Author Archives: danaallen

How to improve a climate model: a 24-year journey from observing melt ponds to their inclusion in climate simulations

By: David Schroeder Melt ponds are puddles of water that form on top of sea ice when the snow and ice melts (see Figure). Not all the water drains immediately into the ocean, but it can stay and accumulate on … Continue reading

Posted in Arctic, Climate modelling, Cryosphere, IPCC, Numerical modelling, Polar | Leave a comment

Cycling In All Weathers

By: David Brayshaw In a few weeks’ time, I’ll be taking some time off for an adventure: spending 3-weeks cycling the entire 3,400 km of this year’s Tour de France (TdF) route.  I’ll be with a team riding just a … Continue reading

Posted in Climate Services, Environmental hazards, Seasonal forecasting, subseasonal forecasting | Leave a comment

Flying Through Storms To Understand Their Interaction with Sea Ice: The Arctic Summer-time Cyclones Project and Field Campaign

By: Ambrogio Volonté Arctic cyclones are the leading type of severe weather system affecting the Arctic Ocean and surrounding land in the summer. They can have serious impacts on sea-ice movement, sometimes resulting in ‘Very Rapid Ice Loss Events’, which … Continue reading

Posted in Arctic, Climate, Climate change, Data collection, extratropical cyclones | Leave a comment

Two Flavours of Ocean Temperature Change and the Implication for Reconstructing the History of Ocean Warming

Introducing Excess and Redistributed Temperatures.  By: Quran Wu Monitoring and understanding ocean heat content change is an essential task of climate science because the ocean stores over 90% of extra heat that is trapped in the Earth system. Ocean warming … Continue reading

Posted in Climate, Climate change, Climate modelling, Oceans | Leave a comment

Using Old Ships To Do New Science

By: Praveen Teleti Weather Rescue at Sea: its goals and progress update. Observing the environment around us is fundamental to learning about and understanding the natural world. Before the Renaissance, everyday weather was thought to be works of divine or … Continue reading

Posted in Climate, Data collection, Data rescue, Historical climatology, Reanalyses | Leave a comment

Including Human Behaviour in Models to Understand the Impact of Climate Change on People

By Megan McGrory In 2020 56% of the global population lived in cities and towns, and they accounted for two-thirds of global energy consumption and over 70% of CO2 emissions. The share of the global population living in urban areas … Continue reading

Posted in Climate, Climate change, Climate modelling, Urban meteorology | Leave a comment

Making Flights Smoother, Safer, and Greener

By: Paul Williams Atmospheric turbulence is the leading cause of weather-related injuries to air passengers and flight attendants. Bumpy air is estimated to cost the global aviation sector up to $1bn annually, and evidence suggests that climate change is causing … Continue reading

Posted in aviation, Climate, Environmental hazards, Turbulence | Leave a comment

From Ürümqi to Minneapolis: Clustering City Climates with Self-Organising Maps

By: Niall McCarroll As a Research Software Engineer, my job involves developing, testing and maintaining software that scientists can use to analyse earth observation and climate data.  Recently I’ve been developing some software that can be used to visualise climate … Continue reading

Posted in Climate, Data Visualisation, Machine Learning | Leave a comment

How On Earth Do We Measure Photosynthesis?

By: Natalie Douglas Photosynthesis is a biological process that removes carbon (in the form of carbon dioxide) from the atmosphere and is therefore a key process in determining the amount of climate change. So, how do we measure it so … Continue reading

Posted in Climate, Climate modelling, earth observation | Leave a comment

Using ChatGPT in Atmospheric Science

By: Mark Muetzelfeldt ChatGPT is amazing. Seriously. Go try it: chat.openai.com/chat. So what is it? It is an artificial intelligence language model that has been trained on vast amounts of data, turning this into an internal representation of the structure of … Continue reading

Posted in Academia, Artificial Intelligence, Climate, Students, Teaching & Learning | Leave a comment