Forecasts, neural networks, and results from the paper: 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

This dataset encompasses data produced in the study ''Seasonal Arctic sea ice forecasting with probabilistic deep learning'', published in Nature Communications. The study introduces a new Arctic sea ice forecasting AI system, IceNet, which predicts monthly-averaged sea ice probability (SIP; probability of sea ice concentration > 15%) up to 6 months ahead at 25 km resolution. The study demonstrated IceNet''s superior seasonal forecasting skill over a state-of-the-art physics-based sea ice forecasting system, ECMWF SEAS5, and a statistical benchmark. This dataset includes three types of data from the study. Firstly, IceNet''s SIP forecasts from 2012/1 - 2020/9. Secondly, the 25 neural network files underlying the IceNet model. Thirdly, CSV files of results from the study. The codebase associated with this work includes a script to download this dataset and reproduce all the paper''s figures.

This dataset is supported by Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "AI for Science" theme within that grant and The Alan Turing Institute. The dataset is also supported by the NERC ACSIS project (grant NE/N018028/1).

Alternate title: Polar Data Centre (PDC) record GB/NERC/BAS/PDC/01526

Date (Publication): 2021-07-21

Citation identifier: http://www.antarctica.ac.uk/dms/metadata.php?id= / GB/NERC/BAS/PDC/01526

Point of contact

Organisation name	Individual name	Electronic mail address	Role
British Antarctic Survey		pdc@bas.ac.uk	Custodian
NERC EDS UK Polar Data Centre	Andersson, T., & Hosking, J.	pdc@bas.ac.uk	Originator

Maintenance and update frequency: Unknown

Keywords

NDGO0001

NERC OAI Harvesting

NERC_DDC

GCMD Parameter Valids

EARTH SCIENCE > Cryosphere > Sea Ice
EARTH SCIENCE > Oceans > Sea Ice

BAS Free-text keywords

Arctic
deep learning
forecasting
machine learning
sea ice

Use limitation: This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v.3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.

Access constraints: Other restrictions

Other constraints: This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v.3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.

Language: English

Topic category

Climatology, meteorology, atmosphere

Begin date: 2012-01-01

End date: 2020-09-30

Reference system identifier: OGP / urn:ogc:def:crs:EPSG::4326

Distribution format

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
Polar Data Centre - British Antarctic Survey		pdc@bas.ac.uk	Distributor

OnLine resource

Protocol	Linkage	Name
http		GET DATA

Hierarchy level: Dataset

Domain consistency

Measure identification: INSPIRE / Conformity_001

Conformance result

Title: INSPIRE Data Specification on unknown theme Guidelines

Date

Explanation: See the referenced specification

Pass: No

Statement: IceNet makes predictions based on ERA5 reanalysis data and OSI-SAF SIC data - for information on their errors see their associated documentation. IceNet''s SIP values were set to zero over a land mask and outside of a monthly maximum SIC climatology mask obtained from OSI-SAF.