On the formation, ventilation, and erosion of mode waters in the North Atlantic and Southern Oceans

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94834/1/jgrc12564.pd

Ocean mass, sterodynamic effects, and vertical land motion largely explain US coast relative sea level rise

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Harvey, T., Hamlington, B. D., Frederikse, T., Nerem, R. S., Piecuch, C. G., Hammond, W. C., Blewitt, G., Thompson, P. R., Bekaert, D. P. S., Landerer, F. W., Reager, J. T., Kopp, R. E., Chandanpurkar, H., Fenty, I., Trossman, D. S., Walker, J. S., & Boening, C. W. Ocean mass, sterodynamic effects, and vertical land motion largely explain US coast relative sea level rise. Communications Earth & Environment, 2(1), (2021): 233, https://doi.org/10.1038/s43247-021-00300-w.Regional sea-level changes are caused by several physical processes that vary both in space and time. As a result of these processes, large regional departures from the long-term rate of global mean sea-level rise can occur. Identifying and understanding these processes at particular locations is the first step toward generating reliable projections and assisting in improved decision making. Here we quantify to what degree contemporary ocean mass change, sterodynamic effects, and vertical land motion influence sea-level rise observed by tide-gauge locations around the contiguous U.S. from 1993 to 2018. We are able to explain tide gauge-observed relative sea-level trends at 47 of 55 sampled locations. Locations where we cannot explain observed trends are potentially indicative of shortcomings in our coastal sea-level observational network or estimates of uncertainty.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. C.G.P. was supported by NASA grant 80NSSC20K1241. B.D.H., T.C.H., and T.F. were supported by NASA JPL Task 105393.281945.02.25.04.59. R.E.K. and J.S.W. were supported by U.S. National Aeronautics and Space Administration (grants 80NSSC17K0698, 80NSSC20K1724 and JPL task 105393.509496.02.08.13.31) and U.S. National Science Foundation (grant ICER-1663807). P.R.T. acknowledges financial support from the NOAA Global Ocean Monitoring and Observing program in support of the University of Hawaii Sea Level Center (NA11NMF4320128). The ECCO project is funded by the NASA Physical Oceanography; Modeling, Analysis, and Prediction; and Cryosphere Programs

Climate Process Team on internal wave–driven ocean mixing

Author Posting. © American Meteorological Society, 2017. 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 98 (2017): 2429-2454, doi:10.1175/BAMS-D-16-0030.1.Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.We are grateful to U.S. CLIVAR for their leadership in instigating and facilitating the Climate Process Team program. We are indebted to NSF and NOAA for sponsoring the CPT series.2018-06-0

Climate Process Team On Internal Wave-Driven Ocean Mixing

The study summarizes recent advances in our understanding of internal wave–driven turbulent mixing in the ocean interior and introduces new parameterizations for global climate ocean models and their climate impacts

Climate Process Team on Internal-Wave Driven Ocean Mixing

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean, and consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Climate models have been shown to be very sensitive not only to the overall level but to the detailed distribution of mixing; sub-grid-scale parameterizations based on accurate physical processes will allow model forecasts to evolve with a changing climate. Spatio-temporal patterns of mixing are largely driven by the geography of generation, propagation and destruction of internal waves, which are thought to supply much of the power for turbulent mixing. Over the last five years and under the auspices of US CLIVAR, a NSF and NOAA supported Climate Process Team has been engaged in developing, implementing and testing dynamics-base parameterizations for internal-wave driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here we review recent progress, describe the tools developed, and discuss future directions

Beyond equilibrium climate sensitivity

ISSN:1752-0908ISSN:1752-089

Oceanic Electrical Conductivity Variability From Observations and Its Budget From an Ocean State Estimate

Because spatio-temporal variations in ocean heat content (OHC) are strongly predicted by ocean conductivity content (OCC) over most of the global ocean, we analyze the dynamical budget and behavior of the electrical conductivity of seawater. To perform these analyses, we use an ocean-model state estimate designed to accurately represent long-term variations in ocean properties in a dynamically and kinematically consistent way. We show that this model accurately reproduces the spatio-temporal variations in electrical conductivity seen in satellite-derived data and in a seasonal climatology product derived from in-situ data, justifying use of the model data to perform further analyses. An empirical orthogonal function analysis suggests that the vast majority of the variance in OHC and OCC can be explained by similar mechanisms. The electrical conductivity budget's most important term is the temperature forcing tendency term, suggesting that ocean heat uptake is the mechanism responsible for the strong relationship between OCC and OHC.https://doi.org/10.1029/2022GL10045