On Wednesday, 10 February 2016 from 9:00 a.m. until noon (USA Mountain Time), AMSR-E, Aquarius, IceBridge, ICESat/GLAS, MODIS, NISE, and SMAP data will be unavailable for ordering due to system maintenance.

Published Research

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


Du, Jinyang, J. S. Kimball, and L. A. Jones. 2016. Passive Microwave Remote Sensing of Soil Moisture Based on Dynamic Vegetation Scattering Properties for AMSR-E. IEEE Transactions on Geoscience and Remote Sensing 54(1): 597-608. doi: http://dx.doi.org/10.1109/TGRS.2015.2462758.

Eastman, Ryan, and Robert Wood. 2016. Factors Controlling Low-Cloud Evolution over the Eastern Subtropical Oceans: A Lagrangian Perspective Using the A-Train Satellites. Journal of the Atmospheric Sciences 73(1): 331-351. . doi: http://dx.doi.org/10.1175/JAS-D-15-0193.1.

Gevaert, A. I., et al. 2016. Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth. International Journal of Applied Earth Observation and Geoinformation 45(pt.B): 235-244. doi: http://dx.doi.org/10.1016/j.jag.2015.08.006.

Stillman, Susan, and Xubin Zeng. 2016. Evaluation of 22 Precipitation and 23 Soil Moisture Products over a Semiarid Area in Southeastern Arizona. Journal of Hydrometeorology 17(1): 211-230. doi: http://dx.doi.org/10.1175/JHM-D-15-0007.1.

Yang, Kun, et al. 2016. Land surface model calibration through microwave data assimilation for improving soil moisture simulations. Journal of Hydrology 533: 266-276. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.12.018.


2015. A multi-source interactive analysis approach for Northern hemispheric snow depth estimation. IGARSS 2015. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 770-773. doi: http://dx.doi.org/10.1109/IGARSS.2015.7325878.

Beitsch, A., S. Kern, and L. Kaleschke. 2015. Comparison of SSM/I and AMSR-E Sea Ice Concentrations With ASPeCt Ship Observations Around Antarctica. IEEE Transactions on Geoscience and Remote Sensing 53(4): 1985-1996. doi: http://dx.doi.org/10.1109/TGRS.2014.2351497.

Berezowski, Tomasz, Jarosław Chormańskia, and Okke Batelaan 2015. Skill of remote sensing snow products for distributed runoff prediction. Journal of Hydrology 524: 718-732. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.03.025.

Bhagat, Vijay S. 2015. Space-borne Passive Microwave Remote Sensing of Soil Moisture: A Review . Recent Progress in Space Technology 4: 119-150.

Bi, Haiyun, Jianwen Ma, and Fangjian Wang. 2015. An Improved Particle Filter Algorithm Based on Ensemble Kalman Filter and Markov Chain Monte Carlo Method. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(2): 447-459. doi: http://dx.doi.org/10.1109/JSTARS.2014.2322096.

Boccolari, Mauro, and and Flavio Parmiggiani. 2015. On the measure of sea ice area from sea ice concentration data sets. Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015 9638. Art. #963804. Bellingham, WA: SPIE. doi: http://dx.doi.org/10.1117/12.2194087.

Boori, Mukesh, and Ralph Ferraro. 2015. Global Land Cover Classification Based on Microwave Polarization and Gradient Ratio (MPGR). Geoinformatics for Intelligent Transportation. New York, NY: Springer International Publishing, 17-37. doi: http://dx.doi.org/10.1007/978-3-319-11463-7_2.

Bradley, Alice C., et al. 2015. Air-Deployed Microbuoy Measurement of Temperatures in the Marginal Ice Zone Upper Ocean during the MIZOPEX Campaign. Journal of Atmospheric and Oceanic Technology 32(5): 1058-1070. doi: http://dx.doi.org/10.1175/JTECH-D-14-00209.1.

Brown, Zachary W., et al. 2015. Aspects of the marine nitrogen cycle of the Chukchi Sea shelf and Canada Basin. Deep-Sea Research Part II - Topical Studies in Oceanography 118A: 73-87. doi: http://dx.doi.org/10.1016/j.dsr2.2015.02.009.

Cho, Eunsang, Heewon Moon, and Minha Choi. 2015. First Assessment of the Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Contents in Northeast Asia. Journal of the Meteorological Society of Japan 93(1): 117-129. doi: http://dx.doi.org/10.2151/jmsj.2015-008.

