The Impact of Global Temperature Increases on Drought Overestimated Using the Palmer Drought Severity Index

The Palmer Drought Severity Index (PDSI) widely used to assess agricultural water availability, appears to indicate that droughts have become far more common and extreme as global climate change proceeds. Sheffield et al., argue in this paper, however, that the PDSI in its traditional form provides an overly simplistic analysis of how increasing global temperatures have impacted the hydrological cycle. They hold that the PDSI overestimates the frequency and severity of global drought because it incorporates only temperature neglects other physical variables known to influence evaporation rates (Sheffield et al. 2012). By reconfiguring the PDSI using the Penman-Monteith (PM) equation that takes into account changes in available energy, humidity, and wind speed as well as temperature. Sheffield et al. suggest that ongoing global warming has had little effect on global drought. –Hilary Haskell
            Sheffield, J., Wood, E.F., Roderick, M.L., 2012. Little change in global drought over the past 60 years. Nature 491, 435-438.


            Sheffield et al. compared two different versions of the PDSI in this study: the traditional one based on Both the Thornthwaite algorithm (PDSI_Th) and the PDSI Penman-Monteith (PDSI_PM). Both calculate potential evaporation (PE), or the rate of evaporation that could potentially occur if unlimited water were present initially, but use different input data.  The PDSI_Th and PDSI_PM are similar in that they rely on data from a global meteorological data set that addresses uncertainty by utilizing four different global precipitation data sets, and that they both predict increases in global drought area. However, the PDSI_Th predicts a much larger increase in drought area than the PDSI_PM, which actually forecasts increased moisture in some areas. According to the PDSI_Th, global drought area increases significantly (Puses a set of fixed meteorological data over a 612 hour period from the same data sources, as well as data from remote sensing and ground observations. Utilizing this data, the PDSI yields analyses that range in scope from regional to global in area and annual to decadal in temporal period. In order to remove any biases over the varying periods of time, observed data for precipitation, air temperature, and shortwave and longwave radiation are merged together. To summarize the data collected from the PDSI analysis, Sheffield et al. used the Mann-Kendall test, and thus calculated a yearly median value for PDSI data.

The PDSI_PM is regarded more highly for its accuracy because it encapsulates temperature, precipitation, radiation, wind-speed, and humidity data in its calculations. In contrast, the PDSI_Th only considers temperature and precipitation data. According to Sheffield et al., utilizing the PDSI_Th equation is problematic in that it creates a discrepancy in global drought data between the PDSI_Th’s predictions and actual observed data and other models. The PDSI_Th calculation produces an increase in potential evaporation that therefore reflects a higher rate of global drought, unnecessarily compounding the effects of fluctuations in precipitation. However, observed data and models have determined that there is a regional decline in evaporation due to the influence of additional physical factors, such as those included in the PDSI_PM, despite some increases in temperatures on a regional scale. Because of this discrepancy, modeling global drought patterns through the PDSI_Th equation can be inaccurate due to its over dependence on temperature data, especially considering the projected impacts of climate change in the future.
The PDSI Index has been used extensively in analysing past droughts and predicting future droughts by the US National Drought Monitor. The PDSI was first used in the 1960s for agricultural purposes. Sheffield et al., discusses initial concerns with the accuracy of the PDSI_Th using tree ring data. This Paleoclimate drought analysis compared with calculated PDSI_Th yields divergent results due to tree ring data that demonstrate climatic factors and disturbances that affected the growth pattern of the tree and thus patterns of evapotranspiration. These evapotranspiration patterns differ from those calculated through the PDSI_Th.
Currently, the leading studies concerning the correlation between global warming and droughts have been released by the Fourth Assessment Report (AR4) and the Intergovernmental Panel on Climate Change IPCC, with the IPCC study highlighting the shortcomings of the PDSI, and the consideration of its overestimation of regional and global droughts. With a more accurate, comprehensive understanding of global drought patterns, and the implications of global warming on these patterns, there is potential to better analyze rising temperatures’ effects on the creation of more arid climates and decreasing soil moisture, both regionally and globally. Previously, increases in temperature were largely attributed to droughts, rather than considering these fluctuations in temperatures as the cause of droughts. This flaw in recognizing the causal relationship of droughts and temperature increases further leads to overestimations of the effects of climate change on droughts. Better understanding of the relation between global climate change and drought patterns can be achieved through a more accurate method of the PDSI: the PDSI_PM that utilizes data beyond precipitation and temperature in analyzing potential evaporation over a long-term timescale, which can be extrapolated globally in analyzing droughts.

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