On Wednesday, August 23, from 10:30 a.m. to 12:00 p.m. (noon) (USA Mountain Time), AMSR-E, Aquarius, IceBridge, ICESat/GLAS, MEaSUREs, MODIS, NISE, SMAP, and VIIRS data will not be available due to system maintenance.

Published Research

The following references cite studies that used MODIS data from NSIDC. Please contact User Services if you have a reference you would like to share on this page.


Abera, Wuletawu, et al. 2017. Estimating the water budget components and their variability in a pre-alpine basin with JGrass-NewAGE. Advances in Water Resources 104: 37-54. doi: http://dx.doi.org/10.1016/j.advwatres.2017.03.010.

Adnan, Muhammad, et al. 2017. Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan. Polish Journal of Environmental Studies 26(2): 525-542. doi: http://dx.doi.org/10.15244/pjoes/66719.

Azmat, M., et al. 2017. Impacts of changing climate and snow cover on the flow regime of Jhelum River, Western Himalayas. Regional Environmental Change 17(3): 813–825. doi: http://dx.doi.org/10.1007/s10113-016-1072-6.

Baldwin, D., et al. 2017. Validation of Suomi-NPP VIIRS sea ice concentration with very high-resolution satellite and airborne camera imagery. ISPRS Journal of Photogrammetry and Remote Sensing 130: 122–138. doi: http://dx.doi.org/10.1016/j.isprsjprs.2017.05.018.

Barry, Roger G. 2017. The Arctic Cryosphere in the Twenty-First Century. Geographical Review 107(1): 69-88. doi: http://dx.doi.org/10.1111/gere.12227.

Bhardwaj, Anshuman, et al. 2017. MODIS-based estimates of strong snow surface temperature anomaly related to high altitude earthquakes of 2015. Remote Sensing of Environment 188: 1-8. doi: http://dx.doi.org/10.1016/j.rse.2016.11.005.

Bright, Ryan M., et al. 2017. Local temperature response to land cover and management change driven by non-radiative processes. Nature Climate Change 7: 296-302. doi: http://dx.doi.org/10.1038/nclimate3250.

Caro, Tim, et al. 2017. Why is the giant panda black and white? . Behavioral Ecology 28(3): 657-667. doi: http://dx.doi.org/10.1093/beheco/arx008.

Chen, Xi, et al. 2017. Improved modeling of snow and glacier melting by a progressive two-stage calibration strategy with GRACE and multisource data: How snow and glacier meltwater contributes to the runoff of the Upper Brahmaputra River basin?. Water Resources Research 53(3): 2431-2466. doi: http://dx.doi.org/10.1002/2016WR019656.

Collados‐Lara, Antonio-Juan, E. Pardo-Igúzquiza, and D. Pulido-Velazquez. 2017. Spatiotemporal estimation of snow depth using point data from snow stakes, digital terrain models, and satellite data. Hydrological Processes 31(10): 1966–1982. doi: http://dx.doi.org/10.1002/hyp.11165.

Curtis, Aaron, and Philip Kyle. 2017. Methods for mapping and monitoring global glaciovolcanism. Journal of Volcanolgy and Geothermal Research 333-334: 134–144. doi: http://dx.doi.org/10.1016/j.jvolgeores.2017.01.017.

Ga, Zhuo, et al. 2017. Distribution of winter-spring snow over the Tibetan Plateau and its relationship with summer precipitation in Yangtze River. Sciences in Cold and Arid Regions 9(1): 20-28. doi: http://dx.doi.org/10.3724/SP.J.1226.2017.00020.

Huang, Xiaodong, et al. 2017. Impact of climate and elevation on snow cover using integrated remote sensing snow products in Tibetan Plateau. Remote Sensing of Environment 190: 274–288. doi: http://dx.doi.org/10.1016/j.rse.2016.12.028.

Hurley, Mark A., et al. 2017. Regional-scale models for predicting overwinter survival of juvenile ungulates. Journal of Wildlife Management 81(3): 364–378. doi: http://dx.doi.org/10.1002/jwmg.21211.

Jin, Suming, et al. 2017. A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011. Remote Sensing of Environment 195: 44-55. doi: http://dx.doi.org/10.1016/j.rse.2017.04.021.

