Paper Citation Record · LEDGER

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

As of 18 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 19 inbound Pith citation observations for arXiv:2412.15687.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.15687 v1

Coverage vector

measured 63 of 63 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

63 of 63 outbound references displayed

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External citation measurements

1
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Outbound references

Observation 8ab0d84b-23cc-4ce2-93c1-4c1275707825 · outbound

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

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 1

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

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Learning skillful medium-range global weather forecasting

Reference 2

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Unresolved cited work

Reference 3

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This paper cites A Foundation Model for the Earth System.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations A Foundation Model for the Earth System

Reference 4

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This paper cites AIFS -- ECMWF's data-driven forecasting system.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations AIFS -- ECMWF's data-driven forecasting system

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This paper cites Hersbach, B.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Hersbach, B

Reference 6

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This paper cites Rabier, H.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Rabier, H

Reference 7

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This paper cites IFS Documentation CY48R1 - P art II : Data Assimilation.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations IFS Documentation CY48R1 - P art II : Data Assimilation

Reference 8

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This paper cites 20 years of 4D-Var : B etter forecasts through a better use of observations.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations 20 years of 4D-Var : B etter forecasts through a better use of observations

Reference 9

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Observation e1cefefe-856d-41ab-8958-263ea2a5575d · outbound

This paper cites Data driven weather forecasts trained and initialised directly from observations.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Data driven weather forecasts trained and initialised directly from observations

Reference 10

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This paper cites Aardvark weather: end-to-end data-driven weather forecasting.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Aardvark weather: end-to-end data-driven weather forecasting

Reference 11

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This paper cites Exploring the Use of Machine Learning Weather Models in Data Assimilation.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Exploring the Use of Machine Learning Weather Models in Data Assimilation

Reference 12

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This paper cites Exploring the integration of a global ai model with traditional data assimilation in weather forecasting.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Exploring the integration of a global ai model with traditional data assimilation in weather forecasting

Reference 13

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This paper cites Score-based Data Assimilation.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Score-based Data Assimilation

Reference 14

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This paper cites DiffDA: a Diffusion Model for Weather-scale Data Assimilation.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations DiffDA: a Diffusion Model for Weather-scale Data Assimilation

Reference 15

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This paper cites FuXi-En4DVar : An assimilation system based on machine learning weather forecasting model ensuring physical constraints.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations FuXi-En4DVar : An assimilation system based on machine learning weather forecasting model ensuring physical constraints

Reference 16

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Observation 1761c4ab-a29a-4b48-a511-fcd0a07f759b · outbound

This paper cites Fuxi- DA : A generalized deep learning data assimilation framework for assimilating satellite observations, 2024 b.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Fuxi- DA : A generalized deep learning data assimilation framework for assimilating satellite observations, 2024 b

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This paper cites FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation

Reference 18

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations David Neelin, Deliang Chen, Jie Feng, Wei Han, Libo Wu, and Yuan Qi

Reference 19

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations ADAF: An Artificial Intelligence Data Assimilation Framework for Weather Forecasting

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This paper cites Machine Learning for Precipitation Nowcasting from Radar Images.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Machine Learning for Precipitation Nowcasting from Radar Images

Reference 21

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations MetNet: A Neural Weather Model for Precipitation Forecasting

Reference 22

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Skilful precipitation nowcasting using deep generative models of radar

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Deep Learning for Day Forecasts from Sparse Observations

Reference 24

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Jordan, and Jianmin Wang

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Red sky at night

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Manuscript in preparation, 2025

Reference 27

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Unresolved cited work

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations A tmospheric M otion V ectors: Past, present and future

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Fast Graph Representation Learning with PyTorch Geometric

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Forecasting Global Weather with Graph Neural Networks

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Mixed Precision Training

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations The quiet revolution of numerical weather prediction

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations The role of satellite data in the forecasting of hurricane S andy

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Distortion representation of forecast errors

