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Research Article

Moderate-resolution snow depth product retrieval from passive microwave brightness data over Xinjiang using machine learning approach

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Article: 2299208 | Received 29 Nov 2022, Accepted 20 Dec 2023, Published online: 01 Jan 2024

References

  • Adib, Arash, Arash Zaerpour, Ozgur Kisi, and Morteza Lotfirad. 2021. “A Rigorous Wavelet-Packet Transform to Retrieve Snow Depth from SSMIS Data and Evaluation of Its Reliability by Uncertainty Parameters.” Water Resources Management 35 (9): 2723–2740. https://doi.org/10.1007/s11269-021-02863-x.
  • Awasthi, Shubham, Shashi Kumar, Praveen K. Thakur, Kamal Jain, Ajeet Kumar, and Snehmani. 2021. “Snow Depth Retrieval in North-Western Himalayan Region Using Pursuit-Monostatic TanDEM-X Datasets Applying Polarimetric Synthetic Aperture Radar Interferometry Based Inversion Modelling.” International Journal of Remote Sensing 42 (8): 2872–2897. https://doi.org/10.1080/01431161.2020.1862439.
  • Awasthi, Shubham, and Divyesh Varade. 2021. “Recent Advances in the Remote Sensing of Alpine Snow: A Review.” GIScience & Remote Sensing 58 (6): 852–888. https://doi.org/10.1080/15481603.2021.1946938.
  • Bair, Edward H., Andre Abreu Calfa, Karl Rittger, and Jeff Dozier. 2018. “Using Machine Learning for Real-Time Estimates of Snow Water Equivalent in the Watersheds of Afghanistan.” The Cryosphere 12 (5): 1579–1594. https://doi.org/10.5194/tc-12-1579-2018.
  • Cao, Yungang, Xiuchun Yang, and Xiaohua Zhu. 2008. “Retrieval Snow Depth by Artificial Neural Network Methodology from Integrated AMSR-E and in-Situ Data—A Case Study in Qinghai-Tibet Plateau” Chinese Geographical Science 18 (4): 356–360. https://doi.org/10.1007/s11769-008-0356-2.
  • Che, Tao, Liyun Dai, Xingming Zheng, Xiaofeng Li, and Kai Zhao. 2016. “Estimation of Snow Depth from Passive Microwave Brightness Temperature Data in Forest Regions of Northeast China.” Remote Sensing of Environment 183:334–349. https://doi.org/10.1016/j.rse.2016.06.005.
  • Che, Tao, Xin Li, Rui Jin, Richard Armstrong, and Tingjun Zhang. 2008. “Snow Depth Derived from Passive Microwave Remote-Sensing Data in China.” Annals of Glaciology 49:145–154. https://doi.org/10.3189/172756408787814690.
  • Chen, Lian Jun, Bala Anand Muthu, and Sivaparthipan Cb. 2021. “Estimating Snow Depth Inversion Model Assisted Vector Analysis Based on Temperature Brightness for North Xinjiang Region of China.” European Journal of Remote Sensing 54 (sup2): 265–274. https://doi.org/10.1080/22797254.2020.1771217.
  • Chen, Tao, Jinmei Pan, Shunli Chang, Chuan Xiong, Jiancheng Shi, Mingyu Liu, Tao Che, Lifu Wang, and Hongrui Liu. 2020. “Validation of the SNTHERM Model Applied for Snow Depth, Grain Size, and Brightness Temperature Simulation at Meteorological Stations in China.” Remote Sensing 12 (3): 507. https://doi.org/10.3390/rs12030507.
  • Collados-Lara, Antonio Juan, David Pulido-Velazquez, Eulogio Pardo-Igúzquiza, and Esteban Alonso-González. 2020. “Estimation of the Spatiotemporal Dynamic of Snow Water Equivalent at Mountain Range Scale Under Data Scarcity.” Science of the Total Environment 741:140485. https://doi.org/10.1016/j.scitotenv.2020.140485.
  • Dai, Liyun, Tao Che, Yongjian Ding, and Xiaohua Hao. 2017. “Evaluation of Snow Cover and Snow Depth on the Qinghai-Tibetan Plateau Derived from Passive Microwave Remote Sensing.” The Cryosphere 11 (4): 1933–1948. https://doi.org/10.5194/tc-11-1933-2017.
