Geoscientific Model Development最新文献

{"title":"Open-ocean tides simulated by ICON-O, version icon-2.6.6","authors":"Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, V. Singh","doi":"10.5194/gmd-16-5179-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5179-2023","url":null,"abstract":"Abstract. This paper evaluates barotropic tides simulated by a newly developed multi-layer ocean general circulation, ICON-O, and assesses processes and model configurations that can impact the quality of the simulated tides. Such an investigation is crucial for applications addressing internal tides that are much more difficult to evaluate than the barotropic tides.\u0000Although not specially tuned for tides and not constrained by any observations, ICON-O is capable of producing the main features of the open-ocean barotropic tides as described by the geographical distributions of amplitude, phase, and amphidromic points. An error analysis shows, however, that the open-ocean tides simulated by ICON-O are less accurate than those simulated by two other ocean general circulation models (OGCMs), especially when not properly adjusting the time step and the parameters used in the time-stepping scheme. Based on a suite of tidal experiments, we show that an\u0000increase in horizontal resolution only improves tides in shallow waters. Relevant for using ICON-O with its telescoping grid capacity, we show that spatial inhomogeneity does not deteriorate the quality of the simulated tides. We further show that implementing a parameterization of topographic wave drag improves the quality of the simulated tides in deep ocean independent of the model configuration used, whereas the implementation of a self-attraction and loading (SAL) parameterization in a low-resolution (40 km) version of ICON-O degrades the quality of tides in shallow ocean.\u0000Finally, we show that the quality of tides simulated by ICON-O with low resolution (40 km) can be significantly improved by adjusting the time step or the parameters in the time-stepping scheme used for obtaining the model solution.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49307180","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":"Improved representation of volcanic sulfur dioxide depletion in Lagrangian transport simulations: a case study with MPTRAC v2.4","authors":"Mingzhao Liu, L. Hoffmann, S. Griessbach, Z. Cai, Yi Heng, Xue Wu","doi":"10.5194/gmd-16-5197-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5197-2023","url":null,"abstract":"Abstract. The lifetime of sulfur dioxide (SO2) in the Earth's atmosphere varies from orders of hours to weeks, mainly depending on whether cloud water is present or not. The volcanic eruption on Ambae Island, Vanuatu, in July 2018 injected a large amount of SO2 into the upper troposphere and lower stratosphere (UT/LS) region with abundant cloud cover. In-cloud removal is therefore expected to play an important role during long-range transport and dispersion of SO2. In order to better represent the rapid decay processes of SO2 observed by the Atmospheric Infrared Sounder (AIRS) and the TROPOspheric Monitoring Instrument (TROPOMI) in Lagrangian transport simulations, we simulate the SO2 decay in a more realistic manner compared to our earlier work, considering gas-phase hydroxyl (OH) chemistry, aqueous-phase hydrogen peroxide (H2O2) chemistry, wet deposition, and convection. The either newly developed or improved chemical and physical modules are implemented in the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) and tested in a case study for the July 2018 Ambae eruption. To access the dependencies of the SO2 lifetime on the complex atmospheric conditions, sensitivity tests are conducted by tuning the control parameters, e.g., by changing the release height, the predefined OH climatology data, the cloud pH value, the cloud cover, and other variables. Wet deposition and aqueous-phase H2O2 oxidation remarkably increased the decay rate of the SO2 total mass, which leads to a rapid and more realistic depletion of the Ambae plume. The improved representation of chemical and physical SO2 loss processes described here is expected to lead to more realistic Lagrangian transport simulations of volcanic eruption events with MPTRAC in future work.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46469224","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":"Metrics for evaluating the quality in linear atmospheric inverse problems: a case study of a trace gas inversion","authors":"Vineet Yadav, Subhomoy Ghosh, Charles E. Miller","doi":"10.5194/gmd-16-5219-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5219-2023","url":null,"abstract":"Abstract. Several metrics have been proposed and utilized to diagnose the performance of linear Bayesian and geostatistical atmospheric inverse problems. These metrics primarily assess the reductions in the prior uncertainties, compare modeled observations to true observations, and check distributional assumptions. Although important, these metrics should be augmented with a sensitivity analysis to obtain a comprehensive understanding of the atmospheric inversion performance and