Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach
The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the...
Main Authors: | Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10487101/ |
Similar Items
-
Design of a Smart Early Warning Hydrometeorological System: The Easy Project in Ermionida
by: Angelos Chasiotis, et al.
Published: (2023-09-01) -
Output updating of a physically based model for gauged and ungauged sites of the Upper Thames River watershed
by: Jeevaragagam Ponselvi, et al.
Published: (2023-09-01) -
Information papers Malaysian Meteorological Service
Published: ([199) -
Kertas-kertas maklumat Perkhidmatan Kajicuaca Malaysia
Published: ([199) -
Advection-Free Convolutional Neural Network for Convective Rainfall Nowcasting
by: Jenna Ritvanen, et al.
Published: (2023-01-01)