Considerations for Estimating the 20th Century Trend in Global Mean Sea Level

Recent efforts in reconstructing historical sea level change have led to a range of published estimates for the global mean sea level trend over the last century. Disagreement in these estimates can be attributed to two factors: (1) differences in analysis and/or reconstruction techniques and (2) differences in tide gauge selection and quality control of the data. Here the impact of tide gauge selection is explored by calculating global mean trends using three different tide gauge data sets that have been utilized in recent reconstruction studies. The inclusion of tide gauge records that are affected by unresolved internal variability and/or unaccounted for vertical land motion are found to significantly impact the estimates of the long-term trend in global mean sea level. In conclusion, several guidelines are presented regarding the selection of tide gauges for use in historical reconstructions focused on estimating the 20th century global mean sea level trend

Effects of Climate Oscillations on Wind Resource Variability in the United States

Natural climate variations in the United States wind resource are assessed by using cyclostationary empirical orthogonal functions (CSEOFs) to decompose wind reanalysis data. Compared to approaches that average climate signals or assume stationarity of the wind resource on interannual time scales, the CSEOF analysis isolates variability associated with specific climate oscillations, as well as their modulation from year to year. Contributions to wind speed variability from the modulated annual cycle (MAC) and the El Nino-Southern Oscillation (ENSO) are quantified, and information provided by the CSEOF analysis further allows the spatial variability of these effects to be determined. The impacts of the MAC and ENSO on the wind resource are calculated at existing wind turbine locations in the United States, revealing variations in the wind speed of up to 30% at individual sites. The results presented here have important implications for predictions of wind plant power output and siting

Is the Detection of Accelerated Sea Level Rise Imminent?

Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This masking arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. A consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade

Improving Sea Level Reconstructions Using Non-Sea Level Measurements

We present a new method for reconstructing sea level involving cyclostationary empirical orthogonal functions (CSEOFs). While we show results from a CSEOF reconstruction using basis functions computed from satellite altimetry and subsequently fit to tide gauge data, our focus is on how other ocean observations such as sea surface temperature can be leveraged to create an improved reconstructed sea level data set spanning the time period from 1900 to present. Basis functions are computed using satellite measurements of sea surface temperature, and using a simple regression technique, these basis functions are transformed to represent a similar temporal evolution to corresponding satellite altimeter-derived sea level basis functions. The resulting sea level and sea surface temperature basis functions are fit to tide gauge data and historical sea surface temperature data, respectively, to produce a reconstructed sea level data set spanning the period from 1900 to present. We demonstrate the use of this reconstructed data set for climate monitoring, focusing primarily on climate signals in the Pacific Ocean. The CSEOF reconstruction technique can be used to create indices computed solely from sea level measurements for monitoring signals such as the eastern Pacific (EP) El Nio-Southern Oscillation (ENSO), Central Pacific (CP) ENSO, and Pacific Decadal Oscillation (PDO). The EP ENSO, CP ENSO, and PDO signals are all well represented in the CSEOF reconstruction relying solely on sea level measurements from 1950 to present; however, significant improvement can be made in reconstructing these signals during the first half of the twentieth century by including sea surface temperature measurements in the sea level reconstruction procedure

Spaceborne Synthetic Aperture Radar Survey of Subsidence in Hampton Roads, Virginia (USA)

Over the past century, the Hampton Roads area of the Chesapeake Bay region has experienced one of the highest rates of relative sea level rise on the Atlantic coast of the United States. This rate of relative sea level rise results from a combination of land subsidence, which has long been known to be present in the region, and rising seas associated with global warming on long timescales and exacerbated by shifts in ocean dynamics on shorter timescales. An understanding of the current-day magnitude of each component is needed to create accurate projections of future relative sea level rise upon which to base planning efforts. The objective of this study is to estimate the land component of relative sea level rise using interferometric synthetic aperture radar (InSAR) analysis applied to ALOS-1 synthetic aperture radar data acquired during 2007–2011 to generate high-spatial resolution (20–30 m) estimates of vertical land motion. Although these results are limited by the uncertainty associated with the small set of available historical SAR data, they highlight both localized rates of high subsidence and a significant spatial variability in subsidence, emphasizing the need for further measurement, which could be done with Sentinel-1 and NASA’s upcoming NISAR mission

