Ocean ModellingPub Date : 2024-09-07DOI: 10.1016/j.ocemod.2024.102440
Juliana Franco Lima , Leandro Farina , Pedro Veras Guimarães , Ana Flávia Caetano Bastos , Pedro de Souza Pereira , Mauro Michelena Andrade
{"title":"The effect of shallow water bathymetry on swash and surf zone modeled by SWASH","authors":"Juliana Franco Lima , Leandro Farina , Pedro Veras Guimarães , Ana Flávia Caetano Bastos , Pedro de Souza Pereira , Mauro Michelena Andrade","doi":"10.1016/j.ocemod.2024.102440","DOIUrl":"10.1016/j.ocemod.2024.102440","url":null,"abstract":"<div><p>Submerged topography in shallow waters is fundamental in the propagation and dissipation of ocean waves in the surf and swash zones. However, obtaining accurate bathymetric data in this region is challenging due to the high temporal and spatial environmental variability. The bottom boundary condition can directly affect the accuracy of numerical models used for shallow water simulations. In this study, the performance of the SWASH numerical model in describing wave runup in the swash zone is assessed using different bathymetric boundary conditions. The first method involves using data measured in the surf zone obtained by a Unmanned Aerial Vehicle (UAV), and analyzing it using the cBathy algorithm. The second method utilizes a regular bathymetric mesh generated from Dean’s equilibrium profile combined with beach topography data. The third method relies exclusively on interpolation methods using data from deep waters and beach profiles. This interpolation approach is the most used among SWASH users when detailed or updated surf zone bathymetry is unavailable. Based on the numerical simulations performed, not incorporating data from the surf zone resulted in a 4% increase in the runup estimated and approximately a 2% difference in identifying the swash zone position. The method to obtain bathymetry through the cBathy algorithm, used in this article, is cost-effective and can be used to reduce uncertainties in surf zone numerical simulations, induced by the lack of knowledge about the bottom conditions.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"192 ","pages":"Article 102440"},"PeriodicalIF":3.1,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142163711","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}
Ocean ModellingPub Date : 2024-09-05DOI: 10.1016/j.ocemod.2024.102431
Liping Deng , Krishna Borhara , Parichart Promchote , Shih-Yu Wang
{"title":"Explainable AI in lengthening ENSO prediction from western north pacific precursor","authors":"Liping Deng , Krishna Borhara , Parichart Promchote , Shih-Yu Wang","doi":"10.1016/j.ocemod.2024.102431","DOIUrl":"10.1016/j.ocemod.2024.102431","url":null,"abstract":"<div><p>In this short communication, we report initial success in utilizing existing Explainable Artificial Intelligence (XAI) methodology to investigate an emerging precursor of the El Niño-Southern Oscillation (ENSO), manifest as sea surface temperature anomalies (SSTA) in the Western North Pacific (WNP), and its impact on enhancing ENSO prediction accuracy. Our analysis reveals that integrating WNP SSTA with established XAI techniques significantly increases the predictability of ENSO states. We found marked improvement in prediction accuracy, from a 60 % baseline to over 85 % for forecasting moderate warm, cold, and neutral ENSO states one year ahead. For higher magnitude events, precision surpasses 90 %. This work, intended as a follow-up to recent studies, underscores the potential of augmenting emerging XAI with additional SST signals to advance long-term climate forecasting capabilities.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"192 ","pages":"Article 102431"},"PeriodicalIF":3.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240421","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}
Ocean ModellingPub Date : 2024-08-31DOI: 10.1016/j.ocemod.2024.102426
Mathias Zeller, Torge Martin
{"title":"On warm bias and mesoscale dynamics setting the Southern Ocean large-scale circulation mean state","authors":"Mathias Zeller, Torge Martin","doi":"10.1016/j.ocemod.2024.102426","DOIUrl":"10.1016/j.ocemod.2024.102426","url":null,"abstract":"<div><p>A realistic representation of the Southern Ocean (SO) in climate models is critical for reliable global climate projections. However, many models are still facing severe biases in this region. Using a fully coupled global climate model at non-eddying (1/2<span><math><msup><mrow></mrow><mrow><mo>∘</mo></mrow></msup></math></span>) and strongly eddying (1/10<span><math><msup><mrow></mrow><mrow><mo>∘</mo></mrow></msup></math></span>) grid resolution in the SO, we investigate the effect of a 0.5 °C, 1.0 °C and 1.6 °C warmer than observed SO on i) the spin-up behaviour of the high-resolution simulation, and ii) the representation of main dynamical features, i.e., the Antarctic circumpolar current (ACC), the subpolar gyres, the overturning circulation and the Agulhas regime in a quasi-equilibrium state. The adjustment of SO dynamics and hydrography critically depends on