National Water Level Observation Network Research Articles

Assessment of water levels from 43 years of NOAA’s Coastal Ocean Reanalysis (CORA) for the Gulf of Mexico and East Coasts

Coastal water level information is crucial for understanding flood occurrences and changing risks. Here, we validate the preliminary version (0.9) of NOAA’s Coastal Ocean Reanalysis (CORA), which is a 43-year reanalysis (1979–2021) of hourly coastal water levels for the Gulf of Mexico and Atlantic Ocean (i.e., the Gulf and East Coast region, or GEC). CORA-GEC v0.9 was conducted by the Renaissance Computing Institute using the coupled ADCIRC+SWAN coastal circulation and wave model. The model uses an unstructured mesh of nodes with varying spatial resolution that averages 400 m near the coast and is much coarser in the open ocean. Water level variations associated with tides and meteorological forcing are explicitly modeled, while lower-frequency water level variations are included by dynamically assimilating observations from NOAA’s National Water Level Observation Network. We compare CORA to water level observations that were either assimilated or not, and find that the reanalysis generally performs better than a state-of-the-art global ocean reanalysis (GLORYS12) in capturing the variability on monthly, seasonal, and interannual timescales as well as the long-term trend. The variability of hourly non-tidal residuals is also shown to be well resolved in CORA when compared to water level observations. Lastly, we present a case study of extreme water levels and coastal inundations around Miami, Florida to demonstrate an application of CORA for studying flood risks. Our assessment suggests that NOAA’s CORA-GEC v0.9 provides valuable information on water levels and flooding occurrence from 1979–2021 in areas that are experiencing changes across multiple time scales. CORA potentially can enhance flood risk assessment along parts of the U.S. Coast that do not have historical water level observations.

Influence of Loop Current and eddy shedding on subseasonal sea level variability along the western Gulf Coast

Mechanisms that generate subseasonal (1-2 months) events of sea level rise along the western Gulf Coast are investigated using the data collected by a dense tide gauge network: Texas Coastal Ocean Observation Network (TCOON) and National Water Level Observation Network (NWLON), satellite altimetry, and high-resolution (0.08°) ocean reanalysis product. In particular, the role of Loop Current and eddy shedding in generating the extreme sea level rise along the coast is emphasized. The time series of sea level anomalies along the western portion of the Gulf Coast derived from the TCOON and NWLON tide gauge data indicate that a subseasonal sea level rise which exceeds 15 cm is observed once in every 2-5 years. Based on the analysis of satellite altimetry data and high-resolution ocean reanalysis product, it is found that most of such extreme subseasonal events are originated from the anti-cyclonic (warm-core) eddy separated from the Loop Current which propagates westward. A prominent sea level rise is generated when the eddy reaches the western Gulf Coast, which occurs about 6-8 months after the formation of strong anti-cyclonic eddy in the central Gulf of Mexico. The results demonstrate that the accurate prediction of subseasonal sea level rise events along the Gulf Coast with the lead time of several months require a full description of large-scale ocean dynamical processes in the entire Gulf of Mexico including the characteristics of eddies separated from the Loop Current.

Global positioning system interferometric reflectometry for accurate tide gauge measurement: Insights from South Beach, Oregon, United States

Global positioning system (GPS) stations located along coastal areas have the ability to measure tide gauge records by reflected signal reception from the sea water surface. In this study we used the GPS signal-to-noise ratio data from the GPS station (44.6257 ⁰N, 124.0455 ⁰W) located at South Beach, Oregon, United States, to estimate the tide gauge records using seasonal measurements. First, we derived the tide gauge record from the station and used traditional tide gauge data from the National Water Level Observation Network (NWLON) sentinel station (Station ID: 9435380) located in Oregon for validation purposes because it was closest to the GPS station. Our results show that the GPS tide gauge and NWLON tide gauge correlate well with the correlation coefficient of 0.942 and the root mean square of their residuals was about 12.90 cm. The corresponding tide gauge prediction by auto-regressive moving average and singular spectrum analysis models are evaluated for their effectiveness over the station. The comparative analysis demonstrates that the GPS tide gauge has improved correlation with auto-regressive moving average predicted tide gauge (correlation coefficient of ~0.981 and root mean square of ~4.80 cm), and singular spectrum analysis predicted tide gauge (correlation coefficient of ~0.998 and root mean square of ~0.88 cm) compared to the NWLON tide gauge (correlation coefficient of ~0.942 and root mean square of ~12.90 cm) values. We believe the outcomes from this study contribute to a better understanding of the numerical modeling of tide gauge records as well as other measurements based on reflectometry techniques.

