Predicting climate: Scientists test periodic-to-decadal conjecture

In new research released in Tellus A, Francois Counillon and co-authors in the Bjerknes Center are testing periodic-to-decadal conjecture.

In the Bjerknes Center, scientists are exploring the opportunity of periodic to decadal climate conjecture. This can be a area still in the infancy, along with a first attempt is made public for that latest Intergovernmental Panel on Global Warming (IPCC) report.

Aside from a couple of isolated regions, conjecture skill was moderate, departing room for improvement. In new research released in Tellus A, periodic-to-decadal conjecture is examined by having an advanced initialisation way in which has shown effective in weather predicting and operational oceanography.

"Regular" climate forecasts are made to represent the persistent change caused by exterior forcings. Such "forecasts" begin with initial problems that are distant from present day climate and therefore neglect to "predict" the entire year-to-year variability and the majority of the decadal variability -- like the pause within the global temperature increase (hiatus) or even the spate of harsh winter within the northern hemisphere. In comparison, weather forecasts depend positioned on the precision of the initial condition because the influence from the exterior forcing is nearly imperceptible.

For periodic-to-decadal time scales both initial condition and also the exterior forcing influence the conjecture. Beginning an environment conjecture from a preliminary condition nearer to the actual weather conditions are therefore essential to yield better conjecture than accounting just for exterior forcing. Within our region of great interest, decadal skill might be accomplished by enhancing the representation from the warmth content transiting in to the Nordic Ocean and as a result is going to influence the precipitation and temperature over Scandinavia.

The technique used to initialise/ correct a dynamical product is known to as data assimilation. It estimations the first condition of the model knowing some sparse findings (a smaller amount than 1% from the sea variables are observed). Rapport between your findings and also the non-observed variables should be found to broaden the corrections.

In addition, the corrections must fulfill the model dynamics to prevent abrupt changes throughout the forecast. The Ensemble Kalman Filter uses statistics from an ensemble of forecasts to estimate the connection between your findings and all sorts of variables for his or her correction. This process is computationally intensive because it requires parallel integrations from the model however it guarantees the relationship evolve using the system, which the corrections fulfill the dynamics from the model.

The Norwegian climate conjecture model (NorCPM) combines the Norwegian Earth System model using the Ensemble Kalman Filter. Over time, we plan to perform retrospective decadal forecasts (hindcasts) during the last century, to check the ability of our bodies on disparate phases from the climate and reveal the relative need for internal and exterior influences on natural climate variability, including the value of feedback systems. Ocean surface temps (SST) would be the only findings readily available for this type of lengthy time period and will also be employed for initialisation.

Our study looks into the possibility abilities of putting together SST only, utilizing an idealised framework, i.e. in which the synthetic option would be obtained from exactly the same model at different occasions. This framework enables a comprehensive validation since the full option would be known and our bodies could be examined from the upper predictive skill (the situation where findings could be available absolutely everywhere). NorCPM shown decadal of a routine for that Atlantic meridional knocking over and warmth content within the Nordic Seas which are near to the model's limit of of a routine. Although these answers are encouraging, the idealised framework assumes the model is ideal minimizing skill is anticipated inside a real framework. This verification is presently ongoing.

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Scientists eye longer-term forecasts of U.S. heat waves

Scientists have fingerprinted a distinctive atmospheric wave pattern high above the Northern Hemisphere that can foreshadow the emergence of summertime heat waves in the United States more than two weeks in advance.

The new research, led by scientists at the National Center for Atmospheric Research (NCAR), could potentially enable forecasts of the likelihood of U.S. heat waves 15-20 days out, giving society more time to prepare for these often-deadly events.

The research team discerned the pattern by analyzing a 12,000-year simulation of the atmosphere over the Northern Hemisphere. During those times when a distinctive "wavenumber-5" pattern emerged, a major summertime heat wave became more likely to subsequently build over the United States.

"It may be useful to monitor the atmosphere, looking for this pattern, if we find that it precedes heat waves in a predictable way," says NCAR scientist Haiyan Teng, the lead author. "This gives us a potential source to predict heat waves beyond the typical range of weather forecasts."

The wavenumber-5 pattern refers to a sequence of alternating high- and low-pressure systems (five of each) that form a ring circling the northern midlatitudes, several miles above the surface. This pattern can lend itself to slow-moving weather features, raising the odds for stagnant conditions often associated with prolonged heat spells.

The study is being published next week in Nature Geoscience. It was funded by the U.S. Department of Energy, NASA, and the National Science Foundation (NSF), which is NCAR's sponsor. NASA scientists helped guide the project and are involved in broader research in this area.

Predicting a lethal event

Heat waves are among the most deadly weather phenomena on Earth. A 2006 heat wave across much of the United States and Canada was blamed for more than 600 deaths in California alone, and a prolonged heat wave in Europe in 2003 may have killed more than 50,000 people.