the initial state and grid resolution. When initialised with an observed ocean state, only the non-eddying configuration quickly builds up a strong warm bias in the SO. The high-resolution configuration initialised with the biased non-eddying model state results in immense spurious open ocean deep convection, as the biased ocean state is not stable at eddying resolution, and thus causes an undesirable imprint on global circulation. The SO heat content also affects the large-scale dynamics in both low- and high-resolution configurations. A warmer SO is associated with a stronger Agulhas current and a temperature-driven reduction of the meridional density gradient at 45<span><math><msup><mrow></mrow><mrow><mo>∘</mo></mrow></msup></math></span>S to 65<span><math><msup><mrow></mrow><mrow><mo>∘</mo></mrow></msup></math></span>S and thus a weaker ACC. The eddying simulations have stronger subpolar gyres under warmer conditions while the response in the non-eddying simulations is inconsistent. In general, SO dynamics are more realistically represented in a mesoscale-resolving model at the cost of requiring an own spin-up.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102426"},"PeriodicalIF":3.1,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324001136/pdfft?md5=c824446514c61f0a304b3c0a1852f65a&pid=1-s2.0-S1463500324001136-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ocean ModellingPub Date : 2024-08-30DOI: 10.1016/j.ocemod.2024.102427
Yuxin Zhao, Dequan Yang, Jianxin He, Kexin Zhu, Xiong Deng
{"title":"Hierarchical stacked spatiotemporal self-attention network for sea surface temperature forecasting","authors":"Yuxin Zhao, Dequan Yang, Jianxin He, Kexin Zhu, Xiong Deng","doi":"10.1016/j.ocemod.2024.102427","DOIUrl":"10.1016/j.ocemod.2024.102427","url":null,"abstract":"<div><p>Sea surface temperature (SST) is a highly complex spatiotemporal variable, which stems from its susceptibility to non-linear dynamical processes and substantial spatiotemporal variability. In particular, accurately forecasting small-scale SST is a formidable challenge due to the compounded effects of diverse physical processes spanning across various scales. In this study, we employ deep learning methods to mine the ocean’s evolutionary patterns, as the ocean’s dynamic mechanisms are inherently embedded in spatiotemporal data. We propose a hierarchical stacked spatiotemporal self-attention mechanism (HSSSA) network architecture. The hierarchical stacked encoder–decoder architecture provides the capability for feature fusion and extraction at different scales. The spatial self-attention and temporal self-attention modules simultaneously focus on information from different spatial locations and time steps, allowing the exploration of spatiotemporal patterns in the complex dynamics of the ocean. The experiments are conducted on a high-resolution East China Sea dataset (<span><math><mrow><mn>1</mn><mo>/</mo><mn>10</mn><mo>°</mo><mo>×</mo><mn>1</mn><mo>/</mo><mn>10</mn><mo>°</mo></mrow></math></span>) to demonstrate the forecast performance of the proposed model for refined ocean variables. The 15-day forecasts indicate that the HSSSA method outperforms the EOF-ARIMA and CNN-Transformer methods.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102427"},"PeriodicalIF":3.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142097210","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}
Ocean ModellingPub Date : 2024-08-28DOI: 10.1016/j.ocemod.2024.102429
Yalin Fan , Zhitao Yu , Peter Sullivan , Adam Rydbeck
{"title":"Dependence of dense filament frontogenesis in a hydrostatic model","authors":"Yalin Fan , Zhitao Yu , Peter Sullivan , Adam Rydbeck","doi":"10.1016/j.ocemod.2024.102429","DOIUrl":"10.1016/j.ocemod.2024.102429","url":null,"abstract":"<div><p>In this study, a hydrostatic model - the Navy Coastal Ocean Model (NCOM) is used to analyze the temporal evolution of a cold filament under moderate wind (along / cross filament) and surface cooling forcing conditions. The experimental framework adhered to the setup used in large eddy simulations by Sulllivan and McWilliams (2018). For each forcing scenario, the impact of horizontal resolutions is systematically explored through varies model resolutions of 100 m, 50 m, and 20 m; and the influence of horizontal mixing is investigated by adjusting the Smagorinsky constant within the Smagorinsky horizontal mixing scheme. The role of surface gravity waves is also assessed by conducting experiments both with and without surface wave forcing.</p><p>The outcomes of our study revealed that while the hydrostatic model is able to predict the correct characteristics/physical appearance of filament frontogenesis, it fails to capture the precise dynamics of the phenomenon. Horizontal mixing parameterization in the model was found to have marginal effect on frontogenesis, and the frontal arrest is controlled by the model's subgrid-scale artificial regularization procedure instead of horizontal shear instability. Consequently, higher resolution is corresponding to stronger frontogenesis in the model. Thus, whether the hydrostatic model can produce realistic magnitude of frontogenesis is purely dependent on the characteristic of the front/filament simulated and model resolution. Moreover, examination of the parameterized effect of surface gravity wave forcing through vertical mixing unveiled a limited impact on frontogenesis, suggesting that the parameterization falls short in representing the real physics of wave-front interaction.