GO-BGC (Global Ocean Biogeochemistry Array). GO-BGC is an NSF Mid-Scale Research Infrastructure (MSRI-2) program to extend Biogeochemical Argo floats with 6 sensors to the global oceans.  It builds on the success of the SOCCOM program in deploying and managing an array of BGC Argo floats in the Southern Ocean. The field programs of the two programs are complementary. As an infrastructure project, GO-BGC’s goal is primarily to build, deploy, and manage 500 floats. GO-BGC is led by principal investigator Ken Johnson (MBARI), co-PIs Lynne Talley (SIO), Steve Riser (UW), Susan Wijffels (WHOI), and Jorge Sarmiento (Princeton U.). At SIO, Sarah Purkey and Todd Martz are senior members of the GO-BGC team.  SIO’s role in GO-BGC is to support Float Deployments for the multi-institutional program, including shipboard support when needed.  Under separate NOPP funding, SIO  developed a BGC Argo float based on the successful SOLO-II Argo float used for core (T/S) Argo. This effort was led by Sarah Purkey overseeing development by the SIO Instrument Development Group; other PIs in the NOPP were myself, Matt Mazloff and Ariane Verdy; Mazloff and Verdy have developed a tropical Pacific state estimate (TPOSE) similar to SOSE (see SOCCOM).

GO-BGC research at SIO includes observing system design. SIO graduate student P. Chamberlain defended his PhD in 2022, with multiple publications. K. Jones is a PhD student who is currently supported by GO-BGC, working on tropical Pacific BGC float observations.

SOCCOM (Southern Ocean Carbon and Climate Observations and Modeling). The primary goal of SOCCOM, which is funded by the NSF Office of Polar Programs, is to improve coupled climate models, to be accomplished through greatly increased understanding and quantification of biogeochemical (carbon) processes in the Southern Ocean. Because of the enormous gaps in Southern Ocean observing, SOCCOM is instrumenting the Southern Ocean with profiling biogeochemical Argo floats, and using a biogeochemical Southern Ocean State Estimate (B-SOSE) to assimilate these and other large data sets. SOCCOM has been led by Jorge Sarmiento (Princeton Univ.), with associate director Ken Johnson (MBARI). The modeling component is led by Joellen Russell (U. Arizona). The observing system is led by Lynne Talley (SIO) and Steve Riser (U. Washington), with support from O. Schofield (Rutgers).  SIO organizes the SOCCOM float deployments and supporting shipboard measurements (SIO STS/ODF and A. Dickson laboratory), and data tracking. B-SOSE is produced by Matt Mazloff and Ariane Verdy (SIO). SIO’s Sarah Gille is a co-PI.  SOCCOM’s funding began in 2014, and will continue through 2024.

SOCCOM research at SIO includes analysis of SOCCOM float data, B-SOSE output, coupled climate model output, and observing system design. Two PhD students are currently associated with the program (B. Taylor, S. Shapiro), and one postdoc (L. Keppler).

U.S. GO-SHIP. The U.S. GO-SHIP Program is a systematic re-occupation of key global hydrographic sections that began in 2003.  It is funded by the NSF Ocean Sciences Division. The sections span all ocean basins and are full-depth, with physical and chemical measurements of the highest ‘reference standard’ accuracy, attainable only with research ships for the foreseeable future. The U.S. program is a major contributor to the international Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP), designed to monitor the ocean’s response to climate change; GO-SHIP is part of the WCRP’s Global Ocean Observing System. SIO academic researchers (L. Talley, S. Purkey, T. Martz) provide project leadership and management. SIO Shipboard Technical Support (Oceanographic Data Facility) has provided the backbone technical support and measurements for U.S. GO-SHIP and predecessor programs since the 1970s.

GO-SHIP research at SIO includes analysis of shipboard hydrographic data and the many ancillary data sets. Each US GO-SHIP cruise has multiple graduate student positions available, and many SIO graduate students have participated on US GO-SHIP cruises, which provide excellent training. Data analysis is funded separately, and many SIO graduate students have incorporated the data sets in their research.