A Combined IR-GPS Satellite Analysis for Potential Applications in Detecting and Predicting Lightning Activity (original) (raw)
Related papers
Detection of lightning activity using GPS PWV measurements
Space Science and …, 2011
Knowledge of lightning activity in the middle atmosphere down to Earth surface and its relationship with a global warming phenomenon is posing a great challenge for observational and prediction studies. This paper utilized the GPS data to monitor the tropospheric precipitable water vapor (PWV) changes as a climate variable due to lightning discharges. Analysis data on November 2009 over Bangi area within the radius of 20 km showed that all the lightning activities were preceded by Intra-Cloud (IC) and followed by Cloud-to-Ground (CG) after a certain time gap. For most cases in this region found that the lightning activity was frequent in the afternoon between 13:00 and 20:00 local time (LT) and the CG was accompanied by IC in all the time but not vice versa. Based on the 14 samples of lightning days, there were 64.29% and 28.57% correlated with an increase and decrease in PWV content, respectively. The finding can be motivating the further research on utilizing the GPS data as a guide to predict the occurrence of lightning.
Proceedings of International Conference on …, 2011
One aspect of severe storms that can be monitored is lightning activity. There is no established and accurate model to predict the lightning occurrence and to explain their comprehensive physical mechanisms. This paper aim to monitor the lightning activity associated with water vapor changes to form convective cloud from evaporation due to solar heating. Water vapor content in term of precipitable water vapor (PWV) derived from GPS signals and the surface meteorological data is used to strengthen the GPS signals affected by the lightning. Data on November 2009 coincided with the winter monsoon (northeast monsoon) are selected, which possibly had a lot of rainfall with a high number of lightning activity. The lightning occurrence is recorded by the Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR). The area for the first study is centered at radius 20 km from UKM GPS station located in Bangi, Malaysia. Results showed that major lightning activity was recorded 12 days during that month and 81% of total sample was correlated with PWV changes before the first strike, and is consistent with an increase in PWV. In most cases in that region found that the lightning activity is frequent in the afternoon between 13:00 and 18:00 local time, which preceded by PWV increase of about 5 mm. The finding suggests that the GPS data can be utilized further as a guide to predict the occurrence of lightning.
Annals of geophysics = Annali di geofisica
The spatial and temporal radio wave delay of the Global Positioning System (GPS) signal can be manipulated to estimate the precipitable water vapor (PWV) which favorable for meteorological applications. A rapid change of the water vapor amount was a precondition for the unbalanced atmospheric charges, which noticeably associated with the development of convective cloud as a lightning chamber. According to this fact, GPS derived PWV will be utilized to nowcasting the lightning event for the next couple of hours. The variances of PWV of four-selected station of the Peninsular Malaysia during the past two inter-monsoons events in May and November 2009 were analyzed. To clarify the response, the changes of PWV in hourly Δ (max-min) before the lightning event was investigated with minimum value 2 mm and is maintained at least three consecutive hours. There are 177 samples were extracted from this method and 69% of the sample showed the lightning occurrence with an average duration was af...
A Lightning Prediction Index that Utilizes GPS Integrated Precipitable Water Vapor*
Weather and Forecasting, 2002
The primary weather forecast challenge at the Cape Canaveral Air Station and Kennedy Space Center is lightning. This paper describes a statistical approach that combines integrated precipitable water vapor (IPWV) data from a global positioning system (GPS) receiver site located at the Kennedy Space Center (KSC) with other meteorological data to develop a new GPS lightning index. The goal of this effort is to increase the forecasting skill and lead time for prediction of a first strike at the KSC. Statistical regression methods are used to identify predictors that contribute skill in forecasting a lightning event. Four predictors were identified out of a field of 23 predictors that were tested, determined using data from the 1999 summer thunderstorm season. They are maximum electric field mill values, GPS IPWV, 9-h change in IPWV, and K index. The GPS lightning index is a binary logistic regression model made up of coefficients multiplying the four predictors. When time series of the GPS lightning index are plotted, a common pattern emerges several hours prior to a lightning event. Whenever the GPS lightning index falls to 0.7 or below, lightning occurs within the next 12.5 h. An index threshold value of 0.7 was determined from the data for lightning prediction. Forecasting time constraints based on KSC weather notification requirements were incorporated into the verification. Forecast verification results obtained by using a contingency table revealed a 26.2% decrease from the KSC's previous-season false alarm rates for a nonindependent period and a 13.2% decrease in false alarm rates for an independent test season using the GPS lightning index. In addition, the index improved the KSC desired lead time by nearly 10%. Although the lightning strike window of 12 h is long, the GPS lightning index provides useful guidance to the forecaster in preparing lighting forecasts, when combined with other resources such as radar and satellite data. Future testing of the GPS lightning index and the prospect of using the logistic regression approach in forecasting related weather hazards are discussed.
