Ocean Modelling最新文献

{"title":"The fastest growing initial error and identification of sensitive area for targeted observation in predicting the Kuroshio intrusion into the South China Sea with a high-resolution regional ocean model","authors":"Peng Liang ,&nbsp;Yonghao Liang ,&nbsp;Qiang Wang ,&nbsp;Lina Yang ,&nbsp;Tianyu Zhang","doi":"10.1016/j.ocemod.2026.102679","DOIUrl":"10.1016/j.ocemod.2026.102679","url":null,"abstract":"<div><div>Kuroshio intrusion (KI) is a critical linkage between the Pacific and the South China Sea (SCS), profoundly influencing the variability of marine dynamical and ecological processes of the SCS. Due to the complex mechanism and the lack of predictability study on KI, the accuracy of KI prediction remains limited. This study obtains the fastest growing initial errors (FGIEs) of KI using the Regional Ocean Modelling System (ROMS) and conditional nonlinear optimal perturbation (CNOP) method. Specifically, the CNOP, which is an effective method in calculating FGIEs in a nonlinear system, refers to the perturbation that can lead to the maximum of an objective function at a target time under certain constraints. The calculation results reveal two types of FGIEs with similar spatial patterns but opposite signs. When superimposed on the background field, both types of errors exhibit rapid growth and northwestward propagation. At prediction time, the CNOP+ (with positive sea surface height error) and CNOP- (with negative sea surface height error) errors respectively cause significant overestimation and underestimation of KI. Notably, CNOP- errors may even lead to complete failure in predicting the occurrence of KI. The rapid error growth primarily originates from barotropic instability induced by the zonal velocity shear of the reference state. Sensitive areas for targeted observations, identified through vertical integration of initial total energy error, extend northwestward from the southern Luzon Strait to the interior SCS, centered near 120.5°E, 20°N. Remarkably, removing initial errors within this sensitive area (covering merely 0.1 % of the total model domain) can improve KI prediction accuracy most effectively, by 25 %∼38 %. This research provides an effective guidance for the design of targeted observation strategies, having great significance in improving the prediction skill of KI.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"201 ","pages":"Article 102679"},"PeriodicalIF":2.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing basin scale modelling for projecting storm surge extremes under climate change scenarios in northwest Ireland","authors":"Tasneem Ahmed ,&nbsp;Andrea Cucco ,&nbsp;Giovanni Quattrocchi ,&nbsp;Leo Creedon ,&nbsp;Iulia Anton ,&nbsp;Michele Bendoni ,&nbsp;Stefano Taddei ,&nbsp;Carlo Brandini ,&nbsp;Salem S Gharbia","doi":"10.1016/j.ocemod.2025.102660","DOIUrl":"10.1016/j.ocemod.2025.102660","url":null,"abstract":"<div><div>This study evaluates the performance of the SHYFEM (System of HydrodYnamic Finite Element Modules) ocean model in simulating storm surges within Donegal Bay (northwest Ireland) for climate projection applications. A high-resolution Basin Scale Model (BSM) configuration of SHYFEM, spanning the North Atlantic is employed in barotropic mode accounting exclusively for atmospheric forcing with no tidal contribution included. To evaluate its accuracy, the BSM is compared against a Limited Area Model (LAM) configuration of SHYFEM implemented at the same study site.</div><div>The LAM includes tidal constituents through the downscaling of sea surface height (SSH) from a calibrated deep-water ocean model provided by the Copernicus Marine Environment Monitoring Service (CMEMS). Comparison is performed to quantify the impact of non-linear tide-surge interaction on residual water levels computation.</div><div>On average the LAM achieves 3 cm greater accuracy than the BSM in reproducing the time series of residual water levels measured by four tide gauges within the bay. Nevertheless, although both models tend to underestimate the extreme values, the BSM better captures the climatological statistics of storm surge events, closely matching the observed return levels associated with 5, 10, 25, and 50 year return periods.</div><div>Further improvements in return level estimates and residual water level error metrics are obtained through iterative calibration of main model parameters, validating the BSM’s effectiveness in simulating storm surges despite the absence of tide-surge interaction.</div><div>A Chi-squared significance test applied to tide gauge observations confirms that tide-surge interaction is statistically non-significant within Donegal Bay for surge thresholds at the 99th, 99.95th, and 99.99th percentiles. These findings support the use of BSM, driven exclusively with atmospheric fields (without including tides), for reliable simulation of storm surges and their climatological statistics in this region.