Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes
Lake surface water temperature (LSWT) is an important parameter with which to assess aquatic ecosystems and to study the lake’s response to climate change. The AVHRR archive of the University of Bern offers great potential to derive consistent LSWT data suited for the study of climate chan...
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doaj-26e45e6e7f5f459ab48180e549ee90892020-11-24T22:38:21ZengMDPI AGRemote Sensing2072-42922018-06-0110799010.3390/rs10070990rs10070990Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European LakesGian Lieberherr0Stefan Wunderle1Institute of Geography, University of Bern, Hallerstrasse 12, CH-3012 Bern, SwitzerlandInstitute of Geography, University of Bern, Hallerstrasse 12, CH-3012 Bern, SwitzerlandLake surface water temperature (LSWT) is an important parameter with which to assess aquatic ecosystems and to study the lake’s response to climate change. The AVHRR archive of the University of Bern offers great potential to derive consistent LSWT data suited for the study of climate change and lake dynamics. To derive such a dataset, challenges such as orbit drift correction, non-water pixel detection, and homogenization had to be solved. The result is a dataset covering over 3.5 decades of spatial LSWT data for 26 European lakes. The validation against in-situ temperature data at 19 locations showed an uncertainty between ±0.8 K and ±2.0 K (standard deviation), depending on locations of the lakes. The long-term robustness of the dataset was confirmed by comparing in-situ and satellite derived temperature trends, which showed no significant difference. The final trend analysis showed significant LSWT warming trends at all locations (0.2 K/decade to 0.8 K/decade). A gradient of increasing trends from south-west to north-east of Europe was revealed. The strong intra-annual variability of trends indicates that single seasonal trends do not well represent the response of a lake to climate change, e.g., autumn trends are dominant in the north of Europe, whereas winter trends are dominant in the south. Intra-lake variability of trends indicates that trends at single in-situ stations do not necessarily represent the lake’s response. The LSWT dataset generated for this study gives some new and interesting insights into the response of European lakes to climate change during the last 36 years (1981–2016).http://www.mdpi.com/2072-4292/10/7/990Advanced Very High Resolution Radiometer (AVHRR)Lake Surface Water Temperature (LSWT)long-term data recordtemperature trendintra-annual variability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gian Lieberherr Stefan Wunderle |
spellingShingle |
Gian Lieberherr Stefan Wunderle Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes Remote Sensing Advanced Very High Resolution Radiometer (AVHRR) Lake Surface Water Temperature (LSWT) long-term data record temperature trend intra-annual variability |
author_facet |
Gian Lieberherr Stefan Wunderle |
author_sort |
Gian Lieberherr |
title |
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes |
title_short |
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes |
title_full |
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes |
title_fullStr |
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes |
title_full_unstemmed |
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes |
title_sort |
lake surface water temperature derived from 35 years of avhrr sensor data for european lakes |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-06-01 |
description |
Lake surface water temperature (LSWT) is an important parameter with which to assess aquatic ecosystems and to study the lake’s response to climate change. The AVHRR archive of the University of Bern offers great potential to derive consistent LSWT data suited for the study of climate change and lake dynamics. To derive such a dataset, challenges such as orbit drift correction, non-water pixel detection, and homogenization had to be solved. The result is a dataset covering over 3.5 decades of spatial LSWT data for 26 European lakes. The validation against in-situ temperature data at 19 locations showed an uncertainty between ±0.8 K and ±2.0 K (standard deviation), depending on locations of the lakes. The long-term robustness of the dataset was confirmed by comparing in-situ and satellite derived temperature trends, which showed no significant difference. The final trend analysis showed significant LSWT warming trends at all locations (0.2 K/decade to 0.8 K/decade). A gradient of increasing trends from south-west to north-east of Europe was revealed. The strong intra-annual variability of trends indicates that single seasonal trends do not well represent the response of a lake to climate change, e.g., autumn trends are dominant in the north of Europe, whereas winter trends are dominant in the south. Intra-lake variability of trends indicates that trends at single in-situ stations do not necessarily represent the lake’s response. The LSWT dataset generated for this study gives some new and interesting insights into the response of European lakes to climate change during the last 36 years (1981–2016). |
topic |
Advanced Very High Resolution Radiometer (AVHRR) Lake Surface Water Temperature (LSWT) long-term data record temperature trend intra-annual variability |
url |
http://www.mdpi.com/2072-4292/10/7/990 |
work_keys_str_mv |
AT gianlieberherr lakesurfacewatertemperaturederivedfrom35yearsofavhrrsensordataforeuropeanlakes AT stefanwunderle lakesurfacewatertemperaturederivedfrom35yearsofavhrrsensordataforeuropeanlakes |
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