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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.03279.

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Outbound references

Observation dcf210da-5572-436b-a0d4-7405bdc739f1 · outbound

This paper cites by Lewis F.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model by Lewis F

Reference 1

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Observation 45e267ff-8b13-49a9-9941-8b5b090ea2bc · outbound

This paper cites Maier and Graeme C.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Maier and Graeme C

Reference 2

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Observation dd650f56-51f0-4dbe-a0ee-6d9f24ceeb38 · outbound

This paper cites Papagiannaki, K.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Papagiannaki, K

Reference 3

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This paper cites Olatunji, Eyitayo Adeoye, Tien-Chien Jen, and Daniel M.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Olatunji, Eyitayo Adeoye, Tien-Chien Jen, and Daniel M

Reference 4

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Observation 354fa125-c176-41d7-a3f0-1db0d5a13cf6 · outbound

This paper cites A description of the advanced research wrf version 3, 06 2008.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model A description of the advanced research wrf version 3, 06 2008

Reference 5

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Observation 9210d936-db15-4495-9cbe-61e7c18970a4 · outbound

This paper cites Skamarock, Joseph B.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Skamarock, Joseph B

Reference 6

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Unresolved cited work

Reference 7

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Observation ecb08d05-c5de-40d2-a97e-9d108501748a · outbound

This paper cites Bruinsma, Tom R.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Bruinsma, Tom R

Reference 8

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Observation bb1e5c07-d76d-47e8-8fcc-a74471f1dbf0 · outbound

This paper cites Learning skillful medium-range global weather forecasting.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Learning skillful medium-range global weather forecasting

Reference 9

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This paper cites A foundation model for the earth system.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model A foundation model for the earth system

Reference 10

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This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 11

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Unresolved cited work

Reference 12

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Reference 13

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Unresolved cited work

Reference 14

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This paper cites Yinglong-weather: Ai-based limited area models for forecasting of non-precipitation surface meteorological vari- ables, 2025.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Yinglong-weather: Ai-based limited area models for forecasting of non-precipitation surface meteorological vari- ables, 2025

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Observation 26e03c32-a2ec-4cb9-a5db-ad0512da8711 · outbound

This paper cites Diffusion-lam: Proba- bilistic limited area weather forecasting with diffusion, 2025.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Diffusion-lam: Proba- bilistic limited area weather forecasting with diffusion, 2025

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Observation a53aba49-0da9-4ca0-aa0b-b56e08391dc0 · outbound

This paper cites Building machine learning limited area models: Kilometer-scale weather forecasting in realistic settings, 2025.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Building machine learning limited area models: Kilometer-scale weather forecasting in realistic settings, 2025

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This paper cites Efficient localized adaptation of neural weather forecasting: A case study in the MENA region, 2024.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Efficient localized adaptation of neural weather forecasting: A case study in the MENA region, 2024

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Unresolved cited work

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Dowell, Curtis R

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This paper cites Challenges and design choices for global weather and climate models based on machine learning.Geoscientific Model Development, 11(10):3999–4009, 2018.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Challenges and design choices for global weather and climate models based on machine learning.Geoscientific Model Development, 11(10):3999–4009, 2018

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This paper cites Can machines learn to predict weather? using deep learning to predict gridded 500-hpa geopotential height from historical weather data.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Can machines learn to predict weather? using deep learning to predict gridded 500-hpa geopotential height from historical weather data

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This paper cites Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere.Journal of Advances in Modeling Earth Systems, 12(9):e2020MS002109, 2020.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere.Journal of Advances in Modeling Earth Systems, 12(9):e2020MS002109, 2020

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This paper cites The graph neural network model.IEEE Transactions on Neural Networks, 2008.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model The graph neural network model.IEEE Transactions on Neural Networks, 2008

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Attention is all you need

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model ClimaX: A foundation model for weather and climate

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Graph-based neural weather prediction for limited area modeling, 2023

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Regional data-driven weather modeling with a global stretched-grid, 2024

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Overview and meteorological validation of the wind integration national dataset toolkit

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Service change notice 22- 68: Correction of the specification of elevation of the great lakes in the high resolution rapid re- fresh (hrrr)

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Era5 hourly data on single levels from 1940 to present

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model The era5 global reanalysis.Quarterly journal of the royal meteorological society, 146(730):1999–2049, 2020

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Accelerating the super-resolution convolu- tional neural network

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Photo-realistic single image super-resolution using a generative adversarial network

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Fast-srgan

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Kilometer-scale convection allowing model emulation using generative diffusion modeling, 2024

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From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model First lessons learnt from metop

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Observation 19d3e40c-2dca-4947-84f9-338ede7f6476 · outbound

This paper cites Era5: Data documentation – observations.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Era5: Data documentation – observations

Reference 39

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Observation fe477865-13b9-4d96-af30-0d897a8d743c · outbound

This paper cites Esa hands over control of the metop-b weather satel- lite to eumetsat.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Esa hands over control of the metop-b weather satel- lite to eumetsat

Reference 40

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Observation d80bf6bb-23a3-4ecc-8743-0f1b05ef9a95 · outbound

This paper cites Danra: The kilometer-scale danish regional atmospheric reanalysis, 2025.

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model Danra: The kilometer-scale danish regional atmospheric reanalysis, 2025

Reference 41

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Pith citing papers

No inbound Pith citation observations are available.