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This study evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean (ECCO) data assimilation (DA) framework to a submesoscale-resolving model [Massachusetts Institute of Technology General Circulation Model (MITgcm), at 1-km grid resolution]. This is in preparation for future studies to understand and assimilate the novel swath measurements of sea surface height from the Surface Water and Ocean Topography (SWOT) satellite mission. The model domain is centered at the SWOT calibration/validation (CalVal) site, located 300 km offshore of Monterey Bay, California. We assimilate vertical profiles of temperature and salinity from a linear array of three SWOT prelaunch CalVal moorings, between September and December 2019. Two model solutions are analyzed: 1) a nonassimilating forward simulation termed "first-guess" and 2) an optimized solution that assimilates the in situ observations. Both runs are nested within the global 1/12° Hybrid Coordinate Ocean Model that uses Navy Coupled Ocean Data Assimilation (HYCOM/NCODA) analysis. We evaluate the performance by comparing the two model solutions against assimilated and withheld in situ observations. We show that by assimilating hydrographic data, the model performance over the first-guess solution is improved with an error-to-observation reduction of 30%–45% for temperature, 14%–41% for salinity, and 44%–56% for steric height. Over the study period, the average steric height error at the three assimilated moorings was 1.27 cm for the optimized solution versus 2.6 cm for the first-guess solution. A comparison to withheld glider observations shows that the optimized solution outperforms the first-guess solution with an error-to-observation reduction of approximately 38% in steric height (1.5 versus 2.4 cm). This study indicates, for the first time, that the MITgcm–ECCO framework can be successfully applied to the reconstruction of submesoscale ocean variability, via the nesting of a high-resolution regional domain into a global outer domain. [ABSTRACT FROM AUTHOR]

A data assimilation system for a high-resolution model has been developed to address the opportunities and challenges posed by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. This developed system is based on a three-dimensional variational data assimilation scheme (3DVAR), which is computationally highly efficient and thus can be applied to a very high-resolution model. A crucial consideration of the system is to use a multiscale data assimilation approach (MSDA) to first assimilate routinely available observations, including conventional satellite altimetry, sea surface temperature (SST) and salinity (SSS), and temperature/salinity vertical profiles, to constrain large scales and large mesoscales. High-resolution (dense) observations and future SWOT measurements can then be effectively and seamlessly assimilated to constrain the smaller scales. The 3DVAR is extended to assimilate observations over a time interval, which specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. Using this system, a reanalysis dataset was produced for the SWOT pre-launch field campaign that took place in the California Current System from September through December, 2019. An evaluation of this system with assimilated and withheld data demonstrates its ability to effectively utilize both routine and campaign observations to produce sea surface heights with the accuracy close to that required by SWOT. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will need the capability of jointly assimilating existing routine observations with SWOT measurements to resolve small-scale ocean processes. [ABSTRACT FROM AUTHOR]

The future Surface Water and Ocean Topography (SWOT) mission aims to map sea surface height (SSH) in wide swaths with an unprecedented spatial resolution and subcentimeter accuracy. The instrument performance needs to be verified using independent measurements in a process known as calibration and validation (Cal/Val). The SWOT Cal/Val needs in situ measurements that can make synoptic observations of SSH field over an O(100) km distance with an accuracy matching the SWOT requirements specified in terms of the along-track wavenumber spectrum of SSH error. No existing in situ observing system has been demonstrated to meet this challenge. A field campaign was conducted during September 2019–January 2020 to assess the potential of various instruments and platforms to meet the SWOT Cal/Val requirement. These instruments include two GPS buoys, two bottom pressure recorders (BPR), three moorings with fixed conductivity–temperature–depth (CTD) and CTD profilers, and a glider. The observations demonstrated that 1) the SSH (hydrostatic) equation can be closed with 1–3 cm RMS residual using BPR, CTD mooring and GPS SSH, and 2) using the upper-ocean steric height derived from CTD moorings enable subcentimeter accuracy in the California Current region during the 2019/20 winter. Given that the three moorings are separated at 10–20–30 km distance, the observations provide valuable information about the small-scale SSH variability associated with the ocean circulation at frequencies ranging from hourly to monthly in the region. The combined analysis sheds light on the design of the SWOT mission postlaunch Cal/Val field campaign. [ABSTRACT FROM AUTHOR]