  • Dai, Liyun, Tao Che, Jian Wang, and Pu Zhang. 2012. “Snow Depth and Snow Water Equivalent Estimation from AMSR-E Data Based on a Priori Snow Characteristics in Xinjiang, China.” Remote Sensing of Environment 127:14–29. https://doi.org/10.1016/j.rse.2011.08.029.
  • Dai, L., T. Che, Lin Xiao, M. Akynbekkyzy, K. Zhao, and L. Leppanen. 2022. “Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations.” IEEE Transactions on Geoscience and Remote Sensing 1–17. https://doi.org/10.1109/TGRS.2021.3064309.
  • Feng, Aixia, Feng Gao, Qiguang Wang, Aiqing Feng, Qiang Zhang, Yan Shi, Zhiqiang Gong, Guolin Feng, and Yufei Zhao. 2021. “Combining Snow Depth from FY-3C and In Situ Data Over the Tibetan Plateau Using a Nonlinear Analysis Method.” Frontiers in Physics 9:308. https://doi.org/10.3389/fphy.2021.672288.
  • Gu, Lingjia, Xintong Fan, Xiaofeng Li, and Yanlin Wei. 2019. “Snow Depth Retrieval in Farmland Based on a Statistical Lookup Table from Passive Microwave Data in Northeast China.” Remote Sensing 11 (24): 3037. https://doi.org/10.3390/rs11243037.
  • Guo, Wenwen, Shengzhi Huang, Qiang Huang, Dunxian She, Haiyun Shi, Guoyong Leng, Ji Li, Liwen Cheng, Yuejiao Gao, and Jian Peng. 2023. “Vertical Distributions of Atmospheric Black Carbon in Dry and Wet Seasons Observed at a 356-m Meteorological Tower in Shenzhen, South China.” Science of the Total Environment 165480. https://doi.org/10.1016/j.scitotenv.2022.158657.
  • Han, Wei, Xiaohan Zhang, Yi Wang, Lizhe Wang, Xiaohui Huang, Jun Li, Sheng Wang, et al. 2023. “A Survey of Machine Learning and Deep Learning in Remote Sensing of Geological Environment: Challenges, Advances, and Opportunities.” ISPRS Journal of Photogrammetry and Remote Sensing 202:87–113. https://doi.org/10.1016/j.isprsjprs.2023.05.032.
  • Hao, Xiaohua, Siqiong Luo, Tao Che, Jian Wang, Hongyi Li, Liyun Dai, Xiaodong Huang, and Qisheng Feng. 2019. “Accuracy Assessment of Four Cloud-Free Snow Cover Products Over the Qinghai-Tibetan Plateau.” International Journal of Digital Earth 12 (4): 375–393. https://doi.org/10.1080/17538947.2017.1421721.
  • Hu, Yanxing, Tao Che, Liyun Dai, and Lin Xiao. 2021. “Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere.” Remote Sensing 13 (7): 1250. https://doi.org/10.3390/rs13071250.
  • Kang, Do Hyuk, Shurun Tan, and Edward J. Kim. 2019. “Evaluation of Brightness Temperature Sensitivity to Snowpack Physical Properties Using Coupled Snow Physics and Microwave Radiative Transfer Models.” IEEE Transactions on Geoscience and Remote Sensing 57 (12): 10241–10251. https://doi.org/10.1109/TGRS.2019.2932732.
  • Kelly, R. E. J. 2009. “The AMSR-E Snow Depth Algorithm: Description and Initial Results.” Journal of The Remote Sensing Society of Japan 29 (1): 307–317. https://doi.org/10.11440/rssj.29.307.
  • Kim, Rhae Sung, Michael Durand, Dongyue Li, Elisabeth Baldo, Steven A. Margulis, Marie Dumont, and Samuel Morin. 2019. “Estimating Alpine Snow Depth by Combining Multifrequency Passive Radiance Observations with Ensemble Snowpack Modeling.” Remote Sensing of Environment 226:1–15. https://doi.org/10.1016/j.rse.2019.03.016.
  • Koch, Franziska, Patrick Henkel, Florian Appel, Lino Schmid, Heike Bach, Markus Lamm, Monika Prasch, Jürg Schweizer, and Wolfram Mauser. 2019. “Retrieval of Snow Water Equivalent, Liquid Water Content, and Snow Height of Dry and Wet Snow by Combining GPS Signal Attenuation and Time Delay.” Water Resources Research 55 (5): 4465–4487. https://doi.org/10.1029/2018WR024431.