Cho, Eunsang, Minha Choi, and Wolfgang Wagner. 2015. An assessment of remotely sensed surface and root zone soil moisture through active and passive sensors in northeast Asia. Remote Sensing of Environment 160: 166-179. doi: http://dx.doi.org/10.1016/j.rse.2015.01.013.

Dai, Liyun, Tao Che, and Yongjian Ding 2015. Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China. Remote Sensing 7(6): 7212-7230. doi: http://dx.doi.org/10.3390/rs70607212.

Djamai, Najib, et al. 2015. Evaluation of SMOS soil moisture products over the CanEx-SM10 area. Journal of Hydrology 520: 254-267. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.11.026.

Du, Jinyang, et al. 2015. Satellite Microwave Retrieval of Total Precipitable Water Vapor and Surface Air Temperature Over Land From AMSR2. IEEE Transactions on Geoscience and Remote Sensing 53(5): 2520-2531. doi: http://dx.doi.org/10.1109/TGRS.2014.2361344.

Dziak, Robert P., et al. 2015. Sources and Levels of Ambient Ocean Sound near the Antarctic Peninsula. PLOS One 10(4). Art. #e0123425. doi: http://dx.doi.org/10.1371/journal.pone.0123425.

Feng, Huihui, and Yuanbo Liu. 2015. Combined effects of precipitation and air temperature on soil moisture in different land covers in a humid basin. Journal of Hydrology 531(pt. 3): 1129-1140. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.11.016.

Fournier, S., et al. 2015. Comparison of spaceborne measurements of sea surface salinity and colored detrital matter in the Amazon plume. JiyebK of Geophysical Research - Oceans 120(5): 3177–3192. doi: http://dx.doi.org/10.1002/2014JC010109.

Frey, Karen E., et al. 2015. Divergent patterns of recent sea ice cover across the Bering, Chukchi, and Beaufort seas of the Pacific Arctic Region. Progress in Oceanography 136: 32-49. doi: http://dx.doi.org/10.1016/j.pocean.2015.05.009.

G A, et al. 2015. Impact of changes in GRACE derived terrestrial water storage on vegetation growth in Eurasia. Environmental Research Letters 10(12). Art. #124024. . doi: http://dx.doi.org/10.1088/1748-9326/10/12/124024.

Good, Elizabeth. 2015. Daily minimum and maximum surface air temperatures from geostationary satellite data. Journal of Geophysical Research - Atmospheres 120(6): 2306-2324. doi: http://dx.doi.org/10.1002/2014JD022438.

Guo, Bing, et al. 2015. An estimation method of soil freeze-thaw erosion in the Qinghai–Tibet Plateau. Natural Hazards : 1808-1823. doi: http://dx.doi.org/10.1007/s11069-015-1808-5.

Gupta, Mukesh, and David G. Barber. 2015. Sub-pixel evaluation of sea ice roughness using AMSR-E data. International Journal of Remote Sensing 36(3): 749-763. doi: http://dx.doi.org/10.1080/01431161.2014.1001081.

Haizhu, Pan, Wang Jian, and Li Hongyi. 2015. Accuracy validation of the MODIS snow albedo products and estimate of the snow albedo under cloud over the Qilian Mountains. Journal of Glaciology and Geocryology 37(1): 49-57. doi: http://dx.doi.org/10.7522/j.issn.1000-0240.2015.0005.

Han, Menglei, et al. 2015. An Algorithm Based on the Standard Deviation of Passive Microwave Brightness Temperatures for Monitoring Soil Surface Freeze/Thaw State on the Tibetan Plateau. IEEE Transactions on Geoscience and Remote Sensing 53(5): 2775-2783. doi: http://dx.doi.org/10.1109/TGRS.2014.2364823.

Han, Xiao-Jing, et al. 2015. Evaluation of temporal variations in soil moisture based on the microwave polarization difference index using in situ data over agricultural areas in China. International Journal of Remote Sensing. doi: http://dx.doi.org/10.1080/01431161.2015.1043161.

Han, Xiao-Jing, et al. 2015. Comparison of AMSR-E soil moisture product and ground-based measurement over agricultural areas in China. IGARSS 2015. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 673 - 676. doi: http://dx.doi.org/10.1109/IGARSS.2015.7325853.

Hao, Cui, Jiahua Zhang, and Fengmei Yao. 2015. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China. International Journal of Applied Earth Observation and Geoinformation 35B: 270-283. doi: http://dx.doi.org/10.1016/j.jag.2014.09.011.

