A generalized framework for deriving nonparametric standardized drought indicators

• This paper introduces the Standardized Drought Analysis Toolbox (SDAT).
• Presents a nonparametric and generalized framework for deriving drought indices.
• SDAT offers statistically consistent drought indices based on different variables.
• Offers a framework that can be applied to different climate variables.

This paper introduces the Standardized Drought Analysis Toolbox (SDAT) that offers a generalized framework for deriving nonparametric univariate and multivariate standardized indices. Current indicators suffer from deficiencies including temporal inconsistency, and statistical incomparability. Different indicators have varying scales and ranges and their values cannot be compared with each other directly. Most drought indicators rely on a representative parametric probability distribution function that fits the data. However, a parametric distribution function may not fit the data, especially in continental/global scale studies. SDAT is based on a nonparametric framework that can be applied to different climatic variables including precipitation, soil moisture and relative humidity, without having to assume representative parametric distributions. The most attractive feature of the framework is that it leads to statistically consistent drought indicators based on different variables.