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Discussion papers | Copyright
https://doi.org/10.5194/tc-2017-249
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Nov 2017

Research article | 30 Nov 2017

Review status
This discussion paper is a preprint. A revision of the manuscript was accepted for the journal The Cryosphere (TC).

Arctic Mission Benefit Analysis: Impact of Sea Ice Thickness, Freeboard, and Snow Depth Products on Sea Ice Forecast Performance

Thomas Kaminski1, Frank Kauker2,5, Leif Toudal Pedersen3, Michael Voßbeck1, Helmuth Haak4, Laura Niederdrenk4, Stefan Hendricks5, Robert Ricker5, Michael Karcher2,5, Hajo Eicken6, and Ola Gråbak7 Thomas Kaminski et al.
  • 1The Inversion Lab, Tewessteg 4, 20249 Hamburg, Germany
  • 2Ocean Atmosphere Systems, Hamburg, Germany
  • 3eolab.dk, København, Denmark
  • 4Max Planck Institute for Meteorology, Hamburg, Germany
  • 5Alfred Wegener Institute, Bremerhaven, Germany
  • 6University of Alaska Fairbanks, Fairbanks, USA
  • 7European Space Agency ESRIN, Frascati (Rome), Italy

Abstract. Assimilation of remote sensing products of sea ice thickness (SIT) into sea ice-ocean models has been shown to improve the quality of sea ice forecasts. Open questions are whether the assimilation of rawer products such as radar freeboard (RFB) can achieve yet a better performance and what performance gain can be achieved by the joint assimilation with a snow depth product. The Arctic Mission Benefit Analysis (ArcMBA) system was developed to address this type of question. Using the quantitative network design (QND) approach, the system can evaluate, in a mathematically rigorous fashion, the observational constraints imposed by individual and groups of data products.

We present assessments of the observation impact (added value) in terms of the uncertainty reduction in a four-week forecast of sea ice volume (SIV) and snow volume (SNV) for three regions along the Northern Sea Route by a coupled model of the sea ice-ocean system. The assessments cover seven satellite products, three real products and four hypothetical products. The real products are monthly SIT, sea ice freeboard (SIFB), and RFB, all derived from CryoSat-2 by the Alfred Wegener Institute. These are complemented by two hypothetical monthly laser freeboard (LFB) products (one with low accuracy and one with high accuracy), as well as two hypothetical monthly snow depth products (again one with low accuracy and one with high accuracy).

On the basis of the per-pixel uncertainty ranges that are provided with the CryoSat-2 SIT, SIFB, and RFB products, the SIT achieves a much better performance for SIV than the SIFB product, while the performance of RFB is more similar to that of SIT. For SNV, the performance of SIT is only low, the performance of SIFB higher and the performance of RFB yet higher. A hypothetical LFB product with low accuracy (20cm uncertainty) lies in performance between SIFB and RFB for both SIV and SNV. A reduction in the uncertainty of the LFB product to 2cm yields a significant increase in performance.

Combining either of the SIT/freeboard products with a hypothetical snow depth product achieves a significant performance increase. The uncertainty in the snow product matters: A higher accuracy product achieves an extra performance gain. The provision of spatial and temporal uncertainty correlations with the EO products would be beneficial not only for QND assessments, but also for assimilation of the products.

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Thomas Kaminski et al.
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We present mathematically rigorous assessments of the observation impact (added value) of remote sensing products and in terms of the uncertainty reduction in a four-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 remote...
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