In a worrying trend, extreme weather events in India are rising with each passing year, claiming thousands of lives. According to the India Meteorological Department’s ‘Climate of India During 2022’ report, extreme weather events claimed 2,227 lives across the country in 2022, out of which 1,285 people — 58% of the total casualties — died due to thunderstorms and lightning.
Given how lethal thunderstorms can be, their accurate predictions can play a major role in saving lives and livelihoods. But generating precise long-range predictions for weeks, months, and seasons remains tricky, as the state of atmospheric systems remains ever-changing.
March 23 is celebrated as World Meteorological Day, and 2023 also marks the World Meteorological Organisation’s (WMO) 150th anniversary, highlighting past achievements, present progress and future potential of weather forecasting. The theme this year is “The future of weather, climate and water across generations”! It celebrates the life-saving role of improved weather forecasts and explores their future potential.
Along these lines, a study published earlier this month appears to have found a better method to predict thunderstorms and help countries like India better tackle this hazard with early warnings.
Led by Pennsylvania State University scientists, the research encourages combining data from the geostationary weather satellite GOES-16 and ground-based Doppler radar to paint a more accurate picture of thunderstorms initiation in the planetary boundary layer — the lowest part of the atmosphere, between 1-2 kilometres above Earth's surface, where thunderstorms form.
Simultaneous assimilation of satellite, radar data generates best results
Study lead Keenan Eure focussed on satellite observations to capture the state of the atmosphere where storms may form, and used the radar observations for inputs on low-level winds that would eventually create the storms.
After this, the scientists used data assimilation — a statistical method that can paint the most accurate possible picture of current weather conditions in the weather model — by optimising the forecaster's understanding of weather systems.
Upon assimilating the satellite and radar data separately and simultaneously, the team was able to achieve the best results by combining infrared brightness temperature data from the satellite and wind velocity and boundary height (distance of PBL from Earth's surface) observations from the radar.
This technique has shown tremendous promise in improving forecasts of convection initiation, a process that causes warm air near the Earth's surface to rise and form clouds, eventually giving rise to storms.
In a specific case study from May 2018, this method could forecast a thunderstorm several hours before it occurred in the Texas Panhandle, USA.
“This observation combination had not been studied previously and ended up adding significant value to the model forecasts,” said David Stensrud, Eure's advisor and co-author on the study.
While there's scope to explore more cases to refine this approach, the current observation could also be employed to improve future forecasts, especially in light of NOAA's 'Warn-On Forecast' project, which aims to make weather warnings more precise and timely.
"We obviously can't model every molecule in the atmosphere, but we want to get as close as possible," concludes Keenan Eure.
This study was published in the journal Monthly Weather Review and can be accessed here.
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