The combined instability index: a new very‐short range convection forecasting technique for southern Africa

Abstract

Thunderstorms, due to their high frequency of occurrence over southern Africa and their dominant contribution to summer rainfall, are the primary focus of very short range forecasting and nowcasting efforts in South Africa. Most southern African countries are heavily reliant on satellite technology due to the limited number of surface and upper-air observations and the limited availability of numerical model output. In developing tools for the first 12 forecast hours, the South African Weather Service has to address both national and regional needs. The blending of techniques in an optimal manner is essential in achieving this. In this paper a description is given of how the Global Instability Index product derived from the European Meteosat Second Generation Satellite was adapted to fit to South African circumstances using a different numerical model as background information, creating the Regional Instability Indices (RII). The focus of the study is the development of a new convection indicator, called the Combined Instability Index (CII), which calculates the probability of convection based on satellite derived instability indices and moisture as well as orographic lift early in the morning when the sky is as cloud free as possible. The CII is an objective way for operational forecasters to calculate the probability for convection later in the day based on satellite and model data. Early morning CII values were evaluated statistically against the occurrence of lightning as well as against satellite derived precipitation later in the same day. It is shown that the CII not only performs well, but also outperforms the individual RII. The CII will be beneficial to operational forecasters to focus their attention on the area which is most favourable for the development of convection later in the day.

Forecast indices from a ground-based microwave radiometer for operational meteorology

“…In the following definitions, T xxx is the temperature at the pressure level xxx (in mb), Td xxx is dew point temperature, θ e xxx is the equivalent potential temperature, and θ WBxxx is the wet bulb potential temperature at the same pressure level. The forecast index definitions below were extracted from review papers (Peppier, 1998;Haklander and Van Delden, 2003;de Coning et al, 2011) as well as from American Meteorological Society glossary (AMS, 2013) and RAOB software manual. According to Haklander and Van Delden (2003), the various forecast indices are a combination of three types, the first accounting for pure conditional instability, the second accounting for pure latent instability, and the third accounting for pure potential instability of certain atmospheric layers.…”

“…usually 2 to 4 times a day. More recently, FIs at higher temporal resolution (∼ 15 min) became available from geostationary satellite retrievals (König, 2002;König and de Coning, 2009;de Coning et al, 2011). Though they are limited to clear-sky conditions, satellite-based FIs offer the advantage of covering large areas (at continental scale).…”

“…Therefore, temperature and humidity profiles retrieved by MWRPs may be given in input to forecast tools developed for computing FIs from PTU radiosondes. FIs from temperature and humidity profiles are also estimated from geostationary satellites retrievals (König, 2002;König and de Coning, 2009;de Coning et al, 2011). These satellite FI estimates are produced operationally and cover most of the Earth's surface at some 3-10 km resolution.…”

Using Satellite and Lightning Data to Track Rapidly Developing Thunderstorms in Data Sparse Regions

“…In order to cover a more extensive period, sixteen more cases from 15 to 30 March 2015 were added to the dataset. On each of these days, the times between 1100 and 1800 Coordinated Universal Time (UTC) were considered, as this coincides with the time when most heat driven convection in South Africa occurs (i.e., late afternoon and early evening in summer time) [16]. The study focused on the area inside the borders of South Africa covered by radar systems.…”

“…When radar data were not available, the coverage domain of that radar was removed from the study domain when calculating the evaluation statistics. considered, as this coincides with the time when most heat driven convection in South Africa occurs (i.e., late afternoon and early evening in summer time) [16]. The study focused on the area inside the borders of South Africa covered by radar systems.…”