Climate quality index

Climate quality is a composite indicator assessed by using parameters that influence water availability to plants, as well as climatic hazards such as frost that inhibit or even prohibit plant growth.

Aim of the method/technique	The method aims to evaluate the quality of the climate with respect to the sensitivity of an area to land degradation and desertification. It is an index proposed by the MEDALUS III European research project for defining environmentally sensitive areas to desertification (ESA).
Scale – spatial and temporal	The scale depends on the scales of the input data and can vary from local to regional (from 30m to 1km of resolution). Meteorological data are usually collected daily and thus averaged on monthly basis. A period of at least 30 years is necessary to describe the prevailing climate quality index of an area.
Brief description	Climate Quality Index (CQI) is assessed using parameters affecting  water availability to plants, such as amount of rainfall, aridity, and slope aspect. Slope aspect is introduced here since it affects micro-climate characteristics of hilly or mountainous areas. This index is calculated by the equation (Kosmas et al. 1999): CQI= (Total annual precipitation * Bagnouls & Gaussen aridity index * Aspect)¹/³
Data requirements	The data required to calculate CQI are monthly and annual rainfall in mm, monthly air temperature in °C, and topographic characteristics of the study area in relation to slope orientation (slope aspect).
Main applications in cropland and forests & shrubland regions	The Climate Quality Index can be used to evaluate the climate quality of cropland and forest regions and to obtain to evaluate sensitivity to land degradation and desertification as in the ESA index, developed within the project MEDALUS (Kosmas et al., 1999) and applied in several forest environments (Ferrara et al., 2008; Ferrara et al. 2009)
Strengths and weaknesses	The possibility to combine climatic data to obtain a CQI map allows verifying regions that are subjected to drier climatic conditions and require more attention  for management planning. The strengths are about the possibility to condense climate properties in a index that can be referred to land degradation. The main weaknesses are associated with the availability of input data in time and space.

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