Seasonal climate forecasts significantly affected by observational uncertainty of Arctic sea ice concentration-Reference-Cited by-同舟云学术

Seasonal climate forecasts significantly affected by observational uncertainty of Arctic sea ice concentration

Published:2016-01-28 Issue:2 Volume:43 Page:852-859
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophys. Res. Lett.

Author:

Bunzel Felix¹,Notz Dirk¹,Baehr Johanna²,Müller Wolfgang A.¹,Fröhlich Kristina³

Affiliation:

1. Ocean in the Earth System, Max Planck Institute for Meteorology Hamburg Germany

2. Institute of Oceanography, Center for Earth System Research and SustainabilityUniversität Hamburg Hamburg Germany

3. Deutscher Wetterdienst Offenbach Germany

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2015GL066928

Reference27 articles.

1. Ensemble initialization of the oceanic component of a coupled model through bred vectors at seasonal-to-interannual timescales

2. The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

3. Evaluation of the ECMWF ocean reanalysis system ORAS4

4. Cavalieri D. J.(1994) Sea ice algorithm in NASA sea ice validation program for the defense meteorological satellite program special sensor microwave imager: Final Rep. NASA Tech. Memo. 104559 pp.25–32 NASA Goddard Space Flight Cent. Greenbelt Md.

5. Cavalieri D. J. C.Parkinson P.Gloersen andH. J.Zwally(1996) Sea ice concentrations from Nimbus‐7 SMMR and DMSP SSM/I‐SSMIS passive microwave data version 1. NASA Natl. Snow and Ice Data Cent. Distrib. Act. Arch. Cent. Boulder Colo. [Available at:http://dx.doi.org/10.5067/8GQ8LZQVL0VL] accessed on 04/08/2014 updated yearly.

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