Sea Level Hazards: Altimetric Monitoring of Tsunamis and Sea Level Rise

Whether on the short timescale of an impending tsunami or the much longer timescale of climate change-driven sea level rise, the threat stemming from rising and inundating ocean waters is a great concern to coastal populations. Timely and accurate observations of potentially dangerous changes in sea level are vital in determining the precautionary steps that need to be taken in order to protect coastal communities. While instruments from the past have provided in situ measurements of sea level at specific locations across the globe, satellites can be used to provide improved spatial and temporal sampling of the ocean in addition to producing more accurate measurements. Since 1993, satellite altimetry has provided accurate measurements of sea surface height (SSH) with near-global coverage. Not only have these measurements led to the first definitive estimates of global mean sea level rise, satellite altimetry observations have also been used to detect tsunami waves in the open ocean where wave amplitudes are relatively small, a vital step in providing early warning to those potentially affected by the impending tsunami. The use of satellite altimetry to monitor two specific sea level hazards is examined in this thesis. The first section will focus on the detection of tsunamis in the open ocean for the purpose of providing early warning to coastal inhabitants. The second section will focus on estimating secular trends using satellite altimetry data with the hope of improving our understanding of future sea level change. Results presented here will show the utility of satellite altimetry for sea level monitoring and will lay the foundation for further advancement in the detection of the two sea level hazards considered

Sea Level Acceleration in the China Seas

While global mean sea level rise (SLR) and acceleration (SLA) are indicators of climate change and are informative regarding the current state of the climate, assessments of regional and local SLR are essential for policy makers responding to, and preparing for, changes in sea level. In this work, three acceleration detection techniques are used to demonstrate the robust SLA in the China Seas. Interannual to multidecadal sea level variations (periods \u3e2 years), which are mainly related to natural internal climate variability and significantly affect estimation of sea level acceleration, are removed with empirical mode decomposition (EMD) analysis prior to the acceleration determination. Consistent SLAs of 0.085 ± 0.020 mm·yr−2 (1950–2013) and 0.074 ± 0.032 mm·yr−2 (1959–2013) in regional tide gauge records are shown to result from the three applied approaches in the Bohai Sea (BS) and East China Sea (ECS), respectively. The SLAs can be detected in records as short as 20 years if long-term sea level variability is adequately removed. The spatial distribution of SLA derived from a sea level reconstruction shows significant SLA in the BS, Yellow Sea (YS) and Yangtze River Estuary

Effects of Climate Oscillations on Wildland Fire Potential in the Continental United States

The effects of climate oscillations on spatial and temporal variations in wildland fire potential in the continental U.S. are examined from 1979 to 2015 using cyclostationary empirical orthogonal functions (CSEOFs). The CSEOF analysis isolates effects associated with the modulated annual cycle and the El Nino-Southern Oscillation (ENSO). The results show that, in early summer, wildland fire potential is reduced in the southwest during El Nino but is increased in the northwest, with opposite trends for La Nina. In late summer, El Nino is associated with increased wildland fire potential in the southwest. Relative to the mean, the largest impacts of ENSO are observed in the northwest and southeast. Climate impacts on fire potential due to ENSO are found to be most closely associated with variations in relative humidity. The connections established here between fire potential and climate oscillations could result in improved wildland fire risk assessment and resource allocation

Reconstruction of Sea Level Around the Korean Peninsula Using Cyclostationary Empirical Orthogonal Functions

Since the advent of the modern satellite altimeter era, the understanding of the sea level has increased dramatically. The satellite altimeter record, however, dates back only to the 1990s. The tide gauge record, on the other hand, extends through the 20th century but with poor spatial coverage when compared to the satellites. Many studies have been conducted to create a dataset with the spatial coverage of the satellite datasets and the temporal length of the tide gauge records by finding novel ways to combine the satellite data and tide gauge data in what is known as sea level reconstruction. However, most of the reconstructions of sea level were conducted on a global scale, leading to reduced accuracy on regional levels, especially when there are relatively few tide gauges. The seas around the Korean Peninsula are one such area with few tide gauges before 1960. In this study, new methods are proposed to reconstruct past sea level around the Korean Peninsula. Using spatial patterns obtained from a cyclostationary empirical orthogonal function decomposition of satellite data, we reconstruct sea level over the period from 1900 to 2014. Sea surface temperature data and altimeter data are used simultaneously in the reconstruction process, leading to an elimination of reliance on tide gauge data. Although we did not use the tide gauge data in the reconstruction process, the reconstructed sea level has a better agreement with the tide gauge observations in the region than previous studies that incorporated the tide gauge data. This study demonstrates a reconstruction technique that can potentially be used at regional levels, with particular emphasis on areas with poor tide gauge coverage

Mechanism of Seasonal Arctic Sea Ice Evolution and Arctic Amplification

Sea ice loss is proposed as a primary reason for the Arctic amplification, although the physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-Interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice loss in the Arctic Ocean and the Arctic amplification. While sea ice loss is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains thin in winter only in the Barents-Kara seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice reduction warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be free of ice. This positive feedback mechanism is not clearly observed in the Laptev, East Siberian, Chukchi, and Beaufort seas, since sea ice refreezes in late fall (November) before excessive turbulent heat flux is available for warming the atmospheric column in winter. A detailed seasonal heat budget is presented in order to understand specific differences between the Barents-Kara seas and Laptev, East Siberian, Chukchi, and Beaufort seas

An Assessment of Regional ICESat-2 Sea-Level Trends

Sea-level rise is an important indicator of ongoing climate change and well observed by satellite altimetry. However, observations from conventional altimetry degrade at the coast where regional sea-level changes can deviate from the open-ocean and impact local communities. With the 2018 launch of the laser altimeter onboard ICESat-2, new high-resolution observations of ice, land, and ocean elevations are available. Here we assess the potential benefits of sea level measured by ICESat-2 by comparing to data from Jason-3 and tide gauges. We find good agreement in the linear rates computed from the independent observations, with an absolute average residual of 3.60 ± 0.03 cm yr−1 between global ICESat-2 and Jason-3 observations at a 1° posting. The recent La Niña is clearly evident in ICESat-2 observations, as well as small-scale features. By demonstrating the quality of the ICESat-2-measured sea level, we provide support for integrating it into the existing suite of sea-level observations

Origin of interannual variability in global mean sea level

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.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.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.2020-12-0

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

Observation-based trajectory of future sea level for the coastal United States tracks near high-end model projections

With its increasing record length and subsequent reduction in influence of shorter-term variability on measured trends, satellite altimeter measurements of sea level provide an opportunity to assess near-term sea level rise. Here, we use gridded measurements of sea level created from the network of satellite altimeters in tandem with tide gauge observations to produce observation-based trajectories of sea level rise along the coastlines of the United States from now until 2050. These trajectories are produced by extrapolating the altimeter-measured rate and acceleration from 1993 to 2020, with two separate approaches used to account for the potential impact of internal variability on the future estimates and associated ranges. The trajectories are used to generate estimates of sea level rise in 2050 and subsequent comparisons are made to model-based projections. It is found that observation-based trajectories of sea level from satellite altimetry are near or above the higher-end model projections contained in recent assessment reports, although ranges are still wide. &nbsp;</p