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  • 1
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    Understanding of contemporary regional sea-level change and the implications for the future (2020)
    American Geophysical Union
    Details
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Reviews of Geophysics 58(3), (2020): e2019RG000672, doi:10.1029/2019RG000672.
    Description: Global sea level provides an important indicator of the state of the warming climate, but changes in regional sea level are most relevant for coastal communities around the world. With improvements to the sea‐level observing system, the knowledge of regional sea‐level change has advanced dramatically in recent years. Satellite measurements coupled with in situ observations have allowed for comprehensive study and improved understanding of the diverse set of drivers that lead to variations in sea level in space and time. Despite the advances, gaps in the understanding of contemporary sea‐level change remain and inhibit the ability to predict how the relevant processes may lead to future change. These gaps arise in part due to the complexity of the linkages between the drivers of sea‐level change. Here we review the individual processes which lead to sea‐level change and then describe how they combine and vary regionally. The intent of the paper is to provide an overview of the current state of understanding of the processes that cause regional sea‐level change and to identify and discuss limitations and uncertainty in our understanding of these processes. Areas where the lack of understanding or gaps in knowledge inhibit the ability to provide the needed information for comprehensive planning efforts are of particular focus. Finally, a goal of this paper is to highlight the role of the expanded sea‐level observation network—particularly as related to satellite observations—in the improved scientific understanding of the contributors to regional sea‐level change.
    Description: The research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors acknowledge support from the National Aeronautics and Space Administration under Grants 80NSSC17K0565, 80NSSC170567, 80NSSC17K0566, 80NSSC17K0564, and NNX17AB27G. A. A. acknowledges support under GRACE/GRACEFO Science Team Grant (NNH15ZDA001N‐GRACE). T. W. acknowledges support by the National Aeronautics and Space Administration (NASA) under the New (Early Career) Investigator Program in Earth Science (Grant: 80NSSC18K0743). C. G. P was supported by the J. Lamar Worzel Assistant Scientist Fund and the Penzance Endowed Fund in Support of Assistant Scientists at the Woods Hole Oceanographic Institution.
    Keywords: Sea level ; Satellite observations ; Remote sensing
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Origin of interannual variability in global mean sea level (2020)
    National Academy of Sciences
    Details
    Publication Date: 2022-10-26
    Description: Author Posting. © National Academy of Sciences, 2020. This article is posted here by permission of National Academy of Sciences for personal use, not for redistribution. The definitive version was published in Proceedings of the National Academy of Sciences of the United States of America 117(25), (2020): 13983-13990, doi: 10.1073/pnas.1922190117.
    Description: The two dominant drivers of the global mean sea level (GMSL) variability at interannual timescales are steric changes due to changes in ocean heat content and barystatic changes due to the exchange of water mass between land and ocean. With Gravity Recovery and Climate Experiment (GRACE) satellites and Argo profiling floats, it has been possible to measure the relative steric and barystatic contributions to GMSL since 2004. While efforts to “close the GMSL budget” with satellite altimetry and other observing systems have been largely successful with regards to trends, the short time period covered by these records prohibits a full understanding of the drivers of interannual to decadal variability in GMSL. One particular area of focus is the link between variations in the El Niño−Southern Oscillation (ENSO) and GMSL. Recent literature disagrees on the relative importance of steric and barystatic contributions to interannual to decadal variability in GMSL. Here, we use a multivariate data analysis technique to estimate variability in barystatic and steric contributions to GMSL back to 1982. These independent estimates explain most of the observed interannual variability in satellite altimeter-measured GMSL. Both processes, which are highly correlated with ENSO variations, contribute about equally to observed interannual GMSL variability. A theoretical scaling analysis corroborates the observational results. The improved understanding of the origins of interannual variability in GMSL has important implications for our understanding of long-term trends in sea level, the hydrological cycle, and the planet’s radiation imbalance.
    Description: The research was carried out at JPL, California Institute of Technology, under a contract with NASA. This study was funded by NASA Grants NNX17AH35G (Ocean Surface Topography Science Team), 80NSSC17K0564, and 80NSSC17K0565 (NASA Sea Level Change Team). The efforts of J.T.F. in this work were also supported by NSF Award AGS-1419571, and by the Regional and Global Model Analysis component of the Earth and Environmental System Modeling Program of the US Department of Energy's Office of Biological & Environmental Research via National Science Foundation Grant IA 1844590. C.G.P. was supported by the J. Lamar Worzel Assistant Scientist Fund and the Penzance Endowed Fund in Support of Assistant Scientists at the Woods Hole Oceanographic Institution.
