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Can temperatures from an online weather forecast service be suitable for modelling growth stages using a CERES-Wheat type phenology model?

Published online by Cambridge University Press:  01 June 2017

M. Launspach ,
J.A. Taylor  and
J. Wilson
M. Launspach*
Affiliation:
School of Agriculture, Food and Rural Development, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK SoilEssentials Ltd., Hilton of Fern, By Brechin, DD9 6SB, UK
J.A. Taylor
Affiliation:
School of Agriculture, Food and Rural Development, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK
J. Wilson
Affiliation:
SoilEssentials Ltd., Hilton of Fern, By Brechin, DD9 6SB, UK
*
†Email: malte.launspach@newcastle.ac.uk
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Abstract

Weather and climate have a fundamental impact on plant development. Monitoring key observables, e.g. temperature and precipitation, is paramount for the interpretation of agricultural experiments and simulation of plant development. Whereas the presence of appropriate sensors in a research environment can be expected, the situation can be different in commercial agricultural settings. Local air temperature from online weather forecasts is investigated as a substitute for local weather station data. Hourly air temperature forecast and station data for several locations in Scotland and North East England are aggregated into daily air temperature values spanning a period of several months. Dates for key growth stages using temperatures from weather stations and weather forecast data are compared. For the examples discussed here the date differences in modelled key growth stages did not exceed 3 days indicating that temperature forecast data is suitable for farm-specific applications.

Keywords

weather stationcrop modelling
Type
Spatial Crop Models
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 684 - 688
Copyright
© The Animal Consortium 2017 

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References

Hoogenboom, G 2000. Contribution of agrometeorology to the simulation of crop production and its applications. Agricultural and Forest Meteorology 103, 137–157.Google Scholar
Johnen, T, Boettcher, U and Kage, H 2012. A variable thermal time of the double ridge to flag leaf emergence phase improves the predictive quality of a CERES-Wheat type phenology model. Computers and Electronics in Agriculture 89, 62–69.Google Scholar
Lennon, JJ and Turner, JRG 1995. Predicting the Spatial Distribution of Climate: Temperature in Great Britain. Journal of Animal Ecology 64, 370–392.Google Scholar
MET Norway 2016. Documentation of the MET Norway weather forecast API http://api.met.no/weatherapi/locationforecast/1.9/documentation. (retrieved 28/11/16).Google Scholar
MET Norway 2016b. FAQ – Locationforecast B.4. http://api.met.no/faq.html#modeldata. (retrieved 01/12/16).Google Scholar
Met Office 2016. Met Office UK DataPoint Service http://www.metoffice.gov.uk/datapoint. (retrieved 28/11/16).Google Scholar
Met Office 2016b. UK climate – Synoptic and climate stations http://www.metoffice.gov.uk/public/weather/climate-network/#?tab=climateNetwork. (retrieved 28/11/16).Google Scholar
Met Office 2016c. UK climate districts map http://www.metoffice.gov.uk/climate/uk/about/districts-map. (retrieved 21/11/16).Google Scholar
Met Office 2016d. Regional values – Year ordered statistics. http://www.metoffice.gov.uk/climate/uk/summaries/datasets. (retrieved 22/11/16).Google Scholar
R Core Team 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Austria https://www.R-project.org.Google Scholar
Tottman, DR and Broad, H 1987. The decimal code for the growth stages of cereals, with illustrations. Annals of Applied Biology 110, 441–454.Google Scholar