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"200 ","pages":"Article 102660"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of a layered snow density evolution scheme on Arctic snow and sea ice simulation in the CICE sea ice model","authors":"Hao Yin ,&nbsp;Jie Su ,&nbsp;Jiping Liu ,&nbsp;Mingfeng Wang","doi":"10.1016/j.ocemod.2025.102640","DOIUrl":"10.1016/j.ocemod.2025.102640","url":null,"abstract":"<div><div>Snow density plays crucial roles in snow and sea ice thermodynamics. However, current coupled global climate models typically rely on empirical constants for snow properties in sea ice model components, limiting our understanding of how snow processes influence snow and sea ice evolution. To address this, we implemented a layered snow density parameterization in the Los Alamos Sea Ice Model (CICE), which explicitly considers strain compaction, wind-driven compaction, and fresh snow deposition. Compared to the control run, our experiments show that this scheme reduces wintertime positive bias in snow depth and cold bias in snow temperature in the Arctic. The reduction in winter conductivity heat loss accounts for the improvement in temperature biases, resulting in an enhanced net surface energy gain in the winter. Eighty-five percent of this additional energy gain is attributed solely to the density-dependent variation of the snow thermal conductivity over the Arctic. Further spatiotemporal analysis reveals distinct seasonal difference in the drivers of snow depth and density changes. Wind compaction and snowfall emerge as competing processes in winter, while ablation dominates during June and July. Their contributions to pan-Arctic multi-year mean snow density change are +0.161 (wind compaction), -0.198 (snowfall), +0.016 (strain compaction), +0.012 (phase changes), and -0.003 (snow-ice) kg·m^-3·hr^-1. The corresponding rates of snow depth changes are -0.095, +0.277, -0.020, -0.103, and -0.009 cm·day^-1.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"199 ","pages":"Article 102640"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of wind-generated shallow water waves in a Benney–Luke equation","authors":"Montri Maleewong ,&nbsp;Roger Grimshaw","doi":"10.1016/j.ocemod.2025.102659","DOIUrl":"10.1016/j.ocemod.2025.102659","url":null,"abstract":"<div><div>In our recent papers Maleewong and Grimshaw (2024b, 2025), we used the Korteweg–de Vries (KdV) equation and its two-dimensional extension, the Kadomtsev–Petviashvili (KP) equation to describe the evolution of wind-driven water wave packets in shallow water. Both equations were modified to include the effect of wind forcing, modelled using the Miles critical level instability theory. In this paper that is extended to a Benney–Luke (BL) equation, similarly modified for wind forcing. The motivation is that the BL equation is isotropic in the horizontal space variables, unlike the KP model, and noting that the KdV model is one-dimensional. The modified BL equation is studied using wave modulation theory as in our previous work on the forced KdV and KP equations, and with comprehensive numerical simulations. Despite the very different spatial structure the results show that under the right initial conditions and parameter settings, solitary wave trains again emerge.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"200 ","pages":"Article 102659"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind-driven exchange flow and inter-basin connectivity in a multi-inlet bay during hurricane and non-hurricane periods","authors":"Wei Huang ,&nbsp;Chunyan Li ,&nbsp;Arnoldo Valle-Levinson ,&nbsp;Daniel Gann ,&nbsp;Michael C. Sukop ,&nbsp;Jayantha T. Obeysekera ,&nbsp;Tiffany Troxler","doi":"10.1016/j.ocemod.2025.102624","DOIUrl":"10.1016/j.ocemod.2025.102624","url":null,"abstract":"<div><div>This study quantifies wind-induced water volume exchanges through bay-ocean interfaces and among sub-bays of a multiple-inlet estuary, Biscayne Bay in Florida. The bay is elongated and oriented roughly in the north-south direction. Numerical simulations were conducted for both typical and extreme (Hurricane Irma) wind conditions. Results show that wind forcing accounts for 〈 10 % of total volume exchanges during typical winds but for 〉 60 % during hurricane conditions. Further, volume transport through seven inlets and five inter-basin transects is mainly driven by the North wind component (∼ parallel to the orientation of the bay). As a result, the major outflow through inlets is related to Ekman transport driven by southerly (or northward) winds. Except for the fifth inlet, volume transport through all the other six inlets is outward under southerly wind (R²&gt;0.65). In contrast, southward inter-basin transports are mainly driven by northerly (or southward) wind and northward transports by southerly (or northward) wind. Inter-basin volume transport is highly related with the N-S wind (R² &gt;0.74), i.e., the northward/southward transport is in line with the southerly/northerly wind. Additionally, the forcing-response joint Empirical Orthogonal Function (EOF) analysis shows that Biscayne Bay exhibits only one predominant exchange pattern, which explains &gt; 90 % under typical winds and &gt; 80 % during hurricane winds.