Changes in the Ice Cover of the Russian Arctic Seas in the 21st Century Based on the Results of Climate Models of the CMIP6 Project


https://doi.org/10.7868/S2412376525030092

Full Text:




Abstract

Ice cover is one of the main parameters describing the state of the ice cover of various water areas. The simplicity of calculation determines the frequency of using the indicator in research work both for reading the seasonal course and interannual changes in the state of the ice cover, and for verifying model data or reanalysis data. In this paper, ice cover is calculated based on five data sources. The comparison is based on satellite data from the NSIDC DAAC archives October 26, 1978 – March 31, 2023; spatial resolution is 25×25 km, temporal resolution is 1 day; the data were collected by the SMMR, SSM/I, SSMI/S sensors on the DMSP program satellites, as well as the Nimbus-7 satellite) and OSISAF (product code OSI-401-d; March 1, 2005 – present; spatial resolution is 10×10 km, temporal resolution is 1 day; the data were collected by the SSMI/S sensor on the DMSP program satellites). Model data from the international CMIP (Coupled Model Intercomparison Project) project are used for comparison and verification. Of the more than 40 models of the sixth phase of the project, two were selected that provided the necessary data and were suitable in terms of spatial and temporal resolution – MPI-ESM1 2-HR and AWI-CM-1-1-MR of the Max Planck Institute and the Alfred Wegener Institute, respectively. For all obtained ice coverage series, the mean, standard deviation, range, correlation intervals, trend coefficients and standard error were estimated relative to the NSIDC series for the data intersection period of 19.09.2016–31.06.2023 in each of the Russian Arctic seas, as well as for the water area as a whole. Using the calculated statistical characteristics, satellite data on ice cover were compared with the results of modeling in accordance with different socioeconomic trajectories (Shared Socioeconomic Pathways, SSP) for both models, the quality of ice cover modeling was assessed, and scenarios were selected that most closely matched the satellite data for both the entire Russian Arctic water area and for individual seas. Based on the assumed optimal scenarios, possible changes in ice content were predicted.

About the Authors

S. V. Tsedrik
Arctic and Antarctic Research Institute; Saint Petersburg State University
Russian Federation
Saint Petersburg


R. I. May
Saint Petersburg State University; Krylov Scientific Center
Russian Federation
Saint Petersburg


References

1. Vyazigina N.A., Timokhov L.A., Egorov E.S., Yulin A.V. The informativeness of hydrometeorological and astrogeophysical factors in the task of describing inter annual fluctuations in the arctic of the Greenland Sea. Led i Sneg. Ice and Snow. 2021: 61, 3: 431–444. https://doi.org/10.31857/S2076673421030099 [In Russian].

2. Krasheninnikova S.B., Krasheninnikova M.A. Causes and features of the long-term variability of the Barents Sea ice cover. Led i Sneg. Ice and Snow. 2019: 59, 1: 112–122. https://doi.org/10.15356/2076-6734-2019-1-112-122 [In Russian].

3. Lis N.A., Chernyavskaya E.A., Mironov E.U., Timokhov L.A., Egorova E.S. Informativeness of factors forming long-period fluctuations in the arctic cover of certain areas of the Barents Sea. Rossiyskaya Arktika. The Russian Arctic. 2023: 5 (2): 17–32 [In Russian].

4. May R.I., Guzenko R.B., Tarovik O.V., Topazh A.G., Yulin A.V. Stochastic modeling of ice cover cohesion fields for assessing navigation conditions along the Northern Sea Route. Led i Sneg. Ice and Snow. 2022: 62 (1): 125–140 [In Russian].

5. Makarov A.S., Mironov E.U., Ivanov V.V., Yulin A.V. Ice conditions of the seas of the Russian Arctic in connection with the ongoing climatic changes and features of the evolution of the ice cover in 2021. Okeanologiya. Oceanology. 2022, 62 (6): 845–856. https://doi.org/10.31857/S0030157422050124 [In Russian].

6. Matveeva T.A., Semenov V.A., Astafieva E.S. The iciness of the Arctic seas and its relation to surface air temperature in the Northern hemisphere. Led i Sneg. Ice and Snow. 2020: 60 (1): 134–148. https://doi.org/10.31857/S2076673421010029 [In Russian].

