Reza Ehsani
Reza Ehsani
Software Engineer, Climate Data Scientist
Verified email at - Homepage
Cited by
Cited by
Comparative assessment of snowfall retrieval from microwave humidity sounders using machine learning methods
A Adhikari, MR Ehsani, Y Song, A Behrangi
Earth and Space Science 7 (11), e2020EA001357, 2020
Assessment of the Advanced Very High Resolution Radiometer (AVHRR) for Snowfall Retrieval in High Latitudes Using CloudSat and Machine …
MR Ehsani, A Behrangi, A Adhikari, Y Song, GJ Huffman, RF Adler, ...
Journal of Hydrometeorology 22 (6), 1591-1608, 2021
2019–2020 Australia fire and its relationship to hydroclimatological and vegetation variabilities
MR Ehsani, J Arevalo, CB Risanto, M Javadian, CJ Devine, A Arabzadeh, ...
Water 12 (11), 3067, 2020
Global intercomparison of atmospheric rivers precipitation in remote sensing and reanalysis products
A Arabzadeh, MR Ehsani, B Guan, S Heflin, A Behrangi
Journal of Geophysical Research: Atmospheres 125 (21), e2020JD033021, 2020
A comparison of correction factors for the systematic gauge-measurement errors to improve the global land precipitation estimate
MR Ehsani, A Behrangi
Journal of Hydrology 610, 127884, 2022
NowCasting-Nets: Representation learning to mitigate latency gap of satellite precipitation products using convolutional and recurrent neural networks
MR Ehsani, A Zarei, HV Gupta, K Barnard, E Lyons, A Behrangi
IEEE Transactions on Geoscience and Remote Sensing 60, 1-21, 2022
Nowcasting-Nets: Deep neural network structures for precipitation nowcasting using IMERG
MR Ehsani, A Zarei, HV Gupta, K Barnard, A Behrangi
arXiv preprint arXiv:2108.06868, 2021
Assessment of Snowfall Accumulation from Satellite and Reanalysis Products Using SNOTEL Observations in Alaska
Y Song, P Broxton, MR Ehsani, A Behrangi
Remote Sensing, 2021
Can deep learning extract useful information about energy dissipation and effective hydraulic conductivity from gridded conductivity fields?
MA Moghaddam, PAT Ferre, MR Ehsani, J Klakovich, HV Gupta
Water 13 (12), 1668, 2021
Application of machine learning methods in inferring surface water groundwater exchanges using high temporal resolution temperature measurements
MA Moghaddam, T Ferre, X Chen, K Chen, MR Ehsani
arXiv preprint arXiv:2201.00726, 2022
On the importance of gauge-undercatch correction factors and their impacts on the global precipitation estimates
MR Ehsani, A Behrangi
Preprints, 2021
Towards Interpretable LSTM-based Modelling of Hydrological Systems
LA De la Fuente, MR Ehsani, HV Gupta, LE Condon
EGUsphere 2023, 1-29, 2023
Computing accurate probabilistic estimates of one-D entropy from equiprobable random samples
HV Gupta, MR Ehsani, T Roy, MA Sans-Fuentes, U Ehret, A Behrangi
Entropy 23 (6), 740, 2021
Application of machine learning and remote sensing for gap-filling daily precipitation data of a sparsely gauged basin in East Africa
M Faramarzzadeh, MR Ehsani, M Akbari, R Rahimi, M Moghaddam, ...
Environmental Processes 10 (1), 8, 2023
2020 Australia fire and its relationship to hydroclimatological and vegetation variabilities, Water, 12, 3067
MR Ehsani, J Arevalo, CB Risanto, M Javadian, CJ Devine, A Arabzadeh, ...
The New Version 3.2 Global Precipitation Climatology Project (GPCP) Monthly and Daily Precipitation Products
GJ Huffman, RF Adler, A Behrangi, DT Bolvin, EJ Nelkin, G Gu, ...
Journal of Climate, 1-44, 2023
Evaluating the evolution of ECMWF precipitation products using observational data for Iran: From ERA40 to ERA5
N Ghajarnia, M Akbari, P Saemian, MR Ehsani, SM Hosseini‐Moghari, ...
Earth and Space Science 9 (10), e2022EA002352, 2022
GPCP V3. 2 Release Notes
GJ Huffman, DT Bolvin, EJ Nelkin, RF Adler, A Behrangi, G Gu, ...
Snowfall Retrieval from Satellite-based Microwave Humidity Sounders using Machine Learning Methods
A Adhikari, MR Ehsani, A Behrangi
AGU Fall Meeting Abstracts 2020, H075-09, 2020
Improving Global Satellite Precipiation Products Utilizing Machine Learning
MR Ehsani
The University of Arizona, 2023
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