March 18, 2004
NASA Explains “Dust Bowl” Drought
NASA scientists have an explanation for one of the worst climatic events
in the history of the United States, the “Dust Bowl” drought,
which devastated the Great Plains and all but dried up an already depressed
American economy in the 1930’s.
Siegfried Schubert of NASA’s Goddard Space Flight Center, Greenbelt,
Md., and colleagues used a computer model developed with modern-era satellite
data to look at the climate over the past 100 years. The study found
cooler than normal tropical Pacific Ocean surface temperatures combined
with warmer tropical Atlantic Ocean temperatures to create conditions
in the atmosphere that turned America’s breadbasket into a dust
bowl from 1931 to 1939. The team’s data is in this week’s
Science magazine.
These changes in sea surface temperatures created shifts in the large-scale
weather patterns and low level winds that reduced the normal supply of
moisture from the Gulf of Mexico and inhibited rainfall throughout the
Great Plains.
“The 1930s drought was the major climatic event in the nation’s
history,” Schubert said. “Just beginning to understand what
occurred is really critical to understanding future droughts and the
links to global climate change issues we’re experiencing today,” he
said.
By discovering the causes behind U.S. droughts, especially severe episodes
like the Plains’ dry spell, scientists may recognize and possibly
foresee future patterns that could create similar conditions. For example,
La Niñas are marked by cooler than normal tropical Pacific Ocean surface
water temperatures, which impact weather globally, and also create dry
conditions over the Great Plains.
The researchers used NASA’s Seasonal-to-Interannual Prediction
Project (NSIPP) atmospheric general circulation model and agency computational
facilities to conduct the research. The NSIPP model was developed using
NASA satellite observations, including; Clouds and the Earth’s
Radiant Energy System radiation measurements; and the Global Precipitation
Climatology Project precipitation data.
The model showed cooler than normal tropical Pacific Ocean temperatures
and warmer than normal tropical Atlantic Ocean temperatures contributed
to a weakened low-level jet stream and changed its course. The jet stream,
a ribbon of fast moving air near the Earth’s surface, normally
flows westward over the Gulf of Mexico and then turns northward pulling
up moisture and dumping rain onto the Great Plains. As the low level
jet stream weakened, it traveled farther south than normal. The Great
Plains dried up and dust storms formed.
The research shed light on how tropical sea surface temperatures can
have a remote response and control over weather and climate. It also
confirmed droughts can become localized based on soil moisture levels,
especially during summer. When rain is scarce and soil dries, there is
less evaporation, which leads to even less precipitation, creating a
feedback process that reinforces lack of rainfall.
The study also shed light on droughts throughout the 20th century.
Analysis of other major U.S. droughts of the 1900s suggests a cool tropical
Pacific was a common factor. Schubert said simulating major events like
the 1930s drought provides an excellent test for computer models. While
the study finds no indication of a similar Great Plains drought in the
near future, it is vital to continue studies relating to climate change.
NASA’s current and planned suite of satellite sensors is uniquely
poised to answer related climate questions.
NASA’s Earth Science Enterprise funded the study. The Enterprise
is dedicated to understanding the Earth as an integrated system and applying
Earth System Science to improve climate, weather, and natural hazard
prediction using the unique vantage point of space.
For information about NASA and agency programs on the Internet, visit:
http://www.nasa.gov
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Contacts:
Krishna Ramanujan
NASA Goddard Space Flight Center
Greenbelt, Md.
Phone: 607/273-2561
Rani Chohan
NASA Goddard Space Flight Center
Greenbelt, MD
Phone: 301/286-2483 |
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Dust Bowl
Dust storm approaching Stratford, Texas. (Credit: NOAA Photo Library,
Historic NWS collection)
More Dustbowl Images
High-Resolution mage
NASA Model Simulation
Abnormal sea surface temperatures (SST) in the Pacific and the Atlantic
Ocean played a strong role in the 1930s dust bowl drought. Scientists
used SST data acquired from old ship records to create starting conditions
for the computer models. They let the model run on its own, driven only
by the observed monthly global sea surface temperatures. The model was
able to reconstruct the Dust Bowl drought quite closely, providing strong
evidence that the Great Plains dry spell originated with abnormal sea
surface temperatures. This sequence shows the warmer than normal SST
(red-orange) in that the Atlantic Ocean and colder than normal SST (blues)
in the Pacific Ocean, followed by a low level jet stream that shifted
and weakened reducing the normal supply of moisture to the Great Plains
View Animation
High-Resolution Image
Where Did the Rain Go?
This illustration shows how cooler than normal tropical Pacific Ocean
temperatures (blues) and warmer than normal tropical Atlantic Ocean temperatures
(red and orange) contributed to a weakened low level jet stream and changed
its course. The jet stream normally flows westward over the Gulf of Mexico
and then turns northward pulling up moisture and dumping rain onto the
Great Plains. During the 1930s, this low level jet stream weakened, carrying
less moisture, and shifted further south. The Great Plains land dried
up and dust storms blew across the U.S
View Animation
High-Resolution
Image 1
High-Resolution
Image 2
Comparing Model Data to Actual
These illustrations compare model and actual rainfall results. The first
(top) image, model data, shows extensive drying throughout the Great
Plains. The dark red represents the driest areas, followed by light red,
then orange, and yellow, which is the least dry. The second (bottom)
image shows observed rainfall maps. The observed results are quite similar
to the model results
View Animation
High-Resolution
Image 1
High-Resolution
Image 2
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