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"199 ","pages":"Article 102624"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145007745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local effect of a submesoscale parameterization scheme and its remote influences on large-scale circulation in the Northwest Pacific","authors":"Ziyi Zhang ,&nbsp;Bo An ,&nbsp;Zhiwei Zhang ,&nbsp;Yuyang Guo ,&nbsp;Jinchao Zhang ,&nbsp;Zhe Feng ,&nbsp;Yongqiang Yu","doi":"10.1016/j.ocemod.2025.102650","DOIUrl":"10.1016/j.ocemod.2025.102650","url":null,"abstract":"<div><div>Submesoscale processes play important roles in vertical heat and mass transport, modulating mesoscale eddies and the energy cycle; thus a parameterization is essential for most ocean models due to submesoscale’s spatial scales (∼100 m–10 km). This study describes the impact of the submesoscale parameterization scheme by Zhang et al. (2023; Zhang23) in a regional eddy-resolving ocean model in the North Pacific. Compared with the numerical experiment without the scheme, the simulated winter mixed-layer depth (MLD) bias is reduced by 70 % in the Kuroshio Extension (KE) region and the KE jet shifted southward from 36.5°N to 35.5°N, closer to observations. Surface cold biases at 32°–34°N and subsurface warm biases at 36–40°N are reduced by ∼1 °C and ∼2 °C across four seasons, respectively. The effect of submesoscale vertical buoyancy fluxes (VBF) on winter MLD is debated. While widely shown to promote basin-scale shoaling via restratification, they are also known to cause powerful, localized deepening in regions with strong fronts and air-sea interaction. Focusing on this latter scenario, our study reveals a more detailed mechanism, notably distinguishing between local (direct) and remote (indirect) impacts on circulation in the mixed layer and subsurface. Enhanced submesoscale VBF drives weather-scale MLD deepening and subduction along tilted isopycnals in boreal winter in the most active eddy region, mainly limited to 38°–42°N/140°–150°E, promoting southward subsurface cooling and strengthening ocean memory. This feedback modulates the KE's large-scale circulation by shifting its path southward, reducing downstream heat transport, and promoting stratification and shoaling in the eastern region throughout all seasons. These findings demonstrate the importance of submesoscale parameterization for improving simulations of western boundary current systems and highlight its effects in representing remote and subsurface dynamic processes.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"199 ","pages":"Article 102650"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving multi-variable wave forecasting with AI: Integrating LSTM and random forest, using a window and flatten technique","authors":"Nerea Portillo Juan,&nbsp;Mónica Ferrer Gómez-Cano,&nbsp;Sara Yagüe Rubio,&nbsp;Vicente Negro Valdecantos","doi":"10.1016/j.ocemod.2025.102638","DOIUrl":"10.1016/j.ocemod.2025.102638","url":null,"abstract":"<div><div>Accurate wave prediction is essential for coastal and ocean engineering, as sea state conditions directly impact the design and operation of marine infrastructure, renewable energy systems, and maritime safety. While most research focuses on forecasting significant wave height (Hs) using increasingly complex models, other essential variables such as wave period (Tp) and direction (Dir) are often overlooked despite their importance in fully characterizing sea states.</div><div>This study addresses this gap by applying Artificial Intelligence (AI) models – Long Short-Term Memory (LSTM) networks and Random Forests (RF) – to predict Hs, Tp, and Dir. A novel window and flatten technique was introduced to restructure temporal data into a format suitable for machine learning, enhancing model performance for Dir and Tp predictions. Both models were tested under various wave conditions in the Mediterranean Sea</div><div>Results show that LSTM generally outperforms RF, particularly for Dir. However, RF models, which are not inherently designed for time series tasks, performed surprisingly well for Hs prediction and for short term Tp predictions. This opens promising avenues for developing hybrid models that combine sequential and non-sequential methods, potentially surpassing traditional sequence-to-sequence approaches in accuracy and robustness.</div><div>The study also highlights the challenge of accurately modelling Tp and the importance of evaluating model performance under varying energy conditions. Significant sensitivity to testing scenarios was observed, underlining the need for careful dataset selection and model validation. These findings provide a foundation for extending wave forecasting tools to more energetic environments such as the Atlantic Ocean and for advancing hybrid AI-based prediction frameworks.