John T. Allen

Climate and Hazardous Convective Weather

Substantial progress has been made recently relating the large-scale climate system and hazardous convective weather (HCW; tornadoes, hail, and damaging wind), particularly over the USA where there are large societal impacts and a long observational record. Despite observational data limitations, HCW has shown to be influenced by the climate system and the tropical atmosphere via the Madden-Julian Oscillation and El Niño-Southern Oscillation. Analysis of the atmospheric environments favorable to HCW (e.g., convective available potential energy and vertical wind shear) avoids observational and model limitations. While few robust trends are seen over recent decades, future climate projections indicate increased frequency of such environments over the USA, Europe, and Australia, suggesting increased future HCW activity. A recent increase in the year-to-year variability of US tornado occurrence is striking, but not yet understood. Dynamical downscaling to convection-permitting resolutions promises improved understanding of the relationships between large-scale climate and HCW occurrence.

Explosive Cyclogenesis: A Global Climatology Comparing Multiple Reanalyses

A global climatology for rapid cyclone intensification has been produced from the second NCEP reanalysis (NCEP2),the25-yrJapaneseReanalysis(JRA-25),andtheECMWFreanalysesovertheperiod1979‐2008.An improved (combined) criterion for identifying explosive cyclones has been developed based on preexisting definitions, offering a more balanced, normalized climatological distribution. The combined definition was found to significantly alter the population of explosive cyclones, with a reduction in ‘‘artificial’’ systems, which are found to compose 20% of the population determined by earlier definitions. Seasonally, winter was found to be the dominant formative period in both hemispheres, with a lower degree of interseasonal variability in the SouthernHemisphere(SH).Consideredovertheperiod1979‐2008,littlechangeisobservedinthefrequencyof systems outside of natural interannual variability in either hemisphere. Significant statistical differences have been found between reanalyses in the SH, while in contrast the Northern Hemisphere (NH) was characterized bystrongpositivecorrelationsbetweenreanalysesinalmostallexaminedcases.Spatially,explosivecyclonesare distributed into several distinct regions, with two regions in the northwest Pacific and the North Atlantic in the NH and three main regions in the SH. High-resolution and modern reanalysis data were also found to increase the climatology population of rapidly intensifying systems. This indicates that the reanalyses have apparently undergone increasing improvements in consistency over time, particularly in the SH.

An Empirical Relation between U.S. Tornado Activity and Monthly Environmental Parameters

AbstractIn previous work the authors demonstrated an empirical relation, in the form of an index, between U.S. monthly tornado activity and monthly averaged environmental parameters. Here a detailed comparison is made between the index and reported tornado activity. The index is a function of two environmental parameters taken from the North American Regional Reanalysis: convective precipitation (cPrcp) and storm relative helicity (SRH). Additional environmental parameters are considered for inclusion in the index, among them convective available potential energy, but their inclusion does not significantly improve the overall climatological performance of the index. The aggregate climatological dependence of reported monthly U.S. tornado numbers on cPrcp and SRH is well described by the index, although it fails to capture nonsupercell and cool season tornadoes. The contributions of the two environmental parameters to the index annual cycle and spatial distribution are examined with the seasonality of cPrc...

An empirical model relating U.S. monthly hail occurrence to large-scale meteorological environment

An empirical model relating monthly hail occurrence to the large-scale environment has been developed and tested for the United States (U.S.). Monthly hail occurrence for each 1°×1° grid box is defined as the number of hail events that occur there during a month; a hail event consists of a 3 h period with at least one report of hail larger than 1 in. The model is derived using climatological annual cycle data only. Environmental variables are taken from the North American Regional Reanalysis (NARR; 1979–2012). The model includes four environmental variables convective precipitation, convective available potential energy, storm relative helicity, and mean surface to 90 hPa specific humidity. The model differs in its choice of variables and their relative weighting from existing severe weather indices. The model realistically matches the annual cycle of hail occurrence both regionally and for the contiguous U.S. (CONUS). The modeled spatial distribution is also consistent with the observed hail climatology. However, the westward shift of maximum hail frequency during the summer months is delayed in the model relative to observations, and the model has a lower frequency of hail just east of the Rocky Mountains compared to observations. Year-to-year variability provides an independent test of the model. On monthly and annual time scales, the model reproduces observed hail frequencies. Overall model trends are small compared to observed changes, suggesting that further analysis is necessary to differentiate between physical and nonphysical trends. The empirical hail model provides a new tool for exploration of connections between large-scale climate and severe weather.

Future Australian Severe Thunderstorm Environments. Part II: The Influence of a Strongly Warming Climate on Convective Environments

AbstractThe influence of a warming climate on the occurrence of severe thunderstorm environments in Australia was explored using two global climate models: Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6), and the Cubic-Conformal Atmospheric Model (CCAM). These models have previously been evaluated and found to be capable of reproducing a useful climatology for the twentieth-century period (1980–2000). Analyzing the changes between the historical period and high warming climate scenarios for the period 2079–99 has allowed estimation of the potential convective future for the continent. Based on these simulations, significant increases to the frequency of severe thunderstorm environments will likely occur for northern and eastern Australia in a warmed climate. This change is a response to increasing convective available potential energy from higher continental moisture, particularly in proximity to warm sea surface temperatures. Despite decreases to the frequency...

