Schreck C.J.,North Carolina State University |
Cordeira J.M.,EarthRisk Technologies |
Cordeira J.M.,Plymouth State University |
Margolin D.,EarthRisk Technologies
Monthly Weather Review | Year: 2013
Tropical convection from the Madden-Julian oscillation (MJO) excites and amplifies extratropical Rossby waves around the globe. This forcing is reflected in teleconnection patterns like the Pacific-North American (PNA) pattern, and it can ultimately result in temperature anomalies over North America. Previous studies have not explored whether the extratropical response might vary from one MJO event to another. This study proposes a new index, the multivariate PNA(MVP), to identify variations in the extratropical waveguide over the North Pacific and North America that might affect the response to the MJO. The MVP is the first combined EOF of 20-100-day OLR, 850-hPa streamfunction, and 200-hPa streamfunction over the North Pacific and North America. The North American temperature patterns that follow each phase of the MJO change with the sign of the MVP. For example, real-time multivariate MJO (RMM) phase 5 usually leads to warm anomalies over eastern North America. This relationship was only found when the MVP was negative, and it was not associated with El Niño or La Nin̈a. RMM phase 8, on the other hand, usually leads to cold anomalies. Those anomalies only occur if the MVP is positive, which happens somewhat more frequently during La Nin̈a years. Composite analyses based on combinations of the MJO and the MVP show that variability in the Pacific jet and its associated wave breaking play a key role in determining whether and how the MJO affects North American temperatures. © 2013 American Meteorological Society.
Schreck C.J.,North Carolina State University |
Bennett S.,CA Technologies |
Cordeira J.M.,Plymouth State University |
Crouch J.,National Oceanic and Atmospheric Administration |
And 7 more authors.
Bulletin of the American Meteorological Society | Year: 2015
Volatility in the natural gas markets can be linked to large temperature variability over the United States in recent winters. © 2015 American Meteorological Society.
News Article | May 10, 2013
The weather is an unforeseeable, ungovernable force and EarthRisk is using big data to predict it. EarthRisk Technologies has developed a new model for predicting extreme weather events. The model identifies weather patterns based on over 82 billion calculations and 60 years of data. It then compares those patterns to current conditions and uses predictive analytics to predict the weather up to 40 days in advance. The technology is derived from research at the University of California at San Diego’s Scripps Institution of Oceanography. Cofounder and CEO John Plavan said the old standard for weather prediction is built on subjective forecast models that are not accurate beyond a week. “Hundreds of thousands of atmospheric variables are changing constantly around the globe and the old models aren’t robust enough to take these into account,” Plavan said in an exclusive interview with VentureBeat. “If there is a change to the initial conditions, the whole thing breaks down. We use statistical relationships to predict eventual outcomes and this technique is not subject to the same chaos. We are applying analytics to an industry that is begging for reinvention.” EarthRisk has collected data from the U.S. and U.K. governments as well as observational data from thousands of scientists and researchers working in the field and the database is updated every day. EarthRisk’s engine searches for correlations and patterns of “statistical significance” and generates forecast probabilities based on this information. The approach uses the past to predict the future. “Utilities corporations, energy traders, and energy producers are majorly impacted by big temperature changes and spend hundreds of millions of dollars trying to predict them,” Plavan said. “If they know there will be an extreme cold event a month from now, they can use that data to make an actionable decision, and these guys will do anything to gain a small edge.” EarthRisk’s flagship product TempRisk is the first commercial application of this technology and is geared towards the research and energy trading communities. The company has been developing, refining, and testing the technology for a few years and now plans to expand the business dramatically and explore more commercialization opportunities. There could be more consumer-focused applications down the road, like the ability to check weather in a tropical location before booking a vacation.