Kwon, Yonghwan, et al. 2017. Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation . Journal of Hydrometeorology 17(11): 2853–2874. doi: http://dx.doi.org/10.1175/JHM-D-16-0028.1.

Le Corre, Mael, Christian Dussault, and Steeve D. Côté. 2017. Weather conditions and variation in timing of spring and fall migrations of migratory caribou . Journal of Mammology 98(1): 260-271. doi: http://dx.doi.org/10.1093/jmammal/gyw177.

Levin, Noam. 2017. The impact of seasonal changes on observed nighttime brightness from 2014 to 2015 monthly VIIRS DNB composites. Remote Sensing of Environment 193: 150-164. doi: http://dx.doi.org/10.1016/j.rse.2017.03.003.

Li, Xinghua, et al. 2017. Monitoring snow cover variability (2000–2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method. Journal of Hydrology 551: 314-327. doi: http://dx.doi.org/10.1016/j.jhydrol.2017.05.049.

Lin, Ya, Hao Xu, and Yuqi Bai. 2017. Semantically Enhanced Catalogue Search Model for Remotely Sensed Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10(4): 1256-1264. doi: http://dx.doi.org/10.1109/JSTARS.2016.2590835.

Liu, J. P., and W. C. Zhang. 2017. Long term spatio-temporal analyses of snow cover in Central Asia using ERA-Interim and MODIS products. IOP Conf. Series: Earth and Environmental Science 57. Art. #UNSP 012033. doi: http://dx.doi.org/10.1088/1755-1315/57/1/012033.

Mernild, Sebastian H., et al. 2017. The Andes Cordillera. Part II: Rio Olivares Basin snow conditions (1979–2014), central Chile. International Journal of Climatology 37(4): 1699–1715. doi: http://dx.doi.org/10.1002/joc.4828.

Mernild, Sebastian H., et al. 2017. The Andes Cordillera. Part IV: spatio-temporal freshwater run-off distribution to adjacent seas (1979–2014). International Journal of Climatology 37(7): 3175–3196. doi: http://dx.doi.org/10.1002/joc.4922.

Mernild, Sebastian H., et al. 2017. The Andes Cordillera. Part I: snow distribution, properties, and trends (1979–2014). International Journal of Climatology 37(4): 1680–1698. doi: http://dx.doi.org/10.1002/joc.4804.

Möller, M., and R. Möller. 2017. Modeling glacier-surface albedo across Svalbard for the 1979–2015 period: The HiRSvaC500-α data set. Journal of Advances in Modeling Earth Systems 9(1): 404–422. doi: http://dx.doi.org/10.1002/2016MS000752.

Negi, H. S., et al. 2017. Observed spatio-temporal changes of winter snow albedo over the north-west Himalaya. International Journal of Climatology 37(5): 2304–2317. doi: http://dx.doi.org/10.1002/joc.4846.

Pardo-Igúzquiza, Eulogio, Antonio-Juan Collados-Lara, and David Pulido-Velazquez. 2017. Estimation of the spatiotemporal dynamics of snow covered area by using cellular automata models. Journal of Hydrology 550: 230–238. doi: http://dx.doi.org/10.1016/j.jhydrol.2017.04.058.

Reichle, Rolf H., et al. 2017. Assessment of MERRA-2 Land Surface Hydrology Estimates . Journal of Climate 30(8): 2937–2960. doi: http://dx.doi.org/10.1175/JCLI-D-16-0720.1.

Saavedra, Fredy A., et al. 2017. A snow climatology of the Andes Mountains from MODIS snow cover data. International Journal of Climatology 37(3): 1526–1539. doi: http://dx.doi.org/10.1002/joc.4795.

Swanson, David K. 2017. Trends in Greenness and Snow Cover in Alaska’s Arctic National Parks, 2000–2016. Remote Sensing 9(6): 514-533. doi: http://dx.doi.org/10.3390/rs9060514.

Titkova T. B., and V. V. Vinogradova. 2017. Snow occurrence time on the Russia’s territory in the early 21st century (from satellite data) (in Russian). Led i Sneg 57(1): 25-33. doi: http://dx.doi.org/10.15356/2076-6734-2017-1-25-33.

Yu, Xiaoqi, et al. 2017. Cloud removing method for daily snow mapping over Central Asia and Xinjiang, China. IOP Conference Series: Earth and Environmental Science 57. Art. # UNSP 012048. doi: http://dx.doi.org/10.1088/1755-1315/57/1/012048.

