A simple model for minimum crop temperature forecasting during nocturnal cooling

• Autores: Lhomme, J.P., Guilioni, L.
• Formato: artículo
• Fecha de Publicación: 2004
• Institución: Servicio Nacional de Meteorología e Hidrología del Perú
• Repositorio: SENAMHI-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.senamhi.gob.pe:20.500.12542/469
• Enlace del recurso: https://hdl.handle.net/20.500.12542/469; https://doi.org/10.1016/j.agrformet.2003.11.001
• Nivel de acceso: acceso cerrado
• Materia: Análisis de Suelo; Heladas; Condición de Suelo; Modelos; https://purl.org/pe-repo/ocde/ford#1.05.10

A simple mechanistic model is developed to forecast the minimum temperature reached by the aerial elements of a crop during nocturnal cooling. The model, whose inputs are meteorological data registered at sunset, has two main characteristics: (1) it uses as a framework a two-layer scheme of the surface–atmosphere interaction which allows one to make a clear difference between the temperature of the crop and the temperature of the soil surface; (2) it does not deal with the rather complex resolution of the non-steady-state regime that most of the physical models intend to solve numerically or analytically; it is based upon a static representation of the soil–plant–atmosphere system assumed to be representative of the conditions reached at the end of the night, when minimum temperatures usually occur. The outputs of the model, i.e. minimum crop and soil surface temperatures, are compared to a set of experimental data collected on a pea crop grown near Paris in winter. It appears that the accuracy of the prediction depends mainly on the correct estimation of the nocturnal atmospheric radiation from the weather data observed at sunset. The model performs relatively well under clear sky conditions, but it is less accurate under cloudy conditions. Two simple procedures of estimating long-wave radiation are tested: their accuracy, however, turns out to be relatively poor. When used predictively, the model shows that all other conditions being kept equal, taller crops experience less severe frosts, while crops with greater leaf area index (LAI) experience more severe frosts. The role of soil characteristics (composition, moisture) is also assessed.