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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Research finds new way to identify which El Niño events will have biggest impact on U.S. winter weather

February 7, 2013

El Niño, warmer than average waters in the Eastern equatorial Pacific (shown in orange on the map), affects weather around the world. A new study, just published in the February 2013 issue of the Journal of Climate, describes an atmospheric El Niño signal that is very strongly associated with U.S. winter weather impacts.

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Weather forecasters have long known that El Niño events can throw seasonal climate patterns off kilter, particularly during winter months. Now, new research from NOAA and the University of Washington suggests that a different way to detect El Niño could help forecasters predict the unusual weather it causes.

A network of buoys that spans the Pacific, the TAO-Triton array, observes conditions in the upper ocean and is essential for forecasting El Niño months in advance, and for monitoring it as it grows and decays. A new study, just published in the February issue of the Journal of Climate, describes an atmospheric El Niño signal that is very strongly associated with U.S. winter weather impacts. Ed Harrison, Ph.D. of the NOAA Pacific Marine Environmental Laboratory in Seattle and Andrew Chiodi, Ph.D., of the NOAA Joint Institute for the Study of the Atmosphere and Ocean at the University of Washington, co-authored the paper.

“When it comes to El Niño’s weather impacts, we are always looking for ways to improve our forecasting skill,” said Harrison. “Our goal is to extract the most useful information to predict El Niño seasonal weather anomalies.”

Harrison and Chiodi looked at all El Niño events that were identified by sea surface temperature measurements since 1979. They then examined satellite imagery for these events and found that a subset of the events showed a sharp dip in heat radiating from the tops of deep convective clouds, an indicator known as outgoing long-wave radiation or OLR. When comparing the El Niño events to historical weather records, the scientists found that the El Niño events with drops in OLR were the ones most likely to play havoc with winter weather.

They also found that El Niño events with no corresponding drop in OLR did not produce statistically significant anomalies in weather patterns. The dip in heat from deep convective clouds usually occurred before winter, so the timing of the signal could help forecasters improve winter seasonal outlooks, the scientists said.

“By sorting El Niño events into two categories, one with OLR changes and one without, forecasters may be able to produce winter seasonal outlooks with more confidence than previously thought possible,” Harrison said.

El Niño refers to a warming of waters along the equator in the Eastern Pacific Ocean. Through its influence on the atmosphere, El Niño shifts tropical rainfall patterns which causes further shifts in weather around the globe, including milder winters in western Canada and parts of the northern United States and wetter winters in the some southern states.

Industry sectors from energy and construction to transportation and tourism are keenly interested in how El Niño will affect their costs. El Niño-influenced weather can affect fuel oil demand, travel delays, and retail sales. Better accuracy in El Niño predictions could help industry to prepare for its impacts more efficiently.

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 at social media channels.

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