{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T09:48:47Z","timestamp":1777110527703,"version":"3.51.4"},"reference-count":58,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T00:00:00Z","timestamp":1715644800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFB3903300"],"award-info":[{"award-number":["2022YFB3903300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFB3903303"],"award-info":[{"award-number":["2022YFB3903303"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["79622"],"award-info":[{"award-number":["79622"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["XDA20100300"],"award-info":[{"award-number":["XDA20100300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"startup funds from Zhejiang University","award":["2022YFB3903300"],"award-info":[{"award-number":["2022YFB3903300"]}]},{"name":"startup funds from Zhejiang University","award":["2022YFB3903303"],"award-info":[{"award-number":["2022YFB3903303"]}]},{"name":"startup funds from Zhejiang University","award":["79622"],"award-info":[{"award-number":["79622"]}]},{"name":"startup funds from Zhejiang University","award":["XDA20100300"],"award-info":[{"award-number":["XDA20100300"]}]},{"name":"Korea Environment Industry and Technology Institute through the Water Management Research Program, funded by the Korea Ministry of Environment","award":["2022YFB3903300"],"award-info":[{"award-number":["2022YFB3903300"]}]},{"name":"Korea Environment Industry and Technology Institute through the Water Management Research Program, funded by the Korea Ministry of Environment","award":["2022YFB3903303"],"award-info":[{"award-number":["2022YFB3903303"]}]},{"name":"Korea Environment Industry and Technology Institute through the Water Management Research Program, funded by the Korea Ministry of Environment","award":["79622"],"award-info":[{"award-number":["79622"]}]},{"name":"Korea Environment Industry and Technology Institute through the Water Management Research Program, funded by the Korea Ministry of Environment","award":["XDA20100300"],"award-info":[{"award-number":["XDA20100300"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022YFB3903300"],"award-info":[{"award-number":["2022YFB3903300"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022YFB3903303"],"award-info":[{"award-number":["2022YFB3903303"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["79622"],"award-info":[{"award-number":["79622"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA20100300"],"award-info":[{"award-number":["XDA20100300"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The retrieval of continuous snow water equivalent (SWE) directly from passive microwave observations is hampered by ambiguity, which can potentially be mitigated by incorporating knowledge on snow hydrological processes. In this paper, we present a data assimilation (DA)-based SWE retrieval framework coupling the QCA-Mie scattering (DMRT-QMS) model (a dense medium radiative transfer (RT) microwave scattering model) and a one-dimensional column-based multiple-layer snow hydrology model. The snow hydrology model provides realistic estimates of the snowpack physical parameters required to drive the DMRT-QMS model. This paper devises a strategy to specify those internal parameters in the snow hydrology and RT models that lack observational records. The modeled snow depth is updated by assimilating brightness temperatures (Tbs) from the X, Ku, and Ka bands using an ensemble Kalman filter (EnKF). The updated snow depth is then used to predict the SWE. The proposed framework was tested using the European Space Agency\u2019s Nordic Snow Radar Experiment (ESA NoSREx) dataset for a snow field experiment from 2009 to 2012 in Sodankyl\u00e4, Finland. The achieved SWE retrieval root mean square error of 34.31 mm meets the requirements of NASA and ESA snow missions and is about 70% less than the open-loop SWE. In summary, this paper introduces a novel SWE retrieval framework that leverages the combined strengths of a snow hydrology model and a radiative transfer model. This approach ensures physically realistic retrievals of snow depth and SWE. We investigated the impact of various factors on the framework\u2019s performance, including observation time intervals and combinations of microwave observation channels. Our results demonstrate that a one-week observation interval achieves acceptable retrieval accuracy. Furthermore, the use of multi-channel and multi-polarization Tbs is preferred for optimal SWE retrieval performance.<\/jats:p>","DOI":"10.3390\/rs16101732","type":"journal-article","created":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T06:28:12Z","timestamp":1715668092000},"page":"1732","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Snow Water Equivalent Retrieval Framework Coupling 1D Hydrology and Passive Microwave Radiative Transfer Models"],"prefix":"10.3390","volume":"16","author":[{"given":"Yuanhao","family":"Cao","sequence":"first","affiliation":[{"name":"Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University, Haining 314400, China"},{"name":"Department of Geography & Environmental Management, University of Waterloo, Waterloo, ON N2L 3G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunzeng","family":"Luo","sequence":"additional","affiliation":[{"name":"Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University, Haining 