AirTemperature: Extensible Software Library to Generate Air Temperature Data

Donatelli, Marcello; Bellocchi, Gianni; Habyarimana, Ephrem; Bregaglio, S.; Baruth, Bettina

doi:10.3814/2010/812789

Cited by 7 publications

(1 citation statement)

References 24 publications

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“…Daily temperature data (maximum and minimum temperature) from 1 January of each year were taken from weather stations placed close to the traps. Hourly temperature data were derived using the model by Stockle included in the AirTemperature software component (Donatelli et al 2010) (http://agsys.cra-cin.it/ tools/airtemperature/help/). The model by Stockle (2002) allows the derivation using just the daily minimum and the maximum temperatures.…”

Section: Data Source and Model Testingmentioning

confidence: 99%

A physiologically based approach for degree-day calculation in pest phenology models: the case of the European Corn Borer (Ostrinia nubilalis Hbn.) in Northern Italy

Maiorano

2011

Int J Biometeorol

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Phenological models based on degree-day accumulation have been developed to support the integrated pest management of many insects. Most of these models are based on linear relationships between temperature and development, and on daily time step simulations using daily minimum and maximum temperatures. This approach represents an approximation that does not take into account the insect physiological response to temperature, and daily temperature fluctuations. The objective of this work has been to develop a phenological model for the European corn borer (ECB) based on the insect physiological response to temperature and running at an hourly time step. Two modeling solutions based on the same generic compartmental system have been compared: the first based on a physiologically based relationship between temperature and development, and using hourly derived temperatures as input (HNL modeling solution); and the second based on a linear relationship between temperature and degree-day accumulation and using daily temperature (DL modeling solution). The two approaches have been compared using ECB moth capture data from the Piemonte region in Northern Italy. The HNL modeling solution showed the best results for all the accuracy indicators. The DL modeling solution showed a tendency to anticipate ECB phenological development too early. This tendency is attributable to the linear relationship between temperature and development, which does not take into account (1) the decline of this relationship at high temperatures, and (2) the daily fluctuation of temperature. As a consequence, degree-days accumulation is accelerated in the DL modeling solution and the phenological development anticipated.

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Section: Data Source and Model Testingmentioning

confidence: 99%