From dusk till dawn: The role of nocturnal low level jets in weather forecasting
Published
16 May 2025
Author
David Crowhurst - Assistant Forecaster
Nocturnal low level jets (NLLJs) can significantly affect local weather conditions in many parts of the world, posing risks to the safety and efficiency of client operations. That’s why accurately predicting these strong, low-altitude winds is integral to our weather forecasting remit.
Understanding NLLJs and their disruptive power
NLLJs are fast moving winds that occur at low levels of the atmosphere during the night. These jets can significantly influence weather conditions when they break down, generating downdrafts that disrupt the typical pattern of surface winds. These downdrafts can also trigger the emission of large quantities of dust, which can significantly impact client operations. That’s why it’s crucial to understand and accurately forecast them.
Vertical profile of a typical NLLJ, showing a peak in wind speed around 1000 m above the surface at approximately 06:00 UTC
Worldwide reach
These fast-moving ribbons of air at low altitudes have been reported in many geographic regions at certain times of year. In Africa, for example, the weather conditions are favourable for the formation of NLLJs between late November and mid-March; and in the USA’s Great Plains it’s during the spring and summer.
The science behind NLLJ formation
NLLJs form due to a combination of atmospheric conditions, such as dry air moving into an area. For example, the cool, dry Harmattan wind in West Africa brings dry air from the Central Sahara, reducing humidity. This means that there are fewer water molecules to absorb heat from the surface, leading to faster-than-usual drops in overnight air temperature. This increases the pressure gradient in the lower atmosphere, which in turn increases wind speeds and leads to the formation of NLLJs.
Bridging the gap between models and expertise
When forecasters rely solely on the output of forecast models, the risk of overlooking these jets can be high.
There’s a very simple explanation. NLLJs are small-scale, complex weather phenomena, but forecast models typically have a relatively coarse resolution, which prevents them from capturing the development of NLLJs and predicting their impacts.
However, our weather forecasting team is challenging the trend. By drawing from their knowledge and practical experience, combined with outputs from observations and models, our forecasters can apply their expertise to make informed decisions that add value, even if the models fail to capture the feature in question.
GFS weather forecast model data from 6 February 2024 over West and Central Africa, displaying NLLJ presence in the Niger Delta around 1000 m above the surface around 06:00 UTC, with strong 25-30 knot winds
The impact of NLLJs
The morning breakdown of NLLJs and subsequent increase in surface wind speed can cause huge quantities of dust to be lifted from the ground. This happens when the wind reaches a critical speed, capable of picking up loose particles. Once airborne, the particles can be transported over long distances. In some West African countries, the emissions are so extensive that locals refer to this effect as ‘Harmattan haze’.
The haze is rather like a heavy, extremely dry fog which impedes visibility. Its effects are far-reaching. The fine dust poses a serious health risk, especially to the respiratory system. Airlines face financial losses due to cancelled and diverted flights. And when the dust finally settles, it can cause significant crop damage.
Expert intervention: A case study of NLLJ prediction in the Niger Delta
In February 2024, our forecaster noticed a pattern in the Niger Delta: calm overnight winds that were escalating each day between 09:00 and 12:00. The forecaster recognised that these windspeeds were typical of NLLJ activity.
Dry Harmattan conditions were expected to continue. With this in mind – and despite the absence of the morning wind speed peaks in the model output – our forecaster manually adjusted their predictions for the next few days to reflect the anticipated continuation of the jet breakdown each day.
We compared the subsequent observations with the manually adjusted forecast and were delighted to see that the NLLJ cycle had indeed continued. This example highlights the added value that informed human intervention can provide for our clients, above and beyond the limitations of weather forecast models.
Surface weather station data from Owerri in the Niger Delta, obtained in early February 2024. The data shows calm overnight surface winds followed by peaks in wind speed between 09:00 and 12:00 UTC each day as the NLLJS higher up in the atmosphere break down, transferring momentum to the surface
An early warning success in North Africa
On the morning of 23 January 2024, the breakdown of NLLJs triggered powerful surface winds that lifted huge quantities of dust into the atmosphere in Central Algeria.
Weather forecast models showed that easterly winds were expected to continue, so our forecaster issued an early warning for dust for Senegal. The warning was based on the anticipation of westward advection of dust, even though none of the dust forecast models picked this up. Our predictions proved to be accurate: the dust plume was dispersed to Senegal, where a significant drop in visibility was recorded in station observations the following day at Dakar Airport.
Your partner in safety
The accurate prediction of NLLJs is essential for ensuring the safety and efficiency of client operations. By combining advanced forecasting models with expert human intervention, we can provide reliable and actionable insights that help mitigate the risks associated with these powerful atmospheric phenomena. Our commitment to understanding and forecasting NLLJs not only enhances operational safety but also supports our clients in navigating the challenges posed by these unique weather events.
Meteosat dust imagery (09:00 UTC, 23 January 2024) showing the initial dust plume activation resulting from the NLLJ breakdown. Copyright 2024 © EUMETSAT
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Weather Forecasting
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