34 citations · 152 across the 14 of their papers we have counts for
14 papers
An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw Cycle
Divya Kumawat, Ardeshir Ebtehaj, Xiaolan Xu +2
Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere is crucial for understanding permafrost response to global warming and changes in regional an…
Global Estimates of L-band Vegetation Optical Depth and Soil Permittivity over Snow-covered Boreal Forests and Permafrost using SMAP Satellite Data
Divya Kumawat, Ardeshir Ebtehaj, Mike Schwank +2
This article expands the tau-omega model to properly simulate L-band microwave emission of the soil-snow-vegetation continuum through a closed-form solution of Maxwell's equations,…
Global Precipitation Nowcasting of Integrated Multi-satellitE Retrievals for GPM: A U-Net Convolutional LSTM Architecture
Reyhaneh Rahimi, Praveen Ravirathinam, Ardeshir Ebtehaj +3
This paper presents a deep learning architecture for nowcasting of precipitation almost globally every 30 min with a 4-hour lead time. The architecture fuses a U-Net and a convolut…
A Deep Learning Architecture for Passive Microwave Precipitation Retrievals using CloudSat and GPM Data
Reyhaneh Rahimi, Sajad Vahedizadeh, Ardeshir Ebtehaj
This paper presents an algorithm that relies on a series of dense and deep neural networks for passive microwave retrieval of precipitation. The neural networks learn from coincide…
Ensemble Riemannian Data Assimilation over the Wasserstein Space
Sagar K. Tamang, Ardeshir Ebtehaj, Peter J. Van Leeuwen +2
In this paper, we present an ensemble data assimilation paradigm over a Riemannian manifold equipped with the Wasserstein metric. Unlike the Eulerian penalization of error in the E…
Regularized Variational Data Assimilation for Bias Treatment using the Wasserstein Metric
Sagar K. Tamang, Ardeshir Ebtehaj, Dongmian Zou +1
This paper presents a new variational data assimilation (VDA) approach for the formal treatment of bias in both model outputs and observations. This approach relies on the Wasserst…