Paper Citation Record · LEDGER

Advancing global aerosol forecasting with artificial intelligence

As of 22 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.02498.

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

pith.paper-citation-record.v1
2412.02498 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:27:39.858062Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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verified fuzzy29
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External citation measurements

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Outbound references

Observation c801d8bc-7f91-4e17-b948-4579a9a39acd · outbound

This paper cites et al.Theatmosphericaerosolsystem:Anoverview.

Advancing global aerosol forecasting with artificial intelligence et al.Theatmosphericaerosolsystem:Anoverview

Reference 1

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Observation 0c3d809d-8c53-4d9e-8d51-bccf124305ce · outbound

This paper cites et al.ClimateForcingbyAnthropogenicAerosols.

Advancing global aerosol forecasting with artificial intelligence et al.ClimateForcingbyAnthropogenicAerosols

Reference 2

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Observation feb13bfd-d3ef-4bf3-8b31-1ac54a996715 · outbound

This paper cites et al.Scatteringandabsorbingaerosolsintheclimatesystem.

Advancing global aerosol forecasting with artificial intelligence et al.Scatteringandabsorbingaerosolsintheclimatesystem

Reference 3

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Observation 7af36a7a-b249-4896-a751-4e52df8dd572 · outbound

This paper cites et al.BoundingGlobalAerosolRadiativeForcingofClimateChange.

Advancing global aerosol forecasting with artificial intelligence et al.BoundingGlobalAerosolRadiativeForcingofClimateChange

Reference 4

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Observation f30828a3-4a83-48ab-a72a-13c22b0b3d06 · outbound

This paper cites et al.AerosolcomponentsderivedfromglobalAERONETmeasurementsbyGRASP:Anew value-addedaerosolcomponentglobaldatasetanditsapplication.

Advancing global aerosol forecasting with artificial intelligence et al.AerosolcomponentsderivedfromglobalAERONETmeasurementsbyGRASP:Anew value-addedaerosolcomponentglobaldatasetanditsapplication

Reference 5

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Observation 2395f562-7183-4811-8342-09b5a3d547e1 · outbound

This paper cites et al.Variabilityofabsorptionandopticalpropertiesofkeyaerosoltypesobservedin worldwidelocations.

Advancing global aerosol forecasting with artificial intelligence et al.Variabilityofabsorptionandopticalpropertiesofkeyaerosoltypesobservedin worldwidelocations

Reference 6

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Observation a9f393b1-3d89-48e4-a0fc-e481c2649f41 · outbound

This paper cites et al.AerosolopticalandradiativepropertiesandtheirenvironmentaleffectsinChina:Areview.

Advancing global aerosol forecasting with artificial intelligence et al.AerosolopticalandradiativepropertiesandtheirenvironmentaleffectsinChina:Areview

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.245410Z

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Observation 385f2df3-a220-43d4-8dc8-806ae46a88a2 · outbound

This paper cites et al.Aerosolclimateeffectsandairqualityimpactsfrom1980to2030.

Advancing global aerosol forecasting with artificial intelligence et al.Aerosolclimateeffectsandairqualityimpactsfrom1980to2030

Reference 8

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Source-reported events for the cited work

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Observation a98e5fb7-4fb3-457c-9206-2b164143f749 · outbound

This paper cites et al.TheSignificantContributionofSmall-SizedandSphericalAerosolParticlestothe DecreasingTrendinTotalAerosolOpticalDepthoverLandfrom2003to2018.

Advancing global aerosol forecasting with artificial intelligence et al.TheSignificantContributionofSmall-SizedandSphericalAerosolParticlestothe DecreasingTrendinTotalAerosolOpticalDepthoverLandfrom2003to2018

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.231597Z

Source-reported events for the cited work

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Observation 6536d115-5985-4956-98df-318246456ad4 · outbound

This paper cites an unresolved cited work.

Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 10

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Source-reported events for the cited work

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Observation 140f605c-b80b-4ee5-827c-7837bf239bbf · outbound

This paper cites et al.Aerosolanalysisandforecastintheeuropeancentreformedium-rangeweather forecastsintegratedforecastsystem:Forwardmodeling.

Advancing global aerosol forecasting with artificial intelligence et al.Aerosolanalysisandforecastintheeuropeancentreformedium-rangeweather forecastsintegratedforecastsystem:Forwardmodeling

Reference 11

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Source-reported events for the cited work

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Observation 79d5ed08-ef2d-479e-90cc-e1ca1d6b3e82 · outbound

This paper cites et al.Areviewofoperational,regional-scale,chemicalweatherforecastingmodelsin Europe.

