Lance M. Leslie

Evolution of the U.S. Tornado Database: 1954–2003

Abstract Over the last 50 yr, the number of tornadoes reported in the United States has doubled from about 600 per year in the 1950s to around 1200 in the 2000s. This doubling is likely not related to meteorological causes alone. To account for this increase a simple least squares linear regression was fitted to the annual number of tornado reports. A “big tornado day” is a single day when numerous tornadoes and/or many tornadoes exceeding a specified intensity threshold were reported anywhere in the country. By defining a big tornado day without considering the spatial distribution of the tornadoes, a big tornado day differs from previous definitions of outbreaks. To address the increase in the number of reports, the number of reports is compared to the expected number of reports in a year based on linear regression. In addition, the F1 and greater Fujita-scale record was used in determining a big tornado day because the F1 and greater series was more stationary over time as opposed to the F2 and greater...

Wind erosion prediction over the Australian continent

Wind erosion is a complicated process influenced by weather patterns, soil conditions, and vegetation cover. In this work we present an integrated wind erosion assessment and prediction system which couples a wind erosion scheme with an atmospheric prediction model and a Geographic Information System database. The system is applied to the February 1996 dust storms over the Australian continent, and the predictions are in good agreement with meteorological records and satellite images. It is found that over the 1 week period from February 6 to 12, 1996, the total dust emission from the Australian continent was around 6 million tons. As demonstrated in this study, the system can be used to identify areas and periods under wind erosion threat and to identify the responsible environmental factors. For atmospheric studies the integrated system provides a possibility of quantifying the sources of dust particles which in turn play an important role in atmospheric radiative processes.

Generalized inversion of a global numerical weather prediction model

SummaryWe construct the generalized inverse of a global numerical weather prediction (NWP) model, in order to prepare initial conditions for the model at time “t=0 hrs”. The inverse finds a weighted, least-squares best-fit to the dynamics for −24<t<0, to the previous initial condition att=−24, and to data att=−24,t=−18,t=−12 andt=0. That is, the inverse is a weak-constraint, four-dimensional variational assimilation scheme. The best-fit is found by solving the nonlinear Euler-Lagrange (EL) equations which determine the local extrema of a penalty functional. The latter is quadratic in the dynamical, initial and data residuals. The EL equations are solved using iterated representer expansions. The technique yields optimal conditioning of the very large minimization problem, which has ∼109 hydrodynamical and thermodynamical variables defined on a 4-dimensional, space-time grid.In addition to introducing the inverse NWP model, we demonstrate it on a medium-sized problem, namely, a study of the impact of reprocessed cloud track wind observations (RCTWO) from the 1990 Tropical Cyclone Motion Experiment (TCM-90). The impact is assessed in terms of the improvement of forecasts in the South China Sea att=+48 hours. The calculation shows that the computations are manageable, the iteration scheme converges, and that the RCTWO have a beneficial impact.

The Basic Relationship between Tropical Cyclone Intensity and the Depth of the Environmental Steering Layer in the Australian Region

Abstract A simple barotropic model is employed to investigate relative impacts on tropical cyclone motion forecasts in the Australian region when wind analyses from different tropospheric levels or layers are used as the input to the model. The model is initialized with selected horizontal wind analyses from individual pressure levels, and vertical averages of several pressure levels (layer-means). The 48-h mean forecast errors (MFE) from this model are analyzed for 300 tropical cyclone cases that cover a wide range of intensities. A significant reduction in the track forecast errors results when the depth of the vertically-averaged initial wind analysis depends upon the initial storm intensity. Mean forecast errors show that the traditionally-utilized 1000-100-hPa deep layer-mean (DLM) analysis is a good approximation of future motion only in cases of very intense tropical cyclones. Shallower, lower-tropospheric layer-means consistently outperform single-level analyses, and are best correlated with futur...

Interannual Variability of Tropical Cyclones in the Australian Region: Role of Large-Scale Environment

Abstract This study investigates the role of large-scale environmental factors, notably sea surface temperature (SST), low-level relative vorticity, and deep-tropospheric vertical wind shear, in the interannual variability of November–April tropical cyclone (TC) activity in the Australian region. Extensive correlation analyses were carried out between TC frequency and intensity and the aforementioned large-scale parameters, using TC data for 1970–2006 from the official Australian TC dataset. Large correlations were found between the seasonal number of TCs and SST in the Nino-3.4 and Nino-4 regions. These correlations were greatest (−0.73) during August–October, immediately preceding the Australian TC season. The correlations remain almost unchanged for the July–September period and therefore can be viewed as potential seasonal predictors of the forthcoming TC season. In contrast, only weak correlations (<+0.37) were found with the local SST in the region north of Australia where many TCs originate; these ...