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102429"},"PeriodicalIF":3.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324001161/pdfft?md5=9775941fed94aa12d3c2c40130b3625f&pid=1-s2.0-S1463500324001161-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ocean ModellingPub Date : 2024-08-27DOI: 10.1016/j.ocemod.2024.102428
Nícolas A. Bose , Leandro Farina
{"title":"A boundary perturbation approach for regional wave ensemble forecast","authors":"Nícolas A. Bose , Leandro Farina","doi":"10.1016/j.ocemod.2024.102428","DOIUrl":"10.1016/j.ocemod.2024.102428","url":null,"abstract":"<div><p>In this study, we developed and validated two wave ensemble prediction systems (WEPS) to forecast wave conditions along the southeastern coast of Australia. Using the SWAN model (GEN3 ST6), we integrated complex bathymetric features with an unstructured grid and validated model outputs against buoy observations from Sydney, Port Kembla, and Batemans Bay. The two WEPS, SWAN-WW3 and SWAN-Pert, utilize different methodologies: SWAN-WW3 derives boundary conditions from NCEP’s Global Wave Ensemble System, while SWAN-Pert employs Latin Hypercube Sampling for boundary perturbations based on historical data. Our results demonstrate that both systems effectively predict significant wave height (<span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span>), with SWAN-Pert showing improved forecast accuracy in certain metrics compared to SWAN-WW3. Despite underdispersion in spread-skill diagrams, both WEPS exhibited good agreement with observed data. Additionally, rank histograms revealed that SWAN-Pert is more reliable at shorter lead times. This study highlights the potential of integrating statistical sampling methods and ensemble systems for enhancing regional wave forecasting accuracy.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102428"},"PeriodicalIF":3.1,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142087313","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}
Ocean ModellingPub Date : 2024-08-23DOI: 10.1016/j.ocemod.2024.102421
Francesca De Santi , Marcello Vichi , Alberto Alberello
{"title":"Estimation of Antarctic sea ice thickness through observation of wave attenuation","authors":"Francesca De Santi , Marcello Vichi , Alberto Alberello","doi":"10.1016/j.ocemod.2024.102421","DOIUrl":"10.1016/j.ocemod.2024.102421","url":null,"abstract":"<div><p>The Close-Packing model – a physically based model for wave attenuation in sea ice – is used to infer sea ice thickness from wave observations collected in the Antarctic marginal ice zone during the PIPERS experiment. The model, calibrated for Arctic conditions, predicts ice thickness in good agreement with independent satellite measurements. The calibrated Close -Packing model, which is expressed in a simple monomial form, appears to have broad validity and, therefore, can be a suitable option for operational purposes.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102421"},"PeriodicalIF":3.1,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324001082/pdfft?md5=2b8eb58fd856e44da2b3b8a8061e889c&pid=1-s2.0-S1463500324001082-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142083993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ocean ModellingPub Date : 2024-08-20DOI: 10.1016/j.ocemod.2024.102425
Montri Maleewong, Roger Grimshaw
{"title":"Effect of atmospheric density stratification on the generation of water waves by wind","authors":"Montri Maleewong, Roger Grimshaw","doi":"10.1016/j.ocemod.2024.102425","DOIUrl":"10.1016/j.ocemod.2024.102425","url":null,"abstract":"<div><p>The critical level instability mechanism for the generation of water waves by wind is re-examined for the situation when the atmosphere is density stratified. The density stratification is confined to the middle and upper atmosphere and then two cases are investigated. In case (A) no internal gravity waves are generated in the upper atmosphere and the effect of the density stratification is very small. In case (B) vertically propagating internal gravity waves form in the upper atmosphere and travel to infinity causing an energy loss, thus inhibiting the critical level instability in the lower atmosphere. Both cases are examined quantitatively for a logarithmic wind shear profile.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102425"},"PeriodicalIF":3.1,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050050","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}
Ocean ModellingPub Date : 2024-08-19DOI: 10.1016/j.ocemod.2024.102420
