Paper Citation Record · LEDGER

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 30 inbound Pith citation observations for arXiv:2412.15832.

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

pith.paper-citation-record.v1
2412.15832 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:08:12.190948Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:34:01.663969Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

37 of 37 outbound references displayed

verified exact5
verified fuzzy3
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

8
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation dbef111a-8f03-49c8-a989-18a02132c130 · outbound

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

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:11.999119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1185be28-ca88-4f1c-9ad2-b8911f191e4d · outbound

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

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score AIFS -- ECMWF's data-driven forecasting system

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.012213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99edaf7c-4951-4b6c-b82d-39c8bab14a67 · outbound

This paper cites Alex Bihlo.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Alex Bihlo

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.055918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dde2450-046c-4486-8e13-d9a880dc62c6 · outbound

This paper cites An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:08:12.700607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9e62af13-88bd-4147-be21-228594bacc76 · outbound

This paper cites Neural General Circulation Models for Weather and Climate.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Neural General Circulation Models for Weather and Climate

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.067929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 634b269a-fbca-430d-b60a-47b2ef2d054e · outbound

This paper cites Enter the ensembles.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Enter the ensembles

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:08:12.772927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9c503dcc-3473-405f-8f53-371e1cf51c87 · outbound

This paper cites Lorenzo Pacchiardi, Rilwan A Adewoyin, Peter Dueben, and Ritabrata Dutta.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Lorenzo Pacchiardi, Rilwan A Adewoyin, Peter Dueben, and Ritabrata Dutta

Reference 17

Resolution: verified exact; doi, observed 2026-08-11T11:08:12.323450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 74b7e18c-ba15-4779-973d-ed1368785f95 · outbound

This paper cites doi:10.1029/2023ms004177.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score doi:10.1029/2023ms004177

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.101422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2c855b5-79ee-4b27-850b-f568cebdae5c · outbound

This paper cites doi:10.1002/qj.2270.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score doi:10.1002/qj.2270

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.114520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9b59e4b-094c-4869-ab66-bc352c09c515 · outbound

This paper cites Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.123686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1279f3e0-2d20-4774-9ee2-b7bcbee783a5 · outbound

This paper cites Forecasting Global Weather with Graph Neural Networks.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Forecasting Global Weather with Graph Neural Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.131355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e214442-3f63-4e9e-aba6-7666c2f913c0 · outbound

This paper cites Molteni, R.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Molteni, R

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.135703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aec9059-ce8f-46e9-9061-9602c1427fad · outbound

This paper cites Hans Hersbach.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Hans Hersbach

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.139084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 926cd201-0c71-4c0b-9d73-a987847fd0eb · outbound

This paper cites Hersbach, B.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Hersbach, B

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:08:12.758346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a77e8489-1961-4a4c-9d0c-61278718e448 · outbound

This paper cites Frédéric Vitart, Roberto Buizza, Magdalena Alonso Balmaseda, Gianpaolo Balsamo, Jean-Raymond Bidlot, Axel Bonet, Manuel Fuentes, Alfred Hofstadler, Franco Molteni, and Tim N.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Frédéric Vitart, Roberto Buizza, Magdalena Alonso Balmaseda, Gianpaolo Balsamo, Jean-Raymond Bidlot, Axel Bonet, Manuel Fuentes, Alfred Hofstadler, Franco Molteni, and Tim N

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.159536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bbe0109-b70e-4869-b187-caa11ebcc90a · outbound

This paper cites Christopher J.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Christopher J

Reference 32

Resolution: verified exact; doi, observed 2026-08-11T11:08:12.235751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 88fe4127-98c8-4abe-8d21-f47cb3143a61 · outbound

This paper cites Frédéric Vitart and Andrew W.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Frédéric Vitart and Andrew W

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.169121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20d98467-7982-4c7d-aa27-a30c4368db08 · outbound

This paper cites Unbiased calculation, evaluation, and calibration of ensemble forecast anomalies.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Unbiased calculation, evaluation, and calibration of ensemble forecast anomalies

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:08:12.455954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3b903639-bdf0-49de-a666-67f22371ec02 · outbound

This paper cites AI-based data assimilation: Learning the functional of analysis estimation.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score AI-based data assimilation: Learning the functional of analysis estimation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.185818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cedc7b84-22b7-44de-a0e8-b7fdb42dee52 · outbound

This paper cites Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.190948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aba8d562-b226-49ae-940e-da41ac8ff74c · outbound

This paper cites An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction

Reference 1971

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:08:12.744456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9a729d8c-30ba-4ac8-82cc-c54210f58894 · outbound

