A Linear Diagnostic Equation for the Nonhydrostatic Vertical Motion W in Severe Storms

A linear diagnostic equation for the nonhydrostatic vertical motion W in severe storms is derived in the Cartesian-earth-spherical coordinates. This W diagnostic equation reveals explicitly how forcing factors work together to exert influence on the nonhydrostatic vertical motion in severe storms. If high-resolution global data are available in Cartesian coordinates with guaranteed quality, the Lax-Crank-Nicolson scheme and the Thomas algorithm might provide a promising numerical solution of this diagnostic equation. As a result, quantitative analyses are expected for the evolution mechanisms of severe storms.

Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

Numerical Study on a Severe Downburst-Producing Thunderstorm on 23 August 2001 in Beijing

A thunderstorm that produced severe wind, heavy rain and hail on 23 August 2001 in Beijing was studied by a three-dimensional cloud model including hail-bin microphysics. This model can provide important information for hail size at the surface, which is not available in hail parameterization cloud models. The results shows that the cloud model, using hail-bin microphysics, could reasonably reflect the storm＇s characteristics such as life cycle, rainfall distribution and the diameter of the hailstones and also can reproduce developing processes of downbursts, where they can then be compared with the observed features of the storm. The downburst formation mechanism was investigated based on the cloud microphysics of the simulated storm and it was found that the downburst was primarily produced by hail-loading and enhanced by cooling processes that were due to hail melting and rain evaporation. The loading and melting of hail played crucial roles in the formation of downbursts within the storm.

Characteristics and Possible Formation Mechanisms of Severe Storms in the Outer Rainbands of Typhoon Mujigae(1522)

To better understand how severe storms form and evolve in the outer rainbands of typhoons, in this study, we in- vestigate the evolutionary characteristics and possible formation mechanisms for severe storms in the rainbands of Typhoon Mujigae, which occurred during 2-5 October 2015, based on the NCEP-NCAR reanalysis data, conventional observations, and Doppler radar data. For the rainbands far from the inner core （eye and eyewall） of Mujigae （dis- tance of approximately 70-800 kin）, wind speed first increased with the radius expanding from the inner core, and then decreased as the radius continued to expand. The Rankine Vortex Model was used to explore such variations in wind speed. The areas of strong stormy rainbands were mainly located in the northeast quadrant of Mujigae, and overlapped with the areas of high winds within approximately 300-550 km away from the inner core, where the strong winds were conducive to the development of strong storms. A severe convective cell in the rainbands de- veloped into waterspout at approximately 500 km to the northeast of the inner core, when Mujigae was strengthening before it made landfall. Two severe convective cells in the rainbands developed into two tornadoes at approximately 350 km to the northeast of the inner core after Mujigae made landfall. The radar echo bands enhanced to 60 dBZ when mesocyclones occurred in the rainbands and induced tornadoes. The radar echoes gradually weakened after the mesocyclones weakened. The tops of parent clouds of the mesocyclones elevated at first, and then suddenly dropped about 20 min before the tornadoes appeared. Thereby, the cloud top variation has the potential to be used as an early warning of tornado occurrence.

THREE-DIMENSIONAL ELASTIC ATMOSPHERIC NUMERICAL MODEL AND THE SIMULATION OF A SEVERE STORM CASE

A three-dimensional meso-γ,scale elastic atmospheric numerical model has been established and used to simulate a severe storm case.The important characteristics of the modeled storm are close to those of the observed case.

Analysis of the severe group dust storms in eastern part of Northwest China

Based on the available original dust storm records from 60 meteorological stations, we discussed the identification standard of severe dust storms at a single station and constructed a quite complete time series of severe group dust storms in the eastern part of Northwest China in 1954–2001. The result shows that there were 99 severe group dust storms in this region in recent 48 years. The spatial distribution indicates that the Alax Plateau, most parts of the Ordos Plateau and most parts of the Hexi Corridor are the main areas influenced by severe group dust storms. In addition, the season and the month with the most frequent severe group dust storms are spring and April, accounting for 78.8% and 41.4% of the total events respectively. During the past 48 years the lowest rate of severe group dust storms occurred in the 1990s. Compared with the other 4 decades, on the average, the duration and the affected area of severe group dust storms are relatively short and small during the 1990s. In 2000 and 2001, there were separately 4 severe group dust storms as the higher value after 1983 in the eastern part of Northwest China.

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.