Zhang, Chunxi, Kevin Hamilton, and Yuqing Wang. 2017. Monitoring and projecting snow on Hawaii Island. Earth's Future 5(5): 436-448. doi: http://dx.doi.org/10.1002/2016EF000478.

Zhang, Yonghong, et al. 2017. Snow Cover Monitoring in Qinghai-Tibetan Plateau Based on Chinese Fengyun-3/VIRR Data. Journal of the Indian Society of Remote Sensing 45(2): 271-283. doi: http://dx.doi.org/10.1007/s12524-015-0527-4.

Zhao, Guosong, et al. 2017. Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration. Remote Sensing 9(2): 121-135. doi: http://dx.doi.org/10.3390/rs9020121.

Zheng, Wenlong, et al. 2017. Vertical distribution of snow cover and its relation to temperature over the Manasi River Basin of Tianshan Mountains, Northwest China. Journal of Geographical Sciences 27(4): 403-419. doi: http://dx.doi.org/10.1007/s11442-017-1384-6.

Østby, Torbjørn Ims, Jon Ove Hagen, and Regine Hock. 2017. Diagnosing the decline in climatic mass balance of glaciers in Svalbard over 1957-2014 . The Cryosphere 11(1): 191-215. doi: http://dx.doi.org/10.5194/tc-11-191-2017#sthash.X1C6r1p9.dpuf.


Ashraf, Arshad, et al. 2016. Remote Sensing of the Glacial Environment Influenced by Climate Change. Environmental Applications of Remote Sensing. Rijeka, Croatia: InTech. doi: http://dx.doi.org/10.5772/62134.

Azmat, Muhammad, et al. 2016. Hydrological modeling to simulate streamflow under changing climate in a scarcely gauged cryosphere catchment. Environmental Earth Sciences 75. Art. #186. doi: http://dx.doi.org/10.1007/s12665-015-5059-2.

Boike, Julia, et al. 2016. Satellite-derived changes in the permafrost landscape of central Yakutia, 2000–2011: Wetting, drying, and fires. Global and Planetary Change 139: 116-127. doi: http://dx.doi.org/10.1016/j.gloplacha.2016.01.001.

Bookhagen, Bodo. 2016. Glaciers and monsoon systems. Monsoon and Climate Change. New York, NY: Springer International Publishing, 225-249. doi: http://dx.doi.org/10.1007/978-3-319-21650-8_11.

Bruggeman, Jason E., et al. 2016. Multi-season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population. IBIS 158(1): 61-74. doi: http://dx.doi.org/10.1111/ibi.12313.

Chen, Xiaona, Shunlin Liang, and Yunfeng Cao. 2016. Satellite observed changes in the Northern Hemisphere snow cover phenology and the associated radiative forcing and feedback between 1982 and 2013. Environmental Research Letters 11. Art. #084002. doi: http://dx.doi.org/10.1088/1748-9326/11/8/084002.

Cornwell, E., N. P. Molotch, and J. McPhee. 2016. Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover . Hydrology and Earth System Sciences 20: 411-430. doi: http://dx.doi.org/10.5194/hess-20-411-2016.

Cui, Yaokui, et al. 2016. Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau. Journal of Hydrology 543B: 242-254. doi: http://dx.doi.org/10.1016/j.jhydrol.2016.10.005.

Da Ronco, Pierfrancesco, et al. 2016. Comparing COSMO-CLM simulations and MODIS data of snow cover extent and distribution over Italian Alps. Climate Dynamics. doi: http://dx.doi.org/10.1007/s00382-016-3054-2.

Dedieu, Jean-Pierre, et al. 2016. On the Importance of High-Resolution Time Series of Optical Imagery for Quantifying the Effects of Snow Cover Duration on Alpine Plant Habitat. Remote Sensing 8(6). Art. #481. doi: http://dx.doi.org/10.3390/rs8060481.

Dong, Chunyu, and Lucas Menzel. 2016. Improving the accuracy of MODIS 8-day snow products with in situ temperature and precipitation data. Journal of Hydrology 534: 466-477. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.12.065.

Dong, Chunyu, and Lucas Menzel. 2016. Producing cloud-free MODIS snow cover products with conditional probability interpolation and meteorological data. Remote Sensing of Environment 186: 439–451. doi: http://dx.doi.org/10.1016/j.rse.2016.09.019.

