Predicting the temperature of the Barents Sea
Knowledge of the influence of the physical environment on commercially important fish stocks in the North Atlantic has increased during the last decade. To allow this information to be used in fisheries management, some forecast of the environment is important. Predictions of temperature in the Arct...
| Published in: | Fisheries Oceanography |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2000
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1046/j.1365-2419.2000.00127.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1046%2Fj.1365-2419.2000.00127.x https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1365-2419.2000.00127.x |
| Summary: | Knowledge of the influence of the physical environment on commercially important fish stocks in the North Atlantic has increased during the last decade. To allow this information to be used in fisheries management, some forecast of the environment is important. Predictions of temperature in the Arcto‐boreal Barents Sea have been given for many years, both as subjective opinions of scientists and implicitly in stock assessment assumptions of, e.g., mortality rates. To evaluate an objective statistical forecasting system, we have analysed time series representing mechanisms previously proposed as influencing the temperature of the Barents Sea. These include components of suggested periodic nature, large‐scale advective effects, regional processes, and atmospheric teleconnections. The predictability of Barents Sea temperature based on the above mechanisms was evaluated through calculations of auto‐ and cross‐correlations, linear regression, spectral analysis and autoregressive modelling. Forecasts based on periodic fluctuations in temperature performed poorly. Advection alone did not explain a major part of the variability. The precision of predictions six months ahead varied with season; forecasts from spring to autumn had least uncertainty. A first‐order autoregressive model, including modelled atmospherically driven volume flux to the western Barents Sea during the preceding year and the position of the Gulf Stream off the eastern coast of the USA two years earlier, explained 50% of the total historical temperature variability. |
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