Future Australian Severe Thunderstorm Environments. Part I: A Novel Evaluation and Climatology of Convective Parameters from Two Climate Models for the Late Twentieth Century

The influence of a warming climate on the occurrence of severe thunderstorms over Australia is, as yet, poorly understood. Based on methods used in the development of a climatology of observed severe thunderstorm environments over the continent, two climate models [Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6) and the Cubic-Conformal Atmospheric Model (CCAM)] have been used to produce simulated climatologies of ingredients and environments favorable to severe thunderstorms for the late twentieth century (1980‐2000). A novel evaluation of these model climatologies against data from both the ECMWF Interim Re-Analysis (ERA-Interim) and reports of severe thunderstorms from observers is used to analyze the capability of the models to represent convective environments in the current climate. This evaluation examines the representation of thunderstorm-favorable environments in terms of their frequency, seasonal cycle, and spatial distribution, while presenting a framework for future evaluations of climate model convective parameters. Both models showed the capability to explain at least 75% of the spatial variance in both vertical wind shear and convective available potential energy (CAPE). CSIRO Mk3.6 struggled to either represent the diurnal cycle over a large portion of the continent or resolve the annual cycle, while in contrast CCAM showed a tendency to underestimate CAPE and 0‐6-km bulk magnitude vertical wind shear (S06). While spatial resolution likely contributes to rendering of features such as coastal moisture and significant topography, the distribution of severe thunderstorm environments is found to have greater sensitivity to model biases. This highlights the need for a consistent approachto evaluating convective parameters andseverethunderstorm environments in present-day climate: an example of which is presented here.

Importance of the Gulf of Mexico as a climate driver for U.S. severe thunderstorm activity

Different features of the Gulf of Mexico (GOM), such as the Loop Current and warm-core rings, are found to influence monthly-to-seasonal severe weather occurrence in different regions of the United States (U.S.). The warmer (cooler) the GOM sea surface temperatures, the more (less) hail and tornadoes occur during March–May over the southern U.S. This pattern is reflected physically in boundary layer specific humidity and mixed-layer convective available potential energy, two large-scale atmospheric conditions favorable for severe weather occurrence. This relationship is complicated by interactions between the GOM and El Nino–Southern Oscillation (ENSO) but persists when analyzing ENSO neutral conditions. This suggests that the GOM can influence hail and tornado occurrence and provides another source of regional predictability for seasonal severe weather.

ENSO‐based probabilistic forecasts of March–May U.S. tornado and hail activity

Extended Logistic Regression is used to predict March-May severe convective storm (SCS) activity based on the preceding December-February (DJF) ENSO state. The spatially-resolved probabilistic forecasts are verified against U.S. tornado counts, hail events and two environmental indices for severe convection. The cross-validated skill is positive for roughly a quarter of the U.S. Overall, indices are predicted with more skill than are storm reports, and hail events are predicted with more skill than tornado counts. Skill is higher in the cool phase of ENSO (La Nina-like) when overall SCS activity is higher. SCS forecasts based on the predicted DJF ENSO state from coupled dynamical models initialized in October of the previous year extend the lead-time with only a modest reduction in skill compared to forecasts based on the observed DJF ENSO state.

An Extreme Value Model for U.S. Hail Size

AbstractThe spatial distribution of return intervals for U.S. hail size is explored within the framework of extreme value theory using observations from the period 1979–2013. The center of the continent has experienced hail in excess of 5 in. (127 mm) during the past 30 yr, whereas hail in excess of 1 in. (25 mm) is more common in other regions, including the West Coast. Observed hail sizes show heavy quantization toward fixed-diameter reference objects and are influenced by spatial and temporal biases similar to those noted for hail occurrence. Recorded hail diameters have been growing in recent decades because of improved reporting. These data limitations motivate exploration of extreme value distributions to represent the return periods for various hail diameters. The parameters of a Gumbel distribution are fit to dithered observed annual maxima on a national 1° × 1° grid at locations with sufficient records. Gridded and kernel-smoothed return sizes and quantiles up to the 200-yr return period are dete...

Relationships between Hourly Rainfall Intensity and Atmospheric Variables over the Contiguous United States

AbstractRainfall intensity displays relationships with atmospheric conditions such as surface temperature, and these relationships have implications for how the intensity of rainfall varies with climate. Here, hourly gauge measurements of rainfall over the contiguous United States (CONUS) are related to atmospheric variables taken from the North American Regional Reanalysis for the period 1979–2012. This analysis extends previous work relating the rainfall process to the environment by including a wider range of variables in univariate and bivariate quantile regressions. Known covariate relationships are used to quantify the regional contributions of different weather regimes to rainfall occurrence and to identify preferential atmospheric states for rainfall occurrence. The efficiency of different sets of regressors is evaluated, and the results show that both moisture availability and vertical instability should be taken into account, with CAPE in combination with specific humidity or dewpoint temperatur...