ALBERT

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in [citation], doi:[doi]. Frajka-Williams, E., Ansorge, I. J., Baehr, J., Bryden, H. L., Chidichimo, M. P., Cunningham, S. A., Danabasoglu, G., Dong, S., Donohue, K. A., Elipot, S., Heimbach, P., Holliday, N. P., Hummels, R., Jackson, L. C., Karstensen, J., Lankhorst, M., Le Bras, I. A., Lozier, M. S., McDonagh, E. L., Meinen, C. S., Mercier, H., Moat, B., I., Perez, R. C., Piecuch, C. G., Rhein, M., Srokosz, M. A., Trenberth, K. E., Bacon, S., Forget, G., Goni, G., Kieke, D., Koelling, J., Lamont, T., McCarthy, G. D., Mertens, C., Send, U., Smeed, D. A., Speich, S., van den Berg, M., Volkov, D., & Wilson, C. Atlantic meridional overturning circulation: Observed transport and variability. Frontiers in Marine Science, 6, (2019): 260, doi:10.3389/fmars.2019.00260.

Description: The Atlantic Meridional Overturning Circulation (AMOC) extends from the Southern Ocean to the northern North Atlantic, transporting heat northwards throughout the South and North Atlantic, and sinking carbon and nutrients into the deep ocean. Climate models indicate that changes to the AMOC both herald and drive climate shifts. Intensive trans-basin AMOC observational systems have been put in place to continuously monitor meridional volume transport variability, and in some cases, heat, freshwater and carbon transport. These observational programs have been used to diagnose the magnitude and origins of transport variability, and to investigate impacts of variability on essential climate variables such as sea surface temperature, ocean heat content and coastal sea level. AMOC observing approaches vary between the different systems, ranging from trans-basin arrays (OSNAP, RAPID 26°N, 11°S, SAMBA 34.5°S) to arrays concentrating on western boundaries (e.g., RAPID WAVE, MOVE 16°N). In this paper, we outline the different approaches (aims, strengths and limitations) and summarize the key results to date. We also discuss alternate approaches for capturing AMOC variability including direct estimates (e.g., using sea level, bottom pressure, and hydrography from autonomous profiling floats), indirect estimates applying budgetary approaches, state estimates or ocean reanalyses, and proxies. Based on the existing observations and their results, and the potential of new observational and formal synthesis approaches, we make suggestions as to how to evaluate a comprehensive, future-proof observational network of the AMOC to deepen our understanding of the AMOC and its role in global climate.