    Description: 2020-12-08
    Keywords: Sea level ; Climate variability ; Global mean sea level ; Satellite altimetry
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
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    Effects of oceanic mesoscale and submesoscale frontal processes on the vertical transport of phytoplankton (2020)
    American Geophysical Union
    Details
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(8), (2019): 5999-6014, doi: 10.1029/2019JC015034.
    Description: Oceanic fronts are dynamically active regions of the global ocean that support upwelling and downwelling with significant implications for phytoplankton production and export. However (on time scales urn:x-wiley:jgrc:media:jgrc23568:jgrc23568-math-0001 the inertial time scale), the vertical velocity is 103–104 times weaker than the horizontal velocity and is difficult to observe directly. Using intensive field observations in conjunction with a process study ocean model, we examine vertical motion and its effect on phytoplankton fluxes at multiple spatial horizontal scales in an oligotrophic region in the Western Mediterranean Sea. The mesoscale ageostrophic vertical velocity (∼10 m/day) inferred from our observations shapes the large‐scale phytoplankton distribution but does not explain the narrow (1–10 km wide) features of high chlorophyll content extending 40–60 m downward from the deep chlorophyll maximum. Using modeling, we show that downwelling submesoscale features concentrate 80% of the downward vertical flux of phytoplankton within just 15% of the horizontal area. These submesoscale spatial structures serve as conduits between the surface mixed layer and pycnocline and can contribute to exporting carbon from the sunlit surface layers to the ocean interior.
    Description: The AlborEx experiment was conducted in the framework of PERSEUS EU‐funded project (Grant 287600) and was led by the Spanish National Research Council (CSIC) and involved other national and international partners: Balearic Islands Coastal Observing and Forecasting System (SOCIB, Spain); Consiglio Nazionale delle Ricerche (CNR, Italy); Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS, Italy); and Woods Hole Oceanographic Institution (WHOI, ONR Grant N00014‐16‐1‐3130). Glider operations were partially funded by JERICO FP7 project. Part of this work has been carried out as part of the Copernicus Marine Environment Monitoring Service (CMEMS) MedSUB project. CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the European Union. S. R. and A. P. acknowledge support from WHOI Subcontract A101339. Data available from authors: Ship CTDs, glider and VM‐ADCP data files are available in the SOCIB data catalog (https://doi.org/10.25704/z5y2-qpye); model data are available at IMEDEA data catalog https://ide.imedea.uib-csic.es/thredds/catalog/data/projects/alborex/catalog.html. We thank all the crew and participants on board R/V SOCIB for their collaboration and Marc Torner and the SOCIB glider Facility for their efficient cooperation. We also thank B. Mourre for numerical data from the Western Mediterranean Operational Model to initialize the Process Study Ocean Model. Figures were created using the cmocean colormaps package (Thyng et al., 2016).
    Keywords: Vertical motion ; Ocean front ; Mesoscale ; Submesoscale ; Transport ; Phytoplankton
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
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    Influence of nonseasonal river discharge on sea surface salinity and height (2022)
    American Geophysical Union
    Details
    Publication Date: 2022-10-26
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chandanpurkar, H. A., Lee, T., Wang, X., Zhang, H., Fournier, S., Fenty, I., Fukumori, I., Menemenlis, D., Piecuch, C. G., Reager, J. T., Wang, O., & Worden, J. Influence of nonseasonal river discharge on sea surface salinity and height. Journal of Advances in Modeling Earth Systems, 14(2), (2022): e2021MS002715, https://doi.org/10.1029/2021MS002715.
    Description: River discharge influences ocean dynamics and biogeochemistry. Due to the lack of a systematic, up-to-date global measurement network for river discharge, global ocean models typically use seasonal discharge climatology as forcing. This compromises the simulated nonseasonal variation (the deviation from seasonal climatology) of the ocean near river plumes and undermines their usefulness for interdisciplinary research. Recently, a reanalysis-based daily varying global discharge data set was developed, providing the first opportunity to quantify nonseasonal discharge effects on global ocean models. Here we use this data set to force a global ocean model for the 1992–2017 period. We contrast this experiment with another experiment (with identical atmospheric forcings) forced by seasonal climatology from the same discharge data set to isolate nonseasonal discharge effects, focusing on sea surface salinity (SSS) and sea surface height (SSH). Near major river mouths, nonseasonal discharge causes standard deviations in SSS (SSH) of 1.3–3 practical salinity unit (1–2.7 cm). The inclusion of nonseasonal discharge results in notable improvement of model SSS against satellite SSS near most of the tropical-to-midlatitude river mouths and minor improvement of model SSH against satellite or in-situ SSH near some of the river mouths. SSH changes associated with nonseasonal discharge can be explained by salinity effects on halosteric height and estimated accurately through the associated SSS changes. A recent theory predicting river discharge impact on SSH is found to perform reasonably well overall but underestimates the impact on SSH around the global ocean and has limited skill when applied to rivers near the equator and in the Arctic Ocean.
