{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T17:08:29Z","timestamp":1776272909252,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,11]],"date-time":"2022-09-11T00:00:00Z","timestamp":1662854400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42075069"],"award-info":[{"award-number":["42075069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Assimilation of satellite-derived humidity with a homogenous static background error covariance (B) matrix computed over the entire computational domain (Full-B) tends to overpredict sea fog coverage. A feature-dependent B (Fog-B) is proposed to address this issue. In Fog-B, the static error statistics for clear air and foggy areas are calculated separately using a feature-dependent binning method. The resultant error statistics are used simultaneously at appropriate locations guided by the satellite-derived sea fog. Diagnostics show that Full-B generally has broader horizontal and vertical length scales and larger error variances than Fog-B below ~300 m except for the vertical length scale near the surface. Experiments on three sea fog cases over the Yellow Sea are conducted to understand and examine the impact of Fog-B on sea fog analyses and forecasts. Results show that using Full-B produces greater and broader water vapor mixing ratio increments and thus predicts larger sea fog coverage than using Fog-B. Further evaluations suggest that using Fog-B has greater forecast skills in sea fog coverage and more accurate moisture conditions than using Full-B.<\/jats:p>","DOI":"10.3390\/rs14184537","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T04:05:41Z","timestamp":1663041941000},"page":"4537","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Impact of Feature-Dependent Static Background Error Covariances for Satellite-Derived Humidity Assimilation on Analyses and Forecasts of Multiple Sea Fog Cases over the Yellow Sea"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8070-2640","authenticated-orcid":false,"given":"Yue","family":"Yang","sequence":"first","affiliation":[{"name":"Key Laboratory of Physical Oceanography, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China"},{"name":"School of Meteorology, University of Oklahoma, Norman, OK 73072, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2697-8379","authenticated-orcid":false,"given":"Shanhong","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Physical Oceanography, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8287-6986","authenticated-orcid":false,"given":"Yongming","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Physical Oceanography, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China"},{"name":"School of Meteorology, University of Oklahoma, Norman, OK 73072, USA"}]},{"given":"Hao","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Physical Oceanography, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,11]]},"reference":[{"key":"ref_1","unstructured":"Wang, B. (1985). Sea Fog, China Ocean Press."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kora\u010din, D., and Dorman, C.E. (2017). Marine fog: Challenges and Advancements in Observations, Modeling, and Forecasting, Springer International Publishing.","DOI":"10.1007\/978-3-319-45229-6"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1175\/BAMS-85-3-395","article-title":"Sea fog research in the United Kingdom and United States","volume":"85","author":"Lewis","year":"2004","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_4","first-page":"359","article-title":"The main advances in sea fog research in China","volume":"38","author":"Zhang","year":"2008","journal-title":"J. Ocean Univ. China"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"6758","DOI":"10.1175\/2009JCLI2806.1","article-title":"Seasonal variations of Yellow Sea fog: Observations and mechanisms","volume":"22","author":"Zhang","year":"2009","journal-title":"J. Clim."},{"key":"ref_6","unstructured":"Fu, G., Zhang, S., Gao, S., and Li, P. (2012). Understanding of Sea Fog over the China Seas, China Meteorological Press."},{"key":"ref_7","unstructured":"WMO (1966). International Meteorological Vocabulary, World Meteorological Organization."},{"key":"ref_8","first-page":"1","article-title":"Ensemble forecast of a sea fog over the Yellow Sea","volume":"44","author":"Gao","year":"2014","journal-title":"J. Ocean Univ. China"},{"key":"ref_9","first-page":"312","article-title":"Sensitivity study of WRF parametrization schemes for the spring sea fog in the Yellow Sea","volume":"25","author":"Lu","year":"2014","journal-title":"J. Appl. Meteorol. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1175\/WAF-D-12-00123.1","article-title":"Assimilating MTSAT-derived humidity in nowcasting sea fog over the Yellow Sea","volume":"29","author":"Wang","year":"2014","journal-title":"Wea. Forecast."},{"key":"ref_11","first-page":"974","article-title":"Sensitivity study of vertical resolution in WRF numerical simulation for sea fog over the Yellow Sea","volume":"74","author":"Yang","year":"2016","journal-title":"Acta Meteorol. Sin."