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. | Bermuda Institute of Ocean Sciences (BIOS) | Co-Principal Investigator |
Lethaby, Paul J. | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Lomas, Debra | Bigelow Laboratory for Ocean Sciences | Scientist |
Smith, Dominic | Bermuda Institute of Ocean Sciences (BIOS) | Scientist |
Davey, Emily | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
Derbyshire, Lucinda | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
Garley, Rebecca | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
May, Rebecca | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
Medley, Claire | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
Stuart, Emma | Bermuda Institute of Ocean Sciences (BIOS) | Technician |
Gerlach, Dana Stuart | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Discrete bottle data collected at the Bermuda Atlantic Time Time-series Study site in the Sargasso Sea during BATS cruises #1 (October 1988) through #416 (June 2024).
Water samples were collected at the Bermuda Atlantic Time-series Study (BATS) site located 80 km southeast of Bermuda (31°40N, 64°10W) in the Sargasso Sea. Measurements were collected monthly and often biweekly during the core monthly BATS cruises and the BATS Bloom cruises (Feb to April) following the methods of Knap et al. (1997).
All bottle fires are included in this dataset, even those that do not have any BATS core parameters, to be of use with other measurements and studies.
Niskin bottles were deployed and accompanying CTD measurements were taken at the depths of water sample collection. Sample parameters include salinity, dissolved oxygen, dissolved inorganic carbon, alkalinity, nutrients (nitrate + nitrite, nitrite, phosphate, silicate), particulate organics (carbon, nitrogen, phosphorous), particulate silicate, total organic carbon and total nitrogen, total dissolved phosphorous, bacterial enumeration, and flow cytometry counts of picoplankton. The HPLC derived phytoplankton pigment data which are collected synoptically with many of the above parameters are reported separately (see https://www.bco-dmo.org/dataset/893521)
Ship information
Research was conducted on many research vessels including:
Numerous chief scientists: Tony Knap, Rachel Dow, Anthony Michaels, Kjell Gundersen, Rodney Johnson, Ann Close, Deborah Steinberg, Paul Lethaby, Julian Mitchell, Vivienne Lochhead, Deborah Lomas, Steven Bell, Jonathan Whitefield, Gwyn Evans, James Sadler, Samuel Monk, Samuel Stevens, Afonso Goncalves, Matt Enright, Fernando Pacheco, Zac Anderson, Claire Medley, and Dominic Smith.
Please see the Supplemental Files section for a listing of the cruises and associated measurements specific to this version of the BATS bottle data (bats_bottle_release_v007_update.txt)
Chapter 3 of the BATS methods manual has details about the steps taken to process and correct the data from the oceanographic sensors. Briefly, temperatures (when the bottles were fired) are extracted from the SeaBird Electronics (SBE) .asc files. Bottle data for each cast is then corrected using static drift/slope corrections based on SBE calibrations.
- Imported data from source file "bats_bottle_v007.txt" into the BCO-DMO data system. Data file imported using missing data identifiers "NA" and -999.
- Imported data from file "bats_bottle_qcmask_v007" into BCO-DMO system. This file is quality flags for the bottle data measurements.
- The 'bottle' and 'mask' files were joined using the keys of bottle ID, date, and time.
- Converted latitude and longitude to decimal degrees.
- Added columns for Cruise type, Cruise number, Cast number, and Bottle number based on the bottle ID
- Zero padded the time column values and then combined with the yyyymmdd time column.
- Converted date and time to ISO8601 format
- Modified parameter (column) names to conform with BCO-DMO naming conventions. The only allowed characters are A-Z,a-z,0-9, and underscores. No spaces, hyphens, commas, parentheses, or Greek letters.