To see if heat waves can be triggered by certain large-scale atmospheric circulation patterns, the scientists looked at data from relatively modern records dating back to 1948. They focused on summertime events in the United States in which daily temperatures reached the top 2.5 percent of weather readings for that date across roughly 10 percent or more of the contiguous United States. However, since such extremes are rare by definition, the researchers could identify only 17 events that met such criteria -- not enough to tease out a reliable signal amid the noise of other atmospheric behavior.

The group then turned to an idealized simulation of the atmosphere spanning 12,000 years. The simulation had been created a couple of years before with a version of the NCAR-based Community Earth System Model, which is funded by NSF and the Department of Energy.

By analyzing more than 5,900 U.S. heat waves simulated in the computer model, they determined that the heat waves tended to be preceded by a wavenumber-5 pattern. This pattern is not caused by particular oceanic conditions or heating of Earth's surface, but instead arises from naturally varying conditions of the atmosphere. It was associated with an atmospheric phenomenon known as a Rossby wave train that encircles the Northern Hemisphere along the jet stream.

During the 20 days leading up to a heat wave in the model results, the five ridges and five troughs that make up a wavenumber-5 pattern tended to propagate very slowly westward around the globe, moving against the flow of the jet stream itself. Eventually, a high-pressure ridge moved from the North Atlantic into the United States, shutting down rainfall and setting the stage for a heat wave to emerge.

When wavenumber-5 patterns in the model were more amplified, U.S. heat waves became more likely to form 15 days later. In some cases, the probability of a heat wave was more than quadruple what would be expected by chance.

In follow-up work, the research team turned again to actual U.S. heat waves since 1948. They recognized that some historical heat wave events are indeed characterized by a large-scale circulation pattern that indicated a wavenumber-5 event.

Extending forecasts beyond 10 days

The research finding suggests that scientists are making progress on a key meteorological goal: forecasting the likelihood of extreme events more than 10 days in advance. At present, there is very limited skill in such long-term forecasts.

Previous research on extending weather forecasts has focused on conditions in the tropics. For example, scientists have found that El Ni?o and La Ni?a, the periodic warming and cooling of surface waters in the central and eastern tropical Pacific Ocean, are correlated with a higher probability of wet or dry conditions in different regions around the globe. In contrast, the wavenumber-5 pattern does not rely on conditions in the tropics. However, the study does not exclude the possibility that tropical rainfall could act to stimulate or strengthen the pattern.

Now that the new study has connected a planetary wave pattern to a particular type of extreme weather event, Teng and her colleagues will continue searching for other circulation patterns that may presage extreme weather events.

"There may be sources of predictability that we are not yet aware of," she says. "This brings us hope that the likelihood of extreme weather events that are damaging to society can be predicted further in advance."

The University Corporation for Atmospheric Research manages the National Center for Atmospheric Research under sponsorship by the National Science Foundation. Any opinions, findings and conclusions, or recommendations expressed in this release are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Scientists nearing forecasts of long-lived wildfires

Scientists have developed a new computer modeling technique that offers the promise, for the first time, of producing continually updated daylong predictions of wildfire growth throughout the lifetime of long-lived blazes.

The technique, devised by scientists at the National Center for Atmospheric Research (NCAR) and the University of Maryland, combines cutting-edge simulations portraying the interaction of weather and fire behavior with newly available satellite observations of active wildfires. Updated with new observations every 12 hours, the computer model predicts critical details such as the extent of the blaze and changes in its behavior.

The breakthrough is described in a study appearing today in an online issue of Geophysical Research Letters, after first being posted online last month.

"With this technique, we believe it's possible to continually issue good forecasts throughout a fire's lifetime, even if it burns for weeks or months," said NCAR scientist Janice Coen, the lead author and model developer. "This model, which combines interactive weather prediction and wildfire behavior, could greatly improve forecasting -- particularly for large, intense wildfire events where the current prediction tools are weakest."

Firefighters currently use tools that can estimate the speed of the leading edge a fire but are too simple to capture crucial effects caused by the interaction of fire and weather.

The researchers successfully tested the new technique by using it retrospectively on the 2012 Little Bear Fire in New Mexico, which burned for almost three weeks and destroyed more buildings than any other wildfire in the state's history.

The research was funded by NASA, the Federal Emergency Management Agency, and the National Science Foundation, which is NCAR's sponsor.

Sharpening the picture

In order to generate an accurate forecast of a wildfire, scientists need a computer model that can both incorporate current data about the fire and simulate what it will do in the near future.

Over the last decade, Coen has developed a tool, known as the Coupled Atmosphere-Wildland Fire Environment (CAWFE) computer model, that connects how weather drives fires and, in turn, how fires create their own weather. Using CAWFE, she successfully simulated the details of how large fires grew.

