Airborne atmospheric research benefits

Contrails

Work done by scientists in the Meteorological Research Flight (MRF) in the early years found that the humidity of the air around an aircraft is a crucial factor in determining whether a contrail will form, and how long that trail will persist. Understanding this, enabled pilots to plan flights so as to minimise contrail production, which reduced the likelihood of their position being given away while flying over enemy territory.

Gate

In 1974 one of the largest international meteorological field campaigns ever undertaken took place near the west coast of Africa. The GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) involved scientists and research platforms from around the world, including eight aircraft from the USA, two from the USSR and the MRF C-130 Hercules from the UK. The data collected during the GATE field campaign provided an invaluable source of truth for scientists developing computer models of tropical meteorology, enabling forecasts for this region, and hence global forecasts, to be improved.

Clear air turbulence

Understanding what causes this turbulence means that it can be forecast, enabling aircraft to avoid areas where severe clear air turbulence is expected, and making air journeys safer and more comfortable.

Acid rain

During the 1970s, concerns were raised over pollution from the UK causing acid rain in Scandinavia. Researchers from the Central Electricity Research Laboratory worked with MRF to investigate the transport of this pollution across the North Sea. This work found that while the transport of UK pollution was having an impact, pollution from across Europe was responsible for the acid rain. This work led to the implementation of clean air restrictions across Europe, reducing the amount of pollution released into the air throughout the continent.

GULFEX

At the end of the first Gulf War, retreating Iraqi troops set hundreds of Kuwaiti oil fires alight, creating a massive cloud of smoke which at times blocked out the sun over Kuwait. Fears of this cloud of smoke spreading and having worldwide impacts were rife, and the Met Office made use of its NAME (Numerical Atmospheric-dispersion Modelling Environment) dispersion model to predict the spread of the smoke. To back up the model predictions, MRF sent its C-130 Hercules to measure the smoke plume. The observations backed up the model predictions and reassured the UK that while the environmental impacts for Kuwait would be massive, these impacts would remain localised.

Stratocumulus

Stratocumulus cloud (large dark masses of cloud at low level) plays an important role in both weather and climate, by reflecting sunlight back out to space the cloud can produce a cooling effect, and can also make for grey and miserable days for those living under it. Scientists working with MRF, and later with the FAAM aircraft, have been researching the structure of stratocumulus clouds since the 1970s and their work has been used to improve the forecasting of such clouds in weather and climate models.

Volcanic ash

In 2010 the Eyjafjallajökull volcano erupted in Iceland, sending a plume of volcanic ash over UK and European airspace. While dispersion modelling and satellite imagery provided some information about the location of volcanic ash in the atmosphere, airborne measurements using the FAAM BAe-146-301 were made, providing confirmation of the model data, and vastly increasing our understanding of volcanic ash.

Clear-skies microwave

Satellite data has become a vital source of information for weather forecasting, providing observations across the globe. Scientists working with MRF, and later with the FAAM aircraft, have been involved with providing data to calibrate and validate the information from satellite platforms since the 1970s, combining state of the art radiometer and in-situ measurements to build up an accurate picture of what a satellite would observe. This work allows information about temperature, humidity and clouds to be extracted from satellite data, and these additional observations lead to improvements in forecasting.