Contributors | Affiliation | Role |
---|---|---|
Bates, Nicholas | Bermuda Institute of Ocean Sciences (BIOS) | Principal Investigator |
Johnson, Rodney J. | Bermuda Institute of Ocean Sciences (BIOS) | Co-Principal Investigator |
Lomas, Michael W. | Bigelow Laboratory for Ocean Sciences | Co-Principal Investigator |
Carlson, Craig A. | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Davey, Emily | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Derbyshire, Lucinda | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Garley, Rebecca | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Lomas, Debra | Bigelow Laboratory for Ocean Sciences | Scientist |
May, Rebecca | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Medley, Claire | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Stuart, Emma | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Lethaby, Paul J. | Bermuda Institute of Ocean Sciences (BIOS) | Data Manager |
Smith, Dominic | Bermuda Institute of Ocean Sciences (BIOS) | Data Manager |
Gerlach, Dana Stuart | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Mickle, Audrey | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
BATS Validation Cruises
Following the first several years of the BATS project it was deemed necessary by the JGOFS steering committee and BATS PI’s to conduct validation cruises in the vicinity of the nominal BATS site to better understand the mesoscale and larger scale variability of the region. In particular, a focus of the BVAL cruises was to assess the spatial scale representation of the BATS and Hydrostation ‘S’ programs. Initial focus of the BVAL cruises was to investigate mesoscale variability and meridional gradients of the local region. Later, cruises focused on specific mesoscale eddies (e.g., Mcgillicuddy et al., 1998; McGillicuddy et al., 1999) and effects of tropical cyclones through the local region.
In 2000 it was deemed more important to document the larger scale changes in the North Atlantic Subtropical gyre and BVAL cruises established a transect line from ~ 35N to 19N (Bermuda to Puerto Rico) very similar to the WOCE A22 repeat hydrography line (Johnson et al., 2020). These annual Bermuda to Puerto Rico transects have been run since 2000 and target stations at every one degree of latitude and typically have been conducted in September/October of each year to capture maximal heat content in the upper ocean. However, since this timeframe coincides with high tropical cyclone activity the cruises were reluctantly (as of 2022) moved to start in June/July of each year for safety and operational reasons. In the pentad prior to 2022 every BVAL cruise was significantly impacted but multiple tropical cyclones. Parameters presented are the same as provided in the standard BATS bottle files.
Data were collected on BVAL cruises from April 1991 (BVAL cruise #50001) through June/July 2024 (BVAL cruise #50061). Research was conducted on the R/V Weatherbird II through 2005 and thereafter on the R/V Atlantic Explorer. There were numerous Chief Scientists for these cruises including Rachel Dow, Anthony Michaels, Kjell Gundersen, Rodney Johnson, Paul Lethaby, Mike Lomas, Steven Bell, Gwyn Evans, Claire Medley, and Dominic Smith.
Water sampling
Full depth water sampling and data collection at the BATS site are achieved with a total of three hydrocasts using a General Oceanics Intelligent Rosette® with an array of 24 12L water bottles and a Sea-Bird Scientific CTD system. Water samples are collected during the upcast with a 1-minute resting period between reaching the sampling depth and triggering the bottle to close. Bottom measurements/ sampling are achieved within 20 meters from the bottom, as determined using an altimeter.
Water samples are taken right after Rosette® recovery. On any cast, if only a single water bottle is collected to sample all biogeochemical parameters, then gas samples are collected first due to their exposure to air when opened. However, if enough bottles are available, two bottles can be taken for a single depth. Water is usually split between large-volume particulate samples (POCN, HPLC, POP and PSi) and all other small volume samples, including gas samples. When two bottles are taken for a single depth, particulate samples are collected first to prevent settling within the Niskin bottle. Samples are fixed or frozen once all same-sample bottles from one cast have been collected. Particulate samples are filtered as soon as collected.
