2014
DOI: 10.1175/jamc-d-13-0167.1
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An Optimized System for the Classification of Meteorological Drought Intensity with Applications in Drought Frequency Analysis

Abstract: The adequacy of meteorological drought intensity threshold levels based on deviations of monthly precipitation totals from normal climatological conditions is reconsidered. The motivation for this study is the observation that reference classification systems are fixed for all climatological regions, and threshold levels have been proposed without regard for the statistical distribution of accumulated precipitation in space and time. This misrepresentation of precipitation variability may lead to erroneous est… Show more

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Cited by 29 publications
(21 citation statements)
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“…However, the difficulty in regional drought identification is how to select a proper drought index for a specific study region. A single consensus or empirical guiding principle in this is absent in this area (Mishra and Singh 2010;Carrão et al 2014). Intuitively, meteorological drought mainly results from a (McKee et al 1993).…”
Section: Drought Indexmentioning
confidence: 99%
“…However, the difficulty in regional drought identification is how to select a proper drought index for a specific study region. A single consensus or empirical guiding principle in this is absent in this area (Mishra and Singh 2010;Carrão et al 2014). Intuitively, meteorological drought mainly results from a (McKee et al 1993).…”
Section: Drought Indexmentioning
confidence: 99%
“…m is computed from a time-series of precipitation totals, P m,1 , … , P m,N , collected for month m over a reference period of N years (we focus on the period . The thresholds of drought onset are derived by means of the "Fisher-Jenks" classification algorithm, which estimates the precipitation totals that optimize the partition of the time-series into "drought" and "nondrought" months along the reference period N, as described in Carrão et al (2014).…”
Section: Drought Hazard Estimation: the Weighted Anomaly Of Standardimentioning
confidence: 99%
“…On account of the fact that dealing with drought concepts in contemporary hyperarid and cold regions is physically meaningless (Lyon and Barnston 2005;Carrão et al 2014;Spinoni et al 2015b), we used the global aridity index dataset from Spinoni et al (2015b) to exclude these areas from drought change analysis, as similar as Russo and Sterl (2012) and Carrão et al (2016). Moreover, since GCMs have difficulty in simulating very dry conditions (Sterl et al 2008), the exclusion of the hyperarid regions from our analysis is also important because future precipitation changes are difficult to interpret there.…”
Section: Robustness and Significance Of Climate Projectionsmentioning
confidence: 99%
“…TAI refers to the ratio between the classification error and the "potential error" inherent to the unclassified data, which is a standardized measure of the data classification [46]:…”
Section: K-means Clusteringmentioning
confidence: 99%