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This article chronicles the 50-year history of tsunami research and development at the NOAA Pacific Marine Environmental Laboratory (PMEL), beginning with the merger in 1973 of the Joint Tsunami Research Effort and PMEL. It traces the development of instrumentation and modeling that brought a better understanding of tsunamis and improved warning systems. The advantage of having observational engineering and flooding modeling under one roof are highlighted. Deep-ocean Assessment and Reporting of Tsunami (DART) research and development led to technology transfer to NOAA’s National Data Buoy Center (NDBC) that now operates and maintains 39 buoys and serves as real-time data distributor for other nations. This technology was also patented and licensed by PMEL to meet the needs of the international community. DART licensee Science Applications International Corporation (SAIC) has manufactured over 60 buoys for eight different countries. DART data are essential for accurate tsunami warnings, so the global society benefits by receiving lifesaving information before the arrival of a tsunami. PMEL’s tsunami flooding modeling research led to technology transfer to NOAA’s tsunami warning centers, the National Tsunami Hazard Mitigation Program, and international tsunami preparedness communities. Short-term flooding modeling research was initiated at PMEL to improve NOAA tsunami warning operations to better serve US coastal communities. The same validated modeling technology was then applied to produce hazard maps for coastal communities in the United States and internationally through the United Nations’ Intergovernmental Oceanographic Commission (IOC). Tsunami hazard maps are an essential first step in preparing a community for the next tsunami. Using these maps and other preparedness criteria, a community can become “Tsunami Ready” for the next event. Tsunami Ready has been adopted by the IOC as the global standard for preparedness of at-risk communities with total populations exceeding 890 million people. 

NOAA Pacific Marine Environmental Laboratory’s (PMEL’s) approach to tsunami research is unique among such laboratories in that tsunami observations and modeling are under one roof, offering the advantages of enhancing the speed and lowering the cost of developments. Here, we chronicle the history of the transfer of deep-ocean observational and flooding modeling technologies within and outside of NOAA and provide a case study for future transfers. PMEL and partners’ efforts in transferring tsunami technology have been very successful, resulting in improved protection of global communities with high tsunami risk while enhancing the new blue economy. The transfer of observational technology within NOAA required years of effort, while the transfer outside of NOAA only required a patent and license agreement. During the transfer process, three additional generations of observational technologies were created. The transfer of tsunami flooding modeling technology required a validation process for transfer into NOAA operations and an international training program to allow access to the technology by other countries. During this model development, a web-based product was created to simplify the use of and access to these models for both real-time and hazard assessment applications. We present lessons learned from these transfers, including the need for support as long as the technology is in use. The tsunami transfer process created a wealth of economic expansion while protecting coastal citizens from future tsunamis. 

The NOAA Pacific Marine Environmental Laboratory (PMEL) Ocean Climate Stations (OCS) project provides in situ measurements for quantifying air-sea interactions that couple the ocean and atmosphere. The project maintains two OceanSITES surface moorings in the North Pacific, one at the Kuroshio Extension Observatory in the Northwest Pacific subtropical recirculation gyre and the other at Station Papa in the Northeast Pacific subpolar gyre. OCS mooring time series are used as in situ references for assessing satellite and numerical weather prediction models. A spinoff of the PMEL Tropical Atmosphere Ocean (TAO) project, OCS moorings have acted as “research aggregating devices.” Working with and attracting wide-ranging partners, OCS scientists have collected process-oriented observations of variability on diurnal, synoptic, seasonal, and interannual timescales associated with anthropogenic climate change. Since 2016, they have worked to expand, test, and verify the observing capabilities of uncrewed surface vehicles and to develop observing strategies for integrating these unique, wind-powered observing platforms within the tropical Pacific and global ocean observing system. PMEL OCS has been at the center of the UN Decade of Ocean Sciences for Sustainable Development (2021–2030) effort to develop an Observing Air-Sea Interactions Strategy (OASIS) that links an expanded network of in situ air-sea interaction observations to optimized satellite observations, improved ocean and atmospheric coupling in Earth system models, and ultimately improved ocean information across an array of essential climate variables for decision-makers. This retrospective highlights not only achievements of the PMEL OCS project but also some of its challenges. 