  • Li, Bohao, Kai Liu, Ming Wang, Yanfang Wang, Qian He, Linmei Zhuang, and Weihua Zhu. 2023. “High-Spatiotemporal-Resolution Dynamic Water Monitoring Using LightGBM Model and Sentinel-2 MSI Data.” International Journal of Applied Earth Observation and Geoinformation 118:103278. https://doi.org/10.1016/j.jag.2023.103278
  • Li, Qian, Tao Yang, Feiyun Zhang, Zhiming Qi, and Lanhai Li. 2019. “Snow Depth Reconstruction Over Last Century: Trend and Distribution in the Tianshan Mountains, China.” Global and Planetary Change 173:73–82. https://doi.org/10.1016/j.gloplacha.2018.12.008.
  • Liang, Jiayong, Xiaoping Liu, Kangning Huang, Xia Li, Xun Shi, Yaning Chen, and Jun Li. 2015. “Improved Snow Depth Retrieval by Integrating Microwave Brightness Temperature and Visible/Infrared Reflectance.” Remote Sensing of Environment 156:500–509. https://doi.org/10.1016/j.rse.2014.10.016.
  • Lin, Jianpeng, Weiwei Lin, Wenjun Lin, Jiangtao Wang, and Hongliang Jiang. 2022. “Thermal Prediction for Air-Cooled Data Center Using Data Driven-Based Model.” Applied Thermal Engineering 217:119207. https://doi.org/10.1016/j.applthermaleng.2022.119207.
  • Liu, Yang, Xi Chen, Jian Sheng Hao, and Lan hai Li. 2020. “Snow Cover Estimation from MODIS and Sentinel-1 SAR Data Using Machine Learning Algorithms in the Western Part of the Tianshan Mountains.” Journal of Mountain Science 17 (4): 884–897. https://doi.org/10.1007/s11629-019-5723-1.
  • Liu, Yang, Xi Chen, Yubao Qiu, Jiansheng Hao, Jinming Yang, and Lanhai Li. 2021a. “Mapping Snow Avalanche Debris by Object-Based Classification in Mountainous Regions from Sentinel-1 Images and Causative Indices.” Catena 206:105559. https://doi.org/10.1016/j.catena.2021.105559.
  • Liu, Yang, Lanhai Li, Xi Chen, Run Zhang, and Jinming Yang. 2018. “Temporal-Spatial Variations and Influencing Factors of Vegetation Cover in Xinjiang from 1982 to 2013 Based on GIMMS-NDVI3g.” Global and Planetary Change 169:145–155. https://doi.org/10.1016/j.gloplacha.2018.06.005.
  • Liu, Lian, Yaoming Ma, Massimo Menenti, Rongmingzhu Su, Nan Yao, and Weiqiang Ma. 2021b. “Improved Parameterization of Snow Albedo in Noah Coupled with Weather Research and Forecasting: Applicability to Snow Estimates for the Tibetan Plateau.” Hydrology and Earth System Sciences 25 (9): 4967–4981. https://doi.org/10.5194/hess-25-4967-2021.
  • Luojus, Kari, Jouni Pulliainen, Matias Takala, Juha Lemmetyinen, Colleen Mortimer, Chris Derksen, Lawrence Mudryk, et al. 2021. “GlobSnow v3.0 Northern Hemisphere Snow Water Equivalent Dataset.” Scientific Data 8 (1): 1–16. https://doi.org/10.1038/s41597-021-00939-2.
  • Markus, T., D. C. Powell, and J. R. Wang. 2006. “Sensitivity of Passive Microwave Snow Depth Retrievals to Weather Effects and Snow Evolution.” IEEE Transactions on Geoscience and Remote Sensing 44 (1): 68–77. https://doi.org/10.1109/TGRS.2005.860208.
  • Mashtayeva, Shamshagul, Liyun Dai, Tao Che, Zhanay Sagintayev, Saltanat Sadvakasova, Marzhan Kussainova, Danara Alimbayeva, and Meerzhan Akynbekkyzy. 2016. “Spatial and Temporal Variability of Snow Depth Derived from Passive Microwave Remote Sensing Data in Kazakhstan.” Journal of Meteorological Research 30 (6): 1033–1043. https://doi.org/10.1007/s13351-016-5109-z.