Fassnacht, Steven R. et al. 2016. Deriving snow-cover depletion curves for different spatial scales from remote sensing and snow telemetry data. Hydrological Processes 30(11): 1708-1717. doi: http://dx.doi.org/10.1002/hyp.10730.

Gafurov, A., et al. 2016. MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data. Environmental Earth Sciences 75(14). Art. #1078. doi: http://dx.doi.org/10.1007/s12665-016-5869-x.

Good, Elizabeth J. 2016. An in situ-based analysis of the relationship between land surface “skin” and screen-level air temperatures. Journal of Geophysical Research - Atmospheres 121(15): 8801-8819. doi: http://dx.doi.org/10.1002/2016JD025318.

Gutjahr, Oliver, et al. 2016. Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model. The Cryosphere 10: 2999-3019. doi: http://dx.doi.org/10.5194/tc-10-2999-2016.

Hawotte, Florent, et al. 2016. Assessment of Automated Snow Cover Detection at High Solar Zenith Angles with PROBA-V. Remote Sensing 8(9). Art. #699. doi: http://dx.doi.org/10.3390/rs8090699.

Huang, Xiaodong, et al. 2016. Spatiotemporaldynamicsofsnowcoverbased onmulti-sourceremotesensingdatainChina. Cryosphere 10(5): 2453-2463. doi: http://dx.doi.org/10.5194/tc-10-2453-2016.

Jeong, Dae Il, Laxmi Sushama, and M. Naveed Khaliq. 2016. Attribution of spring snow water equivalent (SWE) changes over the northern hemisphere to anthropogenic effects. Climate Dynamics 48(11-12): 3645-3658. doi: http://dx.doi.org/10.1007/s00382-016-3291-4.

Jiang, Youyan, et al. 2016. Variation in the snow cover on the Qilian Mountains and its causes in the early 21st century. Geomatics, Natural Hazards and Risk. doi: http://dx.doi.org/10.1080/19475705.2016.1176078.

Kadlec, J., A. Woodruff Miller, and Daniel P. Ames. 2016. Extracting Snow Cover Time Series Data from Open Access Web Mapping Tile Services. Journal of the American Water Resources Association (JAWRA) 52(4): 916-932. doi: http://dx.doi.org/10.1111/1752-1688.12387.

Kadlec, Jiri. 2016. Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping. Ph. D. Brigham Young University.

Kar, Sarat C., and Sarita Tiwari. 2016. Model simulations of heavy precipitation in Kashmir, India, in September 2014. Natural Hazards 81(1): 167-188. doi: http://dx.doi.org/10.1007/s11069-015-2073-3.

Karimi, Hamid, et al. 2016. Comparison of SRM and WetSpa models efficiency for snowmelt runoff simulation. Environmental Earth Sciences 75(8). Art. #664. doi: http://dx.doi.org/10.1007/s12665-016-5490-z.

Krajčí, Pavel, Ladislav Holko, and Juraj Parajka. 2016. Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014. Journal of Hydrology and Hydromechanics 64(1): 12-22. doi: http://dx.doi.org/10.1515/johh-2016-0011.

Li, Haixing, Xingong Li, and Pengfeng Xiao. 2016. Impact of Sensor Zenith Angle on MOD10A1 Data Reliability and Modification of Snow Cover Data for the Tarim River Basin. Remote Sensing 8(9). Art. #750. doi: http://dx.doi.org/10.3390/rs8090750.

Li, Yue, et al. 2016. Evaluating biases in simulated land surface albedo from CMIP5 global climate models. Journal of Geophysical Research - Atmospheres 121(11): 6178–6190. doi: http://dx.doi.org/10.1002/2016JD024774.

Marcil, Gino-Karl, Mélanie Trudel, and Robert Leconte. 2016. Using Remotely Sensed MODIS Snow Product for the Management of Reservoirs in a Mountainous Canadian Watershed. Water Resources Management 30(8): 2735–2747. doi: http://dx.doi.org/10.1007/s11269-016-1319-5.

Martin, Eric, et al. 2016. On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of France. Surveys in Geophysics 37(2): 223-247. doi: http://dx.doi.org/10.1007/s10712-016-9366-2.

