Deep Learning for an Improved Prediction of Rainfall Retrievals From Commercial Microwave Links-Reference-Cited by-同舟云学术

Deep Learning for an Improved Prediction of Rainfall Retrievals From Commercial Microwave Links

Published:2020-06-29 Issue:7 Volume:56 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Pudashine Jayaram¹^ORCID,Guyot Adrien¹^ORCID,Petitjean Francois¹^ORCID,Pauwels Valentijn R. N.¹^ORCID,Uijlenhoet Remko²^ORCID,Seed Alan³^ORCID,Prakash Mahesh⁴^ORCID,Walker Jeffrey P.¹^ORCID

Affiliation:

1. Department of Civil Engineering Monash University Melbourne Victoria Australia

2. Hydrology and Quantitative Water Management Group Wageningen University and Research Wageningen The Netherlands

3. Bureau of Meteorology Victoria Australia

4. Data 61, CSIRO Melbourne Victoria Australia

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019WR026255

Reference50 articles.

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5. Precipitation observation using microwave backhaul links in the alpine and pre-alpine region of Southern Germany

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