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DL-Corrector-Remapper: A grid-free bias-correction deep learning
  methodology for data-driven high-resolution global weather forecasting

DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting

21 October 2022
Tao Ge
Jaideep Pathak
Akshay Subramaniam
K. Kashinath
    AI4Cl
ArXivPDFHTML

Papers citing "DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting"

3 / 3 papers shown
Title
Post-processing improves accuracy of Artificial Intelligence weather forecasts
Post-processing improves accuracy of Artificial Intelligence weather forecasts
Belinda Trotta
Robert Johnson
Catherine de Burgh-Day
Debra Hudson
Esteban Abellan
James Canvin
Andrew Kelly
Daniel Mentiplay
Benjamin Owen
Jennifer Whelan
23
0
0
17 Apr 2025
Foundation Models for Weather and Climate Data Understanding: A
  Comprehensive Survey
Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey
Shengchao Chen
Guodong Long
Jing Jiang
Dikai Liu
Chengqi Zhang
SyDa
AI4CE
44
24
0
05 Dec 2023
WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local
  Numerical Weather Prediction Bias-Correction
WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction
Binqing Wu
Weiqiu Chen
Wengwei Wang
Bingqing Peng
Liang Sun
Ling Chen
18
5
0
09 Oct 2023
1