Adding to Fire Fighter Safety by Including Real-Time Radar Data in Short-Range Forecasts of Thunderstorm-Induced Wind Shifts

Abrupt changes in wind direction and speed caused by thunderstorm-generated gust fronts can, within a few seconds, transform slow-spreading low-intensity flanking fires into high-intensity head fires. Flame heights and spread rates can more than double. Fire mitigation strategies are challenged and the safety of fire crews is put at risk. We propose a class of numerical weather prediction models that incorporate real-time radar data and which can provide fire response units with images of accurate very short-range forecasts of gust front locations and intensities. Real-time weather radar data are coupled with a wind model that simulates density currents over complex terrain. Then two convective systems from formation and merger to gust front arrival at the location of a wildfire at Yarnell, Arizona, in 2013 are simulated. We present images of maps showing the progress of the gust fronts toward the fire. Such images can be transmitted to fire crews to assist decision-making. We conclude, therefore, that very short-range gust front prediction models that incorporate real-time radar data show promise as a means of predicting the critical weather information on gust front propagation for fire operations, and that such tools warrant further study.

Object-based tracking and nowcasting of gust fronts

<p>Thunderstorm gust fronts threaten human safety and property, especially in industries such as aviation and construction. The ability to predict the precise time and location of gust front arrivals would mitigate risk and reduce damage. </p><p>Existing methods for nowcasting gust front locations are based on detecting the gust fronts from individual Doppler weather radars or scanning lidars. Even though these methods are locally effective, they have so far not been applied to large-scale radar mosaics to generate forecasts that could benefit society at large. To address this gap, an object-based method is proposed for nowcasting gust fronts by any number of ground-based Doppler weather radars.  </p><p>The gust fronts are first detected from the radar measurements and presented as objects consisting of spline curves. Given the one-dimensional geometry of the curves, existing object-based tracking methods, designed for tracking thunderstorms and based on two-dimensional polygons, cannot be applied to the gust front objects. Instead, a tracking method is formulated that matches multiple observations of the same gust front based on the location and length of the curves. The tracking considers possible splitting and merging of the gust front objects. After matching the gust front instances between consecutive timesteps, the location of the gust front is nowcast with a Kalman filter algorithm.  </p><p>The methodology is demonstrated with case studies of gust fronts related to mesoscale convective systems (MCS) in Finland. MCSs occur frequently in Finland during summer and cause significant wind and other storm-related damage. Spatially and temporally accurate forecasting of MCS events would aid preparedness and reduce the risk posed to society. The methodology presented in this work can be used to nowcast the gust front trajectory and thus increase preparedness especially for the wind damage related to MCS events. The methodology can also be combined with existing object-based methods for nowcasting convective storm cells, to create comprehensive hazard forecasting systems for thunderstorms.</p>

The characterization of turbulent heat and moisture transport during a gust-front event over the Indian peninsula

The ramifications of gust-front on atmospheric surface layer (ASL) turbulence is a vexing issue, with nearly no information available over the Indian region where such events are not uncommon. Over the Indian peninsula, Chowdhuri et al. (Environ. Fluid Mech. 21(1):263–281, 2021) have shown that, the cold pool associated with the gust-front creates two distinct regimes in ASL turbulence, where the temperature fluctuations display contrasting behavior. To evaluate the corresponding impacts on the moisture fluctuations and turbulent heat and moisture transport, we extend our analysis by using the same field-experimental dataset of Chowdhuri et al. (2021). We discover that, the topology of the turbulent structures which govern the temperature and moisture fluctuations clearly exhibit a regime-wise distinction. In the first regime, the structures in temperature and moisture fluctuations are significantly inclined in the vertical, while demonstrating a self-similarity in their time scales by being related through a power-law distribution. However, in the second regime, the vertical inclination disappears for the temperature structures with hardly any change observed for the moisture. Moreover, the power-law exponents of the turbulent temperature time scales remain sensitive to the regimes, although no such effect is visible in the power-law character of the moisture time scales. Additionally, the dissimilarity in the heat and moisture transport is investigated through a novel polar-quadrant based approach that separates the phases and amplitudes of the flux-transporting motions.