Nutrients
The BATS nutrient methodology is based on the Protocols for the Joint Global Ocean Flux Study (JGOFS) Core Measurements (Intergovernmental Oceanographic Commission, 1994) which describes the method for the determination of dissolved inorganic macronutrients in seawater: nitrite (NO2 – ), nitrate + nitrite (NO3 – + NO2 – ), orthophosphate (PO4 3 – ) and reactive silicate (Si(OH)4) using Continuous Flow Analysis (CFA).
While the definition of the dissolved fraction has changed throughout the years that the BATS time series has operated, the pore size used has remained constant in order to create a comparable temporal dataset. While similar studies in oligotrophic ocean regions have opted to forego the use of nutrient filters under the assumption that the particulate nutrient pool is negligible, we continue the use of filters for the sake of continuity. Sample filtration also removes the potential for turbidity-derived uncertainties during analysis, and may aid preservation of frozen samples.
Discrete samples are collected at the Bermuda Atlantic Time-series Study (BATS) site from surface to bottom depths (∼4,200 meters). Sea water is filtered directly from the Niskin spigot using a 0.8 µm membrane to remove particulates. Collected sea water is preserved by freezing until analysis. Replicate samples are taken during each cast to ensure quality control standards are met during analytical and data processes. Dissolved inorganic nutrients are measured using a SEAL AA500 Autoanalyzer by Continuous Flow Analysis (CFA). During this process, a subset of sample is drawn and further split into four different channels driven by a peristaltic pump. The sample stream is segmented with air or nitrogen bubbles throughout the flow path to enhance the mixing of reagents with the sample. The nutrients, NO2-, nitrate + nitrite (NO3– + NO2-) , PO43– and Si, are chemically reacted in the separate channels to produce a color change and are measured colorimetrically at different wavelengths using a flow-through colorimeter located at the end of the flow path. The light absorption by the sample-reagent mixture is proportional to the concentration of nutrient in the sample according to the principles of the Beer-Lambert Law. Raw absorbance units are converted into nutrient concentrations according to a linear calibration curve formulated from known standards.
Bacterial enumeration
In addition to the casts for shallow water, mode water, and deep water, a separate cast is deployed for the estimation of bacterial growth rates using 3H-thymidine. Heterotrophic bacteria are expected to grow and assimilate 3H-thymidine into nucleic acid material under incubation conditions.
Three replicate samples from the same depth are used as live tubes for thymidine incorporation, and are incubated for four hours. Samples used as killed controls (aka kill tubes) are treated with 100 microliters of 100% TCA (trichloroacetic acid) at the beginning of the incubation to halt biological activity. After incubation, 10 microliters (µl) from the live tubes are extracted for Specific Activities measurements and the biological activity in the live tubes is halted by adding 100% TCA.
All tubes are centrifuged at 14,000 RPM at 4°C for 7 minutes. The supernatant is discarded and DNA is extracted by adding 100% TCA; centrifuging again for 7 minutes at 4°C at 14,000 RPM; adding 80% ethanol and centrifuging once more for 7 minutes at 4°C at 14,000 RPM. The DNA in the resulting pellet is resuspended in Ultima Gold by vortexing. Samples are stored at room temperature until analysis.
Full methodology
Detailed methods are available in Knap et al. (1997).
Data processing steps are outlined in the BATS Methods Manual.
- imported "bval_bottle_v006.txt" and "bval_bottle_qcmask_v006.txt" into BCO-DMO system
m using missing data identifiers 'nd' and '-999'.
