Temporal and spatial variations in the frequency of compound hot, dry, and windy events in the central United States

Abstract

Simultaneous low humidity, high temperature, and high wind speeds disturb the water balance in plants, intensify evapotranspiration, and can ultimately lead to crop damage. In addition, these events have been linked to flash droughts and can play a critical role in the spread of human ignited wildfires. The spatial patterns and temporal changes of hot, dry, and windy events (HDWs) for two time periods, 1949 to 2018 (70-years) and 1969 to 2018 (50-years) were analyzed in the central United States. The highest frequencies of HDWs were observed at stations in western Kansas and west Texas. Annually, the highest number of events happened concurrently with the major heat waves and droughts in 1980 and 2011. Temporally, an overall decrease in the HDWs was significant in the eastern regions of North Dakota and South Dakota, and an upward trend was significant in Texas and the western part of the Great Plains. Significant trends in HDWs co-occurred more frequently with significant trends in extreme temperatures compared with low humidity or strong wind events. The results of this study provide valuable information on the location of places where HDWs are more likely to occur. The information provided could be used to improve water management strategies.

Space-time dependence of compound hot-dry events in the United States: assessment using a multi-site multi-variable weather generator

“…CC BY 4.0 License. Tavakol et al (2020) have shown that at long (i.e. annual) time scales, hot-dry-windy events co-occurred with major heat waves, which is in line with our finding that temperature is an important driver of extreme compound hot-dry events at seasonal to annual time scales.…”

“…an increasing number of studies assessing changes in their frequency of occurrence. Substantial increases in the number of concurrent droughts and heat waves over the last few decades have been reported not just for the US (Alizadeh et al, 2020;Mazdiyasni and AghaKouchak, 2015;Tavakol et al, 2020) but also globally (Feng et al, 2020;Sarhadi et al, 2018) and for other regions of the world such as China (Wu et al, 2019;Zhou and Liu, 2018;Yu and Zhai, 2020) and Europe (Manning et al, 2019).…”

Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator

“…3. Transform the T and P time series from the time to the frequency domain by decomposing the series into an amplitude and phase signal using a continuous wavelet transform with the Morlet wavelet (Torrence and Compo, 1998) (R package wavScalogram; Bolós and Benítez, 2020). The continuous wavelet transform is defined as the convolution of a time series x n of length n:…”

“…The interest in these impactful compound events is reflected in an increasing number of studies assessing changes in their frequency of occurrence. Substantial increases in the number of concurrent droughts and heatwaves over the last few decades that are partly explained by increasing temperatures have been reported not just for the US (Alizadeh et al, 2020;Mazdiyasni and AghaKouchak, 2015;Tavakol et al, 2020) but also globally (Feng et al, 2020;Sarhadi et al, 2018) and for other regions of the world such as China (Wu et al, 2019;Zhou and Liu, 2018;Yu and Zhai, 2020) and Europe (Manning et al, 2019).…”

“…We extend PRSim.wave here to multiple variables by proposing a multi-site multi-variable stochastic weather generator (PRSim.weather) that simulates long time series of spatially consistent temperature (T ) and precipitation (P ) time series. This multi-site multi-variable stochastic model reproduces local variable distributions using flexible distributions for T and P and introduces spatiotemporal and variable dependence using the wavelet transform (Torrence and Compo, 1998) and phase randomization (Schreiber and Schmitz, 2000;Lancaster et al, 2018). Using this multi-site multi-variable generator to simulate a large set of spatial multivariate hot-dry events will help to shed light on the question of how timescale shapes compound event characteristics including spatial extent.…”