NOAA’s national water level observation network (NWLON)

ABSTRACTThe National Oceanographic and Atmospheric Administration National Water Level Observation Network (NWLON) is the foundation of a comprehensive system for observing, communicating, and assessing the impact of changing water levels nationwide. The network also measures other oceanographic parameters in addition to water levels, including meteorological parameters. Although initially established to support navigation, NWLON is a ‘go to’ source for data and products to support coastal community decision making. Real-time water level information available 24/7 is critical to emergency managers and planners monitoring changing water levels and contributes to NOAA’s forecast model for tsunami and storm surge warnings. This article also discusses the role of NWLON in terms of addressing emerging observational needs around emergency management, tracking changes in sea level rise through persistent changes in high tide flooding, establishing new regional sea level scenarios and projections, and restoring tidally influenced habitats. Sea level trends have been computed at 142 water level stations using a minimum span of 30 years of observations at each location. Coupling present trends with projected future scenarios supports decisions that will remain relevant into the future.

Water Level and Wave Height Estimates at NOAA Tide Stations from Acoustic and Microwave Sensors

Abstract The National Oceanic and Atmospheric Administration (NOAA) is transitioning the primary water level sensor at the majority of tide stations in the National Water Level Observation Network (NWLON) from an acoustic ranging system to a microwave radar system. Field comparison of the acoustic and microwave systems finds statistically equivalent performance when temperature gradients between the acoustic sensor and water surface are small and when significant wave height is less than roughly 0.5 m. When significant wave height is greater than approximately 0.5–1 m, the acoustic system consistently reports lower water levels. An analysis of 2 months of acoustic and microwave water level data at Duck, North Carolina, finds that the majority of differences between the two sensors can be attributed to systemic errors in the acoustic system and that the microwave system captures water level variability with higher fidelity than the acoustic system. NWLON real-time data products include the water level standard deviation, a statistic that can serve as a proxy for significant wave height. This study identifies 29 coastal water level stations that are candidates for monitoring wave height based on water level standard deviation, potentially adding a significant source of data for the sparsely sampled coastal wave fields around the United States, and finds that the microwave sensor is better suited than the acoustic system for wave height estimates.

Reducing Wave-Induced Microwave Water-Level Measurement Error with a Least Squares–Designed Digital Filter*

Abstract A microwave water-level sensor, the Design Analysis model H-3611i, will soon enter service at tide stations operated by the National Oceanic and Atmospheric Administration’s Center for Operational Oceanographic Products and Services (CO-OPS) as part of the National Water Level Observation Network. CO-OPS tests include a multisensor deployment at the U.S. Army Corps of Engineers Field Research Facility at Duck, North Carolina, to evaluate microwave water-level measurement error over a wide range of Atlantic Ocean sea states. In situ precision and accuracy of processed (6-min average) water level is found to depend on sea state in addition to data processing methods and sensor operating mode. Estimates over selected 6-h measurement periods show that a degree-two polynomial successfully models the increase in sensor standard error with increasing zero-moment (Hm0) wave height but with differences in rate of error increase dependent on the application of a prefilter and choice of sensor operating mode. Prefiltering of 1-Hz “fast mode” sensor output to remove variance at selected wind-wave frequencies can reduce standard error during extreme conditions (Hm0 ≈ 3 m) from approximately ±3 cm without prefiltering to about ±1 cm using a least squares–designed (LSD) digital filter with a 60-s cutoff period. When wave heights are elevated, skewed non-Gaussian distributions develop within the 1-Hz (360 s) sample domain wherein a 3σ outlier elimination process applied without prefiltering can introduce a negative bias of up to 5 cm in individual 6-min water-level averages.

NOAA/National Ocean Service Platform Harvest instrumentation

NOAA has installed two separate water level measurement systems and a suite of ancillary measurement sensors in support of the TOPEX/Poseidon Verification Experiment at Texaco Platform Harvest. The experimental measurement systems are modifications of NOAA's next‐generation water level measurement system (NGWLMS) that is being implemented into the National Water Level Observation Network of the United States. The primary system is configured with a downward looking acoustic water level sensor and the secondary system with a digital “bubbler”; pressure water level sensor (Digibub). The ancillary measurements being made are of barometric pressure, relative humidity, air temperature, water temperature, and water conductivity. Six‐minute interval measurements from each water level sensor and hourly measurements from each ancillary sensor are collected on independent remote terminal units on the platform. The data are transmitted every 3 h via GOES satellite to NOAA for processing in Silver Spring, Maryland. The installation of the measurement systems on the offshore oil platform has required a unique set of elevation corrections that are applied on an operational basis to the water level elevations. These include acoustic sound path air temperature differences for the acoustic data, and water density, nitrogen, and air column corrections to the Digibub data. NOAA field personnel have completed a platform survey in which elevation differences on the platform between the water level sensor “zeros”; and the GPS reference point were established.