News Article | July 19, 2011
EarthRisk Technologies is mining years of weather data for profit. The San Diego-based start-up today launched HeatRisk, a Web-based application designed to predict extreme heat events 30 to 40 days out. The target audience is meteorologists who work for energy companies or other organizations which need a long-range forecast to hedge their risk from extreme temperatures. Over time, EarthRisk Technologies intends to design a product aimed at less technical users and investigate whether its research method can be applied to predicting extreme storms, according to President and Chief Science Officer Stephen Bennett. Its first product, released last year, is for analyzing the factors that lead to extreme cold events. More researchers are tapping powerful computers and software able to present big sets of data to address environmental problems, such as air and water quality or extreme weather. EarthRisk Technologies originally began as a research project at the Scripps Institute of Oceanography in San Diego, but company founders saw there was a business opportunity buried in its research. "We realized if we could write a software application around our research, it would increase the value of the underlying research tremendously," said Bennett. "The (corporate sponsors) said if you can put together a good application and continue to do cutting-edge research, we will be the first to sign up." Three years ago, Scripps was approached by energy companies and hedge funds which deal in energy futures to see if there was a way to identify major weather events beyond the National Weather Service forecast. In addition to causing safety hazards, extreme weather throws energy markets out of whack by creating an imbalance between supply and demand. A power generator, for example, could use HeatRisk to prepare for a coming heat wave by purchasing fuel for auxiliary generators to meet higher demand. Having a longer lead time than traditional forecasts gives energy buyers and traders an advantage, explained Bennett. Right now, the people who use the software need to be skilled in meteorology and be comfortable analyzing atmospheric conditions directly. Eventually, the company hopes its software could be used by retailers, farmers, or municipalities which can use long-range forecasts to prepare for extreme temperatures, Bennett said. Dominoes lining up The accuracy of weather forecasting has improved over the past decade from supercomputers and simulation software, but the focus tends to be on shorter-term windows than what EarthRisk is doing, Bennett said. And rather than trying to forecast average temperatures, EarthRisk is seeking the factors that lead to specific extreme temperature events. To build the application, researchers analyzed weather data going back to 1948 to identify the patterns that led up to extreme cold or heat. Each pattern is sort of like a domino and when enough of them line up, the software can help identify the probability of an extreme weather event, Bennett explained. In a recent example, a combination of a large high-pressure system over Scandinavia and a low-pressure system in the Atlantic, followed by another system over the Solomon Islands pointed to a heat spike in the U.S. People can use the analytical application through a Web browser and pay a fee for using it during a season and specific regions. A forecasting application could be ready in about six months, Bennett said. Using software to dodge weather risk is new so it's still not clear there is a strong demand for it. But EarthRisk isn't the only company to use cloud computing and large amounts of data to hedge against extreme weather. Earlier this year, WeatherBill launched a service that gives farmers insurance against the effects of extreme weather by continuously analyzing weather data.
News Article | July 21, 2011
There's no getting around it; the number of extreme weather events has significantly increased over the past few years. Heat waves—along with their accompanying droughts and strains on the electrical grid—are some of the most common extreme weather phenomena. And with $485 billion a year of U.S. economic output affected by the weather, it's important to have a handle on when different regions are going to get hit with record high temperatures. EarthRisk Technologies, a San Diego-based startup, thinks it can predict these events up to 40 days in advance (compared to standard two-week predictions), and potentially help energy companies prepare for a power grid strained by air conditioners. The startup announced this week the release of HeatRisk, a piece of software that analyzes jet stream position, air temperature, thunderstorm activity, pressure patterns, and 60 years worth of weather records to predict the likelihood of a major heat wave. The subscription-based service will likely appeal to financial analysts, city planners, and perhaps most importantly, energy companies. "By delivering reliable projections on the likelihood of a heat wave or extreme cold snap well in advance, energy companies can implement critical planning practices to meet air conditioning and heating demand more efficiently and at a lower cost," explains Stephen Bennett, founder and chief science officer of EarthRisk Technologies, in a statement. And if energy companies know that a heat wave is about to arrive, they can be ready—and possibly prevent crippling power failures. So far, EarthRisk's technology has proven successful. The startup's other product, ColdRisk, accurately predicted over 80% of the severe cold fronts that formed in the Midwest and Eastern U.S. between November 1, 2010 and March 31, 2011 up to 20 days in advance, according to Reuters. HeatRisk also accurately predicted this past June's heat wave on the East Coast. The software is still complex enough that it can only be used by skilled meteorologists, so don't think about using HeatRisk to plan your next summer vacation quite yet. But if your power company is using the software, perhaps your power won't go out the next time you're huddled next to the air conditioner in 110 degree heat.
