High-Tide Floods and Storm Surges During Atmospheric Rivers on the US West Coast

Amospheric rivers (ARs) effect inland hydrological impacts related to extreme precipitation. However, little is known about the possible coastal hazards associated with these storms. Here we elucidate high-tide floods (HTFs) and storm surges during ARs through a statistical analysis of data from the US West Coast during 1980-2016. HTFs and landfalling ARs co-occur more often than expected from random chance. Between 10%-63% of HTFs coincide with landfalling ARs, depending on location. However, only 2%-15% of ARs coincide with HTFs, suggesting that ARs typically must co-occur with anomalously high tides or mean sea levels to cause HTFs. Storm surges during ARs are interpretable in terms of local wind, pressure, and precipitation forcing. Meridional wind and barometric pressure are the primary drivers of the storm surge. This study highlights the relevance of ARs to coastal impacts, clarifies the drivers of storm surge during ARs, and identifies future research directions

Ice mass change in Greenland and Antarctica between 1993 and 2013 from satellite gravity measurements

We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a Principal Component Analysis to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite track-ing data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low and high degree potential coe�cients re ected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily in uenced by interannual variations

Teleconnection between the Atlantic meridional overturning circulation and sea level in the Mediterranean Sea

The Mediterranean Sea can be viewed as a “barometer” of the North Atlantic Ocean, because its sea level responds to oceanic-gyre-scale changes in atmospheric pressure and wind forcing, related to the North Atlantic Oscillation (NAO). The climate of the North Atlantic is influenced by the Atlantic Meridional Overturning Circulation (AMOC) as it transports heat from the South Atlantic towards the Subpolar North Atlantic. This study reports on a teleconnection between the AMOC transport measured at 26.5°N and the Mediterranean Sea level during 2004-2017: a reduced/increased AMOC transport is associated with a higher/lower sea level in the Mediterranean. Processes responsible for this teleconnection are analyzed in detail using available satellite and in situ observations, and an atmospheric reanalysis. Firstly, it is shown that on monthly to interannual time scales the AMOC and sea level are both driven by similar NAO-like atmospheric circulation patterns. During a positive/negative NAO state, stronger/weaker trade winds (i) drive northward/southward anomalies of Ekman transport across 26.5°N that directly affect the AMOC, and (ii) are associated with westward/eastward winds over the Strait of Gibraltar that force water to flow out/in the Mediterranean Sea and thus change its average sea level. Secondly, it is demonstrated that interannual changes in the AMOC transport can lead to thermosteric sea level anomalies near the North Atlantic eastern boundary. These anomalies can (i) reach the Strait of Gibraltar and cause sea level changes in the Mediterranean Sea, and (ii) represent a mechanism for negative feedback on the AMOC

Emerging Trends in Global Freshwater Availability

Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002-2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, or climate change. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango delta. Others are consistent with climate model predictions. This observation-based assessment of how the world's water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security

The dominant global modes of recent internal sea level variability

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(4), (2019):2750-2768, doi: 10.1029/2018JC014635.The advances in the modern sea level observing system have allowed for a new level of knowledge of regional and global sea level in recent years. The combination of data from satellite altimeters, Gravity Recovery and Climate Experiment (GRACE) satellites, and Argo profiling floats has provided a clearer picture of the different contributors to sea level change, leading to an improved understanding of how sea level has changed in the present and, by extension, may change in the future. As the overlap between these records has recently extended past a decade in length, it is worth examining the extent to which internal variability on timescales from intraseasonal to decadal can be separated from long‐term trends that may be expected to continue into the future. To do so, a combined modal decomposition based on cyclostationary empirical orthogonal functions is performed simultaneously on the three data sets, and the dominant shared modes of variability are analyzed. Modes associated with the trend, seasonal signal, El Niño–Southern Oscillation, and Pacific decadal oscillation are extracted and discussed, and the relationship between regional patterns of sea level change and their associated global signature is highlighted.The satellite altimetry grids are available from NASA JPL/PO.DAAC at the following location: https://podaac.jpl.nasa.gov/dataset. GRACE land water storage data are available at http://grace.jpl.nasa.gov, supported by the NASA MEaSUREs Program. The gridded fields based on Argo data used to compute the steric sea level data are available at http://www.argo.ucsd.edu/Gridded_fields.html. The gridded fields based on Argo data used to compute the steric sea level data are available at http://www.argo.ucsd.edu/Gridded_fields.html. The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. B. D. H., F. W. L., J. T. R., and P. R. T. acknowledge support from NASA grant 80NSSC17K0564 (NASA Sea Level Change Team). C. G. P. acknowledges support from NSF awards OCE‐1558966 and OCE‐1834739. K. Y. K. was partially supported for this research by the National Science Foundation of Korea under the grant NRF‐ 2017R1A2B4003930.2019-09-2

