Development of an index for frost prediction: Technique and validation
An index for frost prediction is proposed and calibrated against observations. It takes into account: (1) the main meteorological variables that favour or oppose to frost; (2) weights attributed to these variables; and (3) means and standard deviations of these variables, only for cases in which fro...
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| Published in: | Meteorological applications Vol. 27; no. 1 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Chichester, UK
John Wiley & Sons, Ltd
01-01-2020
John Wiley & Sons, Inc Wiley |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | An index for frost prediction is proposed and calibrated against observations. It takes into account: (1) the main meteorological variables that favour or oppose to frost; (2) weights attributed to these variables; and (3) means and standard deviations of these variables, only for cases in which frost occurs, as defined by observation of temperatures that are ≤ 6°C. The meteorological variables used for the frost index IG (from the Portuguese, Índice de Geada) are numerically predicted by a regional weather forecast model. An outcome of the calibration processes results is that temperature has the largest contribution, followed by pressure and winds, while the other variables were adjusted to obey the restriction that the sum of weights are equal to 1. After index calibration and threshold determination, the method was applied for the 2017 winter season, and a case study for May 2018 was also considered. In order to verify whether the new index can satisfactorily contribute to the weather forecasting, the results using the IG were compared with the temperature outputs of the numerical regional model. It was found that for three selected areas, and for all the forecasted hours, the IG produces better results than the model's direct temperature forecasts. Thus, it was concluded that the use of the IG in an operational environment potentially provides considerable improvement in the predictive skill of frost events.
The occurrence of frost, when the crops are sensitive to low air temperature, causes serious damage to agriculture and has negative effects on production. In view of these negative impacts on the economy of Brazil and other neighbouring countries, a regional index IG (from Portuguese Índice de Geada) was developed at the Center for Weather Prediction and Climate Studies ‐ National Institute for Space Research (CPTEC/INPE) in order to identify locations where frosts are most likely to occur. The results show that the IG can improve the prediction of frost events, and could be used to minimize impacts caused by frost events. |
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| ISSN: | 1350-4827 1469-8080 |
| DOI: | 10.1002/met.1807 |