- joined "bval_bottle_qcmask_v006.txt" and "bval_bottle_v006.txt" to add flag columns for the parameters
- converted longitude values to decimal degrees (degrees West are negative)
- converted date to ISO yyyy-mm-dd format
- combine date and time to create ISO UTC timestamp
- added Cruise_type, Cruise_num, Cast, Cast_type, and Bottle_number columns (extracted from ID column)
- added vessel names as defined in "bval_pigments_v006.txt"
- added cast types as defined in "bval_pigments_v006.txt"
- modified parameter names to conform with BCO-DMO naming conventions and to be more consistent with other BATS data submissions
- renamed parameters from mask file to reflect parameter names from data file
Version Notes:
- Oxygen fix temperature and oxygen anomaly are no longer included
- Authors added and order adjusted
- Data from 50061 included
- Extents updated
- See release notes for more information
Parameter | Description | Units |
ID | A unique bottle ID which identifies cruise, cast, and Niskin number | unitless |
ISO_DateTime_UTC | Sampling date in ISO8601 format | unitless |
Vessel | Name of vessel used for cruise | unitless |
Latitude | Latitude of sampling | decimal degrees |
Longitude | Longitude of sampling | decimal degrees |
Cruise_type | Cruise type (BATS Validation) | unitless |
Cruise_num | Cruise number where the 5 represents a BATS Validation cruise followed by the BATS cruise ID | unitless |
Cast_type | Cast type (CTD or Hydrocast) | unitless |
Cast_num | Cast number where 1-80 are CTD casts and 81-99 are Hydrocasts | unitless |
Bottle_num | Niskin (or GoFlo) bottle number | unitless |
QF_Niskin_GoFlo | Quality flag for bottle (-3 = suspect, 1 = unverified, 2 = verified/acceptable) | unitless |
Depth | Depth of sampling | meters (m) |
QF1_Depth | Quality flag for depth; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Temp | Temperature (ITS-90 scale) | degrees Celsius |
QF2_Temp | Quality flag for temperature; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
CTD_Sal | CTD Salinity (PSS-78 scale) | PSS-78 |
QF3_CTD_Sal | Quality flag for CTD salinity; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Sal1 | Salinity-1 (PSS-78 scale) | PSS-78 |
QF4_Sal1 | Quality flag for Salinity-1; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Sigma_theta | Sigma-theta potential density | kilogram per cubic meter (kg/m^3) |
QF5_Sigma_theta | Quality flag for sigma-theta; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
O2 | Oxygen-1 | micromole per kilogram (umol/kg) |
QF6_O2 | Quality flag for oxygen; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
DIC | Dissolved inorganic carbon | micromole per kilogram (umol/kg) |
QF7_DIC | Quality flag for DIC (dissolved inorganic carbon); Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Alkalinity | Alkalinity | microequivalents (uequiv) |
QF8_Alkalinity | Quality flag for alkalinity; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
NO3_NO2 | Nitrate + Nitrite | micromole per kilogram (umol/kg) |
QF9_NO3_NO2 | Quality flag for nitrate + nitrite; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
NO2 | Nitrite | micromole per kilogram (umol/kg) |
QF10_NO2 | Quality flag for nitrite; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
PO4 | Phosphate | micromole per kilogram (umol/kg) |
QF11_PO4 | Quality flag for phosphate; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Silicate | Silicate | micromole per kilogram (umol/kg) |
QF12_Silicate | Quality flag for silicate; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
POC | Particulate organic carbon | micrograms per kilogram (ug/kg) |
QF13_POC | Quality flag for POC; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
PON | Particulate organic nitrogen | micrograms per kilogram (ug/kg) |
QF14_PON | Quality flag for PON; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
TOC | Total organic carbon | micromole per kilogram (umol/kg) |
QF15_TOC | Quality flag for TOC; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
TN | Total nitrogen | micromole per kilogram (umol/kg) |
QF16_TN | Quality flag for total nitrogen; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Bact | Bacteria enumeration | cells times 10^8 per kilogram (cells*10^8/kg) |
QF17_Bact | Quality flag for bacteria enumeration; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
POP | Particulate organic phosphorus | micromole per kilogram (umol/kg) |
QF18_POP | Quality flag for POP; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
TDP | Total dissolved phosphorus | nanomole per kilogram (nmol/kg) |
QF19_TDP | Quality flag for TDP; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
SRP | Low-level phosphorus | nanomole per kilogram (nmol/kg) |