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Ebert, L

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Elucidating the Design Space of Diffusion-Based Generative Models

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Data-driven ensemble forecasting with the AIFS

Reference 40

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Ensemble forecasting with the A rtificial I ntelligence F orecasting S ystem trained with a loss function based on the continuous ranked probability score

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Unresolved cited work

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations ECMWF forecast user guide

Reference 43

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations All-sky assimilation of SSMIS humidity sounding channels over land within the ECMWF system

Reference 44

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Assimilation of AMSU-A in all-sky conditions

Reference 45

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Evaluation of ECMWF forecasts

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Use of forecast departures in verification against observations

Reference 47

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Improved two-metre temperature forecasts in the 2024 upgrade

Reference 48

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Continuous data assimilation for global numerical weather prediction

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Machine learning for model error inference and correction

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GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Development of an offline and online hybrid model for the Integrated Forecasting System

Reference 51

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Observation 20c42ef5-b040-46da-b562-002939215b8f · outbound

This paper cites Statistical modeling of 2-m temperature and 10-m wind speed forecast errors.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Statistical modeling of 2-m temperature and 10-m wind speed forecast errors

Reference 52

Resolution: verified exact; doi, observed 2026-08-11T11:16:44.318903Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c0d24075-4b2e-4d11-b4a2-61aa77b04b59 · outbound

This paper cites Developing an all-surface capability for all-sky microwave radiances.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Developing an all-surface capability for all-sky microwave radiances

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:16:46.306393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c980502-7cd2-404f-b8e1-8222b5b6939e · outbound

This paper cites Shepherd, I.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Shepherd, I

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:16:46.276496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e93846cd-d386-45c1-8fad-f27e3db6fa75 · outbound

This paper cites Laloyaux, M.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Laloyaux, M

Reference 55

Resolution: verified exact; doi, observed 2026-08-11T11:16:44.285887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f95d2343-0da3-491f-a21a-2889fd8097d5 · outbound

This paper cites Improving Ocean Surface Temperature for NWP using All-Sky Microwave Imager Observations , 08/2024 2024.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Improving Ocean Surface Temperature for NWP using All-Sky Microwave Imager Observations , 08/2024 2024

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:16:46.243670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4ec19074-dcd1-4ece-84e7-bb063f31deeb · outbound

This paper cites WeatherBench 2: A benchmark for the next generation of data-driven global weather models.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations WeatherBench 2: A benchmark for the next generation of data-driven global weather models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T11:16:44.061282Z

Source-reported events for the cited work

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Observation b7ece30b-daa3-4a2d-b595-c44f99b271e5 · outbound

This paper cites Scale‐dependent verification of ensemble forecasts.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Scale‐dependent verification of ensemble forecasts

Reference 58

Resolution: verified exact; doi, observed 2026-08-11T11:16:44.239020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 56ded691-0d6c-4b9f-8e7e-066e767a509d · outbound

This paper cites Mogensen, Tim Hewson, Sarah Keeley, and Linus Magnusson.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Mogensen, Tim Hewson, Sarah Keeley, and Linus Magnusson

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:16:46.205339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4df0fc98-0dec-4402-bb1d-60f54efc8ad0 · outbound

This paper cites Coupled data assimilation at ECMWF : current status, challenges and future developments.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Coupled data assimilation at ECMWF : current status, challenges and future developments

Reference 60

Resolution: verified exact; doi, observed 2026-08-11T11:16:46.159958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dd18769e-a6d6-4f22-be49-da8dc771af02 · outbound

This paper cites Exploiting interface observations in a coupled reanalysis system.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Exploiting interface observations in a coupled reanalysis system

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:16:46.134154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b87ffa07-b995-46d9-b158-1a457e95d5dc · outbound

This paper cites Diamond, Carl J.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Diamond, Carl J

Reference 62

Resolution: verified exact; doi, observed 2026-08-11T11:16:46.104596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 50c6da0c-d73a-4c66-87ec-6b64dba60869 · outbound

This paper cites an unresolved cited work.