The Dominant Global Modes of Recent Internal Sea Level Variability

The advances in the modern sea level observing system have allowed for a new level of knowledge of regional and global sea level in recent years. The combination of data from satellite altimeters, Gravity Recovery and Climate Experiment (GRACE) satellites, and Argo profiling floats has provided a clearer picture of the different contributors to sea level change, leading to an improved understanding of how sea level has changed in the present and, by extension, may change in the future. As the overlap between these records has recently extended past a decade in length, it is worth examining the extent to which internal variability on timescales from intraseasonal to decadal can be separated from long‐term trends that may be expected to continue into the future. To do so, a combined modal decomposition based on cyclostationary empirical orthogonal functions is performed simultaneously on the three data sets, and the dominant shared modes of variability are analyzed. Modes associated with the trend, seasonal signal, El Niño–Southern Oscillation, and Pacific decadal oscillation are extracted and discussed, and the relationship between regional patterns of sea level change and their associated global signature is highlighted

Return to rapid ice loss in Greenland and record loss in 2019 detected by the GRACE-FO satellites

Between 2003-2016, the Greenland ice sheet (GrIS) was one of the largest contributors to sea level rise, as it lost about 255 Gt of ice per year. This mass loss slowed in 2017 and 2018 to about 100 Gt yr−1. Here we examine further changes in rate of GrIS mass loss, by analyzing data from the GRACE-FO (Gravity Recovery and Climate Experiment – Follow On) satellite mission, launched in May 2018. Using simulations with regional climate models we show that the mass losses observed in 2017 and 2018 by the GRACE and GRACE-FO missions are lower than in any other two year period between 2003 and 2019, the combined period of the two missions. We find that this reduced ice loss results from two anomalous cold summers in western Greenland, compounded by snow-rich autumn and winter conditions in the east. For 2019, GRACE-FO reveals a return to high melt rates leading to a mass loss of 223 ± 12 Gt month−1 during the month of July alone, and a record annual mass loss of 532 ± 58 Gt yr−1

Concepts and terminology for sea level: mean, variability and change, both local and global

Changes in sea level lead to some of the most severe impacts of anthropogenic climate change. Consequently, they are a subject of great interest in both scientific research and public policy. This paper defines concepts and terminology associated with sea level and sea-level changes in order to facilitate progress in sea-level science, in which communication is sometimes hindered by inconsistent and unclear language. We identify key terms and clarify their physical and mathematical meanings, make links between concepts and across disciplines, draw distinctions where there is ambiguity, and propose new terminology where it is lacking or where existing terminology is confusing. We include formulae and diagrams to support the definitions

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

Measuring global ocean heat content to estimate the earth energy imbalance

The energy radiated by the Earth toward space does not compensate the incoming radiation from the Sun leading to a small positive energy imbalance at the top of the atmosphere (0.4–1 Wm–2). This imbalance is coined Earth’s Energy Imbalance (EEI). It is mostly caused by anthropogenic greenhouse gas emissions and is driving the current warming of the planet. Precise monitoring of EEI is critical to assess the current status of climate change and the future evolution of climate. But the monitoring of EEI is challenging as EEI is two orders of magnitude smaller than the radiation fluxes in and out of the Earth system. Over 93% of the excess energy that is gained by the Earth in response to the positive EEI accumulates into the ocean in the form of heat. This accumulation of heat can be tracked with the ocean observing system such that today, the monitoring of Ocean Heat Content (OHC) and its long-term change provide the most efficient approach to estimate EEI. In this community paper we review the current four state-of-the-art methods to estimate global OHC changes and evaluate their relevance to derive EEI estimates on different time scales. These four methods make use of: (1) direct observations of in situ temperature; (2) satellite-based measurements of the ocean surface net heat fluxes; (3) satellite-based estimates of the thermal expansion of the ocean and (4) ocean reanalyses that assimilate observations from both satellite and in situ instruments. For each method we review the potential and the uncertainty of the method to estimate global OHC changes. We also analyze gaps in the current capability of each method and identify ways of progress for the future to fulfill the requirements of EEI monitoring. Achieving the observation of EEI with sufficient accuracy will depend on merging the remote sensing techniques with in situ measurements of key variables as an integral part of the Ocean Observing System