Weather conditions play a fundamental role in plant growth and development due to their direct and indirect influence on each physical, chemical and biological process, that is regulated by specific requirements and any deviation from these patterns may exert a negative influence (Das et al. 2003). Air and soil temperature, air and soil humidity, solar radiation, wind speed and direction, rainfall, evapotranspiration are the most important variables affecting the vegetative and productive responses of
S. Orlandini and M. Bindi
Climate Adaptation Flagship, GPO Box 2S4, Canberra, ACT 2601 e-mail: [email protected]
K.L. Ebi et al. (eds.), Biometeorology for Adaptation to Climate Variability and Change, 107 © Springer Science + Business Media B.V. 2009
plants, both in natural and cultivated systems. Others can be of interest in particular cases, such as leaf wetness for the analysis of many plant pathogens (Table 6.1).
To define plant responses to weather conditions, and so also to their change and variability, studies can be based on the application of agroclimatic indices and simulation models. These are basically formal expressions of biological, physical and chemical functions fed with environmental and climatic forcing variables. Models are often the only tool available to study the behaviour of complex plant production systems under a variable and changing climate, and they offer unique insights to understand the frequently non-linear interactions among processes in soil-plant systems. In the last few years an increasing interest in this subject has occurred and a high number of computer applications for biometeorological purposes have been developed. Among these it is possible to emphasise plant growth and development, crop yield quality and quantity estimation, water balance, plant protection against pests, diseases, weed and weather hazards, soil erosion and conservation, etc. (Eitzinger et al. 2008).
The analysis of plant responses requires different sources of data, such as meteorological (temperature, rainfall, relative humidity, leaf wetness, solar radiation, wind direction and speed), physical (CO2 concentration, soil structure) and biological (observed symptoms, crop monitoring, plant parameters). Meteorological data are generally required with hourly time step for epidemiological models, while daily data are required for the other kinds of simulations (growth and development); some soil erosion models require a shorter time step (minutes). The availability of meteorological information can be improved by further developing the spatial interpolation methods and by a more effective use of weather radar and satellite information in addition to traditional meteorological ground data. Automation of weather observing stations may have different impacts on the availability of some meteorological parameters. For instance, cloud cover is now rarely measured as it requires visual observation, whereas automatic station are frequently equipped with solar radiation sensors.
Table 6.1 Role of weather conditions in plant-pathosystems processes
Temperature Solar radiation High temperature
Phenological development Biomass assimilation and growth Rate of infection
Threshold of development and survival
Spore and insect conservation
Lower threshold of development and survival
Survival of organism
Dispersion of spore and insect
Survival of spores
Survival of spores
Dispersion of spore and insect
The use of atmospheric models as a source of meteorological data is also an alternative that is worth considering. Large scale models, such as global circulation ones, are provided with a spatial resolution which is still largely insufficient for local scale purposes. The grid size of global models like the ECMWF-model is at the moment about 60 km. Limited Area Models (LAM) were designed with the aim to provide higher resolution atmospheric fields at the continental and regional scale while retaining global modelling capability. Nowadays LAMs use resolutions of 5-30 km and need some external information, i.e. initial conditions and lower and upper boundary conditions, generally provided by Global Circulation Models (Dalla Marta et al. 2003).
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