improve the quality and confidence in the inverse estimates. In this study, we derive closed-form expressions of local sensitivities for various input parameters, including measurements, covariance parameters, covariates, and a forward operator. To further enhance our understanding, we complement the local sensitivity analysis with a framework for a global sensitivity analysis that can apportion the uncertainty in input parameters to the uncertainty associated with inverse estimates. Additionally, we propose a mathematical framework to construct nonstationary correlation matrices from a precomputed forward operator, which is closely tied to the overall quality of inverse estimates. We demonstrate the application of our methodology in the context of an atmospheric inverse problem for estimating methane fluxes in Los Angeles, California.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45323578","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":"Hazard assessment modeling and software development of earthquake-triggered landslides in the Sichuan–Yunnan area, China","authors":"Xiaoyi Shao, Si-yuan Ma, Chong Xu","doi":"10.5194/gmd-16-5113-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5113-2023","url":null,"abstract":"Abstract. To enhance the timeliness and accuracy of spatial prediction of\u0000coseismic landslides, we propose an improved three-stage spatial prediction\u0000strategy and develop corresponding hazard assessment software named\u0000Mat.LShazard V1.0. Based on this software, we evaluate the applicability of\u0000this improved spatial prediction strategy in six earthquake events that have\u0000occurred near the Sichuan–Yunnan region, including the Wenchuan, Ludian,\u0000Lushan, Jiuzhaigou, Minxian, and Yushu earthquakes. The results indicate that\u0000in the first stage (immediately after the quake event), except for the 2013\u0000Minxian earthquake, the area under the curve (AUC) values of the modeling performance are above 0.8. Among them, the AUC value of the Wenchuan\u0000earthquake is the highest, reaching 0.947. The prediction results in the\u0000first stage can meet the requirements of emergency rescue by immediately\u0000obtaining the overall predicted information of the possible coseismic\u0000landslide locations in the quake-affected area. In the second and third\u0000stages, with the improvement of landslide data quality, the prediction\u0000ability of the model based on the entire landslide database is gradually\u0000improved. Based on the entire landslide database, the AUC value of the six\u0000events exceeds 0.9, indicating a very high prediction accuracy. For the\u0000second and third stages, the predicted landslide area (Ap) is relatively\u0000consistent with the observed landslide area (Ao). However, based on the\u0000incomplete landslide data in the meizoseismal area, Ap is much smaller than\u0000Ao. When the prediction model based on complete landslide data is built, Ap\u0000is nearly identical to Ao. This study provides a new application tool for\u0000coseismic landslide disaster prevention and mitigation in different stages\u0000of emergency rescue, temporary resettlement, and late reconstruction after a\u0000major earthquake.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43488740","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":"Use of threshold parameter variation for tropical cyclone tracking","authors":"Bernhard M. Enz, Jan P. Engelmann, U. Lohmann","doi":"10.5194/gmd-16-5093-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5093-2023","url":null,"abstract":"Abstract. Assessing the capacity of numerical models to produce viable tropical cyclones, as well as assessing the climatological behavior of simulated tropical cyclones, requires an objective tracking method. These make use of parameter thresholds to determine whether a detected feature, such as a vorticity maximum or a warm core, is strong enough to indicate a tropical cyclone. The choice of parameter thresholds is generally subjective.\u0000This study proposes and assesses the parallel use of many threshold parameter combinations, combining a number of weaker and stronger values. The tracking algorithm succeeds in tracking tropical cyclones within the model data, beginning at their aggregation stage or shortly thereafter and ending when they interact strongly with extratropical flow and transition into extratropical cyclones or when their warm core decays.\u0000The sensitivity of accumulated cyclone energy to tracking errors is assessed. Tracking errors include the faulty initial detection and termination of valid tropical cyclones and systems falsely identified as tropical cyclones. They are found to not significantly impact the accumulated cyclone energy. Thus, the tracking algorithm produces an adequate estimate of the accumulated cyclone energy within the underlying data.