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"199 ","pages":"Article 102638"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling wave dissipation and mean water level over salt marshes","authors":"Laura Lavaud ,&nbsp;Xavier Bertin ,&nbsp;Kévin Martins","doi":"10.1016/j.ocemod.2025.102672","DOIUrl":"10.1016/j.ocemod.2025.102672","url":null,"abstract":"<div><div>Besides its well-known capacity to dissipate wave energy, salt marsh vegetation can also affect wave setup, although this mechanism has been much less studied and quantified so far. This study reports on a field experiment conducted under moderate energy conditions across a French Atlantic salt marsh. The data analysis is complemented with numerical simulations performed with the 3D fully-coupled wave–current modelling system SCHISM. While the model could already resolve vegetation-induced drag on mean currents and turbulence, it was here extended to account for vegetation intrawave drag effects and the wave force associated with vegetation-induced dissipation. Using published lab data, we first verify the model’s capacity to reproduce wave dissipation by vegetation and its effect on mean water levels, namely a reduction in wave setup, which is controlled by wave–current-vegetation interactions including intrawave processes. In the field, the model also demonstrates good predictive skills in simulating wave parameters across vegetation and suggests that vegetation can decrease the wave setup. However, this last process was too modest to be measured with pressure transducers, calling for future field experiments under storm conditions. This capacity of vegetation to reduce nearshore mean water levels should be thoroughly considered when evaluating the potential of salt marshes as nature-based coastal protection. This study places the SCHISM model as a state-of-the-art, efficient tool to simulate 3D multi-scale wave–current processes over vegetation ecosystems. Our results finally highlight that vegetation and depth-induced breaking induce a frequency-dependent dissipation, whose representation in phase-averaged models is presently limited and will require future research.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"200 ","pages":"Article 102672"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"West-East asymmetry in the South Pacific Western subtropical mode water","authors":"Xueying Wang,&nbsp;Yiyong Luo,&nbsp;Yingying Wang,&nbsp;Ruiyi Chen","doi":"10.1016/j.ocemod.2025.102670","DOIUrl":"10.1016/j.ocemod.2025.102670","url":null,"abstract":"<div><div>This study investigates the spatio-temporal variability and forcing mechanisms of the South Pacific western subtropical mode water (SPWSTMW) using the RG-Argo observations and the eddy-resolving GLORYS12 reanalysis from 2004 to 2023. The SPWSTMW exhibits pronounced zonal asymmetries in both its variability and forcing processes. To better understand these west-east asymmetries, we divide the SPWSTMW into the West (150°E–160°E) and East (160°E–170°W) types. On a seasonal timescale, the West type forms approximately one month earlier than the East type, primarily due to enhanced heat convergence from the mean flow and associated eddies of the East Australian Current. These oceanic processes effectively offset winter surface heat loss, accelerating upper-ocean restratification and subduction. On an interannual timescale, the East type volume correlates strongly with El Niño-Southern Oscillation (ENSO) through direct atmospheric forcing. However, the West type volume shows no significant correlation with ENSO, resulting from the complex interaction of surface heat flux, mean flow-induced heat convergence, and eddy-induced heat convergence. These findings underscore the critical role of regional ocean dynamics in modulating SPWSTMW variations.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"200 ","pages":"Article 102670"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surface current detection in regional seas using Lagrangian coherent structures","authors":"Huy Cong Vu,&nbsp;Binh Quang Nguyen","doi":"10.1016/j.ocemod.2025.102647","DOIUrl":"10.1016/j.ocemod.2025.102647","url":null,"abstract":"<div><div>Eddies play a vital role in the transport of heat, salt, and other materials, as well as in shaping the circulation structure of the ocean. Understanding eddies is therefore essential for elucidating the mechanisms that govern the formation, evolution, and variability of ocean currents. This study aims to analyze the characteristics of ocean currents in the East Vietnam Sea (South China Sea–SCS) by combining two approaches: the Euler method and the Lagrangian Coherent Structures (LCS) method. This integrated approach provides a comprehensive understanding of current dynamics and eddy formation. Using velocity vector images (Euler method), the study identifies the direction, location, and intensity of major ocean currents in the SCS. Meanwhile, the LCS method is applied to detect and delineate the boundaries and sizes of eddies. The ocean current data were obtained from the global HYCOM model on a daily basis throughout 2023. Our findings indicate that: (i) ocean currents in the SCS exhibit a clear seasonal pattern. In winter, the dominant flow moves from north to south along the Vietnamese coast, while in summer, the flow reverses, moving from south to north, with a disruption near 11 °N close to the Vietnamese coast. The current can extend up to 220 km near China, narrowing to 56 km as it approaches Vietnam. (ii) A table summarizing the characteristics of eddies with diameters greater than 100 km is included. The number of eddies is higher during the summer, but larger eddies tend to occur during the winter. In addition to single eddies, the SCS is also home to double and triple eddies.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"199 ","pages":"Article 102647"},"PeriodicalIF":2.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}