This paper cites URL https://journals.ametsoc.org/view/journals/wefo/15/5/1520-0434_2000_015_0559_dotcrp_2_ 0_co_2.xml.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score URL https://journals.ametsoc.org/view/journals/wefo/15/5/1520-0434_2000_015_0559_dotcrp_2_ 0_co_2.xml

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.142890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c118c2b4-cdc2-48b9-8ae2-f658fdcdecab · outbound

This paper cites Martin Leutbecher and Tim N Palmer.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Martin Leutbecher and Tim N Palmer

Reference 2005

Resolution: verified exact; doi, observed 2026-08-11T11:08:12.378389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89aa3440-19dc-4d83-8f78-e177eccd03c5 · outbound

This paper cites an unresolved cited work.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Unresolved cited work

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.108406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a6d525-d231-45f6-9e18-ce639ab8cdb6 · outbound

This paper cites Gregory J Hakim and Sanjit Masanam.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Gregory J Hakim and Sanjit Masanam

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.020022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d8173b7-fbe5-4377-8e34-bd9c601f4c95 · outbound

This paper cites URL https: //journals.ametsoc.org/view/journals/hydr/15/4/jhm-d-14-0008_1.xml.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score URL https: //journals.ametsoc.org/view/journals/hydr/15/4/jhm-d-14-0008_1.xml

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.040826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e2e18a8-fb84-4018-8f10-50cd4fbe3ff0 · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.077524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d353d24-04bc-409d-8f6a-a75981946d59 · outbound

This paper cites Layer Normalization.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Layer Normalization

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.127831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 776a22cd-3552-47c3-8033-be05eac54648 · outbound

This paper cites an unresolved cited work.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Unresolved cited work

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.051038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f67f962e-4546-4b7a-9ac9-4a6f074b2998 · outbound

This paper cites Mixed Precision Training.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Mixed Precision Training

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.146453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d65f999c-dc34-499e-bf14-7925ab6fdcad · outbound

This paper cites URL https://rmets.onlinelibrary.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score URL https://rmets.onlinelibrary

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.119968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a01009e7-2cac-486d-ae6f-2fad607d3733 · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.150842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a49bfeb3-69b1-4bcb-b12f-94c6546cc503 · outbound

This paper cites Martin Leutbecher, Sarah-Jane Lock, Pirkka Ollinaho, Simon T.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Martin Leutbecher, Sarah-Jane Lock, Pirkka Ollinaho, Simon T

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.046170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f59f755-ed29-4b39-a8ba-15f7e778fef8 · outbound

This paper cites GenCast: Diffusion-based ensemble forecasting for medium-range weather.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score GenCast: Diffusion-based ensemble forecasting for medium-range weather

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.083835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 367098bb-4219-4afb-966c-7e9a19ba194a · outbound

This paper cites doi:10.1126/science.adi2336.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score doi:10.1126/science.adi2336

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.006754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22c7f405-9997-4a2e-9b88-7b7cd6bea7b7 · outbound

This paper cites The rise of data-driven weather forecasting: A first statistical assessment of machine learning-based weather forecasts in an operational-like context.

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score The rise of data-driven weather forecasting: A first statistical assessment of machine learning-based weather forecasts in an operational-like context

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.027049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7492c80-2ac3-49c5-8127-0941f42527aa · outbound

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

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Aardvark weather: end-to-end data-driven weather forecasting

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-11T11:08:12.182382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 12691009-88c3-42ae-bab3-bdf303756237 · inbound

Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function cites this paper.

Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T20:34:01.663969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3502cc-0d80-4258-ae2a-bf5bee28f1f0 · inbound

Probabilistic measures afford fair comparisons of AIWP and NWP model output cites this paper.

Probabilistic measures afford fair comparisons of AIWP and NWP model output AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:01:34.571418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efa7c3b5-ba92-49fb-b937-deaa6d239f45 · inbound

DEF: Diffusion-augmented Ensemble Forecasting cites this paper.

DEF: Diffusion-augmented Ensemble Forecasting AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:43:01.547047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f94a891-4313-4727-a287-8d7cfc04272c · inbound

Skillful joint probabilistic weather forecasting from marginals cites this paper.

Skillful joint probabilistic weather forecasting from marginals AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:25:27.501468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e859ed22-9543-4d7a-9f54-52eeeee1ba35 · inbound

Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts cites this paper.

Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T23:58:27.475162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7621196-2f1e-49b3-b6b2-f9fac457890f · inbound

Fair Box ordinate transform for forecasts following a multivariate Gaussian law cites this paper.

