Articles | Volume 15, issue 3
https://doi.org/10.5194/os-15-615-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-15-615-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 May 2019
Research article |
| 29 May 2019
| 29 May 2019
Validation metrics for ice edge position forecasts
Research and development department, Norwegian Meteorological Institute, Oslo, Norway
Cyril Palerme
Development centre for weather forecasting, Norwegian Meteorological Institute, Oslo, Norway
Malte Müller
Development centre for weather forecasting, Norwegian Meteorological Institute, Oslo, Norway
Viewed
Total article views: 2,825 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Jan 2019)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,836 | 912 | 77 | 2,825 | 370 | 79 | 76 |
- HTML: 1,836
- PDF: 912
- XML: 77
- Total: 2,825
- Supplement: 370
- BibTeX: 79
- EndNote: 76
Total article views: 2,220 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 May 2019)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,504 | 652 | 64 | 2,220 | 189 | 65 | 68 |
- HTML: 1,504
- PDF: 652
- XML: 64
- Total: 2,220
- Supplement: 189
- BibTeX: 65
- EndNote: 68
Total article views: 605 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Jan 2019)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 332 | 260 | 13 | 605 | 181 | 14 | 8 |
- HTML: 332
- PDF: 260
- XML: 13
- Total: 605
- Supplement: 181
- BibTeX: 14
- EndNote: 8
Viewed (geographical distribution)
Total article views: 2,825 (including HTML, PDF, and XML)
Thereof 2,387 with geography defined
and 438 with unknown origin.
Total article views: 2,220 (including HTML, PDF, and XML)
Thereof 1,965 with geography defined
and 255 with unknown origin.
Total article views: 605 (including HTML, PDF, and XML)
Thereof 422 with geography defined
and 183 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
17 citations as recorded by crossref.
- Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. 10.3390/rs12071214
- Daily-Scale Prediction of Arctic Sea Ice Concentration Based on Recurrent Neural Network Models J. Feng et al. 10.3390/jmse11122319
- An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport T. Bilge et al. 10.3390/jmse10020265
- Medium range sea ice prediction in support of Japanese research vessel MIRAI’s expedition cruise in 2018 L. De Silva et al. 10.1080/1088937X.2019.1707317
- Edge displacement scores A. Melsom 10.5194/tc-15-3785-2021
- Assessment of predictability of the Loop Current in the Gulf of Mexico from observing system experiments and observing system simulation experiments D. Dukhovskoy et al. 10.3389/fmars.2023.1153824
- Assessment of High‐Resolution Dynamical and Machine Learning Models for Prediction of Sea Ice Concentration in a Regional Application S. Fritzner et al. 10.1029/2020JC016277
- Passive Microwave Sea Ice Edge Displacement Error over the Eastern Canadian Arctic for the period 2013-2021 A. Soleymani et al. 10.1080/07038992.2023.2205531
- Comparing Arctic Sea Ice Model Simulations to Satellite Observations by Multiscale Directional Analysis of Linear Kinematic Features M. Mohammadi-Aragh et al. 10.1175/MWR-D-19-0359.1
- Improving short-term sea ice concentration forecasts using deep learning C. Palerme et al. 10.5194/tc-18-2161-2024
- A comparative study of data input selection for deep learning-based automated sea ice mapping X. Chen et al. 10.1016/j.jag.2024.103920
- Cost–Benefit Analysis of a Trans-Arctic Alternative Route to the Suez Canal: A Method Based on High-Fidelity Ship Performance, Weather, and Ice Forecast Models Z. Li et al. 10.3390/jmse11040711
- Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction Y. Lin et al. 10.3389/fmars.2023.1260047
- The Nansen Legacy . The Nansen Legacy 10.7557/nlrs.5792
- Arctic shipping trends during hazardous weather and sea-ice conditions and the Polar Code’s effectiveness M. Müller et al. 10.1038/s44183-023-00021-x
- An Intercomparison of Verification Scores for Evaluating the Sea Ice Edge Position in Seasonal Forecasts C. Palerme et al. 10.1029/2019GL082482
- Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales L. Zampieri et al. 10.1029/2019GL084096
15 citations as recorded by crossref.
- Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. 10.3390/rs12071214
- Daily-Scale Prediction of Arctic Sea Ice Concentration Based on Recurrent Neural Network Models J. Feng et al. 10.3390/jmse11122319
- An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport T. Bilge et al. 10.3390/jmse10020265
- Medium range sea ice prediction in support of Japanese research vessel MIRAI’s expedition cruise in 2018 L. De Silva et al. 10.1080/1088937X.2019.1707317
- Edge displacement scores A. Melsom 10.5194/tc-15-3785-2021
- Assessment of predictability of the Loop Current in the Gulf of Mexico from observing system experiments and observing system simulation experiments D. Dukhovskoy et al. 10.3389/fmars.2023.1153824
- Assessment of High‐Resolution Dynamical and Machine Learning Models for Prediction of Sea Ice Concentration in a Regional Application S. Fritzner et al. 10.1029/2020JC016277
- Passive Microwave Sea Ice Edge Displacement Error over the Eastern Canadian Arctic for the period 2013-2021 A. Soleymani et al. 10.1080/07038992.2023.2205531
- Comparing Arctic Sea Ice Model Simulations to Satellite Observations by Multiscale Directional Analysis of Linear Kinematic Features M. Mohammadi-Aragh et al. 10.1175/MWR-D-19-0359.1
- Improving short-term sea ice concentration forecasts using deep learning C. Palerme et al. 10.5194/tc-18-2161-2024
- A comparative study of data input selection for deep learning-based automated sea ice mapping X. Chen et al. 10.1016/j.jag.2024.103920
- Cost–Benefit Analysis of a Trans-Arctic Alternative Route to the Suez Canal: A Method Based on High-Fidelity Ship Performance, Weather, and Ice Forecast Models Z. Li et al. 10.3390/jmse11040711
- Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction Y. Lin et al. 10.3389/fmars.2023.1260047
- The Nansen Legacy . The Nansen Legacy 10.7557/nlrs.5792
- Arctic shipping trends during hazardous weather and sea-ice conditions and the Polar Code’s effectiveness M. Müller et al. 10.1038/s44183-023-00021-x
Latest update: 26 Jul 2024
Short summary
Retreating sea ice in the Arctic Ocean gives rise to increased naval traffic with shorter navigation distances. Hence, information about the position of the sea ice edge is crucial for safe navigation.
In the present study we explore methods for examining the quality of sea ice edge forecasts. We conclude that the forecast quality can be monitored with results from a set of four quantities. We also recommend the use of maps which display discrepancies in the positions of the sea ice edge.
Retreating sea ice in the Arctic Ocean gives rise to increased naval traffic with shorter...
