solubility) are routinely monitored. Here we use aerosol and rainwater samples collected during 10 large-scale research cruises to estimate the atmospheric input of iron, aluminum, and manganese to four broad regions of the Atlantic Ocean over two 3 month periods for the years 2001–2005. We estimate total inputs of these metals to our study regions to be 4.2, 17, and 0.27 Gmol in April–June and 4.9, 14, and 0.19 Gmol in September–November, respectively. Inputs were highest in regions of high rainfall (the intertropical convergence zone and South Atlantic storm track), and rainfall contributed higher proportions of total input to wetter regions. By combining input estimates for total and soluble metals for these time periods, we calculated overall percentage solubilities for each metal that account for the contributions from both wet and dry depositions and the relative contributions from different aerosol types. Calculated solubilities were in the range 2.4%–9.1% for iron, 6.1%–15% for aluminum, and 54%–73% for manganese. We discuss sources of uncertainty in our estimates and compare our results to some recent estimates of atmospheric iron input to the Atlantic.

Understanding the Mechanisms of Cell and Population Responses of Coccolithophores to Changing Ocean Chemistry

The calcifying coccolithophores have been proposed as a potentially vulnerable group in the face of increasing surface ocean CO2 levels. A full understanding of the likely responses of this group requires better mechanistic information on pH- and CO2-sensitive processes that underlie cell function at molecular, cellular and population levels. New findings on the mechanisms of pH homeostasis at a molecular and cellular level in both diatoms and coccolithophores are shaping our understanding of how these important groups may respond or acclimate to changing ocean pH. Critical parameters including intracellular pH homeostasis and cell surface pH will be considered. These studies are being carried out in parallel with genetic studies of natural oceanic populations to assess the natural genetic and physiological diversity that will underlie adaptation of populations in the long term.

The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.