New insights into predicting future droughts in California: Natural cycles, sea surface temperatures found to be main drivers in ongoing event

According to a new NOAA-sponsored study, natural oceanic and atmospheric patterns are the primary drivers behind California's ongoing drought. A high pressure ridge off the West Coast (typical of historic droughts) prevailed for three winters, blocking important wet season storms, with ocean surface temperature patterns making such a ridge much more likely. Typically, the winter season in California provides the state with a majority of its annual snow and rainfall that replenish water supplies for communities and ecosystems.

Further studies on these oceanic conditions and their effect on California's climate may lead to advances in drought early warning that can help water managers and major industries better prepare for lengthy dry spells in the future.

"It's important to note that California's drought, while extreme, is not an uncommon occurrence for the state. In fact, multi-year droughts appear regularly in the state's climate record, and it's a safe bet that a similar event will happen again. Thus, preparedness is key," said Richard Seager, report lead author and professor with Columbia University's Lamont Doherty Earth Observatory.

This report builds on earlier studies, published in September in the Bulletin of the American Meteorological Society, which found no conclusive evidence linking human-caused climate change and the California drought. The current study notes that the atmospheric ridge over the North Pacific, which has resulted in decreased rain and snowfall since 2011, is almost opposite to what models project to result from human-induced climate change. The report illustrates that mid-winter precipitation is actually projected to increase due to human-induced climate change over most of the state, though warming temperatures may sap much of those benefits for water resources overall, while only spring precipitation is projected to decrease.

The report makes clear that to provide improved drought forecasts for California, scientists will need to fully understand the links between sea surface temperature variations and winter precipitation over the state, discover how these ocean variations are generated, and better characterize their predictability.

This report contributes to a growing field of science-climate attribution-where teams of scientists aim to identify the sources of observed climate and weather patterns.

"There is immense value in examining the causes of this drought from multiple scientific viewpoints," said Marty Hoerling, report co-author and researcher with NOAA's Earth System Research Laboratory. "It's paramount that we use our collective ability to provide communities and businesses with the environmental intelligence they need to make decisions concerning water resources, which are becoming increasingly strained."

To view the report, visit:?http://cpo.noaa.gov/MAPP/californiadroughtreport.

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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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Raindrop research dials in satellite predicting precision

Calling within the precision of satellite weather predicting may be the goal behind research into raindrop shape and size being carried out in the College of Alabama in Huntsville with a UAH doctorate student who's also an atmospheric researcher within the NASA Paths Intern Employment Program.

Patrick Gatlin states his work calculating the dimensions of raindrops using ground instruments offers an precision baseline that's then scaly as much as ground radar after which to satellite dimensions. He's co-author of the paper around the subject.

"That's truly the whole reason for calculating raindrops, is perfect for remote realizing reasons," Gatlin states. Scaling up precision from the small sensor on the floor to large sections of the world being observed from space requires very precisely adjusted instruments. "Our capability to properly illustrate rain fall utilizing a sensor wide is carefully associated with understanding how precipitation varies, right lower towards the individual raindrop and snowflake size."

Perfecting ground-level instrument findings, increasing the size of individuals to encompass ground-based radar after which going even bigger to build up accurate satellite calculating instruments is the easiest method to reduce error because the area under observation increases. "Before we invest in most this satellite instrumentation," Gatlin states, "let us make certain we have first got it right."

A coming large part of scaling up precipitation predicting is NASA's planned launch of their Global Precipitation Measurement (GPM) satellite toward the finish of Feb. UAH is really a mission contractor, headed in the college by Dr. Ray Carey, an connect professor of atmospheric science, and including UAH Earth System Science Center research researcher Matt Wingo, who's dealing with NASA in their flight facility in Wallops Island, Veterans administration.

"UAH designed the woking platform for a few of the ground-based instruments which will validate the data in the satellite," states Gatlin.

Transporting a sophisticated radar/radiometer system to determine precipitation from space, the GPM may be the core of the items is a global network of calculating satellites which will provide next-generation global findings of snow and rain. It'll function as a reference standard to unify precipitation dimensions from the constellation of research and operational satellites.

Through enhanced dimensions of precipitation globally, the GPM mission will assist you to advance knowledge of Earth's water and cycle, improve predicting of utmost occasions that create natural hazards and problems, and extend current abilities in making use of accurate and timely precipitation information.