After the surface water and ocean topography (SWOT) satellite launches in 2022, an in‐situ field campaign will be conducted to estimate the ocean state for calibration and validation (CalVal) purposes. It is demonstrably difficult to capture the sea surface height (SSH) features that are the focus of SWOT, with short time periods (<20 days) and fine‐scale spatial structures (15–150 km). Therefore, a critical component of the SWOT CalVal will be a data assimilation (DA) system coupled to a primitive equation numerical model that can estimate: (a) the 2D SSH over the SWOT swaths, and (b) the 3D dynamical (velocity) field. To explore the ability of DA to meet the challenges of SWOT fine‐scale observations, a multiscale DA system based on an extended 3D variational method has been developed. Here, we present a strategic evaluation of this DA system, with a focus to assimilate in‐situ data from an observing system to best represent the fine‐scale ocean variability at the CalVal site. The DA estimate is compared to independent observations taken during the 2019 pre‐launch field campaign 300‐km off Monterey Bay, California. The key result is this DA system can reconstruct the upper 500‐m steric height with O(1‐cm) error at hourly resolution, and subcentimeter error for periods longer than 2 days. Plain Language Summary: The surface water and ocean topography (SWOT) satellite mission is the first of its kind to launch. It will provide unprecedented measurements of the sea surface height in two dimensions (2‐D) and shorter spatial scales than previously possible. These measurements will allow oceanographers to study new scales of ocean variability and infer the ocean current velocity field. After SWOT launches, the accuracy of its measurements will need to be verified with observations made using standard instrumentation whose accuracy is well known. However, the cost to produce equivalent measurements for comparison with 2‐D high‐resolution SWOT observations is prohibitive, so the instruments to be deployed are only sufficient to evaluate a small portion of the satellite footprint. To better understand the satellite measurements, the plan is to combine the instrument measurements with a numerical ocean model that provides a four‐dimensional best‐estimate of the ocean state. This is called data assimilation (DA). In this paper, we evaluate a DA system developed to address these challenges, and show its successful performance using observations from a pre‐launch field campaign in 2019. Key Points: Data assimilation (DA) of routine observations of large/mesoscale circulation allows effective assimilation of mooring data at fine scalesMooring DA reconstructs 0‐ to 500‐m hourly steric height with O(1‐cm) error, and subcentimeter error for periods longer than 2‐dayDA performance relies on observing system design; capturing the 2D horizontal gradient field is important for SWOT evaluation [ABSTRACT FROM AUTHOR]

A state-of-the-art data assimilation system for a high-resolution model has been developed to address the opportunities and challenges posed by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. A new 'extended' three -dimensional variational data assimilation scheme (extended-3DVAR) is formulated to assimilate observations over a time interval, and integrated using a multi- scale approach (hereafter MSDA). The new MSDA scheme specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. This developed system is computationally highly efficient, and thus can be applied to a very high- resolution model. A crucial consideration of the system is first to assimilate routinely available observations, including satellite altimetry, sea surface temperature (SST) and temperature/salinity vertical profiles, to constrain large scales and large mesoscales. High-resolution (dense) observations and future SWOT measurements can then be effectively and seamlessly assimilated to constrain the smaller scales. Using this system, a reanalysis dataset was produced for the SWOT pre-launch field campaign that took place in the California Current System from September through December, 2019. An evaluation of this system with assimilated and withheld data demonstrates its ability to effectively utilize both routine and campaign observations. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will require the capability to efficiently assimilate large-volume datasets resolving small-scale ocean processes. [ABSTRACT FROM AUTHOR]

We present a mapping methodology to improve the resolution of gridded sea surface height (SSH) from multisatellite along-track measurements, and apply it in the California Current system. This is motivated by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission, which will collect novel high-resolution wide-swath SSH measurements. The calibration/validation of SWOT will be in the California Current and requires independent observations of SSH spatial variability. Our objective was to discover how far we could push the space--time resolution of SSH maps based on the existing altimetry constellation. Currently, the best SSH maps for the region are from AVISO's global product based on optimal interpolation (OI). Our methodology is based on 2-D variational analysis (2DVAR), and we address some limitations of the AVISO OI global parameterization that restrict the resolution. Key improvements are (1) use of a background field incorporating mesoscale information, as opposed to a long-term mean field; (2) optimized regional parameters; and (3) a representation error term in the observational error covariance matrix to account for the spread of measurements in time. Using a suite of independent remote and in situ observations, we show the 2DVAR method can produce higher-resolution SSH maps in the California Current region that successfully capture smaller-scale ocean features than AVISO, at the expense of an increase in noise. [ABSTRACT FROM AUTHOR]