SWOT Data Assimilation with Correlated Error Reduction: Fitting Model and Error TogetherGille, Sarah T.; Gao, Yu; Cornuelle, Bruce D.; Mazloff, Matthew R.
2025 Journal of Atmospheric and Oceanic Technology
doi: 10.1175/jtech-d-24-0062.1
AbstractThe Surface Water Ocean Topography (SWOT) satellite mission provides high-resolution two-dimensional sea surface height (SSH) data with swath coverage. However, spatially correlated errors affect these SSH measurements, particularly in the cross-track direction. The scales of errors can be similar to the scales of ocean features. Conventionally, instrumental errors and ocean signals have been solved for independently in two stages. Here, we have developed a one-stage procedure that solves for the correlated error at the same time that data are assimilated into a dynamical ocean model. This uses the ocean dynamics to distinguish ocean signals from observation errors. We test its performance relative to the two-stage method using simplified dynamics and a data set consisting of westward propagating Rossby waves, along with correlated instrumental errors of varying magnitudes. In a series of tests, we found that the one-stage approach consistently outperforms the two-stage approach when estimating SSH signal and correlated errors. The one-stage approach can recover over 95% of the SSH signal, while skill for the two-stage approach drops significantly as error increases. Our findings suggest that solving for the correlated errors within the assimilation framework can provide an effective analysis approach, reducing the risks of confounding signal and instrument noise.
SFY — A lightweight, high-frequency and phase-resolving wave-buoy for coastal watersHope, Gaute; Seldal, Torunn Irene; Rabault, Jean; Bryhni, Helge Thomas; Bohlinger, Patrik; Björkqvist, Jan-Victor; Nordam, Tor; Kleven, Atle; Mostaani, Arsalan; Furevik, Birgitte Rugaard; Hole, Lars Robert; Storvik, Roger; Breivik, Øyvind
2025 Journal of Atmospheric and Oceanic Technology
doi: 10.1175/jtech-d-23-0170.1
AbstractSmall lightweight wave buoys, SFYs, designed to operate near the coast, have been developed. The buoys are designed to record and transmit the full time series of surface acceleration at 52 Hz. The buoy uses the cellular network to transfer data and position (up to 80 km from the base station). This reduces costs and increases band-width. The low cost and low weight permits the buoys to be deployed easily, and in arrays in areas where satellite and wave models struggle to resolve wave and current interaction. The buoys are tested in a wave-flume, the open water and in the breaking waves of the surf. The conditions range from calm to significant wave heights exceeding 7 m and crashing breakers with accelerations exceeding 10g. The high sample rate captures the impulse of breaking waves, and allows them to be studied in detail. Breaking waves are measured and quantified in the open water. We measure breaking waves in the surf and recover the trajectory of waves breaking in the field to a higher degree than previously done. The time series of surface elevation, and accurate positioning, permits the signal of adjacent buoys to be correlated in a coherent phase-resolved way. Finally, we offer an explanation and solution for the ubiquitous low-frequency noise in IMU-based buoys and discuss necessary sampling and design to measure in areas of breaking waves.
The Development of a Regional, High-Resolution OSSE Framework to Study the Impact of Observations from Uncrewed Aircraft Systems on Numerical Weather PredictionMurdzek, Shawn S.; Ladwig, Terra T.
2025 Journal of Atmospheric and Oceanic Technology
doi: 10.1175/jtech-d-24-0056.1
AbstractUsing Uncrewed Aircraft Systems (UAS) for routine weather observations is becoming increasingly feasible, but two open questions are the impact UAS observations will have on operational NWP and the optimal configuration of a UAS observing network. Deploying hundreds to thousands of UAS across the US to answer these questions is not feasible, so we propose using an Observing System Simulation Experiment (OSSE) instead. This article describes the development and validation of an OSSE framework for examining the impact of UAS observations on regional, convection-allowing NWP. The OSSE includes two week-long Nature Runs (NRs) over CONUS with 1-km grid spacing, simulated conventional observations, a 3-km forecast system similar to the prototype Rapid-Refresh Forecast System (RRFS), and verification workflows. Comparisons between the NR and various observations show that the NR generally mirrors reality, though the NR tends to produce too many reflectivity objects that are too large and larger coverage of intense precipitation rates compared to reality. Comparing real-data and OSSE RRFS runs indicates that, for the majority of the variables examined, forecast errors are not systematically smaller in the OSSE, suggesting that there is no identical twin issue. Data-denial experiments using either real or simulated conventional observations indicate that the OSSE has a similar ordering of most to least impactful observations, though the impact of aircraft observations tend to be larger in the OSSE. Altogether, these results suggest the OSSE framework can be used to glean meaningful information about UAS observation impacts on regional NWP.
The use of vertical gradients of radar reflectivity factor and radial velocity to diagnose dynamical and microphysical structures in extratropical cyclones: results from IMPACTSZaremba, Troy J.; Rauber, Robert M.
2025 Journal of Atmospheric and Oceanic Technology
doi: 10.1175/jtech-d-24-0016.1
AbstractThe Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms field campaign comprised three deployments in January and February of 2020, 2022, and 2023. Throughout these deployments, the NASA Earth Resources-2 (ER-2) aircraft conducted 26 research flights, equipped with three vertically pointing radars. These radars sampled the vertical structure of extratropical cyclone clouds at four distinct radar wavelengths, enabling a finer scale analysis of reflectivity and radial velocity structures within extratropical cyclones with a vertical sampling resolution of 26.5 m. In this analysis, we introduce a novel technique utilizing vertical gradients in radial velocity and reflectivity, which proved effective in identifying turbulence, waves, and layers of ascent over 132.5 m layers for all flight legs conducted during the campaign. The spatial scale of 132.5 m was chosen to capture fine-scale variations associated with small-scale turbulent eddies and shear zones in frontal regions. The gradient analysis aided in detecting small scale changes in reflectivity and radial velocity that might have gone unnoticed otherwise. Moreover, the corresponding gradients in reflectivity suggest potential interactions of falling ice crystals with turbulence, waves, and shear layers, possibly influencing the microphysical characteristics and the vertical spatial distribution of falling snow. The observed vertical gradients in radial velocity often exhibited linear, layered patterns, but in some instances displayed wave-like appearances, sloped patterns along frontal boundaries, or magnitude fluctuations. This paper focuses on presenting and detailing the vertical gradient technique to examine winter storms. Future work will involve a comprehensive analysis of these gradients in relation to dual-frequency radar measurements and in situ microphysical characteristics.