Carlos E. Villarreal-Olavarrieta , Francisco J. Ocampo-Torres , Pedro Osuna , Rodney E. Mora-Escalante
{"title":"Effect of waves on the magnitude and direction of wind stress over the Ocean","authors":"Carlos E. Villarreal-Olavarrieta , Francisco J. Ocampo-Torres , Pedro Osuna , Rodney E. Mora-Escalante","doi":"10.1016/j.ocemod.2024.102420","DOIUrl":"10.1016/j.ocemod.2024.102420","url":null,"abstract":"<div><p>Correctly estimating the wind stress at the sea surface is of the utmost importance in models for climate studies, weather forecasting, and ocean–atmosphere interaction. The wind stress is mainly obtained by drag coefficient parameterizations, which always consider the wind stress to be aligned with the wind, but this is sometimes the case. Also, during moderate to weak wind conditions, these parameterizations may lead to high estimation errors due to the presence of swell. This study measured the wind stress with a high-rate (100 Hz) sonic anemometer mounted on a spar buoy. The sea state was also characterized by obtaining the directional spectrum of the waves by six wave-staff arrays sensing the free surface level at 10 Hz. Bouy’s movement was corrected by employing an inertial motion unit. The turbulent and wave-coherent wind stress components were also estimated and analyzed. It was observed that during swell conditions with wind traveling in the same direction, the wave-coherent wind stress component has an opposite direction to the wind and dampens the total wind stress magnitude. During counter-directional wind relative to swell events, the wave boundary layer is modified; swell produces a wave-coherent wind stress in the same direction as the wind, resulting in an enhanced total wind stress magnitude. The wave age, significant wave height, and the traveling direction of the swell relative to the wind are essential to correctly estimating the wind stress in swell-dominant conditions. A set of empirical parameterizations for each wind stress component is proposed.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102420"},"PeriodicalIF":3.1,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324001070/pdfft?md5=c4ea3556068250c5b25eb500665fbf6c&pid=1-s2.0-S1463500324001070-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ocean ModellingPub Date : 2024-08-14DOI: 10.1016/j.ocemod.2024.102424
Rui Sun , Sivareddy Sanikommu , Aneesh C. Subramanian , Matthew R. Mazloff , Bruce D. Cornuelle , Ganesh Gopalakrishnan , Arthur J. Miller , Ibrahim Hoteit
{"title":"Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model","authors":"Rui Sun , Sivareddy Sanikommu , Aneesh C. Subramanian , Matthew R. Mazloff , Bruce D. Cornuelle , Ganesh Gopalakrishnan , Arthur J. Miller , Ibrahim Hoteit","doi":"10.1016/j.ocemod.2024.102424","DOIUrl":"10.1016/j.ocemod.2024.102424","url":null,"abstract":"<div><p>We investigate the impact of ocean data assimilation using the Ensemble Adjustment Kalman Filter (EAKF) from the Data Assimilation Research Testbed (DART) on the oceanic and atmospheric states of the Red Sea. Our study extends the ocean data assimilation experiment performed by Sanikommu et al. (2020) by utilizing the SKRIPS model coupling the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. Using a 50-member ensemble, we assimilate satellite-derived sea surface temperature and height and in situ temperature and salinity profiles every three days for one year, starting January 01 2011. Atmospheric data are not assimilated in the experiments. To improve the ensemble realism, perturbations are added to the WRF model using several physics options and the stochastic kinetic energy backscatter (SKEB) scheme. Compared with the control experiments using uncoupled MITgcm with ECMWF ensemble forcing, the EAKF ensemble mean oceanic states from the coupled model are better or insignificantly worse (root-mean-square errors are 23% to −1.3% smaller), especially when the atmospheric model uncertainties are accounted for with stochastic perturbations. We hypothesize that the ensemble spreads of the air–sea fluxes are better represented in the downscaled WRF ensembles when uncertainties are well accounted for, leading to improved representation of the ensemble oceanic states from the new experiments with the coupled model. This indicates the ocean model assimilation will be improved with coupled models and may relax the need for operational centers to provide atmospheric ensembles to drive ocean forecasts. Although the feedback from ocean to atmosphere is included in this two-way regional coupled configuration, we find no significant effect of ocean data assimilation on the ensemble mean latent heat flux and 10-m wind speed over the Red Sea. This suggests that the improved skill using the coupled model is not from the two-way coupling, but from downscaling the ensemble atmospheric forcings (one-way coupled) to drive the ocean model.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"191 ","pages":"Article 102424"},"PeriodicalIF":3.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041116","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}