Harsem, Øistein, et al. 2015. Oil Exploration and Sea Ice Projections in the Arctic. Polar Record 51(1): 91-106. doi: http://dx.doi.org/10.1017/S0032247413000624.

He, Binbin, et al. 2015. A Global Grassland Drought Index (GDI) Product: Algorithm and Validation. Remote Sensing 7(10): 12704-12736. doi: http://dx.doi.org/10.3390/rs71012704.

Hsu, C., et al. 2015. Downscaling Advanced Microwave Scanning Radiometer (AMSR-E) Soil Moisture Retrievals Using a Multiple Time-Scale Exponential Rainfall Adjustment Technique. Journal of Geophysics and Remote Sensing 4(139): 1-15. doi: http://dx.doi.org/10.4172/2169-0049.1000139.

Hu, Guangcheng, and Li Jia. 2015. Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations. Remote Sensing 7(3): 3056-3087. doi: http://dx.doi.org/10.3390/rs70303056.

Hutchings, Jennifer K., and Donald K. Perovich. 2015. Preconditioning of the 2007 sea-ice melt in the eastern Beaufort Sea, Arctic Ocean. Annals of Glaciology 56(69): 94-98. doi: http://dx.doi.org/10.3189/2015AoG69A006.

Ito, Masato, et al. 2015. Observations of supercooled water and frazil ice formation in an Arctic coastal polynya from moorings and satellite imagery. Annals of Glaciology 56(69): 307-314. doi: http://dx.doi.org/10.3189/2015AoG69A839.

Ivan, Igor, et al. 2015. Geoinformatics for Intelligent Transportation. . New York, NY: Springer International Publishing. doi: http://dx.doi.org/10.1007/978-3-319-11463-7.

Ivanova, N., et al. 2015. Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations. The Cryosphere 9: 1797-1817. doi: http://dx.doi.org/10.5194/tc-9-1797-2015.

Kern, S., et al. 2015. The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise. The Cryosphere 9(1): 37-52. doi: http://dx.doi.org/10.5194/tc-9-37-2015.

Kim, Miae, et al. 2015. Landfast sea ice monitoring using multisensor fusion in the Antarctic. GIScience & Remote Sensing 52(2): 239-256. doi: http://dx.doi.org/10.1080/15481603.2015.1026050.

Kostyuchenko, Yuriy V. 2015. Infrastructure Vulnerability Assessment Toward Extreme Meteorological Events Using Satellite Data. Numerical Methods for Reliability and Safety Assessment: Multiscale and Multiphysics Systems. Zurich: Springer International Publishing Switzerland, 425-438. doi: http://dx.doi.org/10.1007/978-3-319-07167-1__15.

La, Hyoung Sul, et al. 2015. High density of ice krill (Euphausia crystallorophias) in the Amundsen sea coastal polynya, Antarctica. Deep Sea Research Part I: Oceanographic Research Papers 95: 75-84. doi: http://dx.doi.org/10.1016/j.dsr.2014.09.002.

Lacava, Teodosio, et al. 2015. Integration of Optical and Passive Microwave Satellite Data for Flooded Area Detection and Monitoring. Engineering Geology for Society and Territory – Volume 3. Zurich: Springer International Publishing Switzerland, 631-635.. doi: http://dx.doi.org/10.1007/978-3-319-09054-2_126.

Lakshmi, Venkat, et al. 2015. Remote sensing of the terrestrial water cycle. . Washington, DC: AGU Pub. Committee & Wiley.

Leck, C., and and E. Svensson. 2015. Importance of aerosol composition and mixing state for cloud droplet activation over the Arctic pack ice in summer. Atmospheric Chemistry and Physics 15: 2545-2568. doi: http://dx.doi.org/10.5194/acp-15-2545-2015.

Lecomte, Olivier, et al. 2015. Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model. Ocean Modelling 87: 67-80. doi: http://dx.doi.org/0.1016/j.ocemod.2014.12.003.

Lee, Sang-Moo, et al. 2015. Retrieving the refractive index, emissivity, and surface temperature of polar sea ice from 6.9GHz microwave measurements: A theoretical development. Journal of Geophysical Research - Atmospheres 120(6): 2293-2305. doi: http://dx.doi.org/10.1002/2014JD022481.

