Hydrologic Sciences and remote sensing Website  | experts@Minnesota |  Google Scholar Citations 

Environmental and Water Resources—physical and data science hydrology, satellite hydrology, remote sensing, land-atmosphere interactions, climate intelligence, and big earth-data analytics

The overarching goal is to provide modern solutions for challenges in sustainable use of water, food, and energy resources. The main focus is on state-of-the-art data and physical science approaches that allow us to better understand land-atmosphere interactions by extracting and integrating the knowledge of remote sensing big-data with the skills of physical models of hydrologic and agricultural systems.

Education

• Ph.D., 2013, Civil Engineering, University of Minnesota
• M.S., 2013, Mathematics, University of Minnesota
• M.Sc., 2001, Environmental Engineering, Iran University of Science and Technology
• B.Sc., 1999, Civil Engineering, Iran University of Science and Technology

Professional Background

• Assistant Professor of Engineering, Department of Civil and Environmental Engineering, Utah State University, 2015-2016
• Postdoctoral Research Fellow, Georgia Institute of Technology, 2013-2015
• Research Assistant, University of Minnesota, 2008-2013

Selected Publications

Ebtehaj, A.M., R. L. Bras (2019), A Physically Constrained Inversion for Super-resolved Passive Microwave Retrieval of Soil Moisture and Vegetation Water Content in L-band, Remote Sensing of Environment, doi: 10.1016/j.rse.2019.111346, arxiv 1806.03298.

Ebtehaj. A.M. , C. D. Kummerow, F. J. Turk (2019), Metric Learning for Approximation of Microwave Channel Error Covariance: Application for Satellite Retrieval of Drizzle and Light Snowfall, IEEE Trans. on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2019.2941682.

Tamang S.K., A.M. Ebtehaj, A. F. Prein, A. J. Heymsfield (2019), Linking Global Changes of Snowfall and Wet-bulb Temperature, Journal of Climate, doi: 10.1175/JCLI-D-19-0254.1, arxiv 1905.07776.

Ebtehaj, A. M. and C. D. Kummerow (2017), Microwave Retrievals of Terrestrial Precipitation over Snow Covered Surfaces: A Lesson from the GPM Satellite, Geophysical Research Letter, doi: 002/2017GL07345.

Ebtehaj, A.M., R.L. Bras, E. Foufoula-Georgiou (2016), Evaluation of ShARP passive rainfall retrievals over snow-covered land surfaces and coastal zones, J. Hydrometeor, 17, 1013–1029. doi: 10.1175/JHM-D-15-0164.1.

Ebtehaj A.M., E. Foufoula-Georgiou, G. Lerman, R. L. Bras (2015), Compressive Earth Observatory: An Insight from AIRS/AMSU Retrievals, Geophys. Res. Lett., 42, doi: 10.1002/2014GL062711

Ebtehaj A.M., R. L. Bras, E. Foufoula-Georgiou, (2015), Shrunken Locally Linear Embedding for Passive Microwave Retrieval of Precipitation, IEEE Trans. on Geosci. and Remote Sens., 99, doi: 10.1109/TGRS.2014.2382436

Lin L., A.M. Ebtehaj, R. L. Bras, A. Flores, J. Wang (2015), Dynamical precipitation downscaling for hydrologic applications via WRF 4D-var data assimilation with Implication in GPM era, J. Hydrometeor, 16, 811-829.

Ebtehaj, A.M., M. Zupanski, G. Lerman, E. Foufoula-Georgiou (2014), Variational data assimilation via sparse regularization, Tellus A, 2014, 66, 21789.