Evaluating Thunderstorm Gust Fronts in New Mexico and Arizona

Strong winds generated by thunderstorm gust fronts can cause sudden changes in fire behavior and threaten the safety of wildland firefighters. Wildfires in complex terrain are particularly vulnerable as gust fronts can be channeled and enhanced by local topography. Despite this, knowledge of gust front characteristics primarily stems from studies of well-organized thunderstorms in flatter areas such as the Great Plains, where the modification of gust fronts by topography is less likely. Here, we broaden the investigation of gust fronts in complex terrain by statistically comparing characteristics of gust fronts that are pushed uphill and propagate atop the Mogollon Rim in Arizona to those that propagate down into and along the Rio Grande Valley in New Mexico. Using operational WSR-88D data and in situ observations from Automated Surface Observing System (ASOS) stations, 122 gust fronts in these regions are assessed to quantify changes in temperature, wind, relative humidity, and propagation speed as they pass over the weather stations. Gust fronts that propagated down into and along the Rio Grande Valley in New Mexico were generally associated with faster propagation speeds, larger decreases in temperature, and larger increases in wind speeds compared to gust fronts that reached the crest of the Mogollon Rim in Arizona. Gust fronts atop the Mogollon Rim in Arizona behaved less in accordance with density current theory compared to those in the Rio Grande Valley in New Mexico. The potential reasons for these results, and their implications for our understanding of terrain influence on gust front characteristics, are discussed.

Toward the Codification of Thunderstorm/Downburst Winds

Non-synoptic winds often exhibit rapid changes during a short period, which may be accompanied by changes in direction. This introduces non-stationarity both in the mean and the standard deviation of wind fluctuations. Thus, design loads in non-synoptic non-stationary winds obtained from conventional analysis frameworks included in codes and standards, such as the gust loading factor approach, may not be appropriate, thus calling for a careful examination of traditional design procedures. This chapter reviews a proposed design procedure for non-synoptic non-stationary winds. In particular, a codification of gust front winds originating from thunderstorms and downbursts is discussed because the event occurs frequently and is well-known to exhibit significant non-stationary characteristics. Two major frameworks reported in the past literature, such as the gust front factor and the thunderstorm response spectrum technique, are examined as a step toward the codification of gust front winds. In addition, a comparison is made between the two frameworks to assess their performance. Finally, a living codification concept through learning and updating invoking the emerging “design thinking” approach is discussed.

Simulated Changes in Storm Morphology Associated with a Sea-Breeze Air Mass

The central east coast of Australia is frequently impacted by large hail and damaging winds associated with severe convective storms, with individual events recording damages exceeding AU$1 billion. These storms present a significant challenge for forecasting due to their development in seemingly marginal environments. They often have been observed to intensify upon approaching the coast, with case studies and climatological analyses indicating that interactions with the sea breeze are key to this process. The relative importance of the additional lifting and vorticity along the sea-breeze front compared to the change to a cooler, moister air mass with stronger low-level shear behind the front has yet to be investigated. Here, the role of the sea-breeze air mass is isolated using idealized numerical simulations of storms developing in a horizontally homogeneous environment. The base-state substitution (BSS) modeling technique is utilized to introduce the sea-breeze air mass following initial storm development. Compared to a simulation without BSS, the storm is longer lived and more intense, ultimately developing supercell characteristics including increased updraft rotation, deviant motion to the left of the mean wind vector, and a strong reflectivity gradient on the inflow edge. Separately simulating the changes in the thermodynamic and wind fields reveals that the enhanced storm longevity and intensity are primarily due to the latter. The change in the low-level environmental winds slows gust front propagation, allowing the storm to continue to ingest warm, potentially buoyant environmental air. At the same time, increased low-level shear promotes the development of persistent updraft rotation causing the storm to transition from a multicell to a supercell.

Investigation of the Weather Conditions During the Collapse of the Morandi Bridge in Genoa on 14 August 2018 Using Field Observations and WRF Model

On 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed to the ground that was 40 m below. This tragedy killed 43 people. Preliminary investigations indicated poor design, questionable building practices, and insufficient maintenance—or a combination of these factors—as a possible cause of the collapse. However, around the collapse time, a thunderstorm associated with strong winds, lightning, and rain also developed over the city. While it is unclear if this thunderstorm played a role in the collapse, the present study examines the weather conditions before and during the bridge collapse. The study particularly focuses on the analysis of a downburst that was observed around the collapse time and a few kilometers away from the bridge. Direct and remote sensing measurements are used to describe the evolution of the thunderstorm during its approached from the sea to the city. The Doppler lidar measurements allowed the reconstruction of the gust front shape and the evaluation of its displacement velocity of 6.6 m s−1 towards the lidar. The Weather Research and Forecasting simulations highlighted that it is still challenging to forecast localized thunderstorms with operational setups. The study has shown that assimilation of radar reflectivity improves the timing and reconstruction of the gust front observed by local measurements.