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November
30, 2007: From the deserts of the American southwest
to the pine forests of the Deep South, drought-weary residents
have one thing on their minds: "I wish it would rain!"
Technically,
what they should be wishing for is "more streamflow,"
says Dr. Ashutosh Limaye, a hydrologist at the National Space
Science and Technology Center (NSSTC) in Huntsville, Alabama.
Streamflow
is a term used by water management specialists to mean, very
simply, the amount of water in streams and rivers. Areas of
drought have reduced streamflow, and experts believe they
can better forecast droughts by studying this key indicator
of dry conditions.
Above:
A map of drought conditions in the United States. [More]
"Streamflow
is always changing, from day to day and even minute to minute,
for a wide variety of reasons: evaporation from the soil and
from bodies of water, runoff from rainfall and snowmelt, transpiration
by plants and trees, and other natural and human influences,"
he explains. National Weather Service River Forecast Centers
have to consider all of these factors when they forecast streamflow.
"If
we can help forecasters estimate any of these elements more
accurately, they can better predict drought conditions months
in advance," says Dr. Limaye. "These predictions
are critical because they influence important decisions about
measures like withholding water in reservoirs and restricting
water use."
When
Limaye's team asked National Oceanic and Atmospheric Administration
(NOAA) officials, including Dr. Mike Smith of the Office of
Hydrologic Development, specifically how NASA could help them
improve streamflow forecasts, the officials pinpointed one
thing -- clouds.
Why
clouds? "Because most of the water that falls on the
ground goes up in evaporation, evaporation is a huge component
of the total surface water," explains Limaye. "So
it's important to get those numbers right. Clouds affect radiation,
which has a big influence on evaporation."
Above:
The complexities of streamflow. [More]
National
Weather Service cloud cover estimates from the 1960s to the
1990s went like this: A trained technician literally walked
outside, tilted his or her head back, eyeballed the sky like
an old farmer, and rated the cloud cover on a 1-8 scale.
In
the 90s, these manual observations were replaced by a device
called a "ceilometer," part of the Automated Surface
Observing System (ASOS), which has a laser beam that aims
at the sky. Returns from this beam are used to detect clouds.
"Believe
it or not, this newer method is not nearly as accurate as
people just looking up," says Dr. Limaye. "The ceilometer
can only detect clouds up to 12,000 feet. If there are no
low clouds to block the view, you and I can see way over 20,000
feet, up to where the wispy Cirrus clouds are floating. And
Cirrus clouds way up high, even patchy ones, can influence
the radiation that drives evaporation."
This
is where Dr. Limaye's team can help. NASA scientists use satellite
instruments to scan the Earth's surface for things like vegetation
cover, ground temperature, and other variables of interest.
Normally, these researchers would view clouds as noise contaminating
the signal they are trying to view. In short, clouds get in
the way. "But one person's noise is another person's
signal," says Limaye. "We can use the cloud cover
data. In fact, it's exactly what NOAA wants to see."
One
NASA satellite instrument called MODIS, short for Moderate
Resolution Imaging Spectroradiometer, can detect clouds all
the way up to the top of the atmosphere. NOAA's ASOS can only
see clouds up to 12,000 feet and lacks MODIS's precision.
ASOS, though, records cloud data continuously, providing a
picture of what happened throughout the day, while MODIS passes
overhead only twice per day. It made perfect sense to Limaye's
team to let the two tools work in concert and complement one
another, each filling in what the other lacked.
"Together
these tools produce much better radiation estimates than either
can do alone," says Limaye. "We'll be able to reestablish
what the National Weather Service lost when they stopped using
manual observations for cloud cover."
Preliminary
analyses show that MODIS cloud data make evaporation estimates
25% more accurate. Now researchers are analyzing how adding
the NASA data improves the actual streamflow estimates that
rely on those evaporation estimates. Those numbers will be
available soon.
After
all that, do you think they could do something to make it
rain?
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Author: Dauna Coulter | Production Editor:
Dr. Tony Phillips | Credit: Science@NASA
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