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October 2015

When the Wind Comes Sweeping Down the Plain

The low-level jet, often rain's windy escort, explained with new modeling techniques

low-level jet storm Kansas
A typical summer storm for the U.S. Great Plains in summer is shown approaching at sunset near Sawyer, Kansas. Storms like these get their moisture from the low-level jet. Photo courtesy of Jacob DeFlitch via the ARM Climate Research Facility website.
zoom Enlarge Image.

Results: Residents of Oklahoma and other plains states are wise to the blustery seasonal force gusting nightly during warm springs and summers, carrying the moisture needed for rain. So emblematic for the region they wrote a song about it, the low-level jet is easy for people to recognize. Still, computer models struggle to capture its complexity. When the models underestimate the amount of water carried in by the jets, they are not good precipitation predictors.

To get more model accuracy, scientists often feed the models specialized datasets called reanalyses that bridge the gaps in measured observations. How well do these sets perform their proxy role? To find out, atmospheric experts at Pacific Northwest National Laboratory compared six reanalyses products against observational data from the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma. The research pinpointed weaknesses that affect the models' ability to accurately predict jet frequency—a key piece of information tied to precipitation. The finding can help farmers, cowhands, and climate researchers alike.

Why It Matters: Low-level jets can quickly ramp up to gale-force levels. And, if the frequency of low-level jets is underestimated, then the amount of moisture they carry will also be miscalculated. This could have implications for farmers watering crops and feeding livestock, or flood control and water resource decisions. The new research provides further insight into how moisture is transported by low-level jets.

For scientists, this research also breaks new ground by evaluating the datasets known as reanalysis products, to find their strengths and weaknesses.

"The various reanalysis products are commonly used to evaluate global simulations, especially when observations are not available," said lead researcher Dr. Larry Berg, PNNL atmospheric scientist. "So we are interested in understanding how closely they mimic observations."

Methods: The PNNL research team evaluated the features of the Southern Great Plains low-level jet above the ARM Climate Research Facility in Oklahoma using six popular reanalysis products:

  • NCEP-Department of Energy Reanalysis 2 (NCEP2)
  • NCEP Climate Forecast System Reanalysis (CFSR)
  • ECMWF Re-Analysis (ERA)-Interim
  • Japanese 25-year Reanalysis (JRA-25)
  • Modern-Era Retrospective Analysis for Research and Applications (MERRA)
  • North American Regional Reanalysis (NARR).

Next, the team evaluated the data using two sets of radiosonde data (see sidebar): the six-week Midlatitude Continental Convective Clouds Experiment (MC3E), and site data from a ten-year period spanning 2001 through 2010. They compared all five reanalysis products to MC3E observational data, and compared the NARR, MERRA, and CFSR only to the ten-year data.

Time evolution of the low-level jet on May 11, 2011. Each panel represents a snapshot in time with an interval of three hours between each plot. Colors indicate the maximum wind speed within the column.

This study is unique because they combined use of the six different reanalysis products, the MC3E data, and long-term ARM radiosonde data sets to understand the hydrological impact of low-level jets over the Great Plains.

While increasing the vertical and horizontal resolution of the models improved prediction of the low-level jets' frequency, the research zeroed in on some shortcomings: the reanalyses tend to overestimate wind speed between certain pressure levels and they place the "nose" of the jet at a higher-than-observed altitude. These shortcomings affected the models' ability to accurately predict the frequency of the jets.

What's Next? Increasing model resolution was a step forward, but the door is open for other factors that may influence frequency. The next steps are to identify the causes of model bias and develop improved reanalysis products that better inform climate models.


Sponsor: This research was supported by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research as part of the Earth System Modeling program, and used data from the ARM Climate Research Facility.

Research Team: Larry Berg, Laura Riihimaki, Yun Qian, Huiping Yan and Maoyi Huang, PNNL

Research Area: Climate & Earth Systems Science

User Facility: ARM Climate Research Facility

Reference: Berg LK, LD Riihimaki, Y Qian, H Yan, and M Huang. 2015. "The Low-Level Jet over the Southern Great Plains Determined from Observations and Reanalysis and Its Impact on Moisture Transport." Journal of Climate 28(17): 6682-6706. DOI: 10.1175/JCLI-D-14-00719.1

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A radiosonde is a meteorological instrument often carried into the atmosphere aboard a weather balloon to measure atmospheric characteristics such as pressure, temperature, relative humidity, and wind speed and direction. The instrument transmits the data to a ground station for weather prediction and research purposes.

In One Sentence: Scientists at Pacific Northwest National Laboratory analyzed the fidelity of reanalyses dataset products to reproduce conditions and characteristics of the low-level jet over the U.S. Southern Great Plains.

In 100 characters: Analyzing dataset fidelity shines light on Great Plains low-level jet's water-carrying ability