Spatial and temporal variation in weather events critical for boreal agriculture: III Frost and winter time fluctuation

Authors

• Pirjo Peltonen-Sainio Natural Resources Institute Finland (Luke)
• Pentti Pirinen Finnish Meteorological Institute
• Mikko Laapas Finnish Meteorological Institute
• Hanna M. Mäkelä Finnish Meteorological Institute
• Hannu Ojanen Natural Resources Institute Finland (Luke)
• Ari Venäläinen Finnish Meteorological Institute

DOI: https://doi.org/10.23986/afsci.51467

Keywords:

crop, frost, overwintering, probability, sowing time, spatial variation

Abstract

In the boreal zone of Europe, differences between the four seasons are considerable. Also, the within-season variation in climatic conditions is substantial. This has many impacts on agriculture that are exceptional when compared to any other environmental zone in Europe. All the meteorological data were based on weather observations made by the Finnish Meteorological Institute. Likelihood (%) for soil frost (≤ 0 °C at 20 cm soil depth) at nine weather stations, and late snow cover (> 1 cm) (10 km × 10 km grid) were estimated for late spring. Probabilities (%) of night frost at the ground surface (March-September) were calculated at nine weather stations by frequencies of the lowest observed night-time temperature: a) between –2 and –5 °C (mild), b) ≤ –5 °C (moderate) and c) ≤ –9 °C (severe). Also, the probabilities (%) of night frost in mid-summer were estimated (≤ –1 °C for at least five hours). Furthermore, a significant shift from mild to below-freezing conditions was measured in winter as a period of at least ten days with daily maximum temperatures above 0°C followed by at least a 10-day period with daily mean temperatures below –5°C in order to characterize high fluctuating winter conditions. All these except late snow cover constitute high risks to crop production. Deep soil frost may postpone sowings, while in advanced springs, night frost may cause damage. For winter crops and perennials, shifts from mild to cold spells outside the growing season are particularly detrimental. Again the data may have many other applications beyond the assessments highlighted in this paper.