QF20_SRP | Quality flag for low-level phosphorus; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Bio_Si | Particulate biogenic silica | micromole per kilogram (umol/kg) |
QF21_Bio_Si | Quality flag for particulate biogenic silica; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Lith_Si | Particulate lithogenic silica | micromole per kilogram (umol/kg) |
QF22_Lith_Si | Quality flag for particulate lithogenic silica; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Prochlorococcus | Prochlorococcus abundance | cells per milliliter (cells/mL) |
QF23_Prochlorococcus | Quality flag for prochlorococcus abundance; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Synechococcus | Synechococcus abundance | cells per milliliter (cells/mL) |
QF24_Synechococcus | Quality flag for synechococcus abundance; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Picoeukaryotes | Picoeukaryote abundance | cells per milliliter (cells/mL) |
QF25_Picoeukaryotes | Quality flag for picoeukaryote abundance; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
Nanoeukaryotes | Nanoeukaryote abundance | cells per milliliter (cells/mL) |
QF26_Nanoeukaryotes | Quality flag for nanoeukaryote abundance; Parameter quality flags defined as 1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data | unitless |
decy | Decimal Year | unitless |
Time | Time in Hour Minute format (hhmm) | unitless |
yyyymmdd | Date in Year Month Day format | unitless |
Dataset-specific Instrument Name | centrifuge |
Generic Instrument Name | Centrifuge |
Dataset-specific Description | All tubes are centrifuged at 14,000 RPM and 4°C for 7 minutes
|
Generic Instrument Description | A machine with a rapidly rotating container that applies centrifugal force to its contents, typically to separate fluids of different densities (e.g., cream from milk) or liquids from solids. |
Dataset-specific Instrument Name | Seabird 911+ |
Generic Instrument Name | CTD Sea-Bird SBE 911plus |
Dataset-specific Description | Samples were collected using a Seabird 911+ |
Generic Instrument Description | The Sea-Bird SBE 911 plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure. The SBE 911 plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 plus and SBE 11 plus is called a SBE 911 plus. The SBE 9 plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 plus and SBE 4). The SBE 9 plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics |
Dataset-specific Instrument Name | Incubation cooler |
Generic Instrument Name | Incubator |
Dataset-specific Description | Incubation coolers are used to hold samples at temperature within ±4°C of their Niskin sampling temperature.
|
Generic Instrument Description | A device in which environmental conditions (light, photoperiod, temperature, humidity, etc.) can be controlled.
Note: we have more specific terms for shipboard incubators (https://www.bco-dmo.org/instrument/629001) and in-situ incubators (https://www.bco-dmo.org/instrument/494). |
Dataset-specific Instrument Name | Niskin bottle |
Generic Instrument Name | Niskin bottle |
Generic Instrument Description | A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc. |
Website | |
Platform | Multiple Vessels |
Start Date | 1991-04-29 |
Description | Following the first several years of the BATS project it was deemed necessary by the JGOFS steering committee and BATS PIs to conduct validation cruises in the vicinity of the nominal BATS site to better understand the mesoscale and larger scale variability of the region. Initial focus of the BVAL cruises was to investigate mesoscale variability and meridional gradients of the local region. Later, cruises focused on specific mesoscale eddies and effects of tropical cyclones through the local region. In the year 2000 it was deemed more important to document the larger scale changes in the North Atlantic Subtropical gyre so BVAL cruises established a transect line from ~ 35N to 19N (Bermuda to Puerto Rico) very similar to the WOCE A22 repeat hydrography line. These annual Bermuda-to-Puerto Rico transects have been run since 2000 and target stations at every one degree of latitude and typically have been conducted in September/October of each year to capture maximal heat content in the upper ocean. However, since this timeframe coincides with high tropical cyclone activity the cruises were reluctantly (as of 2022) moved to begin in June/July of each year for safety and operational reasons. In the pentad prior to 2022 every BVAL cruise was significantly impacted by multiple tropical cyclones. |
A full description of the BATS research program (including links to the processed BATS data) is available from the BATS Web site (see above for Project URL/ Project Website links). Any data contributed from selected ancillary projects are listed (linked) in the 'Datasets Collection' section below.
