New Models Improve Long-Term Grass Pollen Forecasts

More-accurate predictions of the severity of an upcoming grass pollen season based on rainfall and temperature could help allergy sufferers manage their symptoms.

Written byAsher Jones
| 5 min read
grass, poaceae, seasonal allergic rhinitis, hay fever, atmosphere, climate change, modelling, modeling, pollen, aerobiology, allergies, forecasting, season

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Now that spring has arrived in the Northern Hemisphere, many people are celebrating warmer weather and longer days. But for those with hay fever, spring also means itchy eyes, runny noses, headaches, and fatigue. One of the main triggers for seasonal allergic rhinitis, the official name for hay fever, is grass pollen. More pollen in the air usually means more severe hay fever, so accurate pollen predictions could help allergy sufferers to better manage their symptoms.

Although weather apps can predict pollen levels a few days in advance, there aren’t good tools for predicting grass pollen season severity, says Carsten Skjøth, an atmospheric scientist and an aerobiologist at the University of Worcester in the UK. In a study published today (March 26) in Science Advances, Skjøth along with Alexander Kurganskiy, an air pollution modeler at the University of Exeter, and their colleagues describe mathematical models that ...

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