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46335701","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":"Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes","authors":"S. Fathi, Mark Gordon, Yongsheng Chen","doi":"10.5194/gmd-16-5069-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5069-2023","url":null,"abstract":"Abstract. Super-resolution atmospheric modelling can be used to interpret and optimize environmental observations during top-down emission rate retrieval campaigns (e.g. aircraft-based) by providing complementary data that closely correspond to real-world atmospheric pollution transport and dispersion conditions. For this work, super-resolution model simulations with large-eddy-simulation sub-grid-scale parameterization were developed and implemented using WRF-ARW (Weather Research and Forecasting - Advanced Research WRF). We demonstrate a series of best practices for improved (realistic) modelling of atmospheric pollutant dispersion at super-resolutions. These include careful considerations for grid quality over complex terrain, sub-grid turbulence parameterization at the scale of large eddies, and ensuring local and global tracer mass conservation. The study objective was to resolve small dynamical processes inclusive of spatio-temporal scales of high-speed (e.g. 100 m s−1) airborne measurements. This was achieved by downscaling of reanalysis data from 31.25 km to 50 m through multi-domain model nesting in the horizontal and grid-refining in the vertical. Further, WRF dynamical-solver source code was modified to simulate the release of passive tracers within the finest-resolution domain. Different meteorological case studies and several tracer source emission scenarios were considered. Model-generated fields were evaluated against observational data (surface monitoring network and aircraft campaign data) and also in terms of tracer mass conservation. Results indicated agreement between modelled and observed values within 5 ∘C for temperature, 1 %–25 % for relative humidity, and 1–2 standard deviations for wind fields. Model performance in terms of (global and local) tracer mass conservation was within 2 % to 5 % of model input emissions. We found that, to ensure mass conservation within the modelling domain, tracers should be released on a regular-resolution grid (vertical and horizontal). Further, using our super-resolution modelling products, we investigated emission rate estimations based on flux calculation and mass-balancing. Our results indicate that retrievals under weak advection conditions (horizontal wind speeds < 5 m s−1) are not reliable due to weak correlation between the source emission rate and the downwind tracer mass flux.\u0000In this work we demonstrate the development of accurate super-resolution model simulations useful for planning, interpreting, and optimizing top-down retrievals, and we discuss favourable conditions (e.g. meteorological) for reliable mass-balance emission rate estimations.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46520039","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":"Rainbows and climate change: a tutorial on climate model diagnostics and parameterization","authors":"A. Gettelman","doi":"10.5194/gmd-16-4937-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-4937-2023","url":null,"abstract":"Abstract. Earth system models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and\u0000chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an\u0000ESM: the Community Earth System Model version 2 (CESM2). Using the “state” of the model, basic physical laws, and some assumptions, we generate a\u0000representation of this unique optical phenomenon as a diagnostic output. Rainbow occurrence and its possible changes are related to cloud occurrence\u0000and rain formation, which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostic\u0000parameterizations such as assumptions, uncertain parameters, and the difficulty of evaluation against uncertain observations. Results agree\u0000qualitatively with limited available global “observations” of rainbows. Rainbows are seen in expected locations in the subtropics over the ocean\u0000where broken clouds and frequent precipitation occur. The diurnal peak is in the morning over ocean and in the evening over land. The\u0000representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows\u0000are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the\u0000future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic\u0000projects that rainbows will increase in the future, with the largest changes at midlatitudes. The diagnostic may be useful for assessing cloud\u0000parameterizations and is an exercise in how to build and test parameterizations of atmospheric phenomena.