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 s...

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Published in:Journal of Hydrology: Regional Studies
Main Authors: Korbinian Breinl, Giuliano Di Baldassarre
Format: Article in Journal/Newspaper
Language:English
Published: Zenodo 2019
Subjects:
Online Access:https://doi.org/10.1016/j.ejrh.2018.12.002
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spelling ftzenodo:oai:zenodo.org:4043990 2024-09-15T18:37:53+00:00 Space-time disaggregation of precipitation and temperature across different climates and spatial scales Korbinian Breinl Giuliano Di Baldassarre 2019-01-29 https://doi.org/10.1016/j.ejrh.2018.12.002 eng eng Zenodo https://zenodo.org/communities/eu https://doi.org/10.1016/j.ejrh.2018.12.002 oai:zenodo.org:4043990 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/article 2019 ftzenodo https://doi.org/10.1016/j.ejrh.2018.12.002 2024-07-26T19:47:06Z 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. Article in Journal/Newspaper Subarctic Tundra Zenodo Journal of Hydrology: Regional Studies 21 126 146
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
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.
format Article in Journal/Newspaper
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
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 Zenodo
publishDate 2019
url https://doi.org/10.1016/j.ejrh.2018.12.002
genre Subarctic
Tundra
genre_facet Subarctic
Tundra
op_relation https://zenodo.org/communities/eu
https://doi.org/10.1016/j.ejrh.2018.12.002
oai:zenodo.org:4043990
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.1016/j.ejrh.2018.12.002
container_title Journal of Hydrology: Regional Studies
container_volume 21
container_start_page 126
op_container_end_page 146
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