Lee, Yong-Keun, Cezar Kongoli, and Jeffrey Key. 2015. An In-Depth Evaluation of Heritage Algorithms for Snow Cover and Snow Depth Using AMSR-E and AMSR2 Measurements. Journal of Atmospheric and Oceanic Technology 32: 2319–2336. doi: http://dx.doi.org/10.1175/JTECH-D-15-0100.1.

Liang, Jiayong, et al. 2015. Improved snow depth retrieval by integrating microwave brightness temperature and visible/infrared reflectance. Remote Sensing of Environment 158: 500-509. doi: http://dx.doi.org/10.1016/j.rse.2014.10.016.

Liu, Yuqiong, et al. 2015. Blending satellite-based snow depth products with in situ observations for streamflow predictions in the Upper Colorado River Basin. Water Resources Research 51(2): 1182-1202. doi: http://dx.doi.org/10.1002/2014WR016606.

Louvet, Samuel, et al. 2015. SMOS soil moisture product evaluation over West-Africa from local to regional scale. Remote Sensing of Environment 156: 383-394. doi: http://dx.doi.org/10.1016/j.rse.2014.10.005.

Macander, Matthew J., et al. 2015. Landsat-based snow persistence map for northwest Alaska. Remote Sensing of Environment 163: 23-31. doi: http://dx.doi.org/10.1016/j.rse.2015.02.028.

Makynen, M., et al. 2015. Thin Ice Detection in the Barents and Kara Seas With AMSR-E and SSMIS Radiometer Data. IEEE Transactions on Geoscience and Remote Sensing 53(9): 5036-5053. doi: http://dx.doi.org/10.1109/TGRS.2015.2416393.

Masina, Simona 2015. An ensemble of eddy-permitting global ocean reanalyses from the MyOcean project. Climate Dynamics. doi: http://dx.doi.org/10.1007/s00382-015-2728-5.

Maurer, Vera, Norbert Kalthoff, and Leonhard Gantner 2015. Predictability of convective precipitation for West Africa: Does the land surface influence ensemble variability as much as the atmosphere?. Atmospheric Research 157: 91-107. doi: http://dx.doi.org/10.1016/j.atmosres.2015.01.016.

McNyset, Kristina M., Carol J. Volk, and Chris E. Jordan. 2015. Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures. Water 7(12): 6827-6846. doi: http://dx.doi.org/10.3390/w7126660.

Meyers, Patrick C., Ralph R. Ferraro, and Nai-Yu Wang 2015. Updated Screening Procedures for GPROF2010 over Land: Utilization for AMSR-E. Journal of Atmospheric and Oceanic Technology 32: 1015-1028. doi: http://dx.doi.org/10.1175/JTECH-D-14-00149.1.

Mishra, Ashok K., et al. 2015. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought . Journal of Hydrology 526: 15-29. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.10.038.

Muskett, Reginald R., et al. 2015. Active-Layer Soil Moisture Content Regional Variations in Alaska and Russia by Ground-Based and Satellite-Based Methods, 2002 through 2014. International Journal of Geosciences 6(1): 12-41. doi: http://dx.doi.org/10.4236/ijg.2015.61002.

Nakata, Kazuki, et al. 2015. Variability and ice production budget in the Ross Ice Shelf Polynya based on a simplified polynya model and satellite observations. Journal of Geophysical Research - Oceans 120(9): 6234-6252. doi: http://dx.doi.org/10.1002/2015JC010894.

Nihashi, Sohey, and Kay I. Oshima. 2015. Circumpolar Mapping of Antarctic Coastal Polynyas and Landfast Sea Ice: Relationship and Variability. Journal of Climate 28(9): 3650-3670. doi: http://dx.doi.org/10.1175/JCLI-D-14-00369.1.

Norouzi, H., et al. 2015. Consistency analysis among microwave land surface emissivity products to improve GPROF precipitation estimations. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 939 - 942. doi: http://dx.doi.org/10.1109/IGARSS.2015.7325921.

Norouzi, H., et al. 2015. Assessment of the consistency among global microwave land surface emissivity products. Atmospheric Measurement Techniques 8: 1197-1205. doi: http://dx.doi.org/10.5194/amt-8-1197-2015.

Oltmanns, Marilena. 2015. Strong wind events across Greenland's coast and their influence on the ice sheet, sea ice and ocean. . MIT. Ph D.

Paloscia, Simonetta, et al. 2015. A comparison between two algorithms for the retrieval of soil moisture using AMSR-E data. Frontiers in Earth Science 3. 00016. doi: http://dx.doi.org/10.3389/feart.2015.00016.