7. Romanyuk V.A., Zhuravlev G.G. Comparative assessment and comparability of satellite and aviation data on the arctic Sea of Okhotsk. Led i Sneg. Ice and Snow. 2013: 53 (4): 113–118. https://doi.org/10.15356/2076-6734-2013-4-113-118 [In Russian].

8. Kholoptsev A.V., Kononova N.K. Changes in ice cover in winter and variations in the atmospheric pressure field in the Arctic. Slozhnye sistemy. Complex systems. 2017: 22 (1): 15–35 [In Russian].

9. Shapkin B.S., Rubchenya A.V., Ivanov B.V., Revina A.D., Bogryantsev M.V. Long-term changes in the ice cover in the area of the archipelagos of Svalbard and Franz Josef Land. Led i Sneg. Ice and Snow. 2021, 61 (1): 128–136. https://doi.org/10.31857/S2076673421010076 [In Russian].

10. Chen R., Dai G., Liu R., Wang L. Seasonal influence of the atmosphere and ocean on the fall sea ice extent in the Barents-Kara Seas. J. Geophys. Res.: Atmospheres. 2021, 126: e2021JD035144. https://doi.org/10.1029/2021JD035144

11. Latonin M., Bashmachnikov I., Radchenko I., Gnatiuk N., Bobylev L., Pettersson L. Meridional Oceanic and Atmospheric Heat Fluxes at the Entrance to the Atlantic Sector of the Arctic: Verification of CMIP6 Models and Climate Projections Based on the Selected Sub-Ensembles. Russian Journal of Earth Sciences. 2024, 24: ES4007. https://doi.org/10.2205/2024es000917

12. Lopes F., Courtillot V., Gibert D., Mouël J. On the annual and semi-annual components of variations in extent of Arctic and Antarctic sea-ice. Geosciences. 2023, 13: 21. https://doi.org/10.3390/geosciences13010021

13. Mouël J., Lopes F., Courtillot V. A strong link between variations in sea-ice extent and global atmospheric pressure? The Cryosphere Discussions. 2021: 1–28.

14. Riahi K., Vuurenb D., Krieglerc E., Edmondsd J., O’Neille B.C.,Fujimorif S., Bauerc N., Calvin K., Dellink R., Fricko O., Lutza W., Popp A., Cuaresma J.C., Samir K.C., Leimbach M., Jiange L., Kramb T., Rao S., Emmerling S., Ebi K., Hasegawaf T., Havlik P., Humpenöderc F., Da Silva L.A.,Smith S., Stehfestb E., Bosetti V., Eom J., Gernaatb D., Masuif T., Rogel J., Stre

15. flerc J., Drouet L., Kreya V., Ludererc G., Harmsen M., Takahashif K., Baumstarkc L., Doelmanb J.C., Kainuma M., Klimont Z., Marangoni G., Lotze-Campen H., Obersteinera M., Tabeau A., Tavoni M. The Shared Socioeconomic Pathways and their energy, land use, and greenhousegas emissions implications: An overview. Global Environmental Change. 2017, 42: 153–168.

16. Song M. Change of Arctic sea-ice volume and its relationship with sea-ice extent in CMIP5 simulations. Atmospheric and Oceanic Science Letters. 2016, 9 (1): 22–30. https://doi.org/10.1080/16742834.2015.1126153

17. Sorteberg A., Kvingedal B. Atmospheric Forcing on the Barents Sea Winter Ice Extent. Journal of Climate. 2006, 19: 4772–4784.

18. Wernecke A., Notz D., Kern S., Lavergne T. Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals. The Cryosphere. 2024, 18: 2473–2486. https://doi.org/10.5194/tc-18-2473-2024


Supplementary files

For citation: Tsedrik S.V., May R.I. Changes in the Ice Cover of the Russian Arctic Seas in the 21st Century Based on the Results of Climate Models of the CMIP6 Project. Ice and Snow. 2025;65(3):476-486. https://doi.org/10.7868/S2412376525030092

Views: 9

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2076-6734 (Print)
ISSN 2412-3765 (Online)