But without the most updated data about a fire's current state, CAWFE could not reliably produce a longer-term prediction of an ongoing fire. This is because the accuracy of all fine-scale weather simulations declines significantly after a day or two, thus affecting the simulation of the blaze. An accurate forecast would also have to include updates on the effects of firefighting and of such processes as spotting, in which embers from a fire are lofted in the fire plume and dropped ahead of a fire, igniting new flames.

Until now, the kind of real-time data that would be needed to regularly update the model has not been avaliable. Satellite instruments offered only coarse observations of fires, providing images in which each pixel represented an area a little more than a half mile across (1 kilometer by 1 kilometer). These images might show several places burning, but they could not distinguish the boundaries between burning and non-burning areas, except for the largest wildfires.

To solve the problem, Coen's co-author, Wilfrid Schroeder of the University of Maryland, has produced higher-resolution fire detection data from a new satellite instrument, the Visible Infrared Imaging Radiometer Suite (VIIRS), which is jointly operated by NASA and the National Oceanic and Atmospheric Administration (NOAA). Launched in 2011, this new tool provides coverage of the entire globe at intervals of 12 hours or less, with pixels about 1,200 feet across (375 meters). The higher resolution enabled the two researchers to outline the active fire perimeter in much greater detail.

Coen and Schroeder then fed the VIIRS fire observations into the CAWFE model. By restarting the model every 12 hours with the latest observations of the fire extent -- a process known as cycling -- they could accurately predict the course of the Little Bear fire in 12- to 24-hour increments during five days of the historic blaze. By continuing this way, it would be possible to simulate the entire lifetime of even a very long-lived fire, from ignition to extinction.

"The transformative event has been the arrival of this new satellite data," said Schroeder, a professor of geographical sciences who is also a visiting scientist with NOAA. "The enhanced capability of the VIIRS data favors detection of newly ignited fires before they erupt into major conflagrations. The satellite data has tremendous potential to supplement fire management and decision support systems, sharpening the local, regional, and continental monitoring of wildfires."

Keeping firefighters safe

The researchers said that forecasts using the new technique could be particularly useful in anticipating sudden blowups and shifts in the direction of the flames, such as what happened when 19 firefighters perished in Arizona last summer.

In addition, they could enable decision makers to look at several newly ignited fires and determine which pose the greatest threat.

"Lives and homes are at stake, depending on some of these decisions, and the interaction of fuels, terrain, and changing weather is so complicated that even seasoned managers can't always anticipate rapidly changing conditions," Coen said. "Many people have resigned themselves to believing that wildfires are unpredictable. We're showing that's not true."

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Scientists find large Gulf dead zone, but smaller than predicted

July 29, 2013

Map showing the hypoxia area on the Louisiana Gulf of Mexico shelf in 2013.

Download here (Credit: LUMCON (Rabalais))

NOAA-supported scientists found a large Gulf of Mexico oxygen-free or hypoxic “dead” zone, but not as large as had been predicted. Measuring 5,840 square miles, an area the size of Connecticut, the 2013 Gulf dead zone indicates nutrients from the Mississippi River watershed are continuing to affect the nation’s commercial and recreational marine resources in the Gulf.

“A near-record area was expected because of wet spring conditions in the Mississippi watershed and the resultant high river flows which deliver large amounts of nutrients,” said Nancy Rabalais, Ph.D. executive director of the Louisiana Universities Marine Consortium (LUMCON), who led the July 21-28 survey cruise. “But nature’s wind-mixing events and winds forcing the mass of low oxygen water towards the east resulted in a slightly above average bottom footprint.”

Hypoxia is fueled by nutrient runoff from agricultural and other human activities in the watershed. These nutrients stimulate an overgrowth of algae that sinks, decomposes and consumes most of the oxygen needed to support life. Normally the low or no oxygen area is found closer to the Gulf floor as the decaying algae settle towards the bottom. This year researchers found many areas across the Gulf where oxygen conditions were severely low at the bottom and animals normally found at the seabed were swimming at the surface.

Graph showing historical hypoxia trends.

Download here (Credit: LUMCON (Rabalais))

This is in contrast to 2012, when drought conditions resulted in the fourth smallest dead zones on record, measuring 2,889 square miles, an area slightly larger than Delaware. The largest previous dead zone was in 2002, encompassing 8,481 square miles. The smallest recorded dead zone measured 15 square miles in 1988. The average size of the dead zone over the past five years has been 5,176 square miles, more than twice the 1,900 square mile goal set by the Gulf of Mexico / Mississippi River Watershed Nutrient Task Force in 2001 and reaffirmed in 2008.

On June 18, NOAA-sponsored forecast models developed by Donald Scavia, Ph.D., University of Michigan, and R. Eugene Turner, Ph.D., Louisiana State University,  predicted the Gulf hypoxic zone would range in size from 7,286 to 8,561 square miles.