Fair Box ordinate transform for forecasts following a multivariate Gaussian law AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:08:54.606209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 716e70bb-8473-4ebd-8e80-e97b3df40564 · inbound

HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales cites this paper.

HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:27.226401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2ccab6f-00d9-4398-9b5e-01a206352268 · inbound

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale cites this paper.

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T16:59:53.860865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33f78a23-dd9c-43b4-ab3c-08568a3d9b8d · inbound

Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods cites this paper.

Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T17:52:47.125378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6baeae26-7b31-4f56-b13a-1e9eff4c6a79 · 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 AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T16:32:11.562256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2a7473d-ce7e-43d0-b140-95739eaf21cf · inbound

MoWE : A Mixture of Weather Experts cites this paper.

MoWE : A Mixture of Weather Experts AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:49:23.327625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f357812c-feb2-4c14-8e59-1f36a0bbee70 · inbound

EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules cites this paper.

EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T12:01:21.507444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7692b897-f90d-41c3-84e3-1eaca0407d1e · inbound

CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score cites this paper.

CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T10:37:41.445603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e629f1d-62ed-405a-9edd-7a55ad3227d2 · inbound

Evaluating Extreme Precipitation Forecasts: A Threshold-Weighted, Spatial Verification Approach for Comparing an AI Weather Prediction Model Against a High-Resolution NWP Model cites this paper.

Evaluating Extreme Precipitation Forecasts: A Threshold-Weighted, Spatial Verification Approach for Comparing an AI Weather Prediction Model Against a High-Resolution NWP Model AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T07:43:50.145608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 445c2a39-6f00-4385-a339-ce88f89bd857 · inbound

AI-boosted rare event sampling to characterize extreme weather cites this paper.

AI-boosted rare event sampling to characterize extreme weather AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T07:08:26.345508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0cdfb00-b07e-438b-ba16-da41961c506e · inbound

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators cites this paper.

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:16:37.781272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c2673e7a-142a-434a-aab4-d68f5d8c8efb · inbound

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality cites this paper.

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-02T18:44:33.869200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f7d770d-51ff-4da4-b502-042f2d222e51 · inbound

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting cites this paper.

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:41:04.398580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2895771e-c647-4fbe-b9b0-1ea8b7f7e348 · inbound

U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster cites this paper.

U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:45:46.866168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 134dc690-2d80-45d0-a543-a9c839e9d3bd · inbound

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction cites this paper.

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:27:51.472007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 631498b4-0173-4c19-930a-bfec8d620626 · inbound

Uncertainty-aware Machine Learning Interatomic Potentials via Learned Functional Perturbations cites this paper.

Uncertainty-aware Machine Learning Interatomic Potentials via Learned Functional Perturbations AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:34:57.924413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 18336236-2a2f-45f0-9a8e-6e86de7d429a · inbound

The physics of AI weather models cites this paper.

The physics of AI weather models AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-25T02:25:14.233589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cf62f97f-939e-49d3-9010-ff93accc8b31 · inbound

RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges cites this paper.

RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:54:38.123225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c86dc44c-bb0b-4b22-852d-636c1c7dc51c · inbound

Probabilistic storyline attribution using machine learning cites this paper.

Probabilistic storyline attribution using machine learning AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-28T11:42:04.347893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 710cb84d-8f76-4a84-b5e2-7ab96dbb0316 · inbound

AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret cites this paper.

AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T21:56:16.253224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce0daed2-fb78-4481-a1b0-9e9618ed7161 · inbound

Performance Evaluation of GraphCast for Medium-Range Weather Forecasting over Brazil cites this paper.

Performance Evaluation of GraphCast for Medium-Range Weather Forecasting over Brazil AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-06-28T03:11:30.299834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c65314cf-d718-4217-8361-03eb19fb2ab6 · inbound

Disentangling the effects of sea surface temperature and CO$_2$ in global machine learned weather-climate emulators cites this paper.

Disentangling the effects of sea surface temperature and CO$_2$ in global machine learned weather-climate emulators AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-27T19:31:10.549210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4406b492-0448-4bea-9aa9-70ddb8b87ca7 · inbound

Reliability of Probabilistic Emulation of Physical Systems cites this paper.

Reliability of Probabilistic Emulation of Physical Systems AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T13:38:19.233559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation abfaac7b-4caf-47cd-8e88-25d2c0ac6c16 · 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 AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-06-26T22:20:09.524497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 93ae15e5-fbd3-4ec7-b186-889ef293fa70 · inbound

Decision-Aware Training for Sample-Based Generative Models cites this paper.

Decision-Aware Training for Sample-Based Generative Models AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:27:04.738429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.