Abstract
Frequent occurrences of extreme cold weather processes create severe agricultural/forest frost events, even given the background of global warming. In the warm temperate zone of China, which is the largest planting area for fresh apricot, late spring frost disaster has become one of the major meteorological hazards during flowering. To prevent cold weather-induced apricot frost events and reduce potential losses in related fruit economic value, it is vital to establish a meteorological indicator for timely and accurate identification of cold weather process-based apricot frost events, to provide support for timely apricot frost monitoring and warning in late spring. In this study, daily minimax temperature (Tmin) and apricot frost disaster data during flowering were combined to establish meteorological identification indicators of apricot frost based on cold weather processes. A process-based apricot frost model (f(D,Tcum) was firstly constructed, and characteristics of (Tcum) (accumulated harmful temperature) were explored under different D (duration days) based on the representation of historical apricot frost processes. Thresholds for the (Tcum) for apricot frost in 1, 2, 3, 4 and more than 5 days of apricot frost process were determined as -1.51, -2.92, -4.39, -5.84 and − 7.31°C, respectively. Validation results by reserved independent disaster samples were generally consistent with the historical records of apricot frost disasters, with 89.00% accuracy for indicator-based identification results. Typical process tracking of the proposed identification indicator to an apricot frost event that occurred in North Hebei during April 3–9, 2018 revealed that the indicator-based identification result basically coincides with the historical disaster record and can reflect more detailed information about the apricot frost process.
Comparison of simple statistical model and Brunt-type model to predict daily minimum temperature for spring frost protection