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

Future Nuisance Flooding in Norfolk, VA, From Astronomical Tides and Annual to Decadal Internal Climate Variability

Increasing sea level rise will lead to more instances of nuisance flooding along the Virginia coastline in the coming decades, causing road closures and deteriorating infrastructure. These minor flood events can be caused by astronomical tides alone, in addition to internal climate variability on annual to decadal timescales. An assessment of nuisance flooding from these two effects is presented up until the year 2050 for Norfolk, Virginia. The analysis of water levels indicates that nuisance flooding from tides alone in conjunction with a medium-high sea level scenario will result in flooding beginning in 2030 with frequency increasing thereafter. The addition of climate variability, by use of an empirical mode decomposition, leads to a substantial increase of flooding relative to the tides-alone analysis and shows flood events beginning as soon as 2020. High tides in the future will produce nuisance flooding without the need of other drivers such as coastal storms. Plain Language Summary As sea level continues to rise, coastal cities are going to start to see increases in nuisance flooding. This minor flooding is generally caused by tides and wind events, leading to inundation that over time deteriorates roads and infrastructure. Nuisance flooding in Norfolk, Virginia, has increased 325% since 1960 and is becoming more prominent. By combining sea level estimates, tidal estimates, and natural internal climate variability contributions to sea level rise, we have determined how nuisance flooding will increase in the future for Norfolk up until the year 2050. Our analyses show that this flooding will continue to increase in frequency with time, with a potential for well over 200 flood events in the year 2049

A Southern Hemisphere Sea Level Pressure-Based Precursor for ENSO Warm and Cold Events

Past studies have described large-scale sea level pressure (SLP) variations in the Southern Hemisphere that lead to El Nino-Southern Oscillation (ENSO) warm and cold events (WE and CE). By relying on this description and the importance of the related variability in the lead up to WE and CE, Southern Hemisphere SLP variations in May-June-July (MJJ) are shown here to be excellent predictors for the peak warm/cold events in sea-surface temperatures (SST) and sea level pressure that mark the mature phase of a warm/cold event in November-January of the same year. Cyclostationary empirical orthogonal functions (CSEOFs) are used to extract the variability associated with this description of SLP evolution leading to extreme events, underscoring the importance of this signal in the build-up to ENSO events. Using the CSEOF decomposition, an MJJ precursor is established and shown to precede impending warm and cold events in the past sixty years. Furthermore, the precursor developed in this study would have suggested that a significant WE for the latter half of 2014 was unlikely

Cyclostationary Empirical Orthogonal Function Sea-Level Reconstruction

Since 1993, satellite altimetry has provided accurate measurements of sea surface height with near-global coverage. These measurements led to the first definitive estimates of global mean sea-level (GMSL) rise and have improved understanding of how sea levels are changing regionally at decadal time scales. These relatively short records, however, provide no information about the state of the ocean prior to 1993, and with the modern altimetry record spanning only 20 years, the lower frequency signals that are known to be present in the ocean are difficult or impossible to resolve. Tide gauges, on the other hand, have measured sea level over the last 200 years, with some records extending back to 1807. While providing longer records, the spatial resolution of tide gauge sampling is poor, making studies of the large-scale patterns of ocean variability and estimates of GMSL difficult. Combining the satellite altimetry with the tide gauges using a technique known as sea-level reconstruction results in a data set with the record length of the tide gauges and the near-global coverage of satellite altimetry. Cyclostationary empirical orthogonal functions (CSEOFs), derived from satellite altimetry, are combined with historical sea-level measurements from tide gauges to create the Reconstructed Sea Level data set spanning from 1950 to 2009. Previous sea-level reconstructions have utilized empirical orthogonal functions (EOFs) as basis functions, but by using CSEOFs and by addressing other aspects of the reconstruction procedure, an alternative sea-level reconstruction can be computed. The resulting reconstructed sea-level data set has weekly temporal resolution and half-degree spatial resolution