Description: OSNAP is funded by the US National Science Foundation (NSF, OCE-1259013), UK Natural Environment Research Council (NERC, projects: OSNAP NE/K010875/1, Extended Ellett Line and ACSIS); China's national key research and development projects (2016YFA0601803), the National Natural Science Foundation of China (41521091 and U1606402) and the Fundamental Research Funds for the Central Universities (201424001); the German Ministry BMBF (RACE program); Fisheries and Oceans Canada (DFO: AZOMP). Additional support was received from the European Union 7th Framework Programme (FP7 2007–2013: NACLIM 308299) and the Horizon 2020 program (Blue-Action 727852, ATLAS 678760, AtlantOS 633211), and the French Centre National de la Recherche Scientifique (CNRS). RAPID and MOCHA moorings at 26°N are funded by NERC and NSF (OCE1332978). ABC fluxes is funded by the NERC RAPID-AMOC program (grant number: NE/M005046/1). Florida Current cable array is funded by the US National Oceanic and Atmospheric Administration (NOAA). The Meridional Overturning Variability Experiment (MOVE) was funded by the NOAA Climate Program Office-Ocean Observing and Monitoring Division, and initially by the German Federal Ministry of Education and Research (BMBF). SAMBA 34.5°S is funded by the NOAA Climate Program Office-Ocean Observing and Monitoring Division (100007298), the French SAMOC project (11–ANR-56-004), from Brazilian National Council for Scientific and Technological development (CNPq: 302018/2014-0) and Sao Paulo Research Foundation (FAESP: SAMOC-Br grants 2011/50552-4 and 2017/09659-6), the South African DST-NRF-SANAP program and South African Department of Environmental Affairs. The Line W project was funded by NSF (grant numbers: OCE-0726720, 1332667, and 1332834), with supplemental contributions from Woods Hole Oceanographic Institution (WHOI)'s Ocean and Climate Change Institute. The Oleander Program is funded by NOAA and NSF (grant numbers: OCE1536517, OCE1536586, OCE1536851). The 47°N array NOAC is funded by the BMBF (grant numbers: 03F0443C, 03F0605C, 03F0561C, 03F0792A). The Senate Commission of Oceanography from the DFG granted shiptime and costs for travel, transports and consumables. JB's work is funded by DFG under Germany's Excellence Strategy (EXC 2037 Climate, Climatic Change, and Society, Project Number: 390683824), contribution to the Center for Earth System Research and Sustainability (CEN) of Universitat Hamburg. LCJ was funded by the Copernicus Marine Environment Monitoring Service (CMEMS: 23-GLO-RAN LOT 3). MSL was supported by the Overturning in the Subpolar North Atlantic Program (NSF grant: OCE-1259013). GDM was supported by the Blue-Action project (European Union's Horizon 2020 research and innovation programme, grant number: 727852). HM was supported by CNRS. RH acknowledges financial support by the BMBF as part of the cooperative projects RACE (03F0605B, 03F0824C). The National Centre for Atmospheric Research (NCAR) is sponsored by NSF under Cooperative Agreement No. 1852977. JKO was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program (Grant NNX16AO39H).

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Subramanian, A. C., Balmaseda, M. A., Centurioni, L., Chattopadhyay, R., Cornuelle, B. D., DeMott, C., Flatau, M., Fujii, Y., Giglio, D., Gille, S. T., Hamill, T. M., Hendon, H., Hoteit, I., Kumar, A., Lee, J., Lucas, A. J., Mahadevan, A., Matsueda, M., Nam, S., Paturi, S., Penny, S. G., Rydbeck, A., Sun, R., Takaya, Y., Tandon, A., Todd, R. E., Vitart, F., Yuan, D., & Zhang, C. Ocean observations to improve our understanding, modeling, and forecasting of subseasonal-to-seasonal variability. Frontiers in Marine Science, 6, (2019): 427, doi:10.3389/fmars.2019.00427.

Description: Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an important source of information for S2S forecasts. However, the subsurface ocean is challenging to observe, because it cannot be measured by satellite. Subsurface ocean observing systems relevant for understanding, modeling, and forecasting on S2S timescales will continue to evolve with the improvement in technological capabilities. The community must focus on designing and implementing low-cost, high-value surface and subsurface ocean observations, and developing forecasting system capable of extracting their observation potential in forecast applications. S2S forecasts will benefit significantly from higher spatio-temporal resolution data in regions that are sources of predictability on these timescales (coastal, tropical, and polar regions). While ENSO has been a driving force for the design of the current observing system, the subseasonal time scales present new observational requirements. Advanced observation technologies such as autonomous surface and subsurface profiling devices as well as satellites that observe the ocean-atmosphere interface simultaneously can lead to breakthroughs in coupled data assimilation (CDA) and coupled initialization for S2S forecasts. These observational platforms should also be tested and evaluated in ocean observation sensitivity experiments with current and future generation CDA and S2S prediction systems. Investments in the new ocean observations as well as model and DA system developments can lead to substantial returns on cost savings from disaster mitigation as well as socio–economic decisions that use S2S forecast information.

Description: AS was funded by NOAA Climate Variability and Prediction Program (NA14OAR4310276) and the NSF Earth System Modeling Program (OCE1419306). CD was funded by NA16OAR4310094. SG and DG were funded by NASA awards NNX14AO78G and 80NSSC19K0059. DY was supported by NSFC (91858204, 41720104008, and 41421005).