In the own research, Gatlin has ranged from Iowa and Oklahoma to Canada, Finland, Italia and France. Instead of raindrops, the Canadian research is built to collect snowflake images to be able to enhance the precision of calculating products for snowfall.

In every locale, a built-in network of ground-level calculating products happen to be used, such as the Parsivel2, a disdrometer that measures the particle size and velocity of raindrops falling via a laser. Also being used are a couple of-dimensional video disdrometers, designed to use two video angles to produce 2-D pictures which allow resolution of raindrop shapes. A relevant video disdrometer on loan from frequent research collaborator Colorado Condition College is situated around the UAH campus behind Cramer Hall.

Throughout a area study, the instruments on the floor take dimensions while an airplane flies with the clouds to gather actual raindrop information and the other flies high over the clouds with remote realizing equipment to imitate satellite radar recognition. Is a result of all of the measurement techniques are in comparison.

Enhanced satellite-based precipitation dimensions will improve both rain fall and snowfall forecasts on the global scale, Gatlin states. "I will be calculating snow and rain in certain places that we have never measured it before." The opportunity to better measure raindrop size may also have effect on tornados predicting, as small raindrops result in greater evaporation rates which have been correlated with bigger and much more powerful microbursts by UAH's Dr. Kevin Knupp yet others.

Gatlin is going to finish off a worldwide study focusing just on large raindrops 5 millimeters in dimensions and bigger. These drops take time and effort to capture within the small calculating area given by calculating instruments, and thus their observation is rare. Gatlin states from 224 million drops he's investigated, only 8,000 happen to be 5 mm or bigger.

"Despite the fact that large raindrops might have the finest effect on radar dimensions, we do not have advisable of the concentration," he states. "What I have been doing is getting together all of the raindrop data bases which have collected various rain fall data utilizing the same techniques."

Oddly enough, while Sumatra supports the recognition of getting the finest quantity of large drops overall, the biggest drop collected in the study fell via a calculating device in the UAH campus. It measured 9.1 mm and was created inside a hailstorm whenever a falling bit of hail melted before landing.

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Best weather predicting models examined: Which best predicted September 2013 Colorado surges?

Two College of Iowa scientists lately examined ale the earth's innovative weather predicting models to calculate the Sept. 9-16, 2013 extreme rain fall that triggered severe flooding in Boulder, Colo.

The outcomes, released within the December 2013 problem from the journal Geophysical Research Letters, indicated the predicting models generally carried out well, but additionally left room for improvement.

David Lavers and Gabriele Villarini, scientists at IIHR -- Hydroscience and Engineering, a UI research facility, examined rain fall predictions from eight different global statistical weather conjecture (NWP) models.

Throughout September 2013, Boulder County and surrounding areas experienced severe flooding and high rain leading to deaths, losing houses and companies, and also the promise of a significant disaster.

Following the storms had gone away, Lavers and Villarini made the decision to look at how good a few of the leading NWP models tried. Like a constantly enhancing science, NWP involves integrating current climate conditions through mathematical types of the climate-sea system to forecast future weather. For his or her study, the scientists selected the particular rain fall predictions produced by eight condition-of-the-art global NWP models for that duration of the Colorado surges.

"In an prime position time for you to the big event, the rain fall predictions unsuccessful to capture the persistent character from the event's rain fall," states Lavers, corresponding author as well as an IIHR postdoctoral investigator. "However, the rain fall predictions from Sept. 9 (the very first day from the event) did provide guidance showing a substantial duration of rain fall in Colorado."

"Overall, these models tended to underestimate rain fall amounts and placed the rain fall within the wrong area, despite the fact that they provided a sign that a time of heavy rain fall would affect areas of Colorado," states Gabriele Villarini, study co-author, assistant professor within the UI College of Engineering Department of Civil and Environment Engineering and assistant research engineer at IIHR.

Within their study, Lavers and Villarini used a relatively coarse (getting a comparatively low quantity of pixels) global model output. The UI scientists stress that greater spatial resolution NWP models will probably have taken the rain fall to some greater extent.

States Lavers: "It's wished the ongoing growth and development of finer resolution NWP appliances resolve the complex atmospheric motions in mountainous terrain, like the Rocky Mountain tops, will have the ability to enhance the predicting abilities of these extreme rain fall occasions."

The paper is formally entitled: "Were global statistical weather conjecture systems able to predicting the ultimate Colorado rain fall of 9-16 September 2013?"

The study was based on IIHR, the Iowa Ton Center, and also the U.S. Military Corps of Engineers Institute for Water Assets.

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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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