  • Merkouriadi, Ioanna, Juha Lemmetyinen, Glen E. Liston, and Jouni Pulliainen. 2021. “Solving Challenges of Assimilating Microwave Remote Sensing Signatures With a Physical Model to Estimate Snow Water Equivalent.” Water Resources Research 57 (11). https://doi.org/10.1029/2021WR030119.
  • Ntokas, Konstantin F.F., Jean Odry, Marie Amélie Boucher, and Camille Garnaud. 2021. “Investigating ANN Architectures and Training to Estimate Snow Water Equivalent from Snow Depth.” Hydrology and Earth System Sciences 25 (6): 3017–3040. https://doi.org/10.5194/hess-25-3017-2021.
  • Patil, Akshay, Shradha Mohanty, and Gulab Singh. 2020. “Snow Depth and Snow Water Equivalent Retrieval Using X-Band PolInSAR Data.” Remote Sensing Letters 11 (9): 817–826. https://doi.org/10.1080/2150704X.2020.1779373.
  • Revuelto, Jesús, Paul Billecocq, François Tuzet, Bertrand Cluzet, Maxim Lamare, Fanny Larue, and Marie Dumont. 2020. “Random Forests as a Tool to Understand the Snow Depth Distribution and Its Evolution in Mountain Areas.” Hydrological Processes 34 (26): 5384–5401. https://doi.org/10.1002/hyp.13951.
  • Saberi, Nastaran, Richard Kelly, Jinmei Pan, Michael Durand, Joslin Goh, and K. Andrea Scott. 2021. “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.” IEEE Transactions on Geoscience and Remote Sensing 59 (3): 1876–1889. https://doi.org/10.1109/TGRS.2020.3004594.
  • Shin, Jihoon, Sang Hyun Son, and Yoon Kyung Cha. 2022. “Spatial Distribution Modeling of Customer Complaints Using Machine Learning for Indoor Water Leakage Management.” Sustainable Cities and Society 87:104255. https://doi.org/10.1016/j.scs.2022.104255.
  • Sun, Alexander Y., Dingbao Wang, and Xianli Xu. 2014. “Monthly Streamflow Forecasting Using Gaussian Process Regression.” Journal of Hydrology 511:72–81. https://doi.org/10.1016/j.jhydrol.2014.01.023.
  • Tan, Benyan, Ziqi Gan, and Yan Wu. 2023. “The Measurement and Early Warning of Daily Financial Stability Index Based on XGBoost and SHAP: Evidence from China.” Expert Systems with Applications 227:120375. https://doi.org/10.1016/j.eswa.2023.120375.
  • Tedesco, M., and J. Miller. 2007. “Observations and Statistical Analysis of Combined Active-Passive Microwave Space-Borne Data and Snow Depth at Large Spatial Scales.” Remote Sensing of Environment 111 (2-3): 382–397. https://doi.org/10.1016/j.rse.2007.04.019.
  • Venäläinen, Pinja, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala. 2021. “Impact of Dynamic Snow Density on GlobSnow Snow Water Equivalent Retrieval Accuracy.” The Cryosphere 15 (6): 2969–2981. https://doi.org/10.5194/tc-15-2969-2021.
  • Viallon-Galinier, Léo, Pascal Hagenmuller, and Matthieu Lafaysse. 2020. “Forcing and Evaluating Detailed Snow Cover Models with Stratigraphy Observations.” Cold Regions Science and Technology 180:103163. https://doi.org/10.1016/j.coldregions.2020.103163.
  • Wan, Wei, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao. 2022. “A New Snow Depth Data Set Over Northern China Derived Using GNSS Interferometric Reflectometry from a Continuously Operating Network (GSnow-CHINA v1.0, 2013-2022).” Earth System Science Data 14 (8): 3549–3571. https://doi.org/10.5194/essd-14-3549-2022.
  • Wang, Chang, Liang Chang, and Tieyuan Liu. 2022. “Predicting Student Performance in Online Learning Using a Highly Efficient Gradient Boosting Decision Tree.” In IFIP Advances in Information and Communication Technology 508-521, https://doi.org/10.1007/978-3-031-03948-5_41.