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e2019JD031562","DOI":"10.1029\/2019JD031562","article-title":"The impact of turbulent diffusion driven by fog-top cooling on sea fog development","volume":"125","author":"Yang","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Gao, X., Gao, S., and Yang, Y. (2018). A comparison between 3DVAR and EnKF for data assimilation effects on the Yellow Sea fog forecast. Atmosphere, 9.","DOI":"10.20944\/preprints201807.0577.v1"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.atmosres.2018.09.004","article-title":"Sensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea","volume":"215","author":"Yang","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13351-021-1084-0","article-title":"A new observation operator for the assimilation of satellite-derived relative humidity: Methodology and experiments with three sea fog events over the Yellow Sea","volume":"35","author":"Yang","year":"2021","journal-title":"J. Meteorol. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8816185","DOI":"10.1155\/2020\/8816185","article-title":"Impact of Multivariate background error covariance on the WRF-3DVAR assimilation for the Yellow Sea Fog modeling","volume":"2020","author":"Gao","year":"2020","journal-title":"Adv. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Jin, G., Gao, S., Shi, H., Lu, X., Yang, Y., and Zheng, Q. (2022). Impacts of sea\u2013land breeze circulation on the formation and development of coastal sea fog along the Shandong Peninsula: A case study. Atmosphere, 13.","DOI":"10.3390\/atmos13020165"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s00376-007-0065-2","article-title":"A heavy sea fog event over the Yellow Sea in March 2005: Analysis and numerical modeling","volume":"24","author":"Gao","year":"2007","journal-title":"Adv. Atmos. Sci."},{"key":"ref_19","first-page":"10","article-title":"Numerical study on direct assimilation of satellite radiances for sea fog over the Yellow Sea","volume":"42","author":"Li","year":"2012","journal-title":"J. Ocean Univ. China"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1175\/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2","article-title":"The National Meteorological Center\u2019s spectral statistical-interpolation system","volume":"120","author":"Parrish","year":"1992","journal-title":"Mon. Weather Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2004","DOI":"10.1002\/qj.802","article-title":"Heterogeneous background error covariances for the analysis and forecast of fog events","volume":"137","author":"Montmerle","year":"2011","journal-title":"Q. J. R. Meteor. Soc."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2994","DOI":"10.1175\/2011MWR3632.1","article-title":"Heterogeneous convective-scale background error covariances with the in- clusion of hydrometeor variables","volume":"139","author":"Michel","year":"2011","journal-title":"Mon. Weather Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1175\/2009MWR2998.1","article-title":"An examination of background error correlations between mass and rotational wind over precipitation regions","volume":"138","author":"Caron","year":"2010","journal-title":"Mon. Weather Rev."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1002\/qj.655","article-title":"Diagnosis and formulation of heterogeneous background-error covariances at the mesoscale","volume":"136","author":"Montmerle","year":"2010","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2713","DOI":"10.1175\/MWR-D-20-0215.1","article-title":"Development of convective-scale static background error covariance within GSI-Based hybrid EnVar system for direct radar reflectivity data assimilation","volume":"149","author":"Wang","year":"2021","journal-title":"Mon. Weather Rev."},{"key":"ref_26","unstructured":"Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X.Y., Wang, W., and Powers, J.G. (2022, September 08). A Description of the Advanced Research WRF Version 3; NCAR Technical Note, NCAR\/TN-475+STR. Available online: http:\/\/opensky.ucar.edu\/islandora\/object\/technotes:500."},{"key":"ref_27","first-page":"23","article-title":"Detection of nighttime sea fog\/stratus over the Huang-hai Sea using MTSAT-1R IR data","volume":"28","author":"Gao","year":"2009","journal-title":"Acta Oceanol. Sin."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yi, L., Thies, B., Zhang, S., Shi, X., and Bendix, J. (2016). Optical thickness and effective radius retrievals of low stratus and fog from MTSAT daytime data as a prerequisite for Yellow Sea Fog detection. Remote Sens., 8.","DOI":"10.3390\/rs8010008"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Yang, J.H., Yoo, J.M., Choi, Y.S., Wu, D., and Jeong, J.H. (2019). Probability index of low stratus and fog at dawn using dual geostationary satellite observations from COMS and FY-2D near the Korean Peninsula. Remote Sens., 11.","DOI":"10.3390\/rs11111283"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s13143-018-0093-0","article-title":"Development of fog detection algorithm during nighttime using Himawari-8\/AHI satellite and ground observation data","volume":"55","author":"Kim","year":"2019","journal-title":"Asia-Pacific J. Atmos. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kim, D., Park, M.S., Park, Y.J., and Kim, W. (2020). Geostationary Ocean Color Imager (GOCI) marine fog detection in combination with Himawari-8 based on the decision tree. Remote Sens., 12.","DOI":"10.3390\/rs12010149"},{"key":"ref_32","unstructured":"Takahashi, M. (2022, July 25). Algorithm Theoretical Basis Document (ATBD) for GSICS Infrared Inter-Calibration of Imagers on MTSAT-1R\/-2 and Himawari-8\/-9 Using AIRS and IASI Hyperspectral Observations. Meteorological Satellite Center, Japan Meteorological Agency, 2017. Available online: https:\/\/www.data.jma.go.jp\/mscweb\/data\/monitoring\/gsics\/ir\/ATBD_for_JMA_Demonstration_GSICS_Inter-Calibration_of_MTSAT_Himawari-AIRSIASI.pdf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1175\/1520-0434(1995)010<0606:AITDAA>2.0.CO;2","article-title":"Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery","volume":"10","author":"Ellrod","year":"1995","journal-title":"Weather Forecast."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2708","DOI":"10.1175\/1520-0493(1993)121<2708:COCHAO>2.0.CO;2","article-title":"Comparison of cirrus height and optical depth derived from satellite and aircraft measurements","volume":"121","author":"Kriebel","year":"1993","journal-title":"Mon. Weather Rev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1175\/1520-0442(2004)017<0266:TOSRBC>2.0.CO;2","article-title":"Transmission of solar radiation by clouds over snow and ice surfaces: A parameterization in terms of optical depth, solar zenith angle, and surface albedo","volume":"17","author":"Fitzpatrick","year":"2004","journal-title":"J. Clim."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/S0924-4247(02)00063-8","article-title":"Fast humidity sensor for high range 80%\u201395% RH","volume":"100","author":"Sorli","year":"2002","journal-title":"Sens. Actuators"},{"key":"ref_37","unstructured":"Ladwig, T., Alexander, C.R., Dowell, D., Ge, G., Hartsough, C., Hu, M., Kenyon, J., Olson, J., and Weygandt, S.S. (2021, January 13). Cloud observation assimilation in future operational convective-allowing models. Proceedings of the 25th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Virtual. Available online: https:\/\/ams.confex.com\/ams\/101ANNUAL\/meetingapp.cgi\/Paper\/379189."},{"key":"ref_38","first-page":"2673","article-title":"Stratiform cloud-hydrometeor assimilation for HRRR and RAP model short-range weather prediction","volume":"149","author":"Benjamin","year":"2021","journal-title":"Mon. Weather Rev."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1175\/MWR-D-13-00108.1","article-title":"Influence of surface observations in mesoscale data assimilation using an ensemble Kalman filter","volume":"142","author":"Ha","year":"2014","journal-title":"Mon. Weather Rev."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1175\/2010MWR3245.1","article-title":"Incorporating Ensemble Covariance in the Gridpoint Statistical Interpolation Variational Minimization: A Mathematical Framework","volume":"138","author":"Wang","year":"2010","journal-title":"Mon. Weather Rev."},{"key":"ref_41","unstructured":"Daley, R. (1991). Atmospheric Data Analysis, Cambridge University Press."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1175\/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2","article-title":"A Three-Dimensional Variational Data Assimilation System for MM5: Implementation and Initial Results","volume":"132","author":"Barker","year":"2004","journal-title":"Mon. Weather Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"669","DOI":"10.5194\/gmd-8-669-2015","article-title":"Generalized background error covariance matrix model (GEN-BE v2.0)","volume":"8","author":"Descombes","year":"2015","journal-title":"Geosci. Model Dev."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2466","DOI":"10.1175\/MWR3189.1","article-title":"The Use of an Ensemble Approach to Study the Background Error Covariances in a Global NWP Model","volume":"134","author":"Pereira","year":"2006","journal-title":"Mon. Weather Rev."},{"key":"ref_45","unstructured":"Fisher, M. (2003, January 8\u201312). Background error covariance modelling. Proceedings of the Recent Development in Data Assimilation for Atmosphere and Ocean. Shinfield Park, Reading, UK. Available online: https:\/\/www.ecmwf.int\/en\/elibrary\/9404-background-error-covariance-modelling."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Stanesic, A., Horvath, K., and Keresturi, E. (2019). Comparison of NMC and ensemble-based climatological background-error covariances in an operational limited-area data assimilation system. Atmosphere, 10.","DOI":"10.3390\/atmos10100570"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1175\/2009WAF2222289.1","article-title":"Fog prediction from a multimodel mesoscale ensemble prediction system","volume":"25","author":"Zhou","year":"2010","journal-title":"Weather Forecast."