Advancing global aerosol forecasting with artificial intelligence et al.Areviewofoperational,regional-scale,chemicalweatherforecastingmodelsin Europe

Reference 12

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Source-reported events for the cited work

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Observation b6471231-4a60-45ad-94e9-c2d3d1e0e20e · outbound

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Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 13

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Observation bed4b7b5-8ff9-4114-99fb-3fe81bb3996e · outbound

This paper cites et al.TheCopernicusAtmosphereMonitoringServicefromResearchtoOperations.

Advancing global aerosol forecasting with artificial intelligence et al.TheCopernicusAtmosphereMonitoringServicefromResearchtoOperations

Reference 14

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Source-reported events for the cited work

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Observation 6240cdc3-9921-4b3a-bc81-60b6491a5c14 · outbound

This paper cites 4,(2018).

Advancing global aerosol forecasting with artificial intelligence 4,(2018)

Reference 15

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Observation 5b3c462e-205b-4ae1-9af9-2004f7c6a80f · outbound

This paper cites doi:10.1007/978-3-642-30183-4_34.

Advancing global aerosol forecasting with artificial intelligence doi:10.1007/978-3-642-30183-4_34

Reference 16

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Observation 788f9ff8-3fd6-4c4e-8895-e0891e3eab33 · outbound

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

Advancing global aerosol forecasting with artificial intelligence FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 17

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This paper cites et al.Learningskillfulmedium-rangeglobalweatherforecasting.

Advancing global aerosol forecasting with artificial intelligence et al.Learningskillfulmedium-rangeglobalweatherforecasting

Reference 18

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Observation 4d6cc1b7-2ecc-4c66-b070-434828e6506f · outbound

This paper cites et al.Accuratemedium-rangeglobalweatherforecastingwith3Dneuralnetworks.

Advancing global aerosol forecasting with artificial intelligence et al.Accuratemedium-rangeglobalweatherforecastingwith3Dneuralnetworks

Reference 19

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Observation 53a85f2e-b69b-435c-86be-5ef0d3085472 · outbound

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Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 20

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Observation cd22c7b6-5aac-4f15-b4f6-030901313a31 · outbound

This paper cites arXiv preprint arXiv: 2304.02948(2023).

Advancing global aerosol forecasting with artificial intelligence arXiv preprint arXiv: 2304.02948(2023)

Reference 21

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Observation 139ac192-1d40-4421-8bfd-3e090a49ac4d · outbound

This paper cites et al.FuXi:acascademachinelearningforecastingsystemfor15-dayglobalweatherforecast.

Advancing global aerosol forecasting with artificial intelligence et al.FuXi:acascademachinelearningforecastingsystemfor15-dayglobalweatherforecast

Reference 22

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Observation 17bb27a5-5887-46c1-842c-34e82f0bf527 · outbound

This paper cites et al.Neuralgeneralcirculationmodelsforweatherandclimate.

Advancing global aerosol forecasting with artificial intelligence et al.Neuralgeneralcirculationmodelsforweatherandclimate

Reference 23

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Observation 56987f4a-17f5-45a0-8112-ab9df32eb83d · outbound

This paper cites A Foundation Model for the Earth System.

Advancing global aerosol forecasting with artificial intelligence A Foundation Model for the Earth System

Reference 24

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Observation d3a1685d-ad2c-448f-8139-af3086b750ec · outbound

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

Advancing global aerosol forecasting with artificial intelligence AIFS -- ECMWF's data-driven forecasting system

Reference 25

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Source-reported events for the cited work

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Observation 82212e6b-0622-4152-8157-f29fcbcc79c2 · outbound

This paper cites AI-GOMS: Large AI-Driven Global Ocean Modeling System.

Advancing global aerosol forecasting with artificial intelligence AI-GOMS: Large AI-Driven Global Ocean Modeling System

Reference 26

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Source-reported events for the cited work

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Observation 38d30f8a-3b8a-40df-9835-c815b42f366f · outbound

This paper cites XiHe: A Data-Driven Model for Global Ocean Eddy-Resolving Forecasting.

Advancing global aerosol forecasting with artificial intelligence XiHe: A Data-Driven Model for Global Ocean Eddy-Resolving Forecasting

Reference 27

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Observation f3d42335-03b0-4097-b31d-a951694b83aa · outbound

This paper cites DustNet: skillful neural network predictions of Saharan dust.

Advancing global aerosol forecasting with artificial intelligence DustNet: skillful neural network predictions of Saharan dust

Reference 28

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Observation afa64f0a-9116-4a84-88ab-b0c667f5a2d2 · outbound

This paper cites Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet).

Advancing global aerosol forecasting with artificial intelligence Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet)

Reference 29

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Observation 8301b32b-0e1c-4dd4-9039-2e8f8311cfad · outbound

This paper cites et al.AnImageIsWorth16X16Words:TransformersforImageRecognitionAtScale.