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Roemmich, D., Alford, M. H., Claustre, H., Johnson, K., King, B., Moum, J., Oke, P., Owens, W. B., Pouliquen, S., Purkey, S., Scanderbeg, M., Suga, T., Wijffels, S., Zilberman, N., Bakker, D., Baringer, M., Belbeoch, M., Bittig, H. C., Boss, E., Calil, P., Carse, F., Carval, T., Chai, F., Conchubhair, D. O., d'Ortenzio, F., Dall'Olmo, G., Desbruyeres, D., Fennel, K., Fer, I., Ferrari, R., Forget, G., Freeland, H., Fujiki, T., Gehlen, M., Greenan, B., Hallberg, R., Hibiya, T., Hosoda, S., Jayne, S., Jochum, M., Johnson, G. C., Kang, K., Kolodziejczyk, N., Kortzinger, A., Le Traon, P., Lenn, Y., Maze, G., Mork, K. A., Morris, T., Nagai, T., Nash, J., Garabato, A. N., Olsen, A., Pattabhi, R. R., Prakash, S., Riser, S., Schmechtig, C., Schmid, C., Shroyer, E., Sterl, A., Sutton, P., Talley, L., Tanhua, T., Thierry, V., Thomalla, S., Toole, J., Troisi, A., Trull, T. W., Turton, J., Velez-Belchi, P. J., Walczowski, W., Wang, H., Wanninkhof, R., Waterhouse, A. F., Waterman, S., Watson, A., Wilson, C., Wong, A. P. S., Xu, J., & Yasuda, I. On the future of Argo: A global, full-depth, multi-disciplinary array. Frontiers in Marine Science, 6, (2019): 439, doi:10.3389/fmars.2019.00439.

Description: The Argo Program has been implemented and sustained for almost two decades, as a global array of about 4000 profiling floats. Argo provides continuous observations of ocean temperature and salinity versus pressure, from the sea surface to 2000 dbar. The successful installation of the Argo array and its innovative data management system arose opportunistically from the combination of great scientific need and technological innovation. Through the data system, Argo provides fundamental physical observations with broad societally-valuable applications, built on the cost-efficient and robust technologies of autonomous profiling floats. Following recent advances in platform and sensor technologies, even greater opportunity exists now than 20 years ago to (i) improve Argo’s global coverage and value beyond the original design, (ii) extend Argo to span the full ocean depth, (iii) add biogeochemical sensors for improved understanding of oceanic cycles of carbon, nutrients, and ecosystems, and (iv) consider experimental sensors that might be included in the future, for example to document the spatial and temporal patterns of ocean mixing. For Core Argo and each of these enhancements, the past, present, and future progression along a path from experimental deployments to regional pilot arrays to global implementation is described. The objective is to create a fully global, top-to-bottom, dynamically complete, and multidisciplinary Argo Program that will integrate seamlessly with satellite and with other in situ elements of the Global Ocean Observing System (Legler et al., 2015). The integrated system will deliver operational reanalysis and forecasting capability, and assessment of the state and variability of the climate system with respect to physical, biogeochemical, and ecosystems parameters. It will enable basic research of unprecedented breadth and magnitude, and a wealth of ocean-education and outreach opportunities.