    Description: This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) with support from the Physical Oceanography (PO) and Modeling, Analysis, and Prediction (MAP) Programs. High-end computing resources for the numerical simulation were provided by the NASA Advanced Supercomputing Division at the Ames Research Center.
    Keywords: River discharge ; Sea surface salinity ; Sea surface height
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
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    High-tide floods and storm surges during atmospheric rivers on the US West Coast (2022)
    American Geophysical Union
    Details
    Publication Date: 2022-06-06
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Piecuch, C. G., Coats, S., Dangendorf, S., Landerer, F. W., Reager, J. T., Thompson, P. R., & Wahl, T. High-tide floods and storm surges during atmospheric rivers on the US West Coast. Geophysical Research Letters, 49(2), (2022): e2021GL096820, https://doi.org/10.1029/2021GL096820.
    Description: Atmospheric rivers (ARs) cause inland hydrological impacts related to precipitation. However, little is known about coastal hazards associated with these events. We elucidate high-tide floods (HTFs) and storm surges during ARs on the US West Coast during 1980–2016. HTFs and ARs cooccur more often than expected from chance. Between 10% and 63% of HTFs coincide with ARs on average, depending on location. However, interannual-to-decadal variations in HTFs are due more to tides and mean sea-level changes than storminess variability. Only 2–15% of ARs coincide with HTFs, suggesting that ARs typically must cooccur with high tides or mean sea levels to cause HTFs. Storm surges during ARs reflect local wind, pressure, and precipitation forcing: meridional wind and barometric pressure are primary drivers, but precipitation makes secondary contributions. This study highlights the relevance of ARs to coastal impacts, clarifies the drivers of storm surge during ARs, and identifies future research directions.
    Description: This work was supported by National Aeronautics and Space Administration Sea Level Change Team awards 80NSSC20K1241 and 80NM0018D0004 (to C. G. P.). The contribution from F. W. L. and J. T. R. represents research carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004).
    Keywords: atmospheric rivers ; high-tide flooding ; storm surge ; coastal impacts ; coastal hazards ; sea level
    Repository Name: Woods Hole Open Access Server
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  • 6
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    Paleoclimate constraints on the spatiotemporal character of past and future droughts (2021)
    American Meteorological Society
    Details
    Publication Date: 2022-05-26
    Description: 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 Journal of Climate 33(22), (2020): 9883-9903, https://doi.org/10.1175/JCLI-D-20-0004.1.
    Description: Machine-learning-based methods that identify drought in three-dimensional space–time are applied to climate model simulations and tree-ring-based reconstructions of hydroclimate over the Northern Hemisphere extratropics for the past 1000 years, as well as twenty-first-century projections. Analyzing reconstructed and simulated drought in this context provides a paleoclimate constraint on the spatiotemporal characteristics of simulated droughts. Climate models project that there will be large increases in the persistence and severity of droughts over the coming century, but with little change in their spatial extent. Nevertheless, climate models exhibit biases in the spatiotemporal characteristics of persistent and severe droughts over parts of the Northern Hemisphere. We use the paleoclimate record and results from a linear inverse modeling-based framework to conclude that climate models underestimate the range of potential future hydroclimate states. Complicating this picture, however, are divergent changes in the characteristics of persistent and severe droughts when quantified using different hydroclimate metrics. Collectively our results imply that these divergent responses and the aforementioned biases must be better understood if we are to increase confidence in future hydroclimate projections. Importantly, the novel framework presented herein can be applied to other climate features to robustly describe their spatiotemporal characteristics and provide constraints on future changes to those characteristics.
    Description: This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement 1852977. JAF was also supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological & Environmental Research (BER) via National Science Foundation IA 1844590. JS was supported in part by the U.S. National Science Foundation through Grants AGS-1602920 and AGS-1805490, and by the National Oceanic and Atmospheric Administration by Grant NA20OAR4310425. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1) for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portal. We thank the editor and two reviewers for comments that greatly improved the quality of this manuscript. This is SOEST Publication No. 11116 and LDEO Publication No. 8450.
    Description: 2021-04-15
    Keywords: Drought ; Climate change ; Paleoclimate ; Climate models ; Climate variability ; Other artificial intelligence/machine learning
    Repository Name: Woods Hole Open Access Server
    Type: Article
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