Amazon Prime Day is live. See the best deals HERE. Weather models still struggle to parse the millions of datapoints involved in precipitation prediction. Breakthroughs, discoveries, and DIY tips sent every weekday. Most of us generally think of precipitation in terms of three varieties: rain, snow, and sleet .

Recent reports from the Intergovernmental Panel on Climate Change (IPCC) show that climate change is affecting every region of our planet and that some of the changes -- such as rising temperatures and sea levels -- can only be arrested, but are irreversible. Part of the problem stems from how complex an issue climate change is. It has scientific and economic elements and sociopolitical and ethical ones, and it requires cooperation on a scale hitherto unseen. Halting climate change and responding to the effects of the damage already wrought requires two approaches. The first is mitigation, namely trying to remove carbon dioxide from the atmosphere while reducing emissions.

Climate scientists at Agriculture Canada labs have been developing an artificial intelligence program over the past couple of years. They can now apply their AI program to real-world conditions as severe drought continues to plague parts of the Prairies and Great Plains states. Drought monitor programs have been around for decades, but they only provide current weather events and conditions. Trevor Hadwen, a climate specialist at Agriculture Canada's research lab, said their program, called Drought Outlook, is designed to forecast drought conditions and look 30 days into the future.

They can now apply their AI program to real-world conditions as severe drought continues to plague parts of the Prairies and Great Plains states.

Recently, a friend sent me a Wired article entitled "The Power and Paradox of Bad Software". The short piece, written by Paul Ford, discusses the idea that the software industry might be too obsessed with creating better and better tools for itself while neglecting mundane software such as resource scheduling systems or online library catalogs. The author claims that the winners of the bad software lottery are the computational scientists that develop our climate models. Since climate change might be one of the biggest problems for the next generation, some might find it a bit worrying if one of our best tools for examining climate change was written with "bad software". In this post, I discuss the question of wether climate scientists lost the "bad software sweepstakes". I'll cover the basics of climate models, what software is commonly used in climate modeling and why, and what alternative software exists. Best I can tell, the bad software sweepstakes has been won (or lost) by climate change folks.

Seaborne robots have made a startling discovery beneath a 20-mile glacier in Alaska. The technology found the massive rivers of ice may be melting under the LeConte Glacier much faster than previously thought. Scientists programmed autonomous kayaks to swim near the icy cliffs of the glacier to measure the'ambient meltwater intrusions', which shows how much fresh water is flowing into the ocean from underneath the glacier. The study found ambient melting was 100 times higher than models had estimated. This is the first time experts have been able to analyze plumes of meltwater - the water released when snow or ice melts, where glaciers meet the ocean- because the feat is far too dangerous for ships due to falling ice of slabs from the glacier.

To predict the impacts of human emissions, researchers need a complete picture of the atmosphere's methane cycle. They need to know the size of the inputs -- both natural and human -- as well as the outputs. They also need to know how long methane resides in the atmosphere. To help develop this understanding, Tom Weber, an assistant professor of earth and environmental sciences at the University of Rochester; undergraduate researcher Nicola Wiseman '18, now a graduate student at the University of California, Irvine; and their colleague Annette Kock at the GEOMAR Helmholtz Centre for Ocean Research in Germany, used data science to determine how much methane is emitted from the ocean into the atmosphere each year. Their results, published in the journal Nature Communications, fill a longstanding gap in methane cycle research and will help climate scientists better assess the extent of human perturbations.

The dreaded El Niño strikes the globe every 2 to 7 years. As warm waters in the tropical Pacific Ocean shift eastward and trade winds weaken, the weather pattern ripples through the atmosphere, causing drought in southern Africa, wildfires in South America, and flooding on North America's Pacific coast. Climate scientists have struggled to predict El Niño events more than 1 year in advance, but artificial intelligence (AI) can now extend forecasts to 18 months, according to a new study. The work could help people in threatened regions better prepare for droughts and floods, for example by choosing which crops to plant, says William Hsieh, a retired climate scientist in Victoria, Canada, who worked on early El Niño forecasts but who was not involved in the current study. Longer forecasts could have "large economic benefits," he says.

Sometimes it seems the clouds over climate science just won't lift. Computer models of Earth's climate have multiplied in number, complexity, and computational power, yet they remain unable to answer more precisely some of the questions most on the public's mind: How high must we build sea walls to last until 2100? How bad will heat waves get in the next decade? What will Arctic shipping routes look like in 2030? Climate models all agree that global temperatures will continue to rise in response to humanity's greenhouse gas emissions, but uncertainties stubbornly persist over how quickly that will happen and how high temperatures will go. Tapio Schneider, a German-born climate dynamicist at the California Institute of Technology (Caltech) in Pasadena, believes climate science can do better. Later this summer, an academic consortium led by Schneider and backed by prominent technology philanthropists, including former Google CEO Eric Schmidt and Microsoft co-founder Paul Allen, will launch an ambitious project to create a new climate model.

In April 2018, the Nobel Prize Inspiration Initiative and 3M hosted the lecture, Climate Change: Science and Policy with Dr. Mario Molina. Molina won the Nobel Prize for Chemistry for his scientific discovery of the chemistry of the stratospheric ozone layer and its susceptibility to human-made activities. He co-authored research in 1974 in Nature magazine on the threat to the ozone layer from chlorofluorocarbon (CFC) gasses being used in spray cans. Molina has also served on the United States President's Council of Advisors on Science and Technology from 1994 to 2000 and again in 2010-2016. "Science doesn't tell you what to do. Science isn't either good or bad so you can not give Nobel prizes in science to good people, you do that in principle for the science," said Molina.