Articles | Volume 12, issue 8
https://doi.org/10.5194/tc-12-2569-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-12-2569-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Aug 2018
Research article |
| 13 Aug 2018
| 13 Aug 2018
Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance
Thomas Kaminski
CORRESPONDING AUTHOR
The Inversion Lab, Hamburg, Germany
Frank Kauker
Ocean Atmosphere Systems, Hamburg, Germany
Alfred Wegener Institute, Bremerhaven, Germany
Leif Toudal Pedersen
eolab.dk, Copenhagen, Denmark
DTU-Space, Technical University of Denmark, Lyngby, Denmark
Michael Voßbeck
The Inversion Lab, Hamburg, Germany
Helmuth Haak
Max Planck Institute for Meteorology, Hamburg, Germany
Laura Niederdrenk
Max Planck Institute for Meteorology, Hamburg, Germany
Stefan Hendricks
Alfred Wegener Institute, Bremerhaven, Germany
Robert Ricker
Alfred Wegener Institute, Bremerhaven, Germany
Michael Karcher
Ocean Atmosphere Systems, Hamburg, Germany
Alfred Wegener Institute, Bremerhaven, Germany
Hajo Eicken
University of Alaska Fairbanks, Fairbanks, USA
Ola Gråbak
European Space Agency ESRIN, Frascati, Rome, Italy
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Cited
14 citations as recorded by crossref.
- Climate Models as Guidance for the Design of Observing Systems: the Case of Polar Climate and Sea Ice Prediction F. Massonnet 10.1007/s40641-019-00151-w
- Short-term Forecasting of Sea Ice Thickness Based on PredRNN++ Q. Liu et al. 10.1088/1742-6596/2486/1/012017
- Improving Arctic Sea-Ice Thickness Estimates with the Assimilation of CryoSat-2 Summer Observations C. Min et al. 10.34133/olar.0025
- Leveraging Uncertainty Quantification to Design Ocean Climate Observing Systems N. Loose & P. Heimbach 10.1029/2020MS002386
- Assimilating CryoSat-2 freeboard to improve Arctic sea ice thickness estimates I. Sievers et al. 10.5194/tc-17-3721-2023
- Impact of Synthetic Arctic Argo-Type Floats in a Coupled Ocean–Sea Ice State Estimation Framework A. Nguyen et al. 10.1175/JTECH-D-19-0159.1
- Advances in altimetric snow depth estimates using bi-frequency SARAL and CryoSat-2 Ka–Ku measurements F. Garnier et al. 10.5194/tc-15-5483-2021
- A Framework for the Development, Design and Implementation of a Sustained Arctic Ocean Observing System C. Lee et al. 10.3389/fmars.2019.00451
- Incorporating physical constraints in a deep learning framework for short-term daily prediction of sea ice concentration Q. Liu et al. 10.1016/j.apor.2024.104007
- Simulation and investigations on the vibro-acoustic behavior of cylindrical shells in ice-covered water X. Wang et al. 10.1016/j.rinp.2019.102764
- Quantifying Dynamical Proxy Potential Through Shared Adjustment Physics in the North Atlantic N. Loose et al. 10.1029/2020JC016112
- From Observation to Information and Users: The Copernicus Marine Service Perspective P. Le Traon et al. 10.3389/fmars.2019.00234
- Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season G. Smith et al. 10.3389/fmars.2019.00429
- Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance T. Kaminski et al. 10.5194/tc-12-2569-2018
12 citations as recorded by crossref.
- Climate Models as Guidance for the Design of Observing Systems: the Case of Polar Climate and Sea Ice Prediction F. Massonnet 10.1007/s40641-019-00151-w
- Short-term Forecasting of Sea Ice Thickness Based on PredRNN++ Q. Liu et al. 10.1088/1742-6596/2486/1/012017
- Improving Arctic Sea-Ice Thickness Estimates with the Assimilation of CryoSat-2 Summer Observations C. Min et al. 10.34133/olar.0025
- Leveraging Uncertainty Quantification to Design Ocean Climate Observing Systems N. Loose & P. Heimbach 10.1029/2020MS002386
- Assimilating CryoSat-2 freeboard to improve Arctic sea ice thickness estimates I. Sievers et al. 10.5194/tc-17-3721-2023
- Impact of Synthetic Arctic Argo-Type Floats in a Coupled Ocean–Sea Ice State Estimation Framework A. Nguyen et al. 10.1175/JTECH-D-19-0159.1
- Advances in altimetric snow depth estimates using bi-frequency SARAL and CryoSat-2 Ka–Ku measurements F. Garnier et al. 10.5194/tc-15-5483-2021
- A Framework for the Development, Design and Implementation of a Sustained Arctic Ocean Observing System C. Lee et al. 10.3389/fmars.2019.00451
- Incorporating physical constraints in a deep learning framework for short-term daily prediction of sea ice concentration Q. Liu et al. 10.1016/j.apor.2024.104007
- Simulation and investigations on the vibro-acoustic behavior of cylindrical shells in ice-covered water X. Wang et al. 10.1016/j.rinp.2019.102764
- Quantifying Dynamical Proxy Potential Through Shared Adjustment Physics in the North Atlantic N. Loose et al. 10.1029/2020JC016112
- From Observation to Information and Users: The Copernicus Marine Service Perspective P. Le Traon et al. 10.3389/fmars.2019.00234
2 citations as recorded by crossref.
- Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season G. Smith et al. 10.3389/fmars.2019.00429
- Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance T. Kaminski et al. 10.5194/tc-12-2569-2018
Latest update: 14 Nov 2024
Short summary
We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
We present mathematically rigorous assessments of the observation impact (added value) of...