Advancing global aerosol forecasting with artificial intelligence et al.AnImageIsWorth16X16Words:TransformersforImageRecognitionAtScale

Reference 30

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Observation ee05ca66-d093-4150-b967-c05d30352b19 · outbound

This paper cites et al.CARAFE:Content-awarereassemblyoffeatures.

Advancing global aerosol forecasting with artificial intelligence et al.CARAFE:Content-awarereassemblyoffeatures

Reference 31

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Source-reported events for the cited work

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Observation 3d6c42d0-e58d-459b-b416-811bd6e41456 · outbound

This paper cites et al.TheMERRA-2AerosolReanalysis,1980Onward.PartI:SystemDescriptionand DataAssimilationEvaluation.

Advancing global aerosol forecasting with artificial intelligence et al.TheMERRA-2AerosolReanalysis,1980Onward.PartI:SystemDescriptionand DataAssimilationEvaluation

Reference 32

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Observation 32276cf6-7efe-4ee6-bf1e-450f314b5148 · outbound

This paper cites et al.TheMERRA-2aerosolreanalysis,1980onward.PartII:Evaluationandcasestudies.

Advancing global aerosol forecasting with artificial intelligence et al.TheMERRA-2aerosolreanalysis,1980onward.PartII:Evaluationandcasestudies

Reference 33

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Observation 562fe4e6-6fae-45ce-9d5d-9f6ce35fa898 · outbound

This paper cites et al.TroposphericaerosolopticalthicknessfromtheGOCARTmodelandcomparisonswith satelliteandsunphotometermeasurements.

Advancing global aerosol forecasting with artificial intelligence et al.TroposphericaerosolopticalthicknessfromtheGOCARTmodelandcomparisonswith satelliteandsunphotometermeasurements

Reference 34

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Observation ff1bd64c-7a19-495b-95eb-ebefa382fee5 · outbound

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Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 35

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Observation 3bc78724-cc6a-40ad-927f-9157bcb621b7 · outbound

This paper cites an unresolved cited work.

Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 36

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This paper cites et al.TheCAMSreanalysisofatmosphericcomposition.

Advancing global aerosol forecasting with artificial intelligence et al.TheCAMSreanalysisofatmosphericcomposition

Reference 37

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Observation e0d36802-c003-4bcc-9355-d84882e1c0b1 · outbound

This paper cites et al.ConstructionoftheSILAMEulerianatmosphericdispersionmodelbasedonthe advectionalgorithmofMichaelGalperin.

Advancing global aerosol forecasting with artificial intelligence et al.ConstructionoftheSILAMEulerianatmosphericdispersionmodelbasedonthe advectionalgorithmofMichaelGalperin

Reference 38

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Observation fc3c4d16-995e-4bb3-8880-954bd36f9d5e · outbound

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Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 39

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This paper cites et al.AnewglobalclimatemodeloftheMeteorologicalResearchInstitute:MRI-CGCM3: -Modeldescriptionandbasicperformance-.

Advancing global aerosol forecasting with artificial intelligence et al.AnewglobalclimatemodeloftheMeteorologicalResearchInstitute:MRI-CGCM3: -Modeldescriptionandbasicperformance-

Reference 40

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Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 41

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Source-reported events for the cited work

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This paper cites et al.AERONET—AFederatedInstrumentNetworkandDataArchiveforAerosol Characterization.

Advancing global aerosol forecasting with artificial intelligence et al.AERONET—AFederatedInstrumentNetworkandDataArchiveforAerosol Characterization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.056460Z

Source-reported events for the cited work

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This paper cites et al.TheAERONETVersion3aerosolretrievalalgorithm,associateduncertaintiesand comparisonstoVersion2.

Advancing global aerosol forecasting with artificial intelligence et al.TheAERONETVersion3aerosolretrievalalgorithm,associateduncertaintiesand comparisonstoVersion2

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.048973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 397d3f44-f31e-47db-9a9d-2b83dcc60830 · outbound

This paper cites et al.Wavelengthdependenceoftheopticaldepthofbiomassburning,urban,anddesertdust aerosols.

Advancing global aerosol forecasting with artificial intelligence et al.Wavelengthdependenceoftheopticaldepthofbiomassburning,urban,anddesertdust aerosols

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.040593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 24661590-23ae-4457-b25b-e39b5c61effe · outbound

This paper cites an unresolved cited work.

Advancing global aerosol forecasting with artificial intelligence Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-11T23:27:40.032821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dc611df2-b4c9-4283-a3d9-eb8b7830f516 · outbound

This paper cites et al.Attentionisallyouneed.

Advancing global aerosol forecasting with artificial intelligence et al.Attentionisallyouneed

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:27:40.024735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.