Budburst model performance: The effect of the spatial resolution of temperature data sets
(2015) In Agricultural and Forest Meteorology 200. p.302-312- Abstract
- Phenological models have mainly been developed to capture the seasonal development of individual trees and local populations, using data from meteorological stations. Ecosystem models that incorporate phenology are however commonly driven by gridded climate data. Using two phenological models to simulate budburst of birch in Germany, we assessed how combining phenological point observations with gridded climate data in model calibration and evaluation influence model accuracy. The models were driven by observed temperature from a nearby meteorological station, gridded temperature, and observed and gridded temperature adjusted to the location of the tree. Our results indicate that the spatial resolution of temperature can influence the... (More)
- Phenological models have mainly been developed to capture the seasonal development of individual trees and local populations, using data from meteorological stations. Ecosystem models that incorporate phenology are however commonly driven by gridded climate data. Using two phenological models to simulate budburst of birch in Germany, we assessed how combining phenological point observations with gridded climate data in model calibration and evaluation influence model accuracy. The models were driven by observed temperature from a nearby meteorological station, gridded temperature, and observed and gridded temperature adjusted to the location of the tree. Our results indicate that the spatial resolution of temperature can influence the models performance at individual sites, but with no temperature data set generating significantly more accurate simulations than the other temperatures. Irrespective of temperature data, the model simulations represented the average of several trees better than any individual tree. When evaluating the models performance using point observations, the error became smaller when driving the model with adjusted temperature data, and then calculating grid-cell averages based on several observations. (C) 2014 Elsevier B.V. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/5076025
- author
- Olsson, Cecilia LU and Jönsson, Anna Maria LU
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Temperature, Spatial resolution, Budburst, Growing degree-days, Betula, pendula
- in
- Agricultural and Forest Meteorology
- volume
- 200
- pages
- 302 - 312
- publisher
- Elsevier
- external identifiers
-
- wos:000347582300029
- scopus:84910091926
- ISSN
- 1873-2240
- DOI
- 10.1016/j.agrformet.2014.10.003
- language
- English
- LU publication?
- yes
- id
- 54f0f2e2-31d2-4cf5-ae45-359eb75dedd1 (old id 5076025)
- date added to LUP
- 2016-04-01 13:49:21
- date last changed
- 2022-03-14 02:10:35
@article{54f0f2e2-31d2-4cf5-ae45-359eb75dedd1, abstract = {{Phenological models have mainly been developed to capture the seasonal development of individual trees and local populations, using data from meteorological stations. Ecosystem models that incorporate phenology are however commonly driven by gridded climate data. Using two phenological models to simulate budburst of birch in Germany, we assessed how combining phenological point observations with gridded climate data in model calibration and evaluation influence model accuracy. The models were driven by observed temperature from a nearby meteorological station, gridded temperature, and observed and gridded temperature adjusted to the location of the tree. Our results indicate that the spatial resolution of temperature can influence the models performance at individual sites, but with no temperature data set generating significantly more accurate simulations than the other temperatures. Irrespective of temperature data, the model simulations represented the average of several trees better than any individual tree. When evaluating the models performance using point observations, the error became smaller when driving the model with adjusted temperature data, and then calculating grid-cell averages based on several observations. (C) 2014 Elsevier B.V. All rights reserved.}}, author = {{Olsson, Cecilia and Jönsson, Anna Maria}}, issn = {{1873-2240}}, keywords = {{Temperature; Spatial resolution; Budburst; Growing degree-days; Betula; pendula}}, language = {{eng}}, pages = {{302--312}}, publisher = {{Elsevier}}, series = {{Agricultural and Forest Meteorology}}, title = {{Budburst model performance: The effect of the spatial resolution of temperature data sets}}, url = {{http://dx.doi.org/10.1016/j.agrformet.2014.10.003}}, doi = {{10.1016/j.agrformet.2014.10.003}}, volume = {{200}}, year = {{2015}}, }