  • Wang, Jianshun, Xiaodong Huang, Yunlong Wang, and Tiangang Liang. 2020. “Retrieving Snow Depth Information from AMSR2 Data for Qinghai-Tibet Plateau.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13:752–768. https://doi.org/10.1109/JSTARS.2020.2970738.
  • Wang, Yunlong, Xiaodong Huang, Jianshun Wang, Minqiang Zhou, and Tiangang Liang. 2019. “AMSR2 Snow Depth Downscaling Algorithm Based on a Multifactor Approach Over the Tibetan Plateau, China.” Remote Sensing of Environment 231:111268. https://doi.org/10.1016/j.rse.2019.111268.
  • Wang, Guangrui, Li Xiaofeng, Chen Xiuxue, Jiang Tao, Zheng Xingming, Wei Yanlin, Wan Xiangkun, and Wang Jian. 2021. “An Investigation on Microwave Transmissivity at Frequencies of 18.7 and 36.5 GHz for Diverse Forest Types During Snow Season.” International Journal of Digital Earth 14 (10): 1354–1379. https://doi.org/10.1080/17538947.2021.1955985.
  • Wei, Yanlin, Lingjia Gu, Ruizhi Ren, and Fachuan He. 2019. “Verification and Analysis of Passive Microwave Snow Depth Retrieve Algorithm Based on Snow Survey Data in China.” Journal of Hydrology 585:74. https://doi.org/10.1117/12.2527371.
  • Wei, Yanlin, Xiaofeng Li, Lingjia Gu, Xingming Zheng, Tao Jiang, Xiaojie Li, and Xiangkun Wan. 2021. “A Dynamic Snow Depth Inversion Algorithm Derived from AMSR2 Passive Microwave Brightness Temperature Data and Snow Characteristics in Northeast China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14:5123–5136. https://doi.org/10.1109/JSTARS.2021.3079703.
  • Wiesmann, Andreas, and Christian Mätzler. 1999. “Microwave Emission Model of Layered Snowpacks.” Remote Sensing of Environment 70 (3): 307–316. https://doi.org/10.1016/S0034-4257(99)00046-2.
  • Wójcik, Rafal, Konstantinos Andreadis, Marco Tedesco, Eric Wood, Tara Troy, and Dennis Lettenmeier. 2008. “Multimodel Estimation of Snow Microwave Emission During CLPX 2003 Using Operational Parameterization of Microphysical Snow Characteristics.” Journal of Hydrometeorology 9 (6): 1491–1505. https://doi.org/10.1175/2008JHM909.1.
  • Xiao, Xiongxin, Shunlin Liang, Tao He, Daiqiang Wu, Congyuan Pei, and Jianya Gong. 2021. “Estimating Fractional Snow Cover from Passive Microwave Brightness Temperature Data Using MODIS Snow Cover Product Over North America.” The Cryosphere 15 (2): 835–861. https://doi.org/10.5194/tc-15-835-2021.
  • Xiao, Xiongxin, Tingjun Zhang, Xinyue Zhong, and Xiaodong Li. 2020. “Spatiotemporal Variation of Snow Depth in the Northern Hemisphere from 1992 to 2016.” Remote Sensing 12 (17): 2728. https://doi.org/10.3390/rs12172728.
  • Xiao, Xiongxin, Tingjun Zhang, Xinyue Zhong, Wanwan Shao, and Xiaodong Li. 2018. “Support Vector Regression Snow-Depth Retrieval Algorithm Using Passive Microwave Remote Sensing Data.” Remote Sensing of Environment 210:48–64. https://doi.org/10.1016/j.rse.2018.03.008.
  • Xu, Xiaocong, Xiaoping Liu, Xia Li, Qian Shi, Yimin Chen, and Bin Ai. 2022. “Global Snow Depth Retrieval from Passive Microwave Brightness Temperature with Machine Learning Approach.” IEEE Transactions on Geoscience and Remote Sensing 60:1–17. https://doi.org/10.1109/TGRS.2021.3127202.
  • Yang, Jianwei, Lingmei Jiang, Liyun Dai, Jinmei Pan, Shengli Wu, and Gongxue Wang. 2019. “The Consistency of SSM/I vs. SSMIS and the Influence on Snow Cover Detection and Snow Depth Estimation Over China.” Remote Sensing 11 (16): 1879. https://doi.org/10.3390/rs11161879.
