CSI: Climate Scene Investigation
Team investigates sources of unusual climate and weather patterns
Katy Human, Fall 2008
On television's CSI, Gil Grissom leads a team of forensic scientists who investigate brutal crimes. In NOAA's version, Marty Hoerling leads a group of researchers who investigate killer climate patterns such as heat waves, tornadoes, and the floods that struck the Mississippi this summer.
Hoerling and colleagues across NOAA created Climate Scene Investigators, CSI, early last year following chaotic media coverage of the record hot year of 2006. "Even within NOAA, we presented opposite opinions. It was because of global warming, and it was not global warming," said Hoerling, of ESRL's PSD. "There was no organized attribution effort that was timely enough. The questions pop up all the time and you want to respond with the best information."
The CSI team set out to perform fast- response "attribution" work, using models, historic data and recent observations to try to understand the sources of unusual climate and weather patterns.
This is the kind of information increasingly sought by decision-makers and the media, Hoerling said. "They all want to know how well we understand the causes of regional and seasonal climate variation and trends." If an attribution study suggests, for example, that La Niña winters are often associated with extreme snowfall events, communities can use that information to get ready.
In February, a public figure suggested that global warming could be responsible for a series of deadly tornadoes in Florida, and CSI quickly responded with an attribution study. "We found no evidence warming enhances tornadic activity," Hoerling said. "The tornadoes were consistent with La Niña. There was research out there showing higher activity in those places at that time during La Niñas."
In climate attribution work, researchers start by identifying possible underlying causes for weather and climate trends—an increase in greenhouse gases, perhaps, natural changes in ocean temperatures, or land-use changes.
They then use climate models and historic records to ask if such "antecedent conditions" can produce climate patterns consistent with observations. In the case of the February tornadoes, for example, records did not show an increase in the number of tornadoes coincident with rising greenhouse gas levels in the atmosphere. Instead, records and published research revealed an increased risk of tornadoes along a band from Louisiana to Michigan during La Niña years.
This summer's devastating Midwest floods, however, did carry a signature of global warming. The CSI team looked for evidence of a La Niña influence—and found none. However, the severe Midwest drought of 1988 coincided with a recent strong La Niña event. CSI found that global sea surface conditions could have contributed to heavy winter precipitation in the Upper Midwest, which saturated soils and contributed to later floods. Ocean conditions in January through March slightly increase the risk of extra moisture in the upper Midwest in those months.
But the extreme rain events best fit into an emerging pattern of water cycle changes occurring because of greenhouse gas forcing in the atmosphere, CSI concluded.
Although climate models do not predict an increase in mean precipitation falling over the Midwest, models and observations suggest that the character of precipitation is changing in many places. The United Nations' Intergovernmental Panel on Climate Change and the U.S. Climate Change Science Program both note an increase in heavy precipitation events over North America during the last 50 years, which is consistent with more water vapor in the atmosphere,. This, in turn, is consistent with a rise in greenhouse gases.
"I think of NOAA climate services to the nation as currently having two branches—monitoring and prediction. Sitting between them is the service of explaining climate conditions—attribution," Hoerling said. "Our fledgling NOAA-CSI effort at real- time climate attribution is seeking to fill this gap. It's what explains the observations, and that informs predictions."