314400, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shurun","family":"Tan","sequence":"additional","affiliation":[{"name":"Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University, Haining 314400, China"},{"name":"Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"},{"name":"State Key Laboratory of Extreme Photonics and Instrumentation, College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Do-Hyuk","family":"Kang","sequence":"additional","affiliation":[{"name":"NOAA Weather Program Office, Silver Spring, MD 20910, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0173-9515","authenticated-orcid":false,"given":"Yiwen","family":"Fang","sequence":"additional","affiliation":[{"name":"Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University, Haining 314400, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinmei","family":"Pan","sequence":"additional","affiliation":[{"name":"National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3534","DOI":"10.1002\/2017WR020840","article-title":"Water and Life from Snow: A Trillion Dollar Science Question","volume":"53","author":"Sturm","year":"2017","journal-title":"Water Resour. Res."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tsai, Y.-L.S., Dietz, A., Oppelt, N., and Kuenzer, C. (2019). Remote Sensing of Snow Cover Using Spaceborne SAR: A Review. Remote Sens., 11.","DOI":"10.3390\/rs11121456"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1038\/nature04141","article-title":"Potential Impacts of a Warming Climate on Water Availability in Snow-Dominated Regions","volume":"438","author":"Barnett","year":"2005","journal-title":"Nature"},{"key":"ref_4","unstructured":"Pomeroy, J., de Boer, D., and Martz, L.W. (2005). Hydrology and Water Resources of Saskatchewan, Centre for Hydrology, University Saskatchewan."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"D\u00e9ry, S.J., Stahl, K., Moore, R.D., Whitfield, P.H., Menounos, B., and Burford, J.E. (2009). Detection of Runoff Timing Changes in Pluvial, Nival, and Glacial Rivers of Western Canada. Water Resour. Res., 45.","DOI":"10.1029\/2008WR006975"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kim, E., Gatebe, C., Hall, D., Newlin, J., Misakonis, A., Elder, K., Marshall, H.P., Hiemstra, C., Brucker, L., and De Marco, E. (2017, January 23\u201328). NASA\u2019s SnowEx Campaign: Observing Seasonal Snow in a Forested Environment. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8127222"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"171","DOI":"10.3189\/S0260305500012799","article-title":"Snow Depths and Grain-Size Relationships with Relevance for Passive Microwave Studies","volume":"17","author":"Armstrong","year":"1993","journal-title":"Ann. Glaciol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"39","DOI":"10.3189\/S0260305500200736","article-title":"Nimbus-7 SMMR Derived Global Snow Cover Parameters","volume":"9","author":"Chang","year":"1987","journal-title":"Ann. Glaciol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/36.628786","article-title":"Retrieval of Surface Temperature in Boreal Forest Zone from SSM\/I Data","volume":"35","author":"Pulliainen","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1378","DOI":"10.1109\/36.763302","article-title":"HUT Snow Emission Model and Its Applicability to Snow Water Equivalent Retrieval","volume":"37","author":"Pulliainen","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1038\/s41597-021-00939-2","article-title":"GlobSnow v3. 0 Northern Hemisphere Snow Water Equivalent Dataset","volume":"8","author":"Luojus","year":"2021","journal-title":"Sci. Data"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.rse.2017.02.006","article-title":"Application of a Markov Chain Monte Carlo Algorithm for Snow Water Equivalent Retrieval from Passive Microwave Measurements","volume":"192","author":"Pan","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1109\/TGRS.2020.3004594","article-title":"The Use of a Monte Carlo Markov Chain Method for Snow-Depth Retrievals: A Case Study Based on Airborne Microwave Observations and Emission Modeling Experiments of Tundra Snow","volume":"59","author":"Saberi","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.rse.2015.09.009","article-title":"Comparison of Passive Microwave Brightness Temperature Prediction Sensitivities over Snow-Covered Land in North America Using Machine Learning Algorithms and the Advanced Microwave Scanning Radiometer","volume":"170","author":"Xue","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1080\/02723646.2016.1236606","article-title":"Machine Learning Predictions of Passive Microwave Brightness Temperature over Snow-Covered Land Using the Special Sensor Microwave Imager (SSM\/I)","volume":"38","author":"Forman","year":"2017","journal-title":"Phys. Geogr."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"212","DOI":"10.3389\/feart.2019.00212","article-title":"Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference over Snow-Covered Terrain in High Mountain Asia","volume":"7","author":"Ahmad","year":"2019","journal-title":"Front. Earth Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cui, Y., Xiong, C., Lemmetyinen, J., Shi, J., Jiang, L., Peng, B., Li, H., Zhao, T., Ji, D., and Hu, T. (2016). Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss. Remote Sens., 8.","DOI":"10.3390\/rs8060505"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Oveisgharan, S., Esteban-Fernandez, D., Waliser, D., Friedl, R., Nghiem, S., and Zeng, X. (2020). Evaluating the Preconditions of Two Remote Sensing Swe Retrieval Algorithms over the Us. Remote Sens., 12.","DOI":"10.3390\/rs12122021"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"4245","DOI":"10.1029\/2018MS001583","article-title":"The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty","volume":"11","author":"Lawrence","year":"2019","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/0921-8181(95)00046-1","article-title":"Surface Soil Moisture Parameterization of the VIC-2L Model: Evaluation and Modification","volume":"13","author":"Liang","year":"1996","journal-title":"Glob. Planet. Change"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Niu, G.-Y., Yang, Z.-L., Mitchell, K.E., Chen, F., Ek, M.B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., and Rosero, E. (2011). The Community Noah Land Surface Model with Multiparameterization Options (Noah-MP): 1. Model Description and Evaluation with Local-scale Measurements. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2010JD015139"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1016\/j.advwatres.2005.08.004","article-title":"Assimilating Remotely Sensed Snow Observations into a Macroscale Hydrology Model","volume":"29","author":"Andreadis","year":"2006","journal-title":"Adv. Water Resour."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1175\/JHM-D-11-056.1","article-title":"Implications of Representing Snowpack Stratigraphy for the Assimilation of Passive Microwave Satellite Observations","volume":"13","author":"Andreadis","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1175\/JHM505.1","article-title":"Snow Data Assimilation via an Ensemble Kalman Filter","volume":"7","author":"Slater","year":"2006","journal-title":"J. Hydrometeorol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Sun, C., Walker, J.P., and Houser, P.R. (2004). A Methodology for Snow Data Assimilation in a Land Surface Model. J. Geophys. Res. Atmos., 109.","DOI":"10.1029\/2003JD003765"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Durand, M., Molotch, N.P., and Margulis, S.A. (2008). A Bayesian Approach to Snow Water Equivalent Reconstruction. J. Geophys. Res. Atmos., 113.","DOI":"10.1029\/2008JD009894"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Durand, M., Kim, E.J., and Margulis, S.A. (2009). Radiance Assimilation Shows Promise for Snowpack Characterization. Geophys. Res. Lett., 36.","DOI":"10.1029\/2008GL035214"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.rse.2013.12.009","article-title":"Assimilating Passive Microwave Remote Sensing Data into a Land Surface Model to Improve the Estimation of Snow Depth","volume":"143","author":"Che","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1109\/LGRS.2011.2105243","article-title":"A First-Order Characterization of Errors from Neglecting Stratigraphy in Forward and Inverse Passive Microwave Modeling of Snow","volume":"8","author":"Durand","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"771","DOI":"10.5194\/tc-15-771-2021","article-title":"Snow Ensemble Uncertainty Project (SEUP): Quantification of Snow Water Equivalent Uncertainty across North America via Ensemble Land Surface Modeling","volume":"15","author":"Kim","year":"2021","journal-title":"Cryosphere"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"635","DOI":"10.5194\/hess-21-635-2017","article-title":"Evaluation of Snow Data Assimilation Using the Ensemble Kalman Filter for Seasonal Streamflow Prediction in the Western United States","volume":"21","author":"Huang","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"10241","DOI":"10.1109\/TGRS.2019.2932732","article-title":"Evaluation of Brightness Temperature Sensitivity to Snowpack Physical Properties Using Coupled Snow Physics and Microwave Radiative Transfer Models","volume":"57","author":"Kang","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Luo, C., Tan, S., and Kang, D.-H. (2021, January 11\u201316). A Snow Water Equivalent Retrieval Framework Coupling Microwave Remote Sensing and Hydrology Model. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9553317"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1029\/1999RS002270","article-title":"Dense Media Radiative Transfer Theory Based on Quasicrystalline Approximation with Applications to Passive Microwave Remote Sensing of Snow","volume":"35","author":"Tsang","year":"2000","journal-title":"Radio Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1109\/TGRS.2011.2169073","article-title":"Observing System Simulation of Snow Microwave Emissions over Data Sparse Regions\u2014Part I: Single Layer Physics","volume":"50","author":"Kang","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1806","DOI":"10.1109\/TGRS.2011.2169074","article-title":"Observing System Simulation of Snow Microwave Emissions over Data Sparse Regions\u2014Part II: Multilayer Physics","volume":"50","author":"Kang","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/TGRS.2012.2234468","article-title":"Evaluating Passive Microwave Radiometry for the Dynamical Transition from Dry to Wet Snowpacks","volume":"52","author":"Kang","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"403","DOI":"10.5194\/gi-5-403-2016","article-title":"Nordic Snow Radar Experiment","volume":"5","author":"Lemmetyinen","year":"2016","journal-title":"Geosci. Instrum. Methods Data Syst."},{"key":"ref_39","unstructured":"Jordan, R.E. (2023, November 15). A One-Dimensional Temperature Model for a Snow Cover: Technical Documentation for SNTHERM. 