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  • 1
    Publication Date: 2024-04-08
    Description: State of the climate in 2019
    Type: Article , PeerReviewed
    Format: text
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  • 2
    Publication Date: 2024-02-08
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2016-12-13
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 4
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ponte, R. M., Carson, M., Cirano, M., Domingues, C. M., Jevrejeva, S., Marcos, M., Mitchum, G., van de Wal, R. S. W., Woodworth, P. L., Ablain, M., Ardhuin, F., Ballu, V., Becker, M., Benveniste, J., Birol, F., Bradshaw, E., Cazenave, A., De Mey-Fremaux, P., Durand, F., Ezer, T., Fu, L., Fukumori, I., Gordon, K., Gravelle, M., Griffies, S. M., Han, W., Hibbert, A., Hughes, C. W., Idier, D., Kourafalou, V. H., Little, C. M., Matthews, A., Melet, A., Merrifield, M., Meyssignac, B., Minobe, S., Penduff, T., Picot, N., Piecuch, C., Ray, R. D., Rickards, L., Santamaria-Gomez, A., Stammer, D., Staneva, J., Testut, L., Thompson, K., Thompson, P., Vignudelli, S., Williams, J., Williams, S. D. P., Woppelmann, G., Zanna, L., & Zhang, X. Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level. Frontiers in Marine Science, 6, (2019): 437, doi:10.3389/fmars.2019.00437.
    Description: A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.
    Description: RP was funded by NASA grant NNH16CT00C. CD was supported by the Australian Research Council (FT130101532 and DP 160103130), the Scientific Committee on Oceanic Research (SCOR) Working Group 148, funded by national SCOR committees and a grant to SCOR from the U.S. National Science Foundation (Grant OCE-1546580), and the Intergovernmental Oceanographic Commission of UNESCO/International Oceanographic Data and Information Exchange (IOC/IODE) IQuOD Steering Group. SJ was supported by the Natural Environmental Research Council under Grant Agreement No. NE/P01517/1 and by the EPSRC NEWTON Fund Sustainable Deltas Programme, Grant Number EP/R024537/1. RvdW received funding from NWO, Grant 866.13.001. WH was supported by NASA (NNX17AI63G and NNX17AH25G). CL was supported by NASA Grant NNH16CT01C. This work is a contribution to the PIRATE project funded by CNES (to TP). PT was supported by the NOAA Research Global Ocean Monitoring and Observing Program through its sponsorship of UHSLC (NA16NMF4320058). JS was supported by EU contract 730030 (call H2020-EO-2016, “CEASELESS”). JW was supported by EU Horizon 2020 Grant 633211, Atlantos.
    Keywords: Coastal sea level ; Sea-level trends ; Coastal ocean modeling ; Coastal impacts ; Coastal adaptation ; Observational gaps ; Integrated observing system
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-06-09
    Description: Author Posting. © American Meteorological Society, 2021. 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 102(8), (2021): S143–S198, https://doi.org/10.1175/BAMS-D-21-0083.1.
    Description: This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Global ocean conditions in 2020 reflected a transition from an El Niño in 2018–19 to a La Niña in late 2020. Pacific trade winds strengthened in 2020 relative to 2019, driving anomalously westward Pacific equatorial surface currents. Sea surface temperatures (SSTs), upper ocean heat content, and sea surface height all fell in the eastern tropical Pacific and rose in the western tropical Pacific. Efflux of carbon dioxide from ocean to atmosphere was larger than average across much of the equatorial Pacific, and both chlorophyll-a and phytoplankton carbon concentrations were elevated across the tropical Pacific. Less rain fell and more water evaporated in the western equatorial Pacific, consonant with increased sea surface salinity (SSS) there. SSS may also have increased as a result of anomalously westward surface currents advecting salty water from the east. El Niño–Southern Oscillation conditions have global ramifications that reverberate throughout the report.
    Description: Argo data used in the chapter were collected and made freely available by the International Argo Program and the national programs that contribute to it. (https://argo.ucsd.edu, https://www.ocean-ops. org). The Argo Program is part of the Global Ocean Observing System. Many authors of the chapter are supported by NOAA Research, the NOAA Global Ocean Monitoring and Observing Program, or the NOAA Ocean Acidification Program. • L. Cheng is supported by National Natural Science Foundation of China (42076202) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDB42040402. • R. E. Killick is supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. PMEL contribution numbers 5214, 5215, 5216, 5217, and 5247.
    Repository Name: Woods Hole Open Access Server
    Type: Book chapter
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