Meng, Chunlei. 2016. Quantifying the impacts of snow on surface energy balance through assimilating snow cover fraction and snow depth. Meteorology and Atmospheric Physics. doi: http://dx.doi.org/10.1007/s00703-016-0486-5.

Meng, Fanchong, et al. 2016. Impacts of recent climate change on the hydrology in the source region of the Yellow River basin. Journal of Hydrology: Regional Studies 6: 66–81. doi: http://dx.doi.org/10.1016/j.ejrh.2016.03.003.

Minora, Umberto, et al. 2016. Glacier area stability in the Central Karakoram National Park (Pakistan) in 2001–2010. Progress in Physical Geography 40(5): 629 - 660. doi: http://dx.doi.org/10.1177/0309133316643926.

Mishra, P. et al. 2016. Accuracy Assessment of MODIS Fractional Snow Cover Product for Eastern Himalayan Catchment. Journal of the Indian Society of Remote Sensing. doi: http://dx.doi.org/10.1007/s12524-016-0548-7.

Morriss, B. F., et al. 2016. Persistence-based temporal filtering for MODIS snow products. Remote Sensing of Environment 175: 130-137. doi: http://dx.doi.org/10.1016/j.rse.2015.12.030.

Mozaffari, A., et al. 2016. A hierarchical selective ensemble randomized neural network hybridized with heuristic feature selection for estimation of sea-ice thickness. Applied Intelligence 46(1): 16-33. doi: http://dx.doi.org/10.1007/s10489-016-0815-x.

Mozaffari, A., et al. 2016. A modular ridge randomized neural network with differential evolutionary distributor applied to the estimation of sea ice thickness. Soft Computing. doi: http://dx.doi.org/10.1007/s00500-016-2074-5.

Muhammad, P., C. Duguay, and K.-K. Kang. 2016. Monitoring ice break-up on the Mackenzie River using MODIS data. Cryosphere 10(2): 569-584. doi: http://dx.doi.org/10.5194/tc-10-569-2016.

Muto, Atsuhiro, et al. 2016. Subglacial bathymetry and sediment distribution beneath Pine Island Glacier ice shelf modeled using aerogravity and in situ geophysical data: New results. Earth and Planetary Letters 433: 63-75. doi: http://dx.doi.org/10.1016/j.epsl.2015.10.037.

Naeem, Usman Ali, et al. 2016. Investigation of temporal change in glacial extent of Chitral watershed using Landsat data. Environmental Monitoring and Assessment 188. Art. #43. doi: http://dx.doi.org/10.1007/s10661-015-5026-0.

Painter, Tom, et al. 2016. The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo. Remote Sensing of Environment 184: 139-152. doi: http://dx.doi.org/10.1016/j.rse.2016.06.018.

Preußer, Andreas, et al. 2016. Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea. The Cryosphere 10: 3021-3042. doi: http://dx.doi.org/10.5194/tc-10-3021-2016.

Rani, Seema, and S. Sreekesh. 2016. An Analysis of Pattern of Changes in Snow Cover in the Upper Beas River Basin, Western Himalaya. Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment: 899-903. New Dehli: Springer International Publishing. N. Janardhana Raju, editor.. doi: http://dx.doi.org/10.1007/978-3-319-18663-4_139.

Rhoades, Alan, et al. 2016. Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM. Journal of Applied Meteorology and Climatology 55(1): 173-196. doi: http://dx.doi.org/10.1175/JAMC-D-15-0156.1.

Rondeau-Genesse, Gabriel, Mélanie Trudel, and Robert Leconte. 2016. Monitoring snow wetness in an Alpine Basin using combined C-band SAR and MODIS data. Remote Sensing of Environment 183: 304-317. doi: http://dx.doi.org/10.1016/j.rse.2016.06.003.

Rondeau-Genesse, Gabriel, Mélanie Trudel, and Robert Leconte. 2016. Monitoring snow wetness in an Alpine Basin using combined C-band SAR and MODIS data. Remote Sensing of Environment 183: 304-317. doi: http://dx.doi.org/10.1016/j.rse.2016.06.003.

Saleh, Mahdi, and Ghaleb Faour. 2016. Implementation of an automated snow monitoring system using MODIS products in Lebanon . 2016 18th Mediterranean Electrotechnical Conference (MELECON) : 1-4. Lemesos: IEEE. doi: http://dx.doi.org/10.1109/MELCON.2016.7495479.

