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Algorithmic Hallucinations of Near-Surface Winds: Statistical
  Downscaling with Generative Adversarial Networks to Convection-Permitting
  Scales
v1v2v3 (latest)

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales

Artificial Intelligence for the Earth Systems (AI4ES), 2023
17 February 2023
Nicolaas J. Annau
Alex J. Cannon
A. Monahan
ArXiv (abs)PDFHTMLGithub

Papers citing "Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales"

12 / 12 papers shown
A Probabilistic U-Net Approach to Downscaling Climate Simulations
A Probabilistic U-Net Approach to Downscaling Climate Simulations
Maryam Alipourhajiagha
Pierre-Louis Lemaire
Youssef Diouane
Julie Carreau
AI4Cl
538
1
0
05 Nov 2025
Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed
Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed
Harrison J. Goldwyn
Mitchell Krock
J. Rudi
Daniel J. Getter
J. Bessac
UQCV
150
1
0
21 Aug 2025
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
Atlanta Chakraborty
Julie Bessac
142
0
0
18 Jun 2025
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
Xiao Wang
Jong Youl Choi
Takuya Kurihaya
Isaac Lyngaas
Hong-Jun Yoon
...
Dali Wang
Peter Thornton
Prasanna Balaprakash
M. Ashfaq
Dan Lu
341
7
0
07 May 2025
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall Downscaling
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall DownscalingArtificial Intelligence for the Earth Systems (AI4ES), 2025
Marcello Iotti
Paolo Davini
Jost von Hardenberg
Giuseppe Zappa
GAN
240
2
0
17 Mar 2025
Capturing Climatic Variability: Using Deep Learning for Stochastic
  Downscaling
Capturing Climatic Variability: Using Deep Learning for Stochastic Downscaling
Kiri Daust
Adam Monahan
264
7
0
31 May 2024
ExtremeCast: Boosting Extreme Value Prediction for Global Weather
  Forecast
ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast
Wanghan Xu
Kang Chen
Tao Han
Hao Chen
Wanli Ouyang
Mengwei He
AI4Cl
488
24
0
02 Feb 2024
Observation-Guided Meteorological Field Downscaling at Station Scale: A
  Benchmark and a New Method
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu
Hao Chen
Mengwei He
Wenyuan Li
Keyan Chen
Zhengyi Wang
Wanli Ouyang
Zhengxia Zou
Z. Shi
313
6
0
22 Jan 2024
A 3D super-resolution of wind fields via physics-informed pixel-wise
  self-attention generative adversarial network
A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network
Takuya Kurihana
Kyongmin Yeo
Daniela Szwarcman
Bruce Elmegreen
Karthik Mukkavilli
J. Schmude
Levente J. Klein
167
0
0
20 Dec 2023
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
SyDaAI4CE
403
44
0
05 Dec 2023
Evaluating Loss Functions and Learning Data Pre-Processing for Climate
  Downscaling Deep Learning Models
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models
Xingying Huang
168
0
0
19 Jun 2023
Statistical treatment of convolutional neural network super-resolution
  of inland surface wind for subgrid-scale variability quantification
Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantificationArtificial Intelligence for the Earth Systems (AIES), 2022
Daniel J. Getter
J. Bessac
J. Rudi
Yan Feng
271
3
0
30 Nov 2022
1
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