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations Unresolved cited work

Reference 63

Resolution: verified exact; doi, observed 2026-08-11T11:16:44.208329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 6c19783b-52b1-476c-83de-5ff87850ff41 · inbound

Learning from nature: insights into GraphDOP's representations of the Earth System cites this paper.

Learning from nature: insights into GraphDOP's representations of the Earth System GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T16:42:52.659993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5daa12d8-82fe-4fff-b12e-2795c217891b · inbound

Huracan: A skillful end-to-end data-driven system for ensemble data assimilation and weather prediction cites this paper.

Huracan: A skillful end-to-end data-driven system for ensemble data assimilation and weather prediction GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T16:32:11.573397Z

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Observation b7843b20-f205-40ef-864c-b6cc8acdd81c · inbound

AIFS-COMPO: A Global Data-Driven Atmospheric Composition Forecasting System cites this paper.

AIFS-COMPO: A Global Data-Driven Atmospheric Composition Forecasting System GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:08:04.801766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 588a0770-f234-4231-b8f8-2d3217498355 · inbound

Towards accurate extreme event likelihoods from diffusion model climate emulators cites this paper.

Towards accurate extreme event likelihoods from diffusion model climate emulators GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-09T03:45:05.937560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d7dc0969-4ff3-4b59-8aaa-bb5e8320e068 · inbound

Earth-o1: A Grid-free Observation-native Atmospheric World Model cites this paper.

Earth-o1: A Grid-free Observation-native Atmospheric World Model GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:51:08.651398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 39480b48-d039-425e-ade4-6ebdd7e503f4 · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T22:08:03.595840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7ad75e8-f000-43d1-bbd2-c2e56c6aedb3 · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:35:46.059458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6747b9d4-774a-47d3-9b80-db8af49bab49 · inbound

Skillful high-resolution weather forecasting independent of physical models cites this paper.

Skillful high-resolution weather forecasting independent of physical models GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-29T10:03:17.554979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a98ebbcb-93fa-473d-88c3-7c6abab2c8d5 · inbound

Towards a Foundation Model for the Martian Atmosphere cites this paper.

Towards a Foundation Model for the Martian Atmosphere GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 117

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T19:05:00.828106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e801488c-ff08-49be-aa87-e7fd6e671bb5 · inbound

Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networks cites this paper.

Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networks GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 104

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T22:20:09.683633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7454361f-af40-4ea0-bb17-ed1e49595207 · inbound

AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning cites this paper.

AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:49:25.338590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 320674e6-02ee-49ec-9283-8672a931efc2 · inbound

Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction cites this paper.

Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 77

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T18:29:41.705442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f565e860-e5a3-416f-976f-ede8f14c9706 · inbound

Machine learning is revolutionizing weather forecasting -- the next step is a change in how we work cites this paper.

Machine learning is revolutionizing weather forecasting -- the next step is a change in how we work GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:20:06.554037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a595fa68-cfbd-41d8-97f6-66d917eddaab · inbound

Global reanalysis from observations alone with machine learning cites this paper.

Global reanalysis from observations alone with machine learning GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 27

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T16:17:21.442765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8483e198-0701-4132-b502-b54a60da5630 · inbound

OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model cites this paper.

OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T03:05:30.742863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e5b34b3-e282-4b06-8590-3385197bd89c · inbound

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching cites this paper.

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T05:20:09.754720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f89ac30c-63f0-4ca0-be5d-a1c82df0a8c4 · inbound

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching cites this paper.

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:41.581941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cf52ccf-c22d-4805-8ce4-790a3415d2ad · inbound

Timestep-Conditioned Transformers for Global Weather Forecasting cites this paper.

Timestep-Conditioned Transformers for Global Weather Forecasting GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:44:11.756969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e01db659-85cf-4aed-b120-00c7d76ddf36 · inbound

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling cites this paper.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T00:17:37.289313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.