A hybrid ensemble adjustment Kalman filter based high‐resolution data assimilation system for the Red Sea: Implementation and evaluation

Toye, Habib; Sanikommu, Sivareddy; Raboudi, Naila Mohammed Fathi; Hoteit, Ibrahim

doi:10.1002/qj.3894

Cited by 5 publications

(2 citation statements)

References 140 publications

(198 reference statements)

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“…In order to improve the reliability of the sea ice hindcasting data, satellite remote sensing observations of sea ice concentration from the MODIS were assimilated into the NEMO3.6 ocean model using the Ensemble Adjustment Kalman Filter (EAKF) method. The EAKF method uses the dependency relationship and spatial correlation between variables in the model to estimate the optimal state variables of the model from a probabilistic and statistical perspective [23]. Figure 2 shows that the modeled sea ice concentration is closer to the satellite observation after EAKF assimilation.…”

Section: Sea Ice Hindcasting Modellingmentioning

confidence: 91%

Investigation of the Recent Ice Characteristics in the Bohai Sea in the Winters of 2005–2022 Using Multi-Source Data

Li,

Jiao,

Chen

et al. 2024

Water

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The safety of winter activities in the Bohai Sea requires more detailed information on ice characteristics and a more refined ice zone division. In the present study, 1/12°-resolution sea ice characteristic data were obtained based on the NEMO-LIM2 ice–ocean coupling model that assimilated MODIS satellite sea ice observations from the years of 2005 to 2022 to acquire new sea ice hindcasting data. On this basis, the ice period, ice thickness, ice concentration, ice temperature, ice salinity, and design ice thickness for different return periods in the 1/4°-resolution refined zoning were analyzed, which were then compared with the sea ice characteristics in the previous 21-ice-zone standard. The distribution of ice temperature and ice salinity was closely related to the distribution of ice thickness. The results of ice period, ice thickness, and ice concentration, as well as design ice thickness for different return periods, and the comparison with the previous 21-ice-zone standards, showed that the ice condition on the west coast of the Bohai Sea has significantly reduced.

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Section: Sea Ice Hindcasting Modellingmentioning

confidence: 91%

Investigation of the Recent Ice Characteristics in the Bohai Sea in the Winters of 2005–2022 Using Multi-Source Data

Li,

Jiao,

Chen

et al. 2024

Water

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“…The model was implemented on a spherical polar grid at an eddy-resolving horizontal resolution of 0.04 • × 0.04 • and 50 vertical layers, with 4 m spacing on the surface and 300 m spacing near the bottom. Full details of the model, assimilation scheme, and the resulting reanalysis can be found in [45,47,48].…”

Section: Methodsmentioning

confidence: 99%

Multi-Mission Satellite Detection and Tracking of October 2019 Sabiti Oil Spill in the Red Sea

et al. 2022

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A multi-mission satellite remote sensing (MSRS) approach is explored to detect and track leaked oil from the Sabiti oil tanker accident that occurred in the central Red Sea on 11 October 2019 (RSOS-2019). The spilled oil spread rapidly and reached the coastal land near Jeddah, the second largest city of KSA, on 17 October. Different oil spill detection algorithms were implemented on SAR and optical sensor-based satellite images to track the oil spill. Sentinel-1 SAR images were most efficient at detecting the spread and thickness of RSOS-2019, but their spatio-temporal coverage greatly limits their use for tracking the oil movement. The spread and propagation of oil were well captured by Sentinel-2 images up to three weeks after the accident day, in agreement with the SAR images. MODIS successfully detected the narrow patch of oil that was leaked on the incident day and the widespread oil patches two days after. Landsat-8 RGB composite and thermal infrared images captured the oil spill on 13 October. By filtering clouds from the Meteosat images through sequential analysis, the spread and movement of the oil patches were efficiently tracked on 13 October. PlanetScope images available between 12 and 17 October enabled tracking of the oil near the coastal waters. The inferred oil spill movements are consistent with the ocean currents as revealed by a high-resolution regional ocean reanalysis. Our results demonstrate the potential of the MSRS approach to detect and track oil spills in the open and coastal waters of the Red Sea in near real-time.

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Insights from very‐large‐ensemble data assimilation experiments with a high‐resolution general circulation model of the Red Sea

Sanikommu,

Raboudi,

El Gharamti

et al. 2024

Quart J Royal Meteoro Soc

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Ensemble Kalman Filters (EnKFs), which assimilate observations based on statistics derived from an ensemble of samples of ocean states, have become the norm for ocean data assimilation (DA) and forecasting. These schemes are commonly implemented with inflation and localization techniques to increase their ensemble spread and to filter out spurious long‐range correlations resulting from the limited‐size ensembles imposed by computational burden constraints. Such ad‐hoc methods were found to be not necessary in ensemble DA experiments with simplified ocean/atmospheric models and large ensembles. Here, we conduct a series of one‐year‐long ensemble experiments with a fully realistic EnKF‐DA system in the Red Sea using tens ‐to thousands of ensemble members. The system assimilates satellite and in‐situ observations and accounts for model uncertainties by integrating a 4‐km‐resolution ocean model with European Center for Medium Range Weather Forecast (ECMWF) atmospheric ensemble fields, perturbed internal physics and initial conditions for forecasting. OceanOur results indicate that accounting for model uncertainties is more beneficial than simply increasing the ensemble size, with the improvements due to large ensembles leveling off at about 250 members. Besides, and in contrast to what is commonly observed with simplified models, the investigated ensemble DA system still required localization even when implemented with thousands of members. These findings are explained by: (i) amplified spurious long‐range correlations produced by the low‐rank nature of the ECMWF atmospheric forcing ensemble; and (ii) non‐Gaussianity generated by the perturbed internal physical parameterization schemes. Large‐ensemble forcing fields and non‐Gaussian DA methods might be needed to get full benefits from large ensembles in ocean DA.

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A hybrid ensemble adjustment Kalman filter based high‐resolution data assimilation system for the Red Sea: Implementation and evaluation

Cited by 5 publications

References 140 publications

Investigation of the Recent Ice Characteristics in the Bohai Sea in the Winters of 2005–2022 Using Multi-Source Data

Investigation of the Recent Ice Characteristics in the Bohai Sea in the Winters of 2005–2022 Using Multi-Source Data

Multi-Mission Satellite Detection and Tracking of October 2019 Sabiti Oil Spill in the Red Sea

Insights from very‐large‐ensemble data assimilation experiments with a high‐resolution general circulation model of the Red Sea

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