English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  On model differences and skill in predicting sea surface temperature in the Nordic and Barents Seas

Langehaug, H., Matei, D., Eldevik, T., Lohmann, K., & Gao, Y. (2017). On model differences and skill in predicting sea surface temperature in the Nordic and Barents Seas. Climate Dynamics, 48, 913-933. doi:10.1007/s00382-016-3118-3.

Item is

Files

show Files
hide Files
:
10.1007-00382-016-3118-3.pdf (Publisher version), 10MB
Name:
10.1007-00382-016-3118-3.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Langehaug, H.R., Author
Matei, Daniela1, Author                 
Eldevik, T., Author
Lohmann, K., Author
Gao, Y., Author
Affiliations:
1Director’s Research Group OES, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society, ou_913553              

Content

show
hide
Free keywords: -
 Abstract: The Nordic Seas and the Barents Sea is the Atlantic Ocean’s gateway to the Arctic Ocean, and the Gulf Stream’s northern extension brings large amounts of heat into this region and modulates climate in northwestern Europe. We have investigated the predictive skill of initialized hindcast simulations performed with three state-of-the-art climate prediction models within the CMIP5-framework, focusing on sea surface temperature (SST) in the Nordic Seas and Barents Sea, but also on sea ice extent, and the subpolar North Atlantic upstream. The hindcasts are compared with observation-based SST for the period 1961–2010. All models have significant predictive skill in specific regions at certain lead times. However, among the three models there is little consistency concerning which regions that display predictive skill and at what lead times. For instance, in the eastern Nordic Seas, only one model has significant skill in predicting observed SST variability at longer lead times (7–10 years). This region is of particular promise in terms of predictability, as observed thermohaline anomalies progress from the subpolar North Atlantic to the Fram Strait within the time frame of a couple of years. In the same model, predictive skill appears to move northward along a similar route as forecast time progresses. We attribute this to the northward advection of SST anomalies, contributing to skill at longer lead times in the eastern Nordic Seas. The skill at these lead times in particular beats that of persistence forecast, again indicating the potential role of ocean circulation as a source for skill. Furthermore, we discuss possible explanations for the difference in skill among models, such as different model resolutions, initialization techniques, and model climatologies and variance. © 2016 The Author(s)

Details

show
hide
Language(s): eng - English
 Dates: 2016-04-182017-02
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s00382-016-3118-3
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Climate Dynamics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 48 Sequence Number: - Start / End Page: 913 - 933 Identifier: -