},{"key":"ref_48","first-page":"19","article-title":"Analysis on the synoptic characteristics and inversion layer formation of the Yellow Sea fogs","volume":"45","author":"Yang","year":"2015","journal-title":"J. Ocean Univ. China"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.atmosres.2013.12.012","article-title":"Marine fog: A review","volume":"143","author":"Dorman","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1175\/MWR3199.1","article-title":"A new vertical diffusion package with an explicit treatment of entrainment processes","volume":"134","author":"Hong","year":"2006","journal-title":"Mon. Wea. Rev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1002\/qj.665","article-title":"A new stable boundary-layer mixing scheme and its impact on the simulated East Asian summer monsoon","volume":"136","author":"Hong","year":"2010","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1175\/1520-0450(1982)021<1594:AHRMOT>2.0.CO;2","article-title":"A high-resolution model of the planetary boundary layer\u2014Sensitivity tests and comparisons with SESAME-79 data","volume":"21","author":"Zhang","year":"1982","journal-title":"J. Appl. Meteorol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1175\/MWR-D-11-00056.1","article-title":"A revised scheme for the WRF surface layer formulation","volume":"140","author":"Dudhia","year":"2012","journal-title":"Mon. Weather Rev."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1175\/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2","article-title":"Bulk parameterization of the snow field in a cloud model","volume":"22","author":"Lin","year":"1983","journal-title":"J. Clim. Appl. Meteorol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"D13103","DOI":"10.1029\/2008JD009944","article-title":"Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models","volume":"113","author":"Iacono","year":"2008","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1175\/1520-0469(1990)047<2784:AODEPM>2.0.CO;2","article-title":"A one-dimensional entraining\/detraining plume model and its application in convective parameterization","volume":"47","author":"Kain","year":"1990","journal-title":"J. Atmos. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1175\/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2","article-title":"The Kain\u2013Fritsch convective parameterization: An update","volume":"43","author":"Kain","year":"2004","journal-title":"J. Appl. Meteorol."},{"key":"ref_58","unstructured":"Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M.A., Mitchell, K., Ek, M., Gayno, G., Wegiel, J., and Cuenca, R.H. (2004, January 10). Implementation and verification of the unified NOAH land surface model in the WRF model. Proceedings of the 20th Conference on Weather Analysis and Forecasting\/16th Conference on Numerical Weather Prediction, Seattle, WA, USA. Available online: https:\/\/ams.confex.com\/ams\/84Annual\/techprogram\/paper_69061.htm."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1175\/MWR-D-14-00205.1","article-title":"Comparison of the Impacts of Momentum Control Variables on High-ResolutionVariational Data Assimilation and Precipitation Forecasting","volume":"144","author":"Sun","year":"2016","journal-title":"Mon. Wea. Rev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1175\/1520-0450(1999)038<0385:NMSMSO>2.0.CO;2","article-title":"Nonhydrostatic, mesobeta-scale model simulations of cloud ceiling and visibility for an East Coast winter precipitation event","volume":"38","author":"Stoelinga","year":"1999","journal-title":"J. Appl. Meteor."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1175\/1520-0450(1984)023<0034:PODTVA>2.0.CO;2","article-title":"Parameterization of droplet terminal velocity and extinction coefficient in fog models","volume":"23","author":"Kunkel","year":"1984","journal-title":"J. Climate Appl. Meteor."},{"key":"ref_62","first-page":"1","article-title":"Assimilation of Doppler Radar radial velocity in Yellow Sea fog numerical modeling","volume":"46","author":"Wang","year":"2016","journal-title":"J. Ocean Univ. China"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s00024-011-0327-x","article-title":"Forecast of low visibility and fog from NCEP: Current status and efforts","volume":"169","author":"Zhou","year":"2011","journal-title":"Pure Appl. Geophys."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"2473","DOI":"10.1175\/1520-0450(2000)039<2473:SFATKP>2.0.CO;2","article-title":"Sea fog around the Korean Peninsula","volume":"39","author":"Cho","year":"2000","journal-title":"J. Appl. Meteorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.1002\/qj.980","article-title":"Variational assimilation of cloud fraction in the operational Met Office Unified Model","volume":"137","author":"Renshaw","year":"2011","journal-title":"Q. J. R. Meteorol. Soc."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/18\/4537\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:29:24Z","timestamp":1760142564000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/18\/4537"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,11]]},"references-count":65,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["rs14184537"],"URL":"https:\/\/doi.org\/10.3390\/rs14184537","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,11]]}}}