Parard, G., A. A. Charantonis, and A. Rutgerson. 2015. Remote sensing the sea surface CO2 of the Baltic Sea using the SOMLO methodology. Biogeosciences 12: 3369-3384. doi: http://dx.doi.org/10.5194/bg-12-3369-2015.

Patel, Parul, and Hari Shanker Srivastava 2015. An approach to validate soil moisture derived from passive microwave sensors using SAR as an interface. International Journal of Remote Sensing 36(9): 2353-2374. doi: http://dx.doi.org/10.1080/01431161.2015.1034889.

Preußer, Andreas, et al. 2015. Multi-Decadal Variability of Polynya Characteristics and Ice Production in the North Water Polynya by Means of Passive Microwave and Thermal Infrared Satellite Imagery. Remote Sensing 7(12): 15844-15867. doi: http://dx.doi.org/10.3390/rs71215807.

Sanchez-Vidal, Anna, et al. 2015. Particle sources and downward fluxes in the eastern Fram strait under the influence of the west Spitsbergen current. Deep-Sea Research Part I - Oceanographic Research Papers 103: 49-63. doi: http://dx.doi.org/10.1016/j.dsr.2015.06.002.

Santi, E., et al. 2015. Robust assessment of an operational algorithm for the retrieval of soil moisture from AMSR-E data in central Italy. IGARSS 2015. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 1288-1291. doi: http://dx.doi.org/10.1109/IGARSS.2015.7326010.

Schroeder, Ronny, et al. 2015. Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data. Remote Sensing 7(12): 16688-16732. doi: http://dx.doi.org/10.3390/rs71215843.

Scott, M. Chance, and Shouraseni Sen Roy. 2015. Global Emissivity Distribution and Change from 2003 to 2007. The Professional Geographer. doi: http://dx.doi.org/10.1080/00330124.2015.1089131.

Singh, Gagandeep, et al. 2015. Passive Microwave Remote Sensing of Soil Moisture: A Step-ByStep Detailed Methodology using AMSR-E Data over Indian SubContinent. Internation Journal of Advanced Remote Sensing and GIS 4(1): 1045-1063.

Singh, K. K., et al. 2015. Snow depth estimation in the Indian Himalaya using multi-channel passive microwave radiometer. Current Science 108(5): 942-953.

Susca-Lopata, Gabriel, et al. 2015. The Role of Observed Environmental Conditions and Precipitation Evolution in the Rapid Intensification of Hurricane Earl (2010). Monthly Weather Review 143(6): 2207-2223. doi: http://dx.doi.org/10.1175/MWR-D-14-00283.1.

Tamura, Takeshi, et al/ 2015. Helicopter-borne observations with portable microwave radiometer in the Southern Ocean and the Sea of Okhotsk. Annals of Glaciology 56(69): 436-444. doi: http://dx.doi.org/10.3189/2015AoG69A621.

Telegina, A. A. 2015. Studying snow cover in European Russia with the use of remote sensing methods. Proceedings RSHS14 and ICGRHWE14, Guangzhou, China, August 2014 IAHS Pub. 368: 40-45.

Tian, Yudong, et al. 2015. An examination of methods for estimating land surface microwave emissivity. Journal of Geophysical Research - Atmospheres 120(21): 11,114-11,128. doi: http://dx.doi.org/10.1002/2015JD023582.

Virts, Katrina S., and Robert A. Houze, Jr. 2015. Clouds and Water Vapor in the Tropical Tropopause Transition Layer over Mesoscale Convective Systems. Journal of the Atmospheric Sciences 72: 4739-4753. doi: http://dx.doi.org/10.1175/JAS-D-15-0122.1.

Virts, Katrina S., and Robert A. Houze, Jr. 2015. Variation of Lightning and Convective Rain Fraction in Mesoscale Convective Systems of the MJO. Journal of the Atmospheric Sciences 72(5): 1932-1944. doi: http://dx.doi.org/10.1175/JAS-D-14-0201.1.

Wang, Wei, et al. 2015. Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product. Remote Sensing 7(1): 169-194. doi: http://dx.doi.org/10.3390/rs70100169.

Wen, Xin, Hui Lu, Chengwei Li. 2015. An intercomparison of the spatial-temporal characteristics of SMOS and AMSR-E soil moisture products over Mongolia plateau. IGARSS 2015. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 681-684. doi: http://dx.doi.org/10.1109/IGARSS.2015.7325855.

