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Ryan Jewell and Julian Brimelow

Abstract

A one-dimensional, coupled hail and cloud model (HAILCAST) is tested to assess its ability to predict hail size. The model employs an ensemble approach when forecasting maximum hail size, uses a sounding as input, and can be run in seconds on an operational workstation. The model was originally developed in South Africa and then improved upon in Canada, using high quality hail verification data for calibration. In this study, the model was run on a spatially and seasonally diverse set of 914 modified severe hail proximity soundings collected within the contiguous United States between 1989 and 2004. Model output was then compared to the maximum observed hail size for each proximity sounding. Basic verification statistics are presented, showing that the HAILCAST model exhibits considerable skill that can be of use to the operational severe weather forecaster.

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Julian C. Brimelow and Gerhard W. Reuter

Abstract

HAILCAST is a numerical model developed specifically to predict the size of the largest hail reaching the ground. It consists of a steady-state cloud model combined with a time-dependent hailstone growth model. The regional version of the Canadian Global Environmental Multiscale (GEM) model is used to provide prognostic model soundings that are used as input data for HAILCAST. A map of forecasted maximum hail size is thereby obtained. Because hail is typically accompanied by rain, it would be advantageous if the GEM–HAILCAST system were to predict the occurrence of hail only in those regions where the GEM model was predicting precipitation. Hence, the utility of applying a forecast rainfall mask from the GEM model to restrict hail forecasts to those areas where rainfall is forecast during a 12-h window centered on 0000 UTC was tested. The accumulated precipitation filter is objective and integrates both the thermodynamic and dynamic output from the GEM model over many time steps.

To test the utility of applying the GEM forecast precipitation mask, the masking technique was applied to HAILCAST-predicted maximum hail size maps for the three Canadian prairie provinces between 1 June and 31 August 2000. Several case studies will be presented to illustrate the usefulness of adding the precipitation mask. Verification statistics confirm that applying the rainfall mask tends to slightly reduce the false alarm ratio while still identifying the majority of hail events within a special study area over southern Alberta. The performance of the precipitation masking technique was not as effective on severe hail days, especially when attempting to identify both the occurrence and location of severe hail swaths.

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Julian C. Brimelow and Gerhard W. Reuter

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Lagrangian trajectories were computed for three extreme summer rainfall events (with rainfall exceeding 100 mm) over the southern Mackenzie River basin to test the hypothesis that the low-level moisture feeding these rainstorms can be traced back to the Gulf of Mexico. The three-dimensional trajectories were computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT).

For all three events, parcel trajectories were identified that originated near the Gulf of Mexico and terminated over the southern Mackenzie River basin. Specifically, the transport of low-level moisture was found to occur along either quasi-continuous or stepwise trajectories. The time required to complete the journey varied between 6 and 10 days.

Closer examination of the data suggests that, for the three cases in question, the transport of modified Gulf of Mexico moisture to high latitudes was realized when the northward extension of the Great Plains low-level jet to the Dakotas occurred in synch with rapid cyclogenesis over Alberta, Canada. In this way, modified low-level moisture from the Gulf of Mexico arrived over the northern Great Plains at the same time as a strong southerly flow developed over the Dakotas and Saskatchewan, Canada, in advance of the deepening cutoff low over Alberta. This moist air was then transported northward over Saskatchewan and finally westward over the southern Mackenzie River basin, where strong ascent occurred.

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Kit Szeto, Peter Gysbers, Julian Brimelow, and Ronald Stewart
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Julian C. Brimelow, Gerhard W. Reuter, and Eugene R. Poolman

Abstract

A one-dimensional steady-state cloud model was combined with a time-dependent hail growth model to predict the maximum hailstone size on the ground. Model runs were based on 160 proximity soundings recorded within the Alberta Hail Project area for three summers between 1983 and 1985. The forecast hail sizes were verified against reports of maximum hail size gathered from a high-density observation network within the project area. The probability of detection (POD), the false-alarm ratio (FAR), and the Heidke skill score (HSS) were computed for the hail model forecasts and were compared with the skill scores for a nomogram method developed to forecast hail size in Alberta. The hail model was skillful in forecasting hail (POD = 0.85, FAR = 0.26, HSS = 0.64). On days with hail larger than 2 cm in diameter, the hail model performed slightly better (POD = 0.90, FAR = 0.40, HSS = 0.67). Analysis of the skill scores and hail-size forecasts suggests that employing a coupled cloud and hail model noticeably improves the overall skill and accuracy of hail forecasts as compared with those determined using the nomogram.

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Julian C. Brimelow, John M. Hanesiak, and William R. Burrows

Abstract

Linkages between the terrestrial ecosystem and precipitation play a critical role in regulating regional weather and climate. These linkages can manifest themselves as positive or negative feedback loops, which may either favor or inhibit the triggering and intensity of thunderstorms. Although the Canadian Prairies terrestrial system has been identified as having the potential to exert a detectable influence on convective precipitation during the warm season, little work has been done in this area using in situ observations.

