• Better climate modeling

  Advanced cloud research may be silver lining to climate predictions

• To improve climate prediction, we have to look toward the clouds.
  
  Iowa State climate researcher Xiaoqing Wu, associate professor of geological and atmospheric sciences, is the leader of a project to better understand and improve cloud modeling and general circulation simulations to predict future climate.
  
  The research, he said, will help improve global climate models and create more accurate data for policy makers to use to determine safe levels of greenhouse gasses for the earth.
  
  Wu's research group is funded by a three-year, $335,000 Department of Energy Atmospheric Radiation Measurement program grant.
  
  Cloud systems are an important factor in climate modeling. Clouds (both liquid and ice) and convection (the heat transfer caused by rising warm air) affect air temperature, moisture and wind. Clouds also strongly impact the planet's surface temperatures by blocking the solar radiation.
  
  However, climate researchers have always been hindered by a lack of detailed, long-term cloud data that would lead to more accurate climate predictions.

  Major challenge
  General circulation models are major tools for predicting climate, Wu explained, but they have limitations. Individual clouds, he added, have a spatial scale of less than 10 kilometers. Climate models have data measuring points on a grid, often at 200-kilometer intervals.
  
  "Deriving such formulations for convection and clouds has been a major challenge for the climate modeling community due to the lack of observations of cloud properties," Wu said. "We need to represent the ensemble effect of clouds in terms of temperature, moisture and wind fields in the grid box. This is a difficult process."
  
  Wu uses a cloud-resolving model (CRM) that he helped develop in 1993 when he was a researcher at the National Center for Atmospheric Research in Boulder, Colo, and further improved since coming to Iowa State in 2002.
  
  "CRMs provide a useful tool, which is being widely used by the world's atmospheric scientists, to simulate the ensemble effects of cloud systems under various large-scale conditions and over different climate regions," Wu said.
  
  Wu is evaluating the performance of year-long CRM simulations of cloud systems over the south central United States, a "climatically important" region. He is examining the seasonal variation of cloud and radiative properties and their impact on average temperature and climate variability.
  
  "This should provide a valuable, long-term dataset for understanding the characteristics of convective, cloud and radiative properties and the interaction between these processes in global climate models," Wu said.
  
  "We can also use the CRM to see how clouds varied from spring to summer to fall to winter, not just looking at them for one month. We think this approach is working very well."

  Producing data
  The successful, yearlong integration of the cloud resolving models over the U.S. will support their use to produce long-term data for other important climate regions, including the eastern and western Pacific, China and the Indian Ocean.
  
  "We can actually have the multiple-year cloud dataset over those regions," Wu noted.
  
  Wu became interested in weather when in high school in his native China. The ways rural farmers predicted weather fascinated him. Red sky at sunset, good weather ahead; but red sky at sunrise, take warning, for example.
  
  "I wondered, ‘How did they know that?'" Wu recalled.
  
  He eventually came to UCLA for a Ph.D. and studied under an expert in tropical meteorology and cloud diagnostic studies. Wu knew even then that more datasets were required to accurately represent clouds in climate modeling.
  
  Wu's project has gathered the interest of many climate researchers. "We have demonstrated this approach is working. I'm really positive that this has a great future," he said.
  

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September 8-21, 2008