Articles | Volume 9, issue 4
https://doi.org/10.5194/os-9-609-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-9-609-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Jul 2013
Research article |
| 09 Jul 2013
A comparison between gradient descent and stochastic approaches for parameter optimization of a sea ice model
H. Sumata
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
F. Kauker
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
Ocean Atmosphere Systems, Hamburg, Germany
R. Gerdes
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
Jacobs University, Bremen, Germany
C. Köberle
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
M. Karcher
Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
Ocean Atmosphere Systems, Hamburg, Germany
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This study presents an evaluation of Arctic sea ice drift speed for the period 2003–2014 in a state-of-the-art coupled regional model for the Arctic, called HIRHAM–NAOSIM. In particular, the dependency of the drift speed on the near-surface wind speed and sea ice conditions is presented. Effects of sea ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice are discussed.
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Oceanographic data have been collected in the Arctic Ocean over many decades. They were measured by a large variety of platforms. Most of these data are publicly available from the World Ocean Database (WOD). This important online archive, however, does not contain all available modern data and has quality problems in the upper water layers. To enable a quick access to nearly all available temperature and salinity profiles, we compiled UDASH, a complete data archive with a higher quality.
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We estimated spatial and temporal decorrelation scales of temperature and salinity in the Amerasian Basin in the Arctic Ocean. The estimated scales can be applied to representation error assessment in the ocean data assimilation system for the Arctic Ocean.
F. Kauker, T. Kaminski, R. Ricker, L. Toudal-Pedersen, G. Dybkjaer, C. Melsheimer, S. Eastwood, H. Sumata, M. Karcher, and R. Gerdes
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The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-100, https://doi.org/10.5194/tc-2021-100, 2021
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Reliable and detailed Arctic snow data are limited. Evaluation of the performance of atmospheric reanalysis compared to measurements in northeast Greenland generally show good agreement. Both data sets are applied to an Alpine snow model and the performance for Arctic conditions is investigated: Simulated snow depth evolution is reliable, but vertical snow profiles show weaknesses. These are smaller with an adapted parametrisation for the density of newly fallen snow for harsh Arctic conditions.
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Hannes Schulz, Marco Zanatta, Heiko Bozem, W. Richard Leaitch, Andreas B. Herber, Julia Burkart, Megan D. Willis, Daniel Kunkel, Peter M. Hoor, Jonathan P. D. Abbatt, and Rüdiger Gerdes
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Aircraft vertical profiles of black carbon (BC) aerosol from the High Canadian Arctic have shown systematic variability in different levels of the cold, stably stratified polar dome. During spring and summer, efficiencies of BC supply by transport (often from gas flaring and wildfire-affected regions) were different in the lower dome than at higher levels, as apparent from changes in mean particle size and mixing ratios with CO. Summer BC concentrations were a factor of 10 lower than in spring.
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A new version of the coupled Arctic climate model HIRHAM-NAOSIM has been designed to study interactions between atmosphere, sea ice, and ocean in the Arctic. This version utilizes upgraded, high-resolution model components and a revised coupling procedure. Simulations with the new version reveal that Arctic sea ice is thicker in all seasons and closer to observations than in the previous version. Wintertime biases in sea-ice extent and near-surface air temperatures are reduced as well.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
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Axel Behrendt, Hiroshi Sumata, Benjamin Rabe, and Ursula Schauer
Earth Syst. Sci. Data, 10, 1119–1138, https://doi.org/10.5194/essd-10-1119-2018, https://doi.org/10.5194/essd-10-1119-2018, 2018
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Oceanographic data have been collected in the Arctic Ocean over many decades. They were measured by a large variety of platforms. Most of these data are publicly available from the World Ocean Database (WOD). This important online archive, however, does not contain all available modern data and has quality problems in the upper water layers. To enable a quick access to nearly all available temperature and salinity profiles, we compiled UDASH, a complete data archive with a higher quality.
Hiroshi Sumata, Frank Kauker, Michael Karcher, Benjamin Rabe, Mary-Louise Timmermans, Axel Behrendt, Rüdiger Gerdes, Ursula Schauer, Koji Shimada, Kyoung-Ho Cho, and Takashi Kikuchi
Ocean Sci., 14, 161–185, https://doi.org/10.5194/os-14-161-2018, https://doi.org/10.5194/os-14-161-2018, 2018
Short summary
Short summary
We estimated spatial and temporal decorrelation scales of temperature and salinity in the Amerasian Basin in the Arctic Ocean. The estimated scales can be applied to representation error assessment in the ocean data assimilation system for the Arctic Ocean.
F. Kauker, T. Kaminski, R. Ricker, L. Toudal-Pedersen, G. Dybkjaer, C. Melsheimer, S. Eastwood, H. Sumata, M. Karcher, and R. Gerdes
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-5521-2015, https://doi.org/10.5194/tcd-9-5521-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The manuscript describes the use of remotely sensed sea ice observations for the initialization of seasonal sea ice predictions. Among other observations, CryoSat-2 ice thickness is, to our knowledge for the first time, utilized. While a direct assimilation with CryoSat ice thickness could improve the predictions only locally, the use an advanced data assimilation system (4dVar) allows to establish a bias correction scheme, which is shown to improve the seasonal predictions Arctic wide.
M. Thoma, R. Gerdes, R. J. Greatbatch, and H. Ding
Geosci. Model Dev., 8, 51–68, https://doi.org/10.5194/gmd-8-51-2015, https://doi.org/10.5194/gmd-8-51-2015, 2015
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The Cryosphere, 7, 947–959, https://doi.org/10.5194/tc-7-947-2013, https://doi.org/10.5194/tc-7-947-2013, 2013
T. Krumpen, M. Janout, K. I. Hodges, R. Gerdes, F. Girard-Ardhuin, J. A. Hölemann, and S. Willmes
The Cryosphere, 7, 349–363, https://doi.org/10.5194/tc-7-349-2013, https://doi.org/10.5194/tc-7-349-2013, 2013
Related subject area
Approach: Numerical Models | Depth range: Surface | Geographical range: Deep Seas: Arctic Ocean | Phenomena: Sea Ice
Arctic rapid sea ice loss events in regional coupled climate scenario experiments
R. Döscher and T. Koenigk
Ocean Sci., 9, 217–248, https://doi.org/10.5194/os-9-217-2013, https://doi.org/10.5194/os-9-217-2013, 2013
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