“NOAA’s investment in the Gulf of Mexico continues to yield results that confirm the complex dynamics of hypoxia and provide managers and the public with accurate scientific information for managing and restoring the nation's valuable coastal resources,” said Robert Magnien, Ph.D., director of NOAA’s Center for Sponsored Coastal Ocean Research. “For those who depend upon and enjoy the abundant natural resources of the Gulf of Mexico, it is imperative that we intensify our efforts to reduce nutrient pollution before the ecosystem degrades any further.”

This annual measurement provides federal and state agencies working on the 2008 Gulf task force implementation actions with the real consequences of inadequate nutrient pollution management. The task force’s actions are set for review this summer.

The hypoxic zone off the coast of Louisiana and Texas forms each summer threatening the ecosystem supporting valuable commercial and recreational Gulf fisheries that in 2011 had a commercial dockside value of $818 million and an estimated 23 million recreational fishing trips. The Gulf task force, in its 2008 report, states that "hypoxia has negative impacts on marine resources." It further states that research on living resources in the Gulf show long term ecological changes in species diversity and a large scale, often rapid change, in the ecosystem's food-web that is both "difficult and impossible to reverse." Additionally, there are numerous annual areas of the Gulf where large scale fish kills occur as a result of hypoxia.

Two surveys conducted in June and early July, one of which was led by a NOAA-supported Texas A&M University team, suggested a large hypoxic zone was forming in the Gulf, though the LUMCON July measurement will be the official one as required of NOAA by the Task Force. NOAA’s National Marine Fisheries Service, in conducting its Southeast Monitoring and Assessment Program groundfish surveys, also found large expanses of hypoxia in June-early July. Texas A&M will be conducting a follow-up cruise in mid-August to provide its final seasonal update.

Visit the Gulf Hypoxia web site for additional graphics and information concerning this summer’s LUMCON research cruise, and previous cruises.

NOAA’s National Ocean Service has been funding monitoring and research for the dead zone in the Gulf of Mexico since 1985 and currently oversees the NGOMEX program, the hypoxia research effort for the northern Gulf which is authorized by the Harmful Algal Bloom and Hypoxia Research and Control Act.

The National Centers for Coastal Ocean Science is the coastal science office for NOAA’s National Ocean Service.

NOAA’s mission is to understand and predict changes in the Earth's environment, from the depths of the ocean to the surface of the sun, and to conserve and manage our coastal and marine resources. Join us on Facebook, Twitter and our other social media channels.

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Scientists a step closer to predicting tornadoes

For decades, meteorologists have been able to forecast the severity of hurricane seasons several months ahead of time. Yet forecasting the likelihood of a bad tornado season has proved a far greater challenge.

By Charlie Riedel, AP

Brenna Burzinski looks through the rubble in her devastated apartment in Joplin, Mo., on May 25.

By Charlie Riedel, AP

Brenna Burzinski looks through the rubble in her devastated apartment in Joplin, Mo., on May 25.

Now, research from scientists at Columbia University's International Research Institute for Climate and Society could eventually lead to the first seasonal tornado outlooks.

"Understanding how climate shapes tornado activity makes forecasts and projections possible, and allows us to look into the past and understand what happened," said Michael Tippett, lead author of a study in February's journal of Geophysical Research Letters.

The need for such data is reinforced by the still-fresh memory of 550 Americans killed by tornadoes last year — coupled with an unusually violent January for twisters.

In the study, Tippett and his team looked at 30 years of past climate data. They used computer models to determine that the two weather factors most tied to active tornado months and seasons were heavy rain from thunderstorms and extreme wind shear (wind blowing from different directions at different layers of the atmosphere).

"If, in March, we can predict average thunderstorm rainfall and wind shear for April, then we can infer April tornado activity," Tippett says.

The method worked for each month except for September and October, and it worked best in June.

This is the first time a forecast of up to a month in advance has been demonstrated, he says.

"A connection between La Niña and spring tornado activity is often mentioned," Tippett says, "but such a connection really has not been demonstrated in the historical data and hasn't been shown to provide a basis for a skillful tornado activity forecast.

"Our work bridges the gap between what the current technology is capable of forecasting (large-scale monthly averages of rainfall and winds) and tornado activity, which the current technology cannot capture," he says.

The research isn't ready for prime time yet, however, so no official forecast will be made for the upcoming season using these methods.

"This is a useful first step," says Harold Brooks of the National Oceanic and Atmospheric Administration, who was not involved in the study. He says it will be helpful to know, for example, that sometime in the last week of April, conditions will be favorable for lots of tornadoes in the eastern USA.

With greater lead time, a state emergency planner "could be better prepared with generators and supplies," Brooks says.

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