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48052682","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":"The High-resolution Intermediate Complexity Atmospheric Research (HICAR v1.1) model enables fast dynamic downscaling to the hectometer scale","authors":"D. Reynolds, E. Gutmann, B. Kruyt, Michael Haugeneder, T. Jonas, F. Gerber, M. Lehning, R. Mott","doi":"10.5194/gmd-16-5049-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5049-2023","url":null,"abstract":"Abstract. High-resolution (< 1 km) atmospheric modeling is increasingly used to study precipitation distributions in complex terrain and cryosphere–atmospheric processes. While this approach has yielded insightful results, studies over annual timescales or at the spatial extents of watersheds remain unrealistic due to the computational costs of running most atmospheric models. In this paper we introduce a high-resolution variant of the Intermediate Complexity Atmospheric Research (ICAR) model, HICAR. We detail the model development that enabled HICAR simulations at the hectometer scale, including changes to the advection scheme and the wind solver. The latter uses near-surface terrain parameters which allow HICAR to simulate complex topographic flow features. These model improvements clearly influence precipitation distributions at the ridge scale (50 m), suggesting that HICAR can approximate processes dependent on particle–flow interactions such as preferential deposition. A 250 m HICAR simulation over most of the Swiss Alps also shows monthly precipitation patterns similar to two different gridded precipitation products which assimilate available observations. Benchmarking runs show that HICAR uses 594 times fewer computational resources than the Weather Research and Forecasting (WRF) atmospheric model. This gain in efficiency makes dynamic downscaling accessible to ecohydrological research, where downscaled data are often required at hectometer resolution for whole basins at seasonal timescales. These results motivate further development of HICAR, including refinement of parameterizations used in the wind solver and coupling of the model with an intermediate-complexity snow model.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48269400","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":"NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process","authors":"J. Díez-Sierra, Salvador Navas, Manuel del Jesus","doi":"10.5194/gmd-16-5035-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-5035-2023","url":null,"abstract":"Abstract. Long time series of rainfall at different levels of aggregation (daily or hourly in most cases) constitute the basic input for hydrological, hydraulic and climate studies. However, oftentimes the length, completeness, time resolution or spatial coverage of the available records falls short of the minimum requirements to build robust estimations. Here, we introduce NEOPRENE, a Python library to generate synthetic time series of rainfall. NEOPRENE simulates multi-site synthetic rainfall that reproduces observed statistics at different time aggregations. Three case studies exemplify the use of the library, focusing on extreme rainfall, as well as on disaggregating daily rainfall observations into hourly rainfall records. NEOPRENE is distributed from GitHub with an open license (GPLv3), free for research and commercial purposes alike. We also provide Jupyter notebooks with the example use cases to promote its adoption by researchers and practitioners involved in vulnerability, impact and adaptation studies.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44719958","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":"Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations","authors":"A. Pasik, A. Gruber, Wolfgang Preimesberger, D. De Santis, W. Dorigo","doi":"10.5194/gmd-16-4957-2023","DOIUrl":"https://doi.org/10.5194/gmd-16-4957-2023","url":null,"abstract":"Abstract. Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root-zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exist for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations. While the number of available RZSM datasets is growing, they usually do not contain estimates of their uncertainty. In this paper we derive a long-term RZSM dataset (2002–2020) from the Copernicus Climate Change Service (C3S) surface soil moisture (SSM) COMBINED product via the exponential filter (EF) method. We identify the optimal value of the method's model parameter T, which controls the level of smoothing and delaying applied to the surface observations, by maximizing the correlation of RZSM estimates with field measurements from the International Soil Moisture Network (ISMN). Optimized T-parameter values were calculated for four soil depth layers (0–10, 10–40, 40–100, and 100–200 cm) and used to calculate a global RZSM dataset. The quality of this dataset is then globally evaluated against RZSM estimates of the ERA5-Land reanalysis. Results of the product comparison show satisfactory skill in all four layers, with the median Pearson correlation ranging from 0.54 in the topmost to 0.28 in the deepest soil layer. Temporally dynamic product uncertainties for each of the RZSM product layers are estimated by applying standard uncertainty propagation to SSM input data and by estimating structural uncertainties in the EF method from ISMN ground reference measurements taken at the surface and at varying depths. Uncertainty estimates were found to exhibit both realistic absolute magnitudes and temporal variations. The product described here is, to the best of our knowledge, the first global, long-term, uncertainty-characterized, and purely observation-based product for RZSM estimates up to 2 m depth.\u0000","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47193450","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}