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Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(11), (2020): E1891-E1913, https://doi.org/10.1175/BAMS-D-19-0209.1, The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2., We thank the World Climate Research Programme (WCRP) and its core project on Climate and Ocean: Variability, Predictability and Change (CLIVAR), the Indian Ocean Global Ocean Observing System (IOGOOS), the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), the Integrated Marine Biosphere Research (IMBeR) project, the U.S. National Oceanic and Atmospheric Administration (NOAA), and the International Union of Geodesy and Geophysics (IUGG) for providing the financial support to bring international scientists together to conduct this review. We thank the members of the independent review board that provided detailed feedbacks on the review report that is summarized in this article: P. E. Dexter, M. Krug, J. McCreary, R. Matear, C. Moloney, and S. Wijffels. PMEL Contribution 5041. C. Ummenhofer acknowledges support from The Andrew W. Mellon Foundation Award for Innovative Research., 2021-05-01

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jacox, M. G., Alexander, M. A., Siedlecki, S., Chen, K., Kwon, Y., Brodie, S., Ortiz, I., Tommasi, D., Widlansky, M. J., Barrie, D., Capotondi, A., Cheng, W., Di Lorenzo, E., Edwards, C., Fiechter, J., Fratantoni, P., Hazen, E. L., Hermann, A. J., Kumar, A., Miller, A. J., Pirhalla, D., Buil, M. P., Ray, S., Sheridan, S. C., Subramanian, A., Thompson, P., Thorne, L., Annamalai, H., Aydin, K., Bograd, S. J., Griffis, R. B., Kearney, K., Kim, H., Mariotti, A., Merrifield, M., & Rykaczewski, R. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, 183, (2020): 102307, doi:10.1016/j.pocean.2020.102307., Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant., This study was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program through grants NA17OAR4310108, NA17OAR4310112, NA17OAR4310111, NA17OAR4310110, NA17OAR4310109, NA17OAR4310104, NA17OAR4310106, and NA17OAR4310113. This paper is a product of the NOAA/MAPP Marine Prediction Task Force.

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hermes, J. C., Masumoto, Y., Beal, L. M., Roxy, M. K., Vialard, J., Andres, M., Annamalai, H., Behera, S., D'Adamo, N., Doi, T., Peng, M., Han, W., Hardman-Mountford, N., Hendon, H., Hood, R., Kido, S., Lee, C., Lees, T., Lengaigne, M., Li, J., Lumpkin, R., Navaneeth, K. N., Milligan, B., McPhaden, M. J., Ravichandran, M., Shinoda, T., Singh, A., Sloyan, B., Strutton, P. G., Subramanian, A. C., Thurston, S., Tozuka, T., Ummenhofer, C. C., Unnikrishnan, A. S., Venkatesan, R., Wang, D., Wiggert, J., Yu, L., & Yu, W. (2019). A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs. Frontiers in Marine Science, 6, (2019): 355, doi: 10.3389/fmars.2019.00355., The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientificand societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS., This work was supported by the PMEL contribution no. 4934.