Figure 3.1. Annual anomalies of global land-surface air temperature (°C), 1850 to 2005, relative to the 1961 to 1990 mean for CRUTEM3 updated from Brohan et al. (2006). The smooth curves show decadal variations (see Appendix 3.A). The black curve from CRUTEM3 is compared with those from NCDC (Smith and Reynolds, 2005; blue), GISS (Hansen et al., 2001; red) and Lugina et al. (2005; green).
Box 3.1: Drought Terminology and Determination In general terms, drought is a ‘prolonged absence or marked deficiency of precipitation’, a ‘deficiency of precipitation that results in water shortage for some activity or for some group’ or a ‘period of abnormally dry weather sufficiently prolonged for the lack of precipitation to cause a serious hydrological imbalance’ (Heim, 2002). Drought has been defined in a number of ways. ‘Agricultural drought’ relates to moisture deficits in the topmost one metre or so of soil (the root zone) that impact crops, ‘meteorological drought’ is mainly a prolonged deficit of precipitation, and ‘hydrologic drought’ is related to below-normal streamflow, lake and groundwater levels. Drought and its severity can be numerically defined using indices that integrate temperature, precipitation and other variables that affect evapotranspiration and soil moisture. Several indices in different countries assess precipitation deficits in various ways, such as the Standardized Precipitation Index. Other indices make use of additional weather variables. An example is the Keetch-Byrum Drought Index (Keetch and Byrum, 1988), which assesses the severity of drought in soils based on rainfall and temperature estimates to assess soil moisture deficiencies. However, the most commonly used index is the PDSI (Palmer, 1965; Heim, 2002) that uses precipitation, temperature and local available water content data to assess soil moisture. Although the PDSI is not an optimal index, since it does not include variables such as wind speed, solar radiation, cloudiness and water vapour, it is widely used and can be calculated across many climates as it requires only precipitation and temperature data for the calculation of potential evapotranspiration (PET) using Thornthwaite’s (1948) method. Because these data are readily available for most parts of the globe, the PDSI provides a measure of drought for comparison across many regions. However, PET is considered to be more reliably calculated using Penman (1948) type approaches that incorporate the effects of wind, water vapour and solar and longwave radiation. In addition, there has been criticism of most Thornthwaite-based estimates of the PDSI because the empirical constants have not been re-computed for each climate (Alley, 1984). Hence, a self-calibrating version of the PDSI has recently been developed to ensure consistency with the climate at any location (Wells et al., 2004). Also, studies that compute changes or trends in the PDSI effectively remove influences of biases in the absolute values. As the effects of temperature anomalies on the PDSI are small compared to precipitation anomalies (Guttman, 1991), the PDSI is largely controlled by precipitation changes.