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 km(2)), and entire Sweden (447000km(2)). The Province of Trento is a complex mountainous area including subarctic, humid continental and Tundra climates. Sweden, instead, is mainly dominated by a subarctic clima...

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Bibliographic Details
Published in:Journal of Hydrology: Regional Studies
Main Authors: Breinl, Korbinian, Di Baldassarre, Giuliano
Format: Article in Journal/Newspaper
Language:English
Published: Uppsala universitet, Luft-, vatten- och landskapslära 2019
Subjects:
Precipitation
Temperature
Disaggregation
Space-time scaling
Non-parametric
Method of fragments
Ecology
Ekologi
Subarctic
Tundra
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-377221
https://doi.org/10.1016/j.ejrh.2018.12.002
Description
Summary:Study region: This study focuses on two study areas: the Province of Trento (Italy; 6200 km(2)), and entire Sweden (447000km(2)). 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.

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