Figure - available from: Remote Sensing
This content is subject to copyright.
Proportion of error energy at different scales of background errors with the 2DVAR and AVISO methods with different background time average windows.

Proportion of error energy at different scales of background errors with the 2DVAR and AVISO methods with different background time average windows.

Source publication
Article
Full-text available
A satellite altimeter measures sea surface height (SSH) along the nadir track. Multiple satellite altimeters have been in orbit, and the measurements been merged for mapping mesoscale eddies of ~100 km in size in the oceans. The capability of the mapped SSH for resolving mesoscale eddies depends on mapping algorithms. A two-dimensional variational...

Similar publications

Article
Full-text available
Automatic ocean eddy identification algorithms are crucial for global eddy research. In this study, a scale-selective eddy identification algorithm (SEIA) that features improvements in the detection and tracking processes is presented for the global ocean based on sea level anomalies. First, the previous strategy of using thresholds to define eddy...

Citations

... An RMSE value of 0.11 indicates the average error level of the forecasting model on observational data. Differences in rising and falling patterns between these years may reflect variations in ocean dynamics influenced by various factors, such as climate change, ocean currents, or changes in seabed topography [29][30][31] . The context of SSH values in Batam waters from 2021 to 2023 reveals variations in the lowest and highest values that occur in specific months each year. ...
... Seven satellite altimeters are presently in orbit. Altimetry measurements are routinely available in near real time and can be merged to resolve eddies in 2 dimensions down to almost 100 km at midlatitudes [53,102,103]. A fleet of satellites carries infrared and microwave SST sensors that provide daily maps at an effective resolution of a few kilometers (e.g., [104,105]). ...
Article
Full-text available
Mesoscale eddies pervade the global ocean, characterized by a typical horizontal scale of approximately 100 km and a timescale on the order of a month. Forecasting these eddies is the primary objective in predicting the ocean’s “weather” over periods ranging from days to a month. This study provides a historical perspective on milestones in the evolution of successful mesoscale eddy-forecasting systems over the past half-century. Advances in eddy-resolving numerical models, observing systems, and, in particular, data assimilation (DA) algorithms have led to success in forecasting mesoscale eddies. Mesoscale eddies arise from baroclinic flow instabilities, making their forecast highly sensitive to initial conditions. A forecasting model must be appropriately initialized to generate subsequent forecasts successfully. DA integrates various observations into the model forecast, producing optimal estimates of the ocean state to initialize numerical models. An effective combination of observations from the Argo float observing network and a constellation of altimetry satellites is crucial for accurate estimates of the ocean state at the mesoscale through DA, ensuring success in forecasting mesoscale eddies. The temporal and spatial scales of the ocean state at different depths are greatly different. These ocean state characteristics pose multiple challenges in altimetry DA. To tackle these challenges, multiscale DA (MSDA) algorithms have been suggested, formulated, and implemented. Different strategies for the implementation of MSDA are discussed. The most pressing needs for further model development and enhancing mesoscale DA are outlined.
... Although there may be some deviations, this method remains effective in the absence of reliable independent data. Figure 9. Scatter plot distribution, fitting curve, correlation coefficient, correlation, and RMSE of geostrophic flow velocities (GDP) from AVISO1/8° and AVISO1/4° compared with buoy geostrophic flow velocities (GDP) (unit: m/s) [11]. Figure 9 presents a scatter plot distribution of the geostrophic flow velocities from both merged products compared to the buoy geostrophic flow velocities. ...
Article
Full-text available
Based on the orbital data of the Jason3 satellite, the absolute dynamic topography (ADT) of 1/8°×1/8° and 1/4°×1/4° products distributed by AVISO (hereinafter referred to as AVISO1/8° and AVISO1/4°) was interpolated into the Jason3 orbit, and the effective resolution and merged product error of the two products were evaluated with the Northwest Pacific Ocean as the target area. In addition, combined with independent SST data and drifting buoy data, the ground conversion field in the merged data was tested, and the results showed that although the spatial resolution of AVISO1/8° was doubled compared with AVISO1/4°, its effect was not significantly improved, and the error in some areas was even slightly greater than that of AVISO1/4°. Finally, these two merged datasets were used to identify mesoscale vortices. AVISO1/8° have higher precision and make identifying vortex structures easier. The two products are consistent in identifying vortices with relatively large radius, while there are differences in identifying vortices with relatively small radius.
... This Topic covers a wide range of topics, including atmospheric dynamics and physics, synoptic weather, climate variability, climate change, and remote sensing observations for weather and climate studies. There are a total of 29 research papers and two review papers published in "A Themed Issue in Memory of Academician Duzheng Ye (1916-2013)", comprising 14 in Atmosphere [1][2][3][4][5][6][7][8][9][10][11][12][13][14], 2 in Climate [15,16], and 15 in Remote Sensing [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. ...
... The second-to-last paper is on oceanic remote sensing data. Liu et al. [30] conducted a study to find the decorrelation length scale of background errors is a key factor for the two-dimensional variational method (2D-Var) to generate multi-satellite merged maps of altimeters with an effective resolution capable of capturing meso-scale eddies in the ocean. They conclude that having a higher proportion of small-scale signals and a smaller proportion of large-scale dynamic signals result in a smaller decorrelation length scale of background errors and thus a higher effective resolution of the merged altimeter data. ...
Article
Full-text available
This Topic covers a wide range of topics, including atmospheric dynamics and physics, synoptic weather, climate variability, climate change, and remote sensing observations for weather and climate studies [...]
Preprint
Full-text available
The recently launched Surface Water and Ocean Topography (SWOT) satellite mission has reduced the noise levels and increased resolution, thereby improving the ability to detect previously unobserved fine-scale signals. We employed a method to utilize the unique and advanced capabilities of SWOT to validate the accuracy of identified eddies in merged maps of a widely used Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) data product and a newly implemented two-dimensional variational method (2DVAR), which uses a 1/12° grid and reduces decorrelation of spatial length scales. The findings indicate that SWOT provides an enhanced capability in resolving fine-scale and mesoscale eddies in the South China Sea compared with conventional in-situ data, such as drifting buoys. The validation results demonstrated that compared with AVISO, the 2DVAR method exhibited greater consistency with the SWOT observations, especially at small scales, confirming the accuracy and capability of the 2DVAR method in the reconstruction and resolution of fine-scale oceanic dynamical structures.