Statistical modelling of temperature variability in the Barents Sea

During the latter years an effort has been made to find out more about the relations between environmental variation and recruitment, growth, distribution and migration of fish. The rationale has to a large degree been the needs from fisheries management. To utilize this knowledge for management pur...

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Main Authors: Ottersen, Geir, Ådlandsvik, Bjørn, Loeng, Harald
Format: Report
Language:English
Published: ICES 1994
Subjects:
Online Access:http://hdl.handle.net/11250/105354
id ftimr:oai:imr.brage.unit.no:11250/105354
record_format openpolar
spelling ftimr:oai:imr.brage.unit.no:11250/105354 2023-05-15T15:38:46+02:00 Statistical modelling of temperature variability in the Barents Sea Ottersen, Geir Ådlandsvik, Bjørn Loeng, Harald 1994 application/pdf http://hdl.handle.net/11250/105354 eng eng ICES ICES CM Documents;1994/S:2 This report is not to be cited without prior reference to the authors http://hdl.handle.net/11250/105354 17 s. temperature temperatur environmental status miljøstatus monitoring overvåkning VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412 VDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452 Working paper 1994 ftimr 2021-09-23T20:14:41Z During the latter years an effort has been made to find out more about the relations between environmental variation and recruitment, growth, distribution and migration of fish. The rationale has to a large degree been the needs from fisheries management. To utilize this knowledge for management purposes it is necessary to be able to make some kind of forecast of the environmental situation. This work is an early attempt to quantify the future temperature development in the Barents Sea. We use three different methods, all applied to the ocean temperature time series from the Russian Kola-section. The first method uses the principle of least squares to fit a sum of Fourier components to the observations and construct a function which generates future values. We also apply Holt- Winters models with a linear trend and either an additive or a multiplicative seasonal component. The third procedure classifies the different years into a few categories according to temperature. Statistics on the historical temperature patterns can then be used for forecast purposes. Our results indicate temperature conditions below the long term mean up to 1999. The uncertainty of the forecasts grows with the time-span, but we believe that the picture for the 2-3 first years is reasonably reliable. Our hope is that this work will help towards taking the environmental situation into consideration when evaluating the future fisheries resource situation. Report Barents Sea Institute for Marine Research: Brage IMR Barents Sea
institution Open Polar
collection Institute for Marine Research: Brage IMR
op_collection_id ftimr
language English
topic temperature
temperatur
environmental status
miljøstatus
monitoring
overvåkning
VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412
VDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452
spellingShingle temperature
temperatur
environmental status
miljøstatus
monitoring
overvåkning
VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412
VDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452
Ottersen, Geir
Ådlandsvik, Bjørn
Loeng, Harald
Statistical modelling of temperature variability in the Barents Sea
topic_facet temperature
temperatur
environmental status
miljøstatus
monitoring
overvåkning
VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412
VDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452
description During the latter years an effort has been made to find out more about the relations between environmental variation and recruitment, growth, distribution and migration of fish. The rationale has to a large degree been the needs from fisheries management. To utilize this knowledge for management purposes it is necessary to be able to make some kind of forecast of the environmental situation. This work is an early attempt to quantify the future temperature development in the Barents Sea. We use three different methods, all applied to the ocean temperature time series from the Russian Kola-section. The first method uses the principle of least squares to fit a sum of Fourier components to the observations and construct a function which generates future values. We also apply Holt- Winters models with a linear trend and either an additive or a multiplicative seasonal component. The third procedure classifies the different years into a few categories according to temperature. Statistics on the historical temperature patterns can then be used for forecast purposes. Our results indicate temperature conditions below the long term mean up to 1999. The uncertainty of the forecasts grows with the time-span, but we believe that the picture for the 2-3 first years is reasonably reliable. Our hope is that this work will help towards taking the environmental situation into consideration when evaluating the future fisheries resource situation.
format Report
author Ottersen, Geir
Ådlandsvik, Bjørn
Loeng, Harald
author_facet Ottersen, Geir
Ådlandsvik, Bjørn
Loeng, Harald
author_sort Ottersen, Geir
title Statistical modelling of temperature variability in the Barents Sea
title_short Statistical modelling of temperature variability in the Barents Sea
title_full Statistical modelling of temperature variability in the Barents Sea
title_fullStr Statistical modelling of temperature variability in the Barents Sea
title_full_unstemmed Statistical modelling of temperature variability in the Barents Sea
title_sort statistical modelling of temperature variability in the barents sea
publisher ICES
publishDate 1994
url http://hdl.handle.net/11250/105354
geographic Barents Sea
geographic_facet Barents Sea
genre Barents Sea
genre_facet Barents Sea
op_source 17 s.
op_relation ICES CM Documents;1994/S:2
This report is not to be cited without prior reference to the authors
http://hdl.handle.net/11250/105354
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