This dataset consists of the Surface Ocean CO2 Atlas Version 2022 (SOCATv2022) data product files. The ocean absorbs one quarter of the global CO2 emissions from human activity. The community-led Surface Ocean CO2 Atlas (www.socat.info) is key for the quantification of ocean CO2 uptake and its variation, now and in the future. SOCAT version 2022 has quality-controlled in situ surface ocean fCO2 (fugacity of CO2) measurements on ships, moorings, autonomous and drifting surface platforms for the global oceans and coastal seas from 1957 to 2021. The main synthesis and gridded products contain 33.7 million fCO2 values with an estimated accuracy of better than 5 μatm. A further 6.4 million fCO2 sensor data with an estimated accuracy of 5 to 10 μatm are separately available. During quality control, marine scientists assign a flag to each data set, as well as WOCE flags of 2 (good), 3 (questionable) or 4 (bad) to individual fCO2 values. Data sets are assigned flags of A and B for an estimated accuracy of better than 2 μatm, flags of C and D for an accuracy of better than 5 μatm and a flag of E for an accuracy of better than 10 μatm. Bakker et al. (2016) describe the quality control criteria used in SOCAT versions 3 to 2022. Quality control comments for individual data sets can be accessed via the SOCAT Data Set Viewer (www.socat.info). All data sets, where data quality has been deemed acceptable, have been made public. The main SOCAT synthesis files and the gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Access to data sets with an estimated accuracy of 5 to 10 (flag of E) and fCO2 values with flags of 3 and 4 is via additional data products and the Data Set Viewer (Table 8 in Bakker et al., 2016). SOCAT publishes a global gridded product with a 1° longitude by 1° latitude resolution. A second product with a higher resolution of 0.25° longitude by 0.25° latitude is available for the coastal seas. The gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Gridded products are available monthly, per year and per decade. Two powerful, interactive, online viewers, the Data Set Viewer and the Gridded Data Viewer (www.socat.info), enable investigation of the SOCAT synthesis and gridded data products. SOCAT data products can be downloaded. Matlab code is available for reading these files. Ocean Data View also provides access to the SOCAT data products (www.socat.info). SOCAT data products are discoverable, accessible and citable. The SOCAT Data Use Statement (www.socat.info) asks users to generously acknowledge the contribution of SOCAT scientists by invitation to co-authorship, especially for data providers in regional studies, and/or reference to relevant scientific articles. The SOCAT website (www.socat.info) provides a single access point for online viewers, downloadable data sets, the Data Use Statement, a list of contributors and an overview of scientific publications on and using SOCAT. Automation of data upload and initial data checks allows annual releases of SOCAT from version 4 onwards. SOCAT is used for quantification of ocean CO2 uptake and ocean acidification and for evaluation of climate models and sensor data. SOCAT products inform the annual Global Carbon Budget since 2013. The annual SOCAT releases by the SOCAT scientific community are a Voluntary Commitment for United Nations Sustainable Development Goal 14.3 (Reduce Ocean Acidification) (#OceanAction20464). More broadly the SOCAT releases contribute to UN SDG 13 (Climate Action) and SDG 14 (Life Below Water), and to the UN Decade of Ocean Science for Sustainable Development. Hundreds of peer-reviewed scientific publications and high-impact reports cite SOCAT. The SOCAT community-led synthesis product is a key step in the value chain based on in situ inorganic carbon measurements of the oceans, which provides policy makers with critical information on ocean CO2 uptake in climate negotiations. The need for accurate knowledge of global ocean CO2 uptake and its (future) variation makes sustained funding of in situ surface ocean CO2 observations imperative.