Space-time disaggregation of precipitation and temperature across different climates and spatial scales
Study region: This study focuses on two study areas: the Province of Trento (Italy; 6200 km²), and entire Sweden (447000km²). The Province of Trento is a complex mountainous area including subarctic, humid continental and Tundra climates. Sweden, instead, is mainly dominated by a subarctic climate i...
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doaj-9c7b4ffa7c4d4511a76e063ceb4f06c82020-11-25T01:09:47ZengElsevierJournal of Hydrology: Regional Studies2214-58182019-02-0121126146Space-time disaggregation of precipitation and temperature across different climates and spatial scalesKorbinian Breinl0Giuliano Di Baldassarre1Institute of Hydraulic Engineering and Water Resources Management, Technische Universität Wien, Karlsplatz 13/222, 1040 Vienna, Austria; Centre of Natural Hazards and Disaster Science (CNDS), Uppsala, Sweden; Corresponding author at: Institute of Hydraulic Engineering and Water Resources Management, Technische Universität Wien, Karlsplatz 13/222, 1040 Vienna, Austria.Department of Earth Sciences, Uppsala University, Villavägen 16, 752 36 Uppsala, Sweden; Centre of Natural Hazards and Disaster Science (CNDS), Uppsala, SwedenStudy region: This study focuses on two study areas: the Province of Trento (Italy; 6200 km²), and entire Sweden (447000km²). The Province of Trento is a complex mountainous area including subarctic, humid continental and Tundra climates. Sweden, instead, is mainly dominated by a subarctic climate in the North and an oceanic climate in the South.Study focus: Hydrological predictions often require long weather time series of high temporal resolution. Daily observations typically exceed the length of sub-daily observations, and daily gauges are more widely available than sub-daily gauges. The issue can be overcome by disaggregating daily into sub-daily values. We present an open-source tool for the non-parametric space-time disaggregation of daily precipitation and temperature into hourly values called spatial method of fragments (S-MOF). A large number of comparative experiments was conducted for both S-MOF and MOF in the two study regions.New hydrological insights for the region: Our experiments demonstrate the applicability of the univariate and spatial method of fragments in the two temperate/subarctic study regions where snow processes are important. S-MOF is able to produce consistent precipitation and temperature fields at sub-daily resolution with acceptable method related bias. For precipitation, although climatologically more complex, S-MOF generally leads to better results in the Province of Trento than in Sweden, mainly due to the smaller spatial extent of the former region. Keywords: Precipitation, Temperature, Disaggregation, Space-time scaling, Non-parametric, Method of fragmentshttp://www.sciencedirect.com/science/article/pii/S2214581818302283 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Korbinian Breinl Giuliano Di Baldassarre |
spellingShingle |
Korbinian Breinl Giuliano Di Baldassarre Space-time disaggregation of precipitation and temperature across different climates and spatial scales Journal of Hydrology: Regional Studies |
author_facet |
Korbinian Breinl Giuliano Di Baldassarre |
author_sort |
Korbinian Breinl |
title |
Space-time disaggregation of precipitation and temperature across different climates and spatial scales |
title_short |
Space-time disaggregation of precipitation and temperature across different climates and spatial scales |
title_full |
Space-time disaggregation of precipitation and temperature across different climates and spatial scales |
title_fullStr |
Space-time disaggregation of precipitation and temperature across different climates and spatial scales |
title_full_unstemmed |
Space-time disaggregation of precipitation and temperature across different climates and spatial scales |
title_sort |
space-time disaggregation of precipitation and temperature across different climates and spatial scales |
publisher |
Elsevier |
series |
Journal of Hydrology: Regional Studies |
issn |
2214-5818 |
publishDate |
2019-02-01 |
description |
Study region: This study focuses on two study areas: the Province of Trento (Italy; 6200 km²), and entire Sweden (447000km²). The Province of Trento is a complex mountainous area including subarctic, humid continental and Tundra climates. Sweden, instead, is mainly dominated by a subarctic climate in the North and an oceanic climate in the South.Study focus: Hydrological predictions often require long weather time series of high temporal resolution. Daily observations typically exceed the length of sub-daily observations, and daily gauges are more widely available than sub-daily gauges. The issue can be overcome by disaggregating daily into sub-daily values. We present an open-source tool for the non-parametric space-time disaggregation of daily precipitation and temperature into hourly values called spatial method of fragments (S-MOF). A large number of comparative experiments was conducted for both S-MOF and MOF in the two study regions.New hydrological insights for the region: Our experiments demonstrate the applicability of the univariate and spatial method of fragments in the two temperate/subarctic study regions where snow processes are important. S-MOF is able to produce consistent precipitation and temperature fields at sub-daily resolution with acceptable method related bias. For precipitation, although climatologically more complex, S-MOF generally leads to better results in the Province of Trento than in Sweden, mainly due to the smaller spatial extent of the former region. Keywords: Precipitation, Temperature, Disaggregation, Space-time scaling, Non-parametric, Method of fragments |
url |
http://www.sciencedirect.com/science/article/pii/S2214581818302283 |
work_keys_str_mv |
AT korbinianbreinl spacetimedisaggregationofprecipitationandtemperatureacrossdifferentclimatesandspatialscales AT giulianodibaldassarre spacetimedisaggregationofprecipitationandtemperatureacrossdifferentclimatesandspatialscales |
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