Snehmani, et al. 2016. Analysis of snow cover and climatic variability in Bhaga basin located in western Himalaya. Geocarta International 31(10): 1094-1107.

Song, Chengyun, and Li Jia. 2016. A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia. Remote Sensing 8(9): Art. #703. doi: http://dx.doi.org/10.3390/rs8090703.

Spiess, Marina, Eva Huintjes, and Christoph Schneider. 2016. Comparison of modelled- and remote sensing- derived daily snow line altitudes at Ulugh Muztagh, northern Tibetan Plateau. Journal of Mountain Science 13(4): 593-613. doi: http://dx.doi.org/10.1007/s11629-015-3818-x.

Sugg, Johnathan W., et al. 2016. Sub-regional snow cover distribution across the southern Appalachian Mountains. Physical Geography 38(2): 105-123. doi: http://dx.doi.org/10.1080/02723646.2016.1162020.

Tahir, Adnan Ahmad, et al. 2016. Comparative assessment of spatiotemporal snow cover changes and hydrological behavior of the Gilgit, Astore and Hunza River basins (Hindukush–Karakoram–Himalaya region, Pakistan). Meteorology and Atmospheric Physics. doi: http://dx.doi.org/10.1007/s00703-016-0440-6.

Tarasova, L., et al. 2016. Effects of input discretization, model complexity, and calibration strategy on model performance in a data-scarce glacierized catchment in Central Asia. Water Resources Research 52(6): 4674–4699. doi: http://dx.doi.org/10.1002/2015WR018551.

Toure, Ally M., et al. 2016. Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4). Journal of Hydrometeorology 17(1): 153–170. doi: http://dx.doi.org/10.1175/JHM-D-14-0165.1.

Trubilowicz, Joel William. 2016. Hydrometeorology and streamflow response during rain-on-snow events in a coastal mountain region. . Ph. D. University of British Columbia.

Uysal, Gökçen, Aynur Şensoy, and Arda Şorman. 2016. Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products. Journal of Hydrology 543B: 630–650. doi: http://dx.doi.org/10.1016/j.jhydrol.2016.10.037.

Wang, Jun, Yang Wang, and Shiji Wang. 2016. Biophysical and socioeconomic drivers of the dynamics in snow hazard impacts across scales and over heterogeneous landscape in Northern Tibet. Natural Hazards 81(3): 1499-1514. doi: http://dx.doi.org/10.1007/s11069-015-2142-7.

Willmes, Sacha, and Gunther Heinemann. 2016. Sea-Ice Wintertime Lead Frequencies and Regional Characteristics in the Arctic, 2003–2015. Remote Sensing 8(1). Art. #4. doi: http://dx.doi.org/10.3390/rs8010004.

Wu, Xuejiao, et al. 2016. Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, north-west China. Hydrological Processes 30(21): 3967–3977. doi: http://dx.doi.org/10.1002/hyp.10924.

Wulf, Hendrik, Bodo Bookhagena, and Dirk Scherlera. 2016. Differentiating between rain, snow, and glacier contributions to river discharge in the western Himalaya using remote-sensing data and distributed hydrological modeling. Advances in Water Resources 88: 152–169. doi: http://dx.doi.org/10.1016/j.advwatres.2015.12.004.

Wunderle, Stefan, Timm Gross, and Fabia Hüsler. 2016. Snow Extent Variability in Lesotho Derived from MODIS Data (2000–2014). Remote Sensing 8(6). Art. #448. doi: http://dx.doi.org/10.3390/rs8060448.

Xu, Jianhui, et al. 2016. Joint DEnKF-albedo assimilation scheme that considers the common land model subgrid heterogeneity and a snow density-based observation operator for improving snow depth simulations. Journal of Applied Remote Sensing 10(3). Art. #036001. doi: http://dx.doi.org/10.1117/1.JRS.10.036001.

Xu, Jianhui, et al. 2016. Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator. Journal of Hydrometeorology 18(1): 119-138. doi: http://dx.doi.org/10.1175/JHM-D-16-0149.1.

Xu, Y., V. Ramanathan, and W. M. Washington. 2016. Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols. Atmospheric Chemistry and Physics 16: 1303-1315. doi: http://dx.doi.org/10.5194/acp-16-1303-2016.