Parameter | Description | Units |
ISO_DateTime_UTC | Date and Time in ISO8601 standard format | unitless |
Bottle_ID | Unique bottle ID which identifies cruise type, cruise, cast, and Niskin bottle number | unitless |
Latitude | Latitude | decimal degrees |
Longitude | Longitude (West is negative) | decimal degrees |
Vessel | Research vessel used for sampling | unitless |
Cruise_ID | Cruise ID where first digit indicates cruise type followed by cruise number | unitless |
Cruise_type | Cruise type (BATS core, BATS Bloom A, or BATS Bloom B) | unitless |
Cruise_num | Cruise number | unitless |
Cast_num | Cast number; 1-80=CTD casts, 81-99=Hydrocasts (i.e. 83 = Data from Hydrocast number 3 | unitless |
Bottle_num | Bottle number of sample | unitless |
QF_bottle | Quality flag for Niskin or Go-Flo bottles (-3 =suspect, 1=unverified, 2=verified/acceptable) | unitless |
Depth | Depth | meters (m) |
QF_Depth | Quality flag for depth (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Temperature | Temperature in ITS-90 standard | degrees Celsius ( °C) |
QF_Temp | Quality flag for Temperature (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
CTD_Salinity | CTD Salinity on PSS-78 scale | dimensionless |
QF_CTD_Sal | Quality flag for CTD salinity (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Salinity | Salinity-1 measurement on PSS-78 scale | dimensionless |
QF_Salinity | Quality flag for Salinity-1 (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Sigma_theta | Sigma-theta measurement | kilograms per cubic meter (kg/m^3) |
QF_Sigma_theta | Quality flag for sigma-theta measurement (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Oxygen_1 | Oxygen-1 | micromoles per kilogram (umol/kg) |
QF_Oxygen | Quality flag for Oxygen-1 measurement (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
CO2 | Dissolved inorganic carbon | micromoles per kilogram (umol/kg) |
QF_DIC | Quality flag for dissolved inorganic carbon (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Alkalinity | Alkalinity | microequivalents |
QF_Alk | Quality flag for Alkalinity (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
NO3_plus_NO2 | Nitrate plus nitrite (NO3+NO2) | micromoles per kilogram (umol/kg) |
QF_NO3_NO2 | Quality flag for nitrate plus nitrite (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
NO2 | Nitrite | micromoles per kilogram (umol/kg) |
QF_NO2 | Quality flag for nitrite (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
PO4 | Phosphate | micromoles per kilogram (umol/kg) |
QF_PO4 | Quality flag for phosphate (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Silicate | Silicate | micromoles per kilogram (umol/kg) |
QF_Silicate | Quality flag for silicate (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
POC | Particulate Organic Carbon | micrograms per kilogram (ug/kg) |
QF_POC | Quality flag for particulate organic carbon (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
PON | Particulate Organic Nitrogen | micrograms per kilogram (ug/kg) |
QF_PON | Quality flag for particulate organic nitrogen (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
TOC | Total Organic Carbon | micromoles per kilogram (umol/kg) |
QF_TOC | Quality flag for total organic carbon (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
TN | Total Nitrogen (prior to BATS 121, DON is reported instead of TN) | micromoles per kilogram (umol/kg) |
QF_TN | Quality flag for total nitrogen (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Bact_Enum | Bacteria enumeration | cells times 10^8 per kilogram |
QF_Bact_enum | Quality flag for bacterial enumeration (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
POP | Particulate Organic Phosphorus | micromoles per kilogram (umol/kg) |
QF_POP | Quality flag for particulate organic phosphorus (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
TDP | Total Dissolved Phosphorus | nanomoles per kilogram (nmol/kg) |
QF_TDP | Quality flag for total dissolved phosphorus (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
SRP | Low-level phosphorus (soluble reactive phosphorus) | nanomoles per kilogram (nmol/kg) |
QF_LLP_SRP | Quality flag for low-level phosphorus (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Bio_Si | Particulate biogenic silica | micromoles per kilogram (umol/kg) |
QF_bio_Si | Quality flag for particulate biogenic silica (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Litho_Si | Particulate lithogenic silica | micromoles per kilogram (umol/kg) |
QF_litho_Si | Quality flag for lithogenic silica (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Prochlorococcus | Prochlorococcus | cells per milliliter (cells/mL) |
QF_Prochloro | Quality flag for prochlorococcus (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Synechococcus | Synechococcus | cells per milliliter (cells/mL) |
QF_Synecho | Quality flag for synechococcus (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Picoeukaryotes | Picoeukaryotes | cells per milliliter (cells/mL) |
QF_Picoeuk | Quality flag for picoeukaryotes (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
Nanoeukaryotes | Nanoeukaryotes | cells per milliliter (cells/mL) |
QF_Nanoeuk | Quality flag for nanoeukaryotes (1= unverified, 2= verified acceptable, 3= questionable, 4= bad, 9= no data) | unitless |
yyyymmdd | Date in year, month, day | unitless |
time | Time in hour, min | unitless |
decimal_year | Decimal Year | unitless |
Dataset-specific Instrument Name | CTD Sea-Bird 911 |
Generic Instrument Name | CTD Sea-Bird 911 |
Generic Instrument Description | The Sea-Bird SBE 911 is a type of CTD instrument package. The SBE 911 includes the SBE 9 Underwater Unit and the SBE 11 Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 and SBE 11 is called a SBE 911. The SBE 9 uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 and SBE 4). The SBE 9 CTD can be configured with 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 | Olympus AX70 Fluoresence Microscope |
Generic Instrument Name | Fluorescence Microscope |
Dataset-specific Description | Bacterial enumeration methods include DAPI stained Epifluoresence Microscopy / Olympus AX70 |
Generic Instrument Description | Instruments that generate enlarged images of samples using the phenomena of fluorescence and phosphorescence instead of, or in addition to, reflection and absorption of visible light. Includes conventional and inverted instruments. |
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 |
Report | |
Start Date | 1988-10-20 |
Description | Bermuda Institute of Ocean Science established the Bermuda Atlantic Time-series Study with the objective of acquiring diverse and detailed time-series data. BATS makes monthly measurements of important hydrographic, biological and chemical parameters throughout the water column at the BATS Study Site, located at 31 40N, 64 10W. |
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) | |
NSF Division of Ocean Sciences (NSF OCE) |