Collaborative Research: The Bermuda Atlantic Time-series Study: Sustained Biogeochemical, Ecosystem and Ocean Change Observations and Linkages in the North Atlantic (Years 31-35)
Awards OCE-1756105, OCE-1756054, and OCE-1756312)
NSF award abstract
Long-term observations over several decades are a powerful tool for investigating ocean physics, biology, and chemistry, and the response of the oceans to environmental change. The Bermuda Atlantic Time-Series Study, known as BATS, has been running continuously since 1988. The research goals of the BATS program are: (1) to improve our understanding of the time-varying components of the ocean carbon cycle and the cycles of related nutrient elements such as nitrogen, phosphorus, and silicon; and, (2) to identify the relevant physical, chemical and ecosystem properties responsible for this variability. In addition, the BATS program has strong and diverse broader impacts, contributing to the field of ocean sciences by providing high quality ocean observations and data for seagoing scientists and modelers, and a framework through which researchers can conceive and test hypotheses. This award will support the operations of the BATS program for five more years.
The primary BATS research themes are as follows: (1) Quantify the role of ocean-atmosphere coupling and climate variability on air-sea exchange of CO2, and carbon export to the ocean interior; (2) Document trends and the controls on the interannual to decadal scale variability in carbon and nutrient cycles to their coupling in the surface and deep ocean via the Redfield Ratio paradigm; (3) Quantify the response of planktonic community structure and function, and impact on biogeochemical cycles to variability in surface fluxes and dynamical processes; (4) Facilitate development, calibration and validation of next generation oceanographic sensors, tools and technologies; and, (5) Generate a dataset that can be utilized by empiricists, modelers and students. This research integrates ocean physics, chemistry and biology into a framework for understanding oceanic processes and ocean change in the North Atlantic subtropical gyre. The existing 29 years of BATS data provide robust constraints on seasonal and interannual variability, the response of the Sargasso Sea ecosystem to natural climate variability, and signal detection of potential ocean changes. This project would extend the BATS program through years 31-35 to address a series of ten interlinked questions through integrated research approaches and a multitude of collaborative efforts. In addition to the themes above, and embedded into the ten questions and approaches, the BATS team will focus on, for example, coupling of particle production and biogeochemistry; revisiting the complexities of the biological carbon pump; oxygen decline; and changes in the hydrography, physics, ocean carbon cycle and biogeochemistry of the Sargasso Sea. The highest quality data observation and collection will be maintained and used to address these questions. Importantly, a wide range of collaborations at the BATS site, spanning the physical and biogeochemical disciplines, will aid these broad goals. Strong links to community stakeholders, and close collaboration (including methods intercomparisons and personnel exchanges) with the Hawaii Ocean Time-series are proposed. This work will extend the research findings of the project into educational and training opportunities within and beyond the oceanographic community, including training and mentorship of both undergraduate and graduate students.
Please see the BATS Web site (http://bats.bios.edu) for additional information.
The Ocean Carbon and Biogeochemistry (OCB) program focuses on the ocean's role as a component of the global Earth system, bringing together research in geochemistry, ocean physics, and ecology that inform on and advance our understanding of ocean biogeochemistry. The overall program goals are to promote, plan, and coordinate collaborative, multidisciplinary research opportunities within the U.S. research community and with international partners. Important OCB-related activities currently include: the Ocean Carbon and Climate Change (OCCC) and the North American Carbon Program (NACP); U.S. contributions to IMBER, SOLAS, CARBOOCEAN; and numerous U.S. single-investigator and medium-size research projects funded by U.S. federal agencies including NASA, NOAA, and NSF.
The scientific mission of OCB is to study the evolving role of the ocean in the global carbon cycle, in the face of environmental variability and change through studies of marine biogeochemical cycles and associated ecosystems.
