Comment on “Characteristics and trends in various forms of the Palmer Drought Severity Index (PDSI) during 1900–2008” by Aiguo Dai

Abstract

[1] Dai [2011] (henceforth D11) reported that the Palmer Drought Severity Index (PDSI) is superior to other statistically based drought indices including the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). D11 argued that given the physical character of the PDSI water balance model, the index provides robust estimates of drought severity because it takes the preceding conditions into account, in contrast to other drought indices that are based purely on past statistics of particular climate variable(s). However, D11 has overestimated the ability of the PDSI to realistically simulate the distributed soil water balance at large spatial scales, and ignored the inherent complexity and multiscalar character of drought phenomena, which are related to more than the moisture conditions of the soil. In this comment we discuss the complex characteristics of droughts and the limitations of the PDSI to quantify drought conditions in a variety of hydrological systems. We describe the advantages of statistically based drought indices including the SPI and the SPEI. The fact that the SPI and the SPEI are not (and do not intend to be) physically based indices is more liberating than constraining, especially when the physical basis of PDSI can be seriously questioned. [2] Drought is a complex phenomenon that involves both human and natural factors. In contrast to other extreme events such as floods, which are typically restricted to small regions and well defined temporal intervals, droughts are difficult to pinpoint in time and space, and affect large areas over long periods of time. It is very difficult to identify the moment when a drought starts and finishes, and to quantify its duration, magnitude and spatial extent [Burton et al., 1978; Wilhite, 2000]. For these reasons substantial efforts have been devoted to developing methods to quantify drought severity. The main efforts have been directed at developing drought indices that enable earlier identification of droughts, and quantification of their severity and spatial extent. Several drought indices were developed during the 20th Century, based on a range of variables and parameters (see reviews by Heim [2002], Keyantash and Dracup [2002], Mishra and Singh [2010], and Sivakumar et al. [2010]). Thus, drought indices have become very important for monitoring drought continuously in time and space, and drought early warning systems are based primarily on the information that drought indices provide [Svoboda et al., 2002]. [3] D11 analyzed the spatial and temporal patterns of drought variability and drought trends at a global scale using the Palmer Drought Severity Index (PDSI) under different modalities (original and self-calibrated; sc) and using two different models to calculate the potential evapotranspiration as input to the Penmann-Montheith and Thornthwaite model. Global studies including D11 are central to obtaining a deep understanding of changes in drought severity, the associated atmospheric mechanisms, and the possible impacts on surface hydrology, water resources, agriculture and ecology. [4] D11 noted that the PDSI is a physically based water balance model and stated that it is superior to other statistically based drought indices because it accounts for the basic effect of global warming through Palmer's water balance model of droughts and wet periods. D11 questioned the applicability of drought indices that are based on the statistical characteristics of particular climate variables. He specifically drew attention to the Standardized Precipitation Evapotranspiration Index (SPEI) [Vicente-Serrano et al., 2010a], critically noting that it is based on potential evapotranspiration (PE) and not on actual evapotranspiration (E). The rationale was that it is E and not PE that determines the surface water balance and the drought conditions. It was argued that because PE and E are often decoupled (or even anti-correlated) over many water limited land areas where drought studies are most relevant, a physical model is necessary to calculate the moisture condition near the surface, from which a drought index should be derived. [5] We discuss here shortcomings of the PDSI in adequately modeling the soil water balance, and its limited ability to quantify and monitor droughts of different types. Conversely, we describe the advantages of statistically based drought indices in analyzing the spatial and temporal variability of drought, identifying drought impacts in a variety of systems, and monitoring drought conditions in real time. [6] It is widely recognized that the PDSI has numerous deficiencies [e.g., Alley, 1984]. Karl [1986] showed that the PDSI is highly affected by the selected calibration period. In addition, the parameters necessary to calculate the PDSI were determined empirically and mainly tested in the U.S.A., which restricts its use in other regions [see Akinremi et al., 1996]. It has been shown th