Xu, Xiaoyong 2015. Assimilation of Remotely Sensed Soil Moisture in the MESH Model. Ph. D. University of Waterloo.

Yan, Hongxiang, C. M. DeChant, and H. Moradkhani. 2015. Improving Soil Moisture Profile Prediction With the Particle Filter-Markov Chain Monte Carlo Method. IEEE Transactions on Geoscience and Remote Sensing 53(11): 6134-6147. doi: http://dx.doi.org/10.1109/TGRS.2015.2432067.

Yan, Qiaoling, et al. 2015. Causal effects of shelter forests and water factors on desertification control during 2000–2010 at the Horqin Sandy Land region, China. Journal of Forestry Research 26(1): 33-45. doi: http://dx.doi.org/10.1007/s11676-014-0012-x.

Zeng, Jiangyuan, et al. 2015. Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations. Remote Sensing of Environment 163: 91-110. doi: http://dx.doi.org/10.1016/j.rse.2015.03.008.

Zhai, Chengxing, Jonathan H. Jiang, and Hui Su. 2015. Long-term cloud change imprinted in seasonal cloud variation: More evidence of high climate sensitivity. Geophysical Research Letters 42(20): 8729-8737. doi: http://dx.doi.org/10.1002/2015GL065911.

Zhan, W., et al. 2015. Correction of real-time satellite precipitation with satellite soil moisture observations. Hydrology and Earth System Sciences 19: 4275-4291. doi: http://dx.doi.org/10.5194/hess-19-4275.

Zhang, Miming, et al. 2015. Linking Phytoplankton Activity in Polynyas and Sulfur Aerosols over Zhongshan Station, East Antarctica. Journal of the Atmospheric Sciences 72(12): 4629–4642. doi: http://dx.doi.org/10.1175/JAS-D-15-0094.1.

Zheng, Jing, et al. 2015. The impact of AIRS atmospheric temperature and moisture profiles on hurricane forecasts: Ike (2008) and Irene (2011). Advances in Atmospheric Sciences 32(3): 319-335. doi: http://dx.doi.org/10.1007/s00376-014-3162-z.

Zhou, Ji, et al. 2015. Developing a Temporally Land Cover-Based Look-Up Table (TL-LUT) Method for Estimating Land Surface Temperature Based on AMSR-E Data over the Chinese Landmass. International Journal of Applied Earth Observation and Geoinformation 34: 35-50. doi: http://dx.doi.org/10.1016/j.jag.2014.07.001.

Zhu, Tingting, et al. 2015. Snow depth retrieval based on a novel sea ice concentration algorithm from AMSR-E datasets. Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 762-765. doi: http://dx.doi.org/10.1109/IGARSS.2015.7325876.


Al-Shrafany, Deleen, et al. 2014. Comparative assessment of soil moisture estimation from land surface model and satellite remote sensing based on catchment water balance. Meteorological Applications 21(3): 521-534. doi: http://dx.doi.org/10.1002/met.1357.

Al-Yarri, A., et al. 2014. Merging two passive microwave remote sensing (SMOS and AMSR_E) datasets to produce a long term record of Soil Moisture. Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International: 2269-2272. doi: http://dx.doi.org/10.1109/IGARSS.2014.6946922.

Barrett, Brian W., and George P. Petropoulos. 2014. Satellite Remote Sensing of Surface Soil Moisture. IN: Remote Sensing of Energy Fluxes and Soil Moisture Content edited by George P. Petropoulos: 85-120. Boca Raton: CRC Press.

Bergeron, Jean, et al. 2014. Snow cover estimation using blended MODIS and AMSR-E data for improved watershed-scale spring streamflow simulation in Quebec, Canada. Hydrological Processes 29(16): 4626-4639. doi: http://dx.doi.org/10.1002/hyp.10123.

Bin, C. J., Y. B. Qiu, and L. J. Shi. 2014. Validation and Algorithms Comparative Study for Microwave Remote Sensing of Snow Depth over China. 35th International Symposium on Remote Sensing of Environment (ISRSE35) (Conf. Series: Earth and Environmental Science) 17:. Art. #012148. doi: http://dx.doi.org/10.1088/1755-1315/17/1/012148.

Boori, Mukesh, Ralph Ferraro, and V. Voženílek. 2014. NASA EOS Aqua Satellite AMSR-E Data for Snow Variation. Journal of Geology and Geosciences 3:. Art. #e116. doi: http://dx.doi.org/10.4172/2329-6755.1000e116.