Things to Do in L.A. Tap to enable a layout that focuses on the article. Chance of more showers in L.A., with a new storm set to hit Thursday A driver navigates a flooded street during a storm Monday in Santa Barbara. This is read by an automated voice. Please report any issues or inconsistencies here . Showers could linger in Los Angeles on Tuesday following four straight days of rain -- and even more rain is likely on Thursday and Friday.

Power traders are fueling a boom in weather data, which helps them to anticipate sudden price swings. Weather forecasters are finding a lucrative niche in Japan's power-trading boom, selling hyper-specialized data to firms seeking an edge in one of the world's most volatile electricity markets. Weathernews is among a handful of companies cashing in on demand for meteorological data. The Tokyo-listed company's shares have surged 50% in the last year as investors bet on its expanded use of artificial intelligence, among other factors. The firm says it's supplying -- or is in talks to provide -- data to several dozen power traders, about a third of which are based outside Japan.

Weather companies want to do their best so that consumers and businesses can have reliable forecasts – not just for the day but in advance of it. Accuracy matters to weather services such as the Weather Channel and AccuWeather and predictive analytics, along with Data Science, is allowing them to get more precise weather reports than ever before. We all like to discuss what is going on outside, and we want to know if enough snow is expected for good skiing on an upcoming vacation, whether it will be pouring on a special occasion, or if the expectation of heavy storms with high winds requires a business to activate disaster recovery plans. In fact, a multi-year study of forecast accuracy – Analysis of One- to Five-Day-Out Global Temperature, Probability of Precipitation and Wind Speed Forecasts – found that AccuWeather was the most accurate provider for wind and precipitation forecasts and was a co-leader in accuracy for temperature forecasts. For temperature forecasts, AccuWeather was the most accurate for high temperature forecasts, while The Weather Channel was the most accurate for low temperature forecasts.

Amy McGovern is a Lloyd G. and Joyce Austin Presidential Professor in the School of Computer Science and an Adjunct Professor in the School of Meteorology at the University of Oklahoma. She has been leading the development of AI/ML for weather applications for 15 years. As climate change affects weather patterns and sea levels rise, the world's need for accurate, usable predictions of weather and ocean and their impacts has never been greater. At the same time, the quantity and quality of Earth observation and modeling systems are increasing dramatically, offering a deluge of data so rich that only automated intelligent systems can fully exploit it. In this talk, I will discuss our approach to developing trustworthy AI methods for environmental science.

Mixing artificial intelligence with climate science helps researchers to identify previously unknown atmospheric processes and rank climate models. Many of the latest climate models seek to increase the detail in simulations of cloud structure. As Earth-observing satellites become more plentiful and climate models more powerful, researchers who study global warming are facing a deluge of data. Some are now turning to the latest trend in artificial intelligence (AI) to help trawl through all the information, in the hope of discovering new climate patterns and improving forecasts. "Climate is now a data problem," says Claire Monteleoni, a computer scientist at George Washington University in Washington DC who has helped to pioneer the marriage of machine-learning techniques with climate science.

As Earth-observing satellites become more plentiful and climate models more powerful, researchers who study global warming are facing a deluge of data. Some are now turning to the latest trend in artificial intelligence (AI) to help trawl through all the information, in the hope of discovering new climate patterns and improving forecasts. "Climate is now a data problem," says Claire Monteleoni, a computer scientist at George Washington University in Washington DC who has helped to pioneer the marriage of machine-learning techniques with climate science. In machine learning, AI systems improve in performance as the amount of data that they analyse grows. This approach is a natural fit for climate science: a single run of a high-resolution climate model can produce a petabyte of data, and the archive of climate data maintained by the UK Met Office, the national weather service, now holds about 45 petabytes of information--and adds 0.085 petabytes a day.

It's now a hired gun for thousands of companies in at least 20 industries. David Kenny took the helm of IBM's Watson Group ibm in February, after Big Blue acquired The Weather Company, where Kenny had served as CEO. In the months since then, the Watson business has grown dramatically, with well over 100,000 developers worldwide now working with more than three dozen Watson application program interfaces (APIs). Fortune Deputy Editor Clifton Leaf caught up with Kenny in mid-October, when IBM Watson's General Manager was in San Francisco, getting ready to open Watson West--the AI system's newest business outpost--and to launch the company's second World of Watson conference, a gathering of its burgeoning ecosystem of partners and users, in Las Vegas on Oct. 24. KENNY: Deep learning is a subset of machine learning, which essentially is a set of algorithms. Deep-learning uses more advanced things like convolutional neural networks, which basically means you can look at things more deeply into more layers. Machine learning could work, for example, when it came to reading text.