The authors present findings from a novel study designed to explore linkages between the normalized difference vegetation index (NDVI) and lightning duration (DUR) from the Canadian Lightning Detection Network for 38 census agricultural regions (CARs) on the Canadian Prairies. Statistics Canada divides the prairie agricultural zone into CARs (polygons of varying size and shape) for the purpose of calculating agricultural statistics. Here, DUR is used as a proxy for thunderstorm activity. Statistical analyses were undertaken for 38 CARs for summers [June–August (JJA)] between 1999 and 2008. Specifically, coefficients of determination were calculated between pairs of standardized anomalies of DUR and NDVI by season and by month. Correlations were also calculated for CARs grouped by size and/or magnitude of the NDVI anomalies.

The main findings are as follows: 1) JJA lightning activity is overwhelmingly below average within larger dry areas (i.e., areas with below-average NDVI); that is, the linkages between NDVI and DUR increased significantly as both the area and magnitude of the dry anomaly increased. 2) In contrast, CARs with above-average NDVI did not consistently experience above-average lightning activity, regardless of the CAR size. 3) The lower threshold for the length scale of the dry anomalies required to affect the boundary layer sufficiently to reduce lightning activity was found to be approximately 150 km (~18 000 km2). 4) The authors’ analysis suggests that the surface-convection feedback appears to be a real phenomenon, in which drought tends to perpetuate drought with respect to convective storms and associated rainfall, within the limits found in 1) and 3).

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Julian C. Brimelow, John M. Hanesiak, and William R. Burrows

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The purpose of this study was to focus on how anomalies in the normalized difference vegetation index (NDVI; a proxy for soil moisture) over the Canadian Prairies can condition the convective boundary layer (CBL) so as to inhibit or facilitate thunderstorm activity while also considering the role of synoptic-scale forcing. This study focused on a census agricultural region (CAR) over central Alberta for which we had observed lightning data (proxy for thunderstorms), remotely sensed NDVI data, and in situ rawinsonde data (to quantify impacts of vegetation vigor on the CBL characteristics) for 11 summers from 1999 to 2009. The authors’ data suggest that the occurrence of lightning over the study area is more likely (and is of longer duration) when storms develop in an environment in which the surface and upper-air synoptic-scale forcing are synchronized. On days when surface forcing and midtropospheric ascent are present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. Additionally, the authors found the response of thunderstorm duration to NDVI anomalies to be asymmetric. That is, the response of lightning duration to anomalies in NDVI is marked when NDVI is below average but is not necessarily discernible when NDVI is above average. The authors propose a conceptual model, based largely on observations, that integrates all of the above findings to describe how a reduction in vegetation vigor—in response to soil moisture deficits—modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating lifting condensation level heights, which in turn affect lightning activity.

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Kit Szeto, Xuebin Zhang, Robert Edward White, and Julian Brimelow
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Andrew Heymsfield, Miklós Szakáll, Alexander Jost, Ian Giammanco, Robert Wright, and Julian Brimelow

Abstract

This corrigendum improves upon the size-dependent representation of graupel and hail terminal velocities, kinetic energies, and mass fluxes that were reported in the study. In particular, representation of these dependencies on diameter over the full range of particle sizes is improved upon by correcting minor errors and by developing representations that cover different size ranges.

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Julian Brimelow, Kit Szeto, Barrie Bonsal, John Hanesiak, Bohdan Kochtubajda, Fraser Evans, and Ronald Stewart

Abstract

In the spring and early summer of 2011, the Assiniboine River basin in Canada experienced an extreme flood that was unprecedented in terms of duration and severity. The flood had significant socioeconomic impacts and caused over $1 billion (Canadian dollars) in damage. Contrary to what one might expect for such an extreme flood, individual precipitation events before and during the 2011 flood were not extreme; instead, it was the cumulative impact and timing of precipitation events going back to the summer of 2010 that played a key role in the 2011 flood. The summer and fall of 2010 were exceptionally wet, resulting in above-normal soil moisture levels at the time of freeze-up. This was followed by record high snow water equivalent values in March and April 2011. Cold temperatures in March delayed the spring melt, resulting in the above-average spring freshet occurring close to the onset of heavy rains in May and June. The large-scale atmospheric flow during May and June 2011 favored increased cyclone activity in the region, which produced an anomalously large number of heavy rainfall events over the basin. All of these factors combined generated extreme flooding. Japanese 55-year Reanalysis Project (JRA-55) data are used to quantify the relative importance of snowmelt and spring precipitation in contributing to the unprecedented flood and to demonstrate how the 2011 flood was unique compared to previous floods. This study can be used to validate and improve flood forecasting techniques over this important basin; the findings also raise important questions regarding floods in a changing climate over basins that experience pluvial and nival flooding.

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