Search

There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed. [ABSTRACT FROM AUTHOR]

A cloud‐resolved storm and chemistry simulation of a severe convective system in Oklahoma constrained by anvil aircraft observations of NOx was used to estimate the mean production of NOx per flash in this storm. An upward ice flux scheme was used to parameterize flash rates in the model. Model lightning was also constrained by observed lightning flash types and the altitude distribution of flash channel segments. The best estimate of mean NOx production by lightning in this storm was 80–110 mol per flash, which is smaller than many other literature estimates. This result is likely due to the storm having been a high flash rate event in which flash extents were relatively small. Over the evolution of this storm a moderate negative correlation was found between the total flash rate and flash extent and energy per flash. A longer‐term simulation at 36‐km horizontal resolution with parameterized convection was used to simulate the downwind transport and chemistry of the anvil outflow from the same storm. Convective transport of low‐ozone air from the boundary layer decreased ozone in the anvil outflow by up to 20–40 ppbv compared with the initial conditions, which contained stratospheric influence. Photochemical ozone production in the lightning‐NOx enhanced convective plume proceeded at a rate of 10–11 ppbv per day in the 9–11 km outflow layer over the 24‐hr period of downwind transport to the Southern Appalachians. Photochemical production plays a large role in the restoration of upper tropospheric ozone following deep convection. Plain Language Summary: Nitrogen oxides are important precursors for tropospheric ozone, an important greenhouse gas. The global amount of nitrogen oxides produced by lightning remains highly uncertain, primarily because of uncertainty in the amount produced per flash. In this paper we use an approach that involves cloud‐resolved modeling with chemistry, constrained by observed flash rates and aircraft measurements of nitrogen oxides, to make an estimate of the mean production per flash for an observed severe storm over Oklahoma. We estimate that the mean production rate was 80–110 mol per flash for this high flash rate storm, which is at the lower end of the range reported in the literature. We use a regional model to follow the outflow of the Oklahoma storm downwind to estimate the amount of ozone produced in the upper tropospheric outflow plume by the lightning‐generated nitrogen oxides. Our estimate is in the range found in previous studies, and we note that the ozone production by photochemistry is an important process in restoring upper tropospheric ozone following storms that lofted low values of ozone from the layer of air near the surface. Key Points: Mean lightning NOx production was 80–110 mol flash−1 for a high flash rate storm, based on a model constrained by flash and NOx observationsNet O3 production in the upper outflow of a high flash rate storm was at a rate of 10–11 ppbv day−1 during 24 hr of downwind transportProduction of O3 due to lightning NOx contributed to the recovery of upper tropospheric O3 following reductions due to convective transport [ABSTRACT FROM AUTHOR]

'Lightning flashes can be as big as the thunderstorm complex that made them, and modern lightning mapping can connect strike points on the ground to the whole channel in the [...]

There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous two decades that attempt to address this need, but most have limitations on the type of data they can be used with; computational and/or memory expenses that make them unwieldy with larger datasets; or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed. [ABSTRACT FROM AUTHOR]

Electrification and lightning are simulated for a small continental multicell storm. The results are consistent with observations and thus provide additional understanding of the charging processes and evolution of this storm. The first six observed lightning flashes were all negative cloud-to-ground (CG) flashes, after which intracloud (IC) flashes also occurred between middle and upper levels of the storm. The model simulation reproduces the basic evolution of lightning from low and middle levels to upper levels. The observed lightning indicated an initial charge structure of at least an inverted dipole (negative charge above positive). The simulations show that noninduetive charge separation higher in the storm can enhance the main negative charge sufficiently to produce negative CG flashes before upper-level IC flashes commence. The result is a 'bottom-heavy' tripole charge structure with midlevel negative charge and a lower positive charge region that is more significant than the upper positive region, in contrast to the traditional tripole structure that has a less significant lower positive charge region. Additionally, the occurrence of cloud-to-ground lightning is not necessarily a result of excess net charge carried by the storm, but it is primarily caused by the local potential imbalance between the lowest charge regions. The two-moment microphysics scheme used for this study predicted mass mixing ratio and number concentration of cloud droplets, rain, ice crystals, snow, and graupel. Bulk particle density of graupel was also predicted, which allows a single category to represent a greater range of particle characteristics. (An additional hail category is available but was not needed for the present study.) The prediction of hydrometeor number concentration is particularly critical for charge separation at higher temperatures (-5[degrees] < T < - 20[degrees]C) in the mixed phase region, where ice crystals are produced by time fracturing (Hallett--Mossop process) and by splintering of freezing drops. Cloud droplet concentration prediction also affected the rates of inductive charge separation between graupel and droplets. DOI: 10.1175/2009JAS2965.1