Articles | Volume 15, issue 8
https://doi.org/10.5194/tc-15-3989-2021
© Author(s) 2021. 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-15-3989-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2021
Research article |
| 23 Aug 2021
| 23 Aug 2021
Calibration of sea ice drift forecasts using random forest algorithms
Development Centre for Weather Forecasting, Norwegian Meteorological Institute, Oslo, Norway
Malte Müller
Development Centre for Weather Forecasting, Norwegian Meteorological Institute, Oslo, Norway
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Short summary
Methods have been developed for calibrating sea ice drift forecasts from an operational prediction system using machine learning algorithms. These algorithms use predictors from sea ice concentration observations during the initialization of the forecasts, sea ice and wind forecasts, and some geographical information. Depending on the calibration method, the mean absolute error is reduced between 3.3 % and 8.0 % for the direction and between 2.5 % and 7.1 % for the speed of sea ice drift.
Methods have been developed for calibrating sea ice drift forecasts from an operational...