News Article | February 9, 2013
Punxsutawney Phil didn’t see it coming, but this weekend’s New England blizzard is actually a triumph for modern weather forecasting. Specifically, it’s a triumph for numerical weather prediction models—the primary method used to forecast the weather one to two weeks in advance. These computer-generated simulations are run primarily by large governmental agencies. The National Center for Environmental Prediction (NCEP) in the United States and the European Center for Medium-range Weather Forecasting (ECMWF) in the United Kingdom are the two primary global centers for numerical weather prediction. Both Superstorm Sandy and what The Weather Channel is now calling Winterstorm Nemo were well forecast by the ECMWF several days before they occurred. Meteorologists have been keenly watching Nemo with every new run of NCEP’s Global Forecast System (GFS) and the ECMWF forecasts (there are twelve new model runs each day), and many have been calling for a “storm of historic proportions” since early in the week. Many people are discussing the similarities between this storm and Superstorm Sandy. Why is this happening? Is it just a coincidence? As a meteorologist, I must say that Sandy and Nemo are not physically or dynamically connected. The ingredients that produced Sandy are entirely independent of those leading to Nemo. With that said, climate science has produced a volume of robust research over the past five to 10 years suggesting that extreme weather events like Sandy and Nemo might become more frequent and/or more intense in the decades ahead. This research suggests the changing global climate is likely to change how weather patterns evolve. It’s controversial, but certainly possible, that Sandy and Nemo could be symptoms of a broader global condition. For residents of New Jersey and Long Island, however, it’s just bad luck. Two super storms within a few months of one another, following very similar paths is just like hitting blackjack in the casino on two hands in a row. Sure it’s possible—but it’s unlikely. On the other hand, play long enough and you’re sure to see it happen. At EarthRisk Technologies, a San Diego startup, we’re using “big data” analytics and statistical and empirical techniques to forecast beyond the limits of reliable numerical weather prediction. TempRisk, our company’s flagship product, uses more than 60 years of global weather data, along with pattern recognition algorithms and current observational data to objectively quantify the risk for extreme temperature events—by as many as 40 days in advance. Our goal is to provide ample notice for businesses to prepare for extreme cold that often accompanies storms like Nemo. Xconomy explained the potential commercial value of such long-range weather forecasts last year. More recently, EarthRisk partnered with scientists at the University at Albany in New York to develop a new approach to long-term forecasting that strives to quantify how energetic the global atmosphere may be at any point in time. This new system is based on something called the Global Wind Oscillation (GWO) index. The GWO is an integrated measure of global atmospheric variability, which is usually associated with the position of jet streams around the globe. At times, this variability can lead to episodes of extreme weather and rapidly changing weather patterns. Developed by Dr. Klaus Weickmann and Ed Berry in 2009 while both were scientists at the National Oceanic and Atmospheric Administration (NOAA), the GWO index identifies conditions that could lead to outbreaks of anomalous cold weather in the big population centers of the U.S. and Europe. Conversely, other GWO variations can lead to extreme periods of warm weather. EarthRisk and the University at Albany are working together to develop algorithms that forecast the GWO. Ph.D. student Nick Schiraldi developed the process under the direction of Professor Paul Roundy and EarthRisk’s David Margolin. The system currently ingests data from NCEP’s GFS. As the system matures, we plan to introduce other inputs, such as the ECMWF. So were we able to use the GWO index to forecast Nemo? Not directly. The GWO Index was in what we’d call a “breakout pattern” during the latter half of January. This breakout told us to be alert for … Next Page » Stephen Bennett, J.D., is a founding partner and the chief science and products officer for San Diego-based EarthRisk Technologies. Prior to founding EarthRisk, Steve spent three years at the Scripps Institution of Oceanography at UC San Diego, forging ties between earth systems research and energy, insurance, and financial firms. He has been a meteorologist since 1995. Follow @
News Article | June 2, 2011
Approximately 24 minutes. That's roughly the amount of time that the residents of Joplin, Mo., had to prepare for the oncoming tornado that ripped through the town. Tornado Alley residents are used to the sirens, I suppose, but I'm sure that someone in my own town would react totally differently. I mean, I wonder how much time the folks in Springfield, Mass., had this week when a much smaller tornado touched down in Massachusetts. Who expects a tornado in Massachusetts? Yet, extreme weather is apparently something that Americans need to think about living with. It even made the cover of Newsweek, which has penned an article about our need to adapt to a "warmer, wilder world." I'm sure that article will prompt a whole flurry of teeth-gnashing about the myths of climate change. But, fact is, we humans are subject to the whims of the weather and we need to get better about knowing what it might or might not do. So it is fitting that Earth Networks has just announced new forecasting technology that it hopes with provide us with more advanced notice of major heat waves and cold snaps. (Although not necessarily the sorts of violent storms that have taken such a dreadful human and economic toll this year.) The new technology, called TempRisk, is made possible through a collaboration between Earth Networks (the developer of the WeatherBug service) and EarthRisk Technologies, an analysis company born out of the Scripps Institution of Oceanography in San Diego. The application is focused on energy companies and utilities that could use the information to help better manage energy resources. In the press release for the service, EarthRisk Founder and CEO Stephen Bennett noted: For example, the companies said that TempRisk predicted the record cold-air mass affecting more than 80 million Americans in December 2010 about 20 days closer to its arrival. You may be a skeptic, as I am, about the accuracy of forecasting services, but eventually the science will get better and Earth Networks is definitely a company to watch in this space. I wrote four months back about its monitoring networks, which it will use to measure the affects of climate change. The latest partner in that rather ambitious project is the National Institute of Standards and Technologies (NIST). NIST is interested in much of the data that Earth Networks is gathering; the two will collaborate on measurement and observations of carbon dioxide and methane trace gases on a "regional-to-local scale." Here's the rationale, as explained by James Whetstone, special assistant to the director, Greenhouse Gases, NIST: "NIST is developing new tools and capabilities to measure the amount of greenhouse gases in the atmosphere, to determine their movement through it both locally and regionally, to attribute emissions to sources, and to assess the portion that is man-made. By collaborating with Earth Networks in this research effort, NIST can take advantage of private sector capabilities and expertise to gain a better understanding and evaluate the certainty of the measurements, models and data derived from a geographically dense network of greenhouse gas observing stations."