Are Long Tide Gauge Records in the Wrong Place to Measure Global Mean Sea Level Rise?

Ocean dynamics, land motion, and changes in Earth\u27s gravitational and rotational fields cause local sea level change to deviate from the rate of global mean sea level rise. Here we use observations and simulations of spatial structure in sea level change to estimate the likelihood that these processes cause sea level trends in the longest and highest-quality tide gauge records to be systematically biased relative to the true global mean rate. The analyzed records have an average twentieth century rate of approximately 1.6 mm/yr, but based on the locations of these gauges, we show that the simple average underestimates the twentieth century global mean rate by 0.1 ± 0.2 mm/yr. Given the distribution of potential sampling biases, we find tha

GPS displacement dataset for the study of elastic surface mass variations

Quantification of uncertainty in surface mass change signals derived from Global Positioning System (GPS) measurements poses challenges, especially when dealing with large datasets with continental or global coverage. We present a new GPS station displacement dataset that reflects surface mass load signals and their uncertainties. We assess the structure and quantify the uncertainty of vertical land displacement derived from 3045 GPS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. We list the required corrections to isolate surface mass signals in GPS estimates and screen the data using GRACE(-FO) as external validation. Evaluation of GPS time series is a critical step, which identifies (a) corrections that were missed, (b) sites that contain non-elastic signals (e.g., close to aquifers), and (c) sites affected by background modeling errors (e.g., errors in the glacial isostatic model). Finally, we quantify uncertainty of GPS vertical displacement estimates through stochastic modeling and quantification of spatially correlated errors. Our aim is to assign weights to GPS estimates of vertical displacements, which will be used in a joint solution with GRACE(-FO). We prescribe white, colored, and spatially correlated noise. To quantify spatially correlated noise, we build on the common mode imaging approach by adding a geophysical constraint (i.e., surface hydrology) to derive an error estimate for the surface mass signal. We study the uncertainty of the GPS displacement time series and find an average noise level between 2 and 3 mm when white noise, flicker noise, and the root mean square (rms) of residuals about a seasonality and trend fit are used to describe uncertainty. Prescribing random walk noise increases the error level such that half of the stations have noise &gt; 4 mm, which is systematic with the noise level derived through modeling of spatially correlated noise. The new dataset is available at https://doi.org/10.5281/zenodo.8184285 (Peidou et al., 2023) and is suitable for use in a future joint solution with GRACE(-FO)-like observations.</p

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

Observation-Driven Estimation of the Spatial Variability of 20th Century Sea Level Rise

Over the past two decades, sea level measurements made by satellites have given clear indications of both global and regional sea level rise. Numerous studies have sought to leverage the modern satellite record and available historic sea level data provided by tide gauges to estimate past sea level rise, leading to several estimates for the 20th century trend in global mean sea level in the range between 1 and 2 mm/yr. On regional scales, few attempts have been made to estimate trends over the same time period. This is due largely to the inhomogeneity and quality of the tide gauge network through the 20th century, which render commonly used reconstruction techniques inadequate. Here, a new approach is adopted, integrating data from a select set of tide gauges with prior estimates of spatial structure based on historical sea level forcing information from the major contributing processes over the past century. The resulting map of 20th century regional sea level rise is optimized to agree with the tide gauge-measured trends, and provides an indication of the likely contributions of different sources to regional patterns. Of equal importance, this study demonstrates the sensitivities of this regional trend map to current knowledge and uncertainty of the contributing processes

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

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

Highly efficient polymer solar cells cast from non-halogenated xylene/anisaldehyde solution

Several high performance polymer:fullerene bulk-heterojunction photo-active layers, deposited from the non-halogenated solvents o-xylene or anisole in combination with the eco-compatible additive p-anisaldehyde, are investigated. The respective solar cells yield excellent power conversion efficiencies up to 9.5%, outperforming reference devices deposited from the commonly used halogenated chlorobenzene/1,8-diiodooctane solvent/additive combination. The impact of the processing solvent on the bulk-heterojunction properties is exemplified on solar cells comprising benzodithiophene-thienothiophene co-polymers and functionalized fullerenes (PTB7:PC71BM). The additive p-anisaldehyde improves film formation, enhances polymer order, reduces fullerene agglomeration and shows high volatility, thereby positively affecting layer deposition, improving charge carrier extraction and reducing drying time, the latter being crucial for future large area roll-to-roll device fabrication. © The Royal Society of Chemistry 2015

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

Correction to: Concepts and Terminology for Sea Level: Mean, Variability and Change, Both Local and Global

In the author group at the start of the article and in the affiliations section at the end of the article, the sixth author’s name was incorrectly spelled as “Ichiro Fukimori”. However, the correct name should read as “Ichiro Fukumori”