Description: DR, MS, and NZ were supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). WO, SJ, and SWi were supported by the US Argo Program through the NOAA Grant NA14OAR4320158 (CINAR). EuroArgo scientists were supported by the two grants: (1) AtlantOS funding by the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement No. 633211 and (2) Monitoring the Oceans and Climate Change with Argo (MOCCA) Co-funded by the European Maritime and Fisheries Fund (EMFF) Project No. SI2.709624. This manuscript represents a contribution to the following research projects for HC, CaS, and FD: remOcean (funded by the European Research Council, grant 246777), NAOS (funded by the Agence Nationale de la Recherche in the frame of the French “Equipement d’avenir” program, grant ANR J11R107-F), AtlantOS (funded by the European Union’s Horizon 2020 Research and Innovation Programme, grant 2014-633211), and the BGC-Argo project funded by the CNES. DB was funded by the EU RINGO project (730944 H2020-INFRADEV-2016-1). RF was supported by the AGS-1835576. GCJ was supported by the Global Ocean Monitoring and Observing Program, National Oceanic and Atmospheric Administration (NOAA), U.S., and the Department of Commerce and NOAA Research. LT was funded under the SOCCOM Grant No. NSF PLR-1425989. VT’s contribution was supported by the French National Research Agency (ANR) through the EQUIPEX NAOS (Novel Argo Observing System) under the reference ANR-10-EQPX-40 and by the European H2020 Research and Innovation Programme through the AtlantOS project under the reference 633211. WW was supported by the Argo Poland program through the Ministry of Sciences and Higher Education Grant No. DIR/WK/2016/12. AmW was funded by the NSF-OCE1434722. K-RK is funded by the National Institute of Meteorological Sciences’ Research and Development Program “Development of Marine Meteorology Monitoring and Next-generation Ocean Forecasting System” under the grant KMA2018-00421. CSchmid is funded by NOAA/AOML and the US Argo Program through NOAA/OOMD. MBa is funded by NOAA/AOML.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Todd, R. E., Chavez, F. P., Clayton, S., Cravatte, S., Goes, M., Greco, M., Ling, X., Sprintall, J., Zilberman, N., V., Archer, M., Aristegui, J., Balmaseda, M., Bane, J. M., Baringer, M. O., Barth, J. A., Beal, L. M., Brandt, P., Calil, P. H. R., Campos, E., Centurioni, L. R., Chidichimo, M. P., Cirano, M., Cronin, M. F., Curchitser, E. N., Davis, R. E., Dengler, M., deYoung, B., Dong, S., Escribano, R., Fassbender, A. J., Fawcett, S. E., Feng, M., Goni, G. J., Gray, A. R., Gutierrez, D., Hebert, D., Hummels, R., Ito, S., Krug, M., Lacan, F., Laurindo, L., Lazar, A., Lee, C. M., Lengaigne, M., Levine, N. M., Middleton, J., Montes, I., Muglia, M., Nagai, T., Palevsky, H., I., Palter, J. B., Phillips, H. E., Piola, A., Plueddemann, A. J., Qiu, B., Rodrigues, R. R., Roughan, M., Rudnick, D. L., Rykaczewski, R. R., Saraceno, M., Seim, H., Sen Gupta, A., Shannon, L., Sloyan, B. M., Sutton, A. J., Thompson, L., van der Plas, A. K., Volkov, D., Wilkin, J., Zhang, D., & Zhang, L. Global perspectives on observing ocean boundary current systems. Frontiers in Marine Science, 6, (2010); 423, doi: 10.3389/fmars.2019.00423.

Description: Ocean boundary current systems are key components of the climate system, are home to highly productive ecosystems, and have numerous societal impacts. Establishment of a global network of boundary current observing systems is a critical part of ongoing development of the Global Ocean Observing System. The characteristics of boundary current systems are reviewed, focusing on scientific and societal motivations for sustained observing. Techniques currently used to observe boundary current systems are reviewed, followed by a census of the current state of boundary current observing systems globally. The next steps in the development of boundary current observing systems are considered, leading to several specific recommendations.

Description: RT was supported by The Andrew W. Mellon Foundation Endowed Fund for Innovative Research at WHOI. FC was supported by the David and Lucile Packard Foundation. MGo was funded by NSF and NOAA/AOML. XL was funded by China’s National Key Research and Development Projects (2016YFA0601803), the National Natural Science Foundation of China (41490641, 41521091, and U1606402), and the Qingdao National Laboratory for Marine Science and Technology (2017ASKJ01). JS was supported by NOAA’s Global Ocean Monitoring and Observing Program (Award NA15OAR4320071). DZ was partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063. BS was supported by IMOS and CSIRO’s Decadal Climate Forecasting Project. We gratefully acknowledge the wide range of funding sources from many nations that have enabled the observations and analyses reviewed here.