NDLI: Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

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Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

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16th International Congress of Biometeorology

International Journal of Biometeorology : Volume 45

International Journal of Biometeorology : Volume 44

International Journal of Biometeorology : Volume 43

International Journal of Biometeorology : Volume 42

International Journal of Biometeorology : Volume 41

International Journal of Biometeorology : Volume 40

Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

Content Provider	Springer Nature Link
Author	Bergant, Klemen Kajfež Bogataj, Lučka Črepinšek, Zalika
Copyright Year	2001
Abstract	Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predictand data for the period 1960–1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990–2019 and 2020–2049 in comparison with the period 1960–1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990–2019. The analogous results for the period 2020–2049 are a 10- and 11-day earlier occurrence.
Starting Page	22
Ending Page	32
Page Count	11
File Format	PDF
ISSN	00207128
Journal	International Journal of Biometeorology
Volume Number	46
Issue Number	1
e-ISSN	14321254
Language	English
Publisher	Springer-Verlag
Publisher Date	2001-12-05
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Environment Biophysics and Biological Physics Meteorology Animal Physiology Plant Physiology Environmental Health
Content Type	Text
Resource Type	Article
Subject	Ecology Health, Toxicology and Mutagenesis Atmospheric Science

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Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

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