INFLUENCE OF PHYSICAL GEOGRAPHICAL
FEATURES ON LIGHTNING IN THE FREE STATE
PROVINCE OF SOUTH AFRICA: A METHODOLOGY
Catherine Odendaal1, A.S. Steyn1, H.-D. Betz2
1. Department of Soil, Crop and Climate Sciences, University of the Free State, South Africa
2. Physics Faculty, Ludwig-Maximilians University of Munich, Germany
INTRODUCTION
South Africa is a lightning prone country with one of the highest lightning ground flash densities in the world. The global
average is estimated at 44 ± 5 times per second with an annual total of nearly 14 billion flashes. Lightning is an
atmospheric discharge of electricity produced in convective systems such as thunderstorms. Great loss to animal and
human lives are caused by lightning strikes every year in addition to the extensive damage to infrastructure and
electronic equipment. It is thus imperative to know which areas are more lightning prone in order to implement the
necessary protective measures to reduce the number of lightning-related incidents. It is important to identify those
factors that influence the spatial distribution of cloud-to-ground flashes. The objectives of this study are to describe the
Lightning Flash Density (LFD) distribution of the Free State province and to determine the relationship between
lightning (the predictand) and physical geographical features such as topography, land type, land use as well as
geological and climatological zones (the predictors).
METHODS
A flash density map was obtained from the South African Weather Service (SAWS) depicting the annual average
number of strikes per km2 for the period 2006 – 2010. Stepwise linear regression will be used to rank the predictor
variables and develop a LFD forecast equation for the study area. Subsequently this equation will be used to produce a
map of the forecast LFD over the Free State province. This will be compared to Lightning Imaging Sensor data
obtained from the TRMM satellite. Verification measures and scores can then be calculated at each grid point and
averaged over the entire study area. These verification statistics will include the Mean Error (ME) or Bias, Mean
Absolute Error (MAE), Mean Squared Error (MSE), coefficient of determination (R2) as well as the Anomaly Correlation
Coefficient (ACC).
Altitude
Rock Types
Land Cover
Lightning Flash Density
(flashes per square km)
Soil Types
Vegetation Types
Land Types
Population Density
Morphology