Drought assessment has been outpaced by climate change: empirical arguments for a paradigm shift

A brief description.

Figure 1: Conceptual model describing the drought metric bias associated with a non-stationary climate scenario A theoretical accumulated precipitation dataset is presented on the horizontal axis, while the associated probability density function (PDF) is on the vertical axis. [left] Conceptual model showing one way that probability distributions can shift in time when conditions transition from a wetter, less variable state to a drier, more variable state. [right] Demonstration of how this shift can produce both a dry bias during dry times and a wet bias during wet times for a theoretical distribution.
Figure 1: Conceptual model describing the drought metric bias associated with a non-stationary climate scenario A theoretical accumulated precipitation dataset is presented on the horizontal axis, while the associated probability density function (PDF) is on the vertical axis. [left] Conceptual model showing one way that probability distributions can shift in time when conditions transition from a wetter, less variable state to a drier, more variable state. [right] Demonstration of how this shift can produce both a dry bias during dry times and a wet bias during wet times for a theoretical distribution.
Figure 2: Probability distribution shift for Global Historical Climatology Network (GHCN) site USC00381770 located at Clemson University in South Carolina [left] Subplots show 30-year moving window values of the gamma distribution rate and shape parameters, mean precipitation and coefficient of variation (CV) of precipitation for a 30-day timescale on August 1st. Horizontal lines represent values computed using the temporally integrated distribution. [right] Probability density functions (PDFs) for each of the 30-year moving windows. The color scale represents the 30-year moving window’s final year and the black and white dashed line represents the temporally integrated PDF.
Figure 2: Probability distribution shift for Global Historical Climatology Network (GHCN) site USC00381770 located at Clemson University in South Carolina [left] Subplots show 30-year moving window values of the gamma distribution rate and shape parameters, mean precipitation and coefficient of variation (CV) of precipitation for a 30-day timescale on August 1st. Horizontal lines represent values computed using the temporally integrated distribution. [right] Probability density functions (PDFs) for each of the 30-year moving windows. The color scale represents the 30-year moving window’s final year and the black and white dashed line represents the temporally integrated PDF.