89. 1991; pp. 5. Available online: https:\/\/erdc-library.erdc.dren.mil\/jspui\/handle\/11681\/11677."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"990","DOI":"10.1109\/TGRS.2006.888854","article-title":"Modeling Active Microwave Remote Sensing of Snow Using Dense Media Radiative Transfer (DMRT) Theory with Multiple-Scattering Effects","volume":"45","author":"Tsang","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3663","DOI":"10.1109\/TGRS.2008.922143","article-title":"The Effects of Layers in Dry Snow on Its Passive Microwave Emissions Using Dense Media Radiative Transfer Theory Based on the Quasicrystalline Approximation (QCA\/DMRT)","volume":"46","author":"Liang","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3811","DOI":"10.1109\/JSTARS.2014.2343519","article-title":"Dense Media Radiative Transfer Applied to SnowScat and SnowSAR","volume":"7","author":"Chang","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s10236-003-0036-9","article-title":"The Ensemble Kalman Filter: Theoretical Formulation and Practical Implementation","volume":"53","author":"Evensen","year":"2003","journal-title":"Ocean. Dyn."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Evensen, G. (2009). Data Assimilation: The Ensemble Kalman Filter, Springer.","DOI":"10.1007\/978-3-642-03711-5"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1719","DOI":"10.1175\/1520-0493(1998)126<1719:ASITEK>2.0.CO;2","article-title":"Analysis Scheme in the Ensemble Kalman Filter","volume":"126","author":"Burgers","year":"1998","journal-title":"Mon. Weather. Rev."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1175\/1520-0493(1998)126<0796:DAUAEK>2.0.CO;2","article-title":"Data Assimilation Using an Ensemble Kalman Filter Technique","volume":"126","author":"Houtekamer","year":"1998","journal-title":"Mon. Wea. Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1175\/JHM495.1","article-title":"Data Assimilation for Estimating the Terrestrial Water Budget Using a Constrained Ensemble Kalman Filter","volume":"7","author":"Pan","year":"2006","journal-title":"J. Hydrometeorol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"4927","DOI":"10.5194\/hess-21-4927-2017","article-title":"State and Parameter Estimation of Two Land Surface Models Using the Ensemble Kalman Filter and the Particle Filter","volume":"21","author":"Zhang","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1175\/2008JHM877.1","article-title":"NASA Cold Land Processes Experiment (CLPX 2002\/03): Field Measurements of Snowpack Properties and Soil Moisture","volume":"10","author":"Elder","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_50","unstructured":"Rott, H., Duguay, C., Essery, R., Haas, C., Macelloni, G., and Malnes, E. (2009). ESA SP-1313\/3 Candidate Earth Explorer Core Missions Report for Assessment: CoReH20\u2014Cold Regions Hydrology High Resolution Observatory. ESA Commun. Prod. Off."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1175\/JHM-D-17-0241.1","article-title":"Quantifying Snow Mass Mission Concept Trade-Offs Using an Observing System Simulation Experiment","volume":"20","author":"Garnaud","year":"2019","journal-title":"J. Hydrometeorol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3157870","article-title":"Improving Fractional Snow Cover Retrieval From Passive Microwave Data Using a Radiative Transfer Model and Machine Learning Method","volume":"60","author":"Xiao","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"113476","DOI":"10.1016\/j.rse.2023.113476","article-title":"Evaluation of passive microwave dry snow detection algorithms and application to SWE retrieval during seasonal snow accumulation","volume":"288","author":"Zschenderlein","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1175\/JHM-D-14-0089.1","article-title":"The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study","volume":"16","author":"Carrera","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Kwon, Y., Forman, B.A., Ahmad, J.A., Kumar, S.V., and Yoon, Y. (2019). Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia. Remote Sens., 11.","DOI":"10.3390\/rs11192265"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s40641-020-00159-7","article-title":"Data Assimilation Improves Estimates of Climate-Sensitive Seasonal Snow","volume":"6","author":"Girotto","year":"2020","journal-title":"Curr. Clim. Chang. Rep."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1002\/hyp.6204","article-title":"ALPINE3D: A Detailed Model of Mountain Surface Processes and Its Application to Snow Hydrology","volume":"20","author":"Lehning","year":"2006","journal-title":"Hydrol. Process."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"4418","DOI":"10.1109\/JSTARS.2015.2469290","article-title":"Modeling Both Active and Passive Microwave Remote Sensing of Snow Using Dense Media Radiative Transfer (DMRT) Theory With Multiple Scattering and Backscattering Enhancement","volume":"8","author":"Tan","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1732\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:42:02Z","timestamp":1760107322000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1732"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,14]]},"references-count":58,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["rs16101732"],"URL":"https:\/\/doi.org\/10.3390\/rs16101732","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,14]]}}}