Lightning in Zimbabwe Kills 19 Cattle


19 Cattle Dead

Lightning in Zimbabwe struck and killed 19 cattle during a strong storm. Three local families from Chikomba district owned the affected the animals. Officials estimate the total financial loss near $10,000. In Masendu Village, Mable Njowa lost 10 animals. In Munhindorima Village, brothers Masiyiwa and Martin Juru lost four animals. Cikomba district’s livestock production and development officer, Cosma Ratsakatika, reported that the incident occurred close to the families’ homesteads.

The tragedy occurred on Saturday, 18 February 2017 during the afternoon hours. These livestock deaths are hard on Zimbabwe farmers, who lost thousands of cattle last year during the drought. Around this time last year, officials estimate the drought claimed over 24,000 animals.

Lightning in Zimbabwe

We detected 2,194 total lightning strikes during the storm that killed the livestock. The purple icons represent in-cloud strikes while the yellow icons represent deadly cloud-to-ground strikes. In the video below, you can see the lightning concentrations to the south and east of Chikomba converge in Mashonaland East province. The time-lapse represents a 10-hour period during 18 February 2017.

Earlier in the weekend, flash flooding occurred in Bulawayo. The heavy rains and high winds were what was left of tropical storm Dineo. The flooding destroyed approximately 50 homes in the area. The weather reportedly injured two people in Zimbabwe, while the death toll rose to 9 in Mozambique.

Agriculture Insurance

Natural disasters can oftentimes have extremely negative effects on farmers. Lightning, floods and droughts can destroy both crops and livestock. It is important for farmers who live in areas that offer agriculture insurance to enroll.

It is also key for insurers to utilize commercial-grade weather data in their prediction models to improve risk management for their customers. Weather data can also empower insurers to calculate the most effective premiums and plans for farmers depending on location. To learn more about how weather data can optimize your insurance company, please click here.