Military Conflict Accelerates Climate Emergency

Military Conflict Accelerates Climate Emergency

The climate cost of the first two years of Russia’s war on Ukraine was greater than the annual greenhouse gas emissions generated individually by 175 countries, exacerbating the global climate emergency in addition to the mounting death toll and widespread destruction. The conflict has generated at least 175 million tons of GHG emissions including carbon dioxide, nitrous oxide, and hexafluoride, the most potent of all GHGs. Direct warfare, landscape fires, rerouted flights, forced migration, and leaks caused by military attacks on fossil fuel infrastructure, and future carbon costs for reconstruction all contributed. The UN general assembly thinks Russia should pay for the costs of climate emissions, which could come out to around $185 per ton of GHG emissions.

Nina Lakhani, The Guardian

Goodbye El Niño!

After a year of dominance, El Niño is officially over. El Niño likely contributed to many months of record-high global ocean and air temperatures, extreme heat stress to coral reefs, drought in the Amazon, precipitation extremes in Africa, low ice cover on the Great Lakes, and more. Recent observations show that ocean surface temperatures are close to average, meaning ENSO neutral conditions are now present. But it may not last long. NOAA forecasters predict that La Niña will take hold by July-September. If that pans out, it would be around in time to influence the peak of Atlantic hurricane season, and would likely stick around for winter. There have only been 10 times on record where ENSO flipped from El Niño to La Niña within a year. Historically, strong El Niños like we just experienced have evolved into strong La Niñas 4 out of 6 times. However, the strongest El Niño of all time led to the weakest La Niña of all time, so experts say it is hard to draw any conclusions from this small sample size.

Rebecca Lindsey, NOAA

New Method for Climate Modeling

Climate models are a key technology in predicting the impacts of climate change. Climate model simulations help scientists and policymakers estimate conditions like sea level rise, flooding, and rising temperatures, and make decisions about how to respond. Current climate models struggle to provide this information in a timely manner, and at a smaller scale that would be useful to cities. A new paper reveals a method to leverage machine learning to utilize these benefits, while reducing costs and time. Using adversarial learning, simplifying the physics, and supplementing it with statistics from historical data, they were able to generate the results they needed. The current model only looks at extreme precipitation, but training it to examine other events like tropical storms, winds, and temperature is the next step of the project.

Paige Colley, Phys.org