  • Yang, J. W., L. M. Jiang, J. Lemmetyinen, J. M. Pan, K. Luojus, and M. Takala. 2021. “Improving Snow Depth Estimation by Coupling HUT-Optimized Effective Snow Grain Size Parameters with the Random Forest Approach.” Remote Sensing of Environment 264:112630. https://doi.org/10.1016/j.rse.2021.112630.
  • Yang, Jianwei, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu. 2020. “Snow Depth Estimation and Historical Data Reconstruction Over China Based on a Random Forest Machine Learning Approach.” The Cryosphere 14 (6): 1763–1778. https://doi.org/10.5194/tc-14-1763-2020.
  • Yang, Jianwei, Lingmei Jiang, Shengli Wu, Gongxue Wang, Jian Wang, and Xiaojing Liu. 2019. “Development of a Snow Depth Estimation Algorithm Over China for the FY-3D/MWRI.” Remote Sensing 11 (8): 977. https://doi.org/10.3390/rs11080906.
  • Yang, Jianwei, Jiang Lingmei, Pan Jinmei, Shi Jiancheng, Wu Shengli, Wang Jian, Pan Fangbo. 2022. “Comparison of Machine Learning-Based Snow Depth Estimates and Development of a New Operational Retrieval Algorithm Over China.” Remote Sensing 14 (12): 2800. https://doi.org/10.3390/rs14122800.
  • Yu, Hui, Xuetong Zhang, Tiangang Liang, Hongjie Xie, Xianwei Wang, Qisheng Feng, and Quangong Chen. 2012. “A new Approach of Dynamic Monitoring of 5-day Snow Cover Extent and Snow Depth Based on MODIS and AMSR-E Data from Northern Xinjiang Region” Hydrological Processes 26 (20): 3052–3061. https://doi.org/10.1002/hyp.8253.
  • Yue, Shanna, Che Tao, Dai Liyun. 2022. “Characteristics of Snow Depth and Snow Phenology in the High Latitudes and High Altitudes of the Northern Hemisphere from 1988 to 2018.” Remote Sensing 14 (19): 5057. https://doi.org/10.3390/rs14195057.
  • Zaerpour, Arash, Arash Adib, and Ali Motamedi. 2020. “Snow Depth Retrieval from Passive Microwave Imagery Using Different Artificial Neural Networks.” Arabian Journal of Geosciences 13 (15): 1–16. https://doi.org/10.1007/s12517-020-05642-x.
  • Zhang, Renping, Tiangang Liang, Qisheng Feng, Xiaodong Huang, Wei Wang, Hongjie Xie, and Jing Guo. 2017. “Evaluation and Adjustment of the AMSR2 Snow Depth Algorithm for the Northern Xinjiang Region, China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (9): 3892–3903. https://doi.org/10.1109/JSTARS.2016.2620521.
  • Zhang, Jie, Veijo A. Pohjola, Rickard Pettersson, Björn Norell, Wolf Dietrich Marchand, Ilaria Clemenzi, and David Gustafsson. 2021. “Improving the Snowpack Monitoring in the Mountainous Areas of Sweden from Space: A Machine Learning Approach.” Environmental Research Letters 16 (8): 084007. https://doi.org/10.1088/1748-9326/abfe8d.
  • Zheng, Zeshi, Qin Ma, Shichao Jin, Yanjun Su, Qinghua Guo, and Roger C. Bales. 2019. “Canopy and Terrain Interactions Affecting Snowpack Spatial Patterns in the Sierra Nevada of California.” Water Resources Research 55 (11): 8721–8739. https://doi.org/10.1029/2018WR023758.
  • Zhu, Jiyue, Shurun Tan, Leung Tsang, Do Hyuk Kang, and Edward Kim. 2021. “Snow Water Equivalent Retrieval Using Active and Passive Microwave Observations.” Water Resources Research 57 (7): e2020WR027563. https://doi.org/10.1029/2020WR027563.
  • Zolles, Tobias, and Andreas Born. 2021. “Sensitivity of the Greenland Surface Mass and Energy Balance to Uncertainties in Key Model Parameters.” The Cryosphere 15 (6): 2917–2938. https://doi.org/10.5194/tc-15-2917-2021.