High-Frequency Variations in Pearl River Plume Observed by Soil Moisture Active Passive Sea Surface Salinity

Liao, Xiaomei; Du, Yan; Wang, Tianyu; Hu, Shuibo; Zhan, Haigang; Liu, Huizeng; Wu, Guofeng

doi:10.3390/rs12030563

Cited by 5 publications

(3 citation statements)

References 47 publications

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“…The plumelike features and associated dynamics are similar to LLC270 in both runs. Additionally, the higher-resolution LLC540R resolves fine-scale plume structure for a number of major rivers, which was previously revealed by satellite observations, regional simulations, or neural network methods (e.g., meanders and rings of the AZ plume due to the NBC retroflection; Molleri et al, 2010); "horseshoe" patterns of the MR plume associated with Texas floods (Fournier et al, 2016b); and the bidirectional CO plume during variable summer wind patterns (Liu et al, 2009). Overall, EOF SSS analysis shows that general plume pattern and dynamics are grid independent; however, fine-scale plume structures are only resolved by high-resolution simulations.…”

Section: Eof Analysis Of Sssmentioning

confidence: 78%

“…When focusing on large river mouth regions (e.g., AZ, PA, and CJ), the SSS bias is reduced in LLC540R. This demonstrates that the choice of runoff forcing impacts SSS at predominantly local scales; however, background currents can transport the signal downstream or offshore to the open ocean (Liu et al, 2009;Molleri et al, 2010).…”

Section: Comparison With Smap and Woa18mentioning

confidence: 92%

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Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions

et al. 2021

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Abstract. In this study, we improve the representation of global river runoff in the Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) framework, allowing for a more realistic treatment of coastal plume dynamics. We use a suite of experiments to explore the sensitivity of coastal plume regions to runoff forcing, model grid resolution, and grid type. The results show that simulated sea surface salinity (SSS) is reduced as the model grid resolution increases. Compared to Soil Moisture Active Passive (SMAP) observations, simulated SSS is closest to SMAP when using daily, point-source runoff (DPR) and the intermediate-resolution LLC270 grid. The Willmott skill score, which quantifies agreement between models and SMAP, yields up to 0.92 for large rivers such as the Amazon. There was no major difference in SSS for tropical and temperate coastal rivers when the model grid type was changed from the ECCO v4 latitude–longitude–polar-cap grid to the ECCO2 cube–sphere grid. We also found that using DPR forcing and increasing model resolution from the coarse-resolution LLC90 grid to the intermediate-resolution LLC270 grid elevated the river plume area, volume, stabilized the stratification and shoal the mixed layer depth (MLD). Additionally, we find that the impacts of increasing model resolution from the intermediate-resolution LLC270 grid to the high-resolution LLC540 grid are regionally dependent. The Mississippi River Plume is more sensitive than other regions, possibly because the wider and shallower Texas–Louisiana shelf drives a stronger baroclinic effect, as well as relatively weak sub-grid vertical mixing and adjustment in this region. Since rivers deliver large amounts of freshwater and anthropogenic materials to coastal regions, improving the representation of river runoff in global, high-resolution models will advance studies of coastal hypoxia, carbon cycling, and regional weather and climate and will ultimately help to predict land–ocean–atmospheric feedbacks seamlessly in the next generation of Earth system models.

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Section: Eof Analysis Of Sssmentioning

confidence: 78%

Section: Comparison With Smap and Woa18mentioning

confidence: 92%

Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions

et al. 2021

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“…Temporal variability of river runoff from estuaries is as well an important factor (Cole et al., 2020). Moreover, the offshore transport of freshwater is also driven concurrently by wind forcing or offshore currents at various time scales (Liao et al., 2020). These factors all together determine the complexity of estuarine dynamics.…”

Section: Introductionmentioning

confidence: 99%

Data‐Driven Method With Numerical Model: A Combining Framework for Predicting Subtropical River Plumes

Wang

Jiang

et al. 2022

JGR Oceans

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Numerical models are of fundamental usage for estuarine and coastal sciences. Although numerical simulations are widely applied, analyzing and improving them are often challenging tasks given their large volume and huge parameter space. In this study, a novel data‐driven framework is introduced to study the Minjiang River Plume (MJRP). The framework combines Self‐Organizing Map (SOM) clustering with a Hidden Markov Model (HMM). A three‐dimensional Regional Ocean Model System for MJRP is first configurated with realistic atmospheric, oceanic, and riverine forcings. By applying SOM clustering to the modeled sea surface salinity (SSS) with ∼2,000 2‐day averaged records from 2010 to 2020, we identify six major patterns of MJRP. Each pattern exhibits distinct circulation and plume structures. These MJRP patterns contain not only seasonal signals, but also rich short‐term variabilities driven by the riverine inputs and oceanic dynamics. Then, the SOM‐HMM method was applied to predict the future of the hidden state (i.e., patterns of MJRP) from the observable states (wind and river runoff). With a hypothetic SSS product from a geostationary satellite as the ground truth, we show that the SOM‐HMM method can predict MJRP patterns considerably high prediction accuracy and computational efficiency. Further, these patterns were translated back to SSS with high forecast skills. Combining a conventional numerical model with a data‐driven method, this approach can be promisingly applied in the short‐term marine forecast to support the utilization and management of other estuaries.

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Two-Decade Variability of Sea Surface Temperature and Chlorophyll-a in the Northern South China Sea as Revealed by Reconstructed Cloud-Free Satellite Data

Zhao

et al. 2021

IEEE Trans. Geosci. Remote Sensing

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High-Frequency Variations in Pearl River Plume Observed by Soil Moisture Active Passive Sea Surface Salinity

Cited by 5 publications

References 47 publications

Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions

Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions

Data‐Driven Method With Numerical Model: A Combining Framework for Predicting Subtropical River Plumes

Two-Decade Variability of Sea Surface Temperature and Chlorophyll-a in the Northern South China Sea as Revealed by Reconstructed Cloud-Free Satellite Data

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