Australian East-Coast Cyclones. Part I: Synoptic Overview and Case Study

Abstract The meteorological conditions for the development of Australian east-coast cyclones are described. The main synoptic precursor is a trough (or “dip”) in the easterly wind regime over eastern Australia. The cyclones are a mesoscale development which occurs on the coast in this synoptic environment. They form preferentially at night, in the vicinity of a marked low-level baroclinic zone, and just equatorward of a region of enhanced convection resulting from flow over the coastal ranges. Three different types of east-coast cyclone have been identified. Types 1 and 3 are very small systems which can have lifetimes as short as 16 hours, during which hurricane force winds have been observed to develop. The other, type 2, system is a meso/synoptic-scale cyclone that can bring sustained strong winds and flood rainfall over several days. Because of their intensity, rapid development, and occasional tiny size, these systems are a major forecast problem.

A Real-Time System for Forecasting Tropical Cyclone Storm Surges

Abstract The depth-averaged, numerical storm-surge model developed by Hubbert et al. (1990) has been configured to provide a stand-alone system to forecast tropical cyclone storm surges. The atmospheric surface pressure and surface winds are derived from the analytical-empirical model of Holland (1980) and require only cyclone positions, central pressures, and radii of maximum winds. The model has been adapted to run on personal computers in a few minutes so that multiple forecast scenarios can be tested in a forecast office in real time. The storm surge model was tested in hindcast mode on four Australian tropical cyclones. For these case studies the model predicted the sea surface elevations and arrival times of surge peaks accurately, with typical elevation errors of 0.1 to 0.2 m and arrival time errors of no more than 1 h. Second order effects, such as coastally-trapped waves, were also well simulated. The model is now being used by the Australian Tropical Cyclone Warning Centres (TCWCs) for operatio...

Three-Dimensional Mass-Conserving Semi-Lagrangian Scheme Employing Forward Trajectories

Abstract Through the use of the dimensional splitting “cascade” method of grid-to-grid interpolation, it is shown that consistently high-order-accurate semi-Lagrangian integration of a three-dimensional hydrostatic primitive equations model can be carried out using forward (downstream) trajectories instead of the backward (upstream) trajectory computations that are more commonly employed in semi-Lagrangian models. Apart from the efficiency resulting directly from the adoption of the cascade method, improved computational performance is achieved partly by the selective implicit treatment of only the deepest vertical gravity modes and partly by obviating the need to iterate the estimation of each trajectorys location. Perhaps the main distinction of our present semi-Lagrangian method is its inherent exact conservation of mass and passive tracers. This is achieved by adopting a simple variant of the cascade interpolation that incorporates mass (and tracer) conservation directly and at only a very modest add...

Tropical Cyclone Prediction Using a Barotropic Model Initialized by a Generalized Inverse Method

Abstract A nested, nondivergent barotropic numerical weather prediction model for forecasting tropical cyclone motion out to 48 h is initialized at time t = 0 by assimilating data from the preceding 24 h. The assimilation scheme finds the generalized inverse of the model and data for −24 ≤ t ≤ 0. That is, the inverse estimate of the streamfunction is a weighted least-squares best fit to the initial conditions at t = −24, to the data at t = −12 and t = 0, and to the dynamics and the boundary conditions in the interval −24 ≤ t ≤ 0. In particular, the dynamics are imposed only as a weak constraint. The inverse estimate satisfies the Euler-Lagrange equations for a least-squares penalty functional; these nonlinear equations are solved using an iterative technique that yields a sequence of linear Euler-Lagrange equations. A representer expansion produces explicit expressions for the reduced penalty functional, which may be shown to be a χ2 variable with as many degrees of freedom as them are data. The represent...

On the bogussing of tropical cyclones in numerical models: A comparison of vortex profiles

SummaryAt the resolutions currently in use, and with the sparse oceanic data coverage, numerical analyses cannot adequately represent tropical cyclone circulations for use in numerical weather prediction models. In many cases there is no circulation present at all. Most numerical weather prediction centers therefore employ a “bogussing” scheme to force a tropical cyclone vortex into the numerical analysis. The standard procedure is to define a synthetic data distribution based on an analytically prescribed vortex, which is passed to the analysis scheme as a set of high quality observations.In this study, four commonly used bogus vortices are examined by comparing resultant forecast tracks in an environment at rest, and in a background flow that simulates a typical monsoon trough-subtropical ridge structure. There are three main findings, each of which has significance for operational tropical cyclone track prediction. First, great care is needed in the choice of the characteristics of the bogus vortex, such as the radius and magnitude of the maximum wind. Second, the tropical cyclone trajectories can be very sensitive to their initial position in the idealised environment. Third, the bogus vortex can substantially influence the environment, especially over longer time periods and for vortices of larger size.