Decline in temperature variability on Svalbard
The variability in the temperature on Svalbard, Norway, has been decreasing over the last four decades. This may be due to the reduction in sea ice, transitioning the regional climate to a more stable, coastal one.We quantify this transition in terms of decreasing volatility in a daily average tempe...
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Online Access: | https://hdl.handle.net/11250/2766778 https://doi.org/10.1175/JCLI-D-20-0174.1 |
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ftunivbergen:oai:bora.uib.no:11250/2766778 2023-05-15T15:07:50+02:00 Decline in temperature variability on Svalbard Hølleland, Sondre Karlsen, Hans 2020 application/pdf https://hdl.handle.net/11250/2766778 https://doi.org/10.1175/JCLI-D-20-0174.1 eng eng AMS urn:issn:0894-8755 https://hdl.handle.net/11250/2766778 https://doi.org/10.1175/JCLI-D-20-0174.1 cristin:1826445 Journal of Climate. 2020, 33 (19), 8475-8486. Copyright 2020 American Meteorological Society Journal of Climate 8475-8486 33 19 Journal article Peer reviewed 2020 ftunivbergen https://doi.org/10.1175/JCLI-D-20-0174.1 2023-03-14T17:43:46Z The variability in the temperature on Svalbard, Norway, has been decreasing over the last four decades. This may be due to the reduction in sea ice, transitioning the regional climate to a more stable, coastal one.We quantify this transition in terms of decreasing volatility in a daily average temperature time series at Svalbard Airport from 1976 to 2019. We use two different approaches: a nonstochastic model and a time-dependent generalized autoregressive conditional heteroskedasticity (GARCH) model. These parametric approaches include a time-dependent trend, where the slope depends on the day of the year. For Svalbard, the slope has a minimum in late August and the steepest slope during winter is estimated to be 20.18C2 yr21. The nonstochastic model, for which the conditional and unconditional variances are the same, only depends on the marginal distribution and is perhaps the easiest to interpret. The GARCH model extends the nonstochastic model by including short-range temporal dependence in the volatility and is thus more locally adapted. Volatility modeling is important for a complete statistical description of the temperature dynamics on Svalbard as an Arctic representative. In combination with increasing temperatures, the volatility reduction makes the extremely cold days during winter occur less frequently. Although we focus exclusively on the Svalbard Airport series, the models should be suitable for other temperature or climatic time series. publishedVersion Article in Journal/Newspaper Arctic Sea ice Svalbard University of Bergen: Bergen Open Research Archive (BORA-UiB) Arctic Norway Svalbard Journal of Climate 33 19 8475 8486 |
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Open Polar |
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University of Bergen: Bergen Open Research Archive (BORA-UiB) |
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ftunivbergen |
language |
English |
description |
The variability in the temperature on Svalbard, Norway, has been decreasing over the last four decades. This may be due to the reduction in sea ice, transitioning the regional climate to a more stable, coastal one.We quantify this transition in terms of decreasing volatility in a daily average temperature time series at Svalbard Airport from 1976 to 2019. We use two different approaches: a nonstochastic model and a time-dependent generalized autoregressive conditional heteroskedasticity (GARCH) model. These parametric approaches include a time-dependent trend, where the slope depends on the day of the year. For Svalbard, the slope has a minimum in late August and the steepest slope during winter is estimated to be 20.18C2 yr21. The nonstochastic model, for which the conditional and unconditional variances are the same, only depends on the marginal distribution and is perhaps the easiest to interpret. The GARCH model extends the nonstochastic model by including short-range temporal dependence in the volatility and is thus more locally adapted. Volatility modeling is important for a complete statistical description of the temperature dynamics on Svalbard as an Arctic representative. In combination with increasing temperatures, the volatility reduction makes the extremely cold days during winter occur less frequently. Although we focus exclusively on the Svalbard Airport series, the models should be suitable for other temperature or climatic time series. publishedVersion |
format |
Article in Journal/Newspaper |
author |
Hølleland, Sondre Karlsen, Hans |
spellingShingle |
Hølleland, Sondre Karlsen, Hans Decline in temperature variability on Svalbard |
author_facet |
Hølleland, Sondre Karlsen, Hans |
author_sort |
Hølleland, Sondre |
title |
Decline in temperature variability on Svalbard |
title_short |
Decline in temperature variability on Svalbard |
title_full |
Decline in temperature variability on Svalbard |
title_fullStr |
Decline in temperature variability on Svalbard |
title_full_unstemmed |
Decline in temperature variability on Svalbard |
title_sort |
decline in temperature variability on svalbard |
publisher |
AMS |
publishDate |
2020 |
url |
https://hdl.handle.net/11250/2766778 https://doi.org/10.1175/JCLI-D-20-0174.1 |
geographic |
Arctic Norway Svalbard |
geographic_facet |
Arctic Norway Svalbard |
genre |
Arctic Sea ice Svalbard |
genre_facet |
Arctic Sea ice Svalbard |
op_source |
Journal of Climate 8475-8486 33 19 |
op_relation |
urn:issn:0894-8755 https://hdl.handle.net/11250/2766778 https://doi.org/10.1175/JCLI-D-20-0174.1 cristin:1826445 Journal of Climate. 2020, 33 (19), 8475-8486. |
op_rights |
Copyright 2020 American Meteorological Society |
op_doi |
https://doi.org/10.1175/JCLI-D-20-0174.1 |
container_title |
Journal of Climate |
container_volume |
33 |
container_issue |
19 |
container_start_page |
8475 |
op_container_end_page |
8486 |
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1766339255160799232 |