Global lightning and severe storm monitoring from GPS orbit
2004
Over the last few decades, there has been a growing interest to develop and deploy an automated and continuously operating satellite-based global lightning mapper [e.g. Christian et al., 1989; Weber et al., 1998; Suszcynsky et al., 2000]. Lightning is a direct consequence of the electrification and breakdown processes that take place during the convective stages of thunderstorm development. Satellite-based lightning
Submitted to …, 2008
This work presents a relationship between atmospheric discharges and penetrative convective clouds. It combines Infrared and Water Vapor channels from the GOES-12 geostationary satellite with cloud-ground lightning data from the Brazilian Integrated Lightning Detection Network (RINDAT) during the period from January to February 2005. The difference between water vapor and infrared brightness temperature is a tracer penetrating clouds. Due to the water vapor channel's strong absorption, this difference is positive only during overshooting cases, when convective clouds penetrate the stratosphere. From this difference and the cloud-ground electrical discharge, measured on the ground by RINDAT, it was possible to adjust exponential curves that relate the brightness temperature difference from these two channels to the probability of occurrence of cloud-ground electrical discharges, with a very high coefficient of determination. If WV-IR brightness temperature difference is larger than-15K there is a high potential for cloudground lightning activity. As this difference increases the cloud-ground lightning probably increase, for example: if this difference is equal zero, the probability of having at least one cloud-ground electrical discharge is 10.9 %, 7.0% for two, 4.4% for four, 2.7% for eight and 1.5% for sixteen cloud-ground lightning discharges Through this process, was developed a scheme that estimates the probability of occurrence of cloud-ground lightning over all the continental region of South America.
Revisiting Lightning Activity and Parameterization Using Geostationary Satellite Observations
Remote Sensing
The Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite 16 (GOES-16) detects total lightning continuously, with a high spatial resolution and detection efficiency. Coincident data from the GLM and the Advanced Baseline Imager (ABI) are used to explore the correlation between the cloud top properties and flash activity across the continental United States (CONUS) sector from May to September 2020. A large number of collocated infrared (IR) brightness temperature (TBB), cloud top height (CTH) and lightning data provides robust statistics. Overall, the likelihood of lightning occurrence and high flash density is higher if the TBB is colder than 225 K. The higher CTH is observed to be correlated with a larger flash rate, a smaller flash size, stronger updraft, and larger optical energy. Furthermore, the cloud top updraft velocity (w) is estimated based on the decreasing rate of TBB, but it is smaller than the updraft velocity of the convective c...
A study about the correlation link between lightning data and meteorological data
Lightning Imager (LI) is one of the candidates to fly on the European Meteosat satellite platform of third generation (MTG). Therefore with the MTG it will be available the lightning data on the whole Euro-African zone. The LI is a product of the application field of nowcasting, but the implications of its applications are seen also in hydrology, monitoring of land and forest and management of the crisis. Collaboration between CNMCA (Centro Nazionale di Meteorologia e climatologia dell'Aeronautica) and SELEX-GALILEO (a Finmeccanica company) aims to study a possible methodology use of lightning data, to supply more information about the modalities of LI data in the decision management. In detail this research proposes an algorithm for the identification of convective areas through the use of data LAMPINET (lightning ground network of the Italian Air Force Metereological service), SEVIRI, NEFODINA (a software developed by Italian Air Force Meteorological service that is able to identify convective system and to forecast their developments in the next 15 minutes), radar, and subsequently to characterize the cloud and its precipitation.