The overarching OCB science themes include improved understanding and prediction of: 1) oceanic uptake and release of atmospheric CO2 and other greenhouse gases and 2) environmental sensitivities of biogeochemical cycles, marine ecosystems, and interactions between the two.
The OCB Research Priorities (updated January 2012) include: ocean acidification; terrestrial/coastal carbon fluxes and exchanges; climate sensitivities of and change in ecosystem structure and associated impacts on biogeochemical cycles; mesopelagic ecological and biogeochemical interactions; benthic-pelagic feedbacks on biogeochemical cycles; ocean carbon uptake and storage; and expanding low-oxygen conditions in the coastal and open oceans.
The United States Joint Global Ocean Flux Study was a national component of international JGOFS and an integral part of global climate change research.
The U.S. launched the Joint Global Ocean Flux Study (JGOFS) in the late 1980s to study the ocean carbon cycle. An ambitious goal was set to understand the controls on the concentrations and fluxes of carbon and associated nutrients in the ocean. A new field of ocean biogeochemistry emerged with an emphasis on quality measurements of carbon system parameters and interdisciplinary field studies of the biological, chemical and physical process which control the ocean carbon cycle. As we studied ocean biogeochemistry, we learned that our simple views of carbon uptake and transport were severely limited, and a new "wave" of ocean science was born. U.S. JGOFS has been supported primarily by the U.S. National Science Foundation in collaboration with the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration, the Department of Energy and the Office of Naval Research. U.S. JGOFS, ended in 2005 with the conclusion of the Synthesis and Modeling Project (SMP).
Program description text taken from Chapter 1: Introduction from the Global Intercomparability in a Changing Ocean: An International Time-Series Methods Workshop report published following the workshop held November 28-30, 2012 at the Bermuda Institute of Ocean Sciences. The full report is available from the workshop Web site hosted by US OCB: http://www.whoi.edu/website/TS-workshop/home
Decades of research have demonstrated that the ocean varies across a range of time scales, with anthropogenic forcing contributing an added layer of complexity. In a growing effort to distinguish between natural and human-induced earth system variability, sustained ocean time-series measurements have taken on a renewed importance. Shipboard biogeochemical time-series represent one of the most valuable tools scientists have to characterize and quantify ocean carbon fluxes and biogeochemical processes and their links to changing climate (Karl, 2010; Chavez et al., 2011; Church et al., 2013). They provide the oceanographic community with the long, temporally resolved datasets needed to characterize ocean climate, biogeochemistry, and ecosystem change.
The temporal scale of shifts in marine ecosystem variations in response to climate change are on the order of several decades. The long-term, consistent and comprehensive monitoring programs conducted by time-series sites are essential to understand large-scale atmosphere-ocean interactions that occur on interannual to decadal time scales. Ocean time-series represent one of the most valuable tools scientists have to characterize and quantify ocean carbon fluxes and biogeochemical processes and their links to changing climate.
Launched in the late 1980s, the US JGOFS (Joint Global Ocean Flux Study; http://usjgofs.whoi.edu) research program initiated two time-series measurement programs at Hawaii and Bermuda (HOT and BATS, respectively) to measure key oceanographic measurements in oligotrophic waters. Begun in 1995 as part of the US JGOFS Synthesis and Modeling Project, the CARIACO Ocean Time-Series (formerly known as the CArbon Retention In A Colored Ocean) Program has studied the relationship between surface primary production, physical forcing variables like the wind, and the settling flux of particulate carbon in the Cariaco Basin.
The objective of these time-series effort is to provide well-sampled seasonal resolution of biogeochemical variability at a limited number of ocean observatories, provide support and background measurements for process-oriented research, as well as test and validate observations for biogeochemical models. Since their creation, the BATS, CARIACO and HOT time-series site data have been available for use by a large community of researchers.
Data from those three US funded, ship-based, time-series sites can be accessed at each site directly or by selecting the site name from the Projects section below.
Funding Source | Award |
---|---|
NSF Division of Ocean Sciences (NSF OCE) | |
NSF Division of Ocean Sciences (NSF OCE) |