WMOD00268

• Applicant: CWCB
• Sponsor Name: USBR
• Project Name: Final Report Weather Damage Mitigation Program
• Title: Numerical Simulations of Snowpack Augmentation for Drought Mitigation Studies in the Colorado Rocky Mountains
• Prepared For: USBR - WDMP
• Prepared By: Curt Hartzell, Dr. William Cotton, Joe Busto
• Date: 9/1/2005
• State: CO
• Weather Modification - Doc Type: Scientific Study

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1.5 Denver Water Operational Cloud Seeding Program

Due to continuing drought conditions in the central Colorado Rocky
Mountains, in the fall of 2002 Denver Water (OW) contracted with Western
Weather Consultants, LLC (WWC) to expand the Vail/Beaver Creek (BC) Ski
Resort Program to the east and southeast to cover the watersheds within OW's
water collection system. The OW 2002-2003 Program's target area included the
Blue, Fraser, Williams Fork, and Upper South Platte River basins above 9,000
feet elevation.

The OW 2002-2003 Program consisted of 43 manually-operated cloud-
seeding generators (38 new generator sites plus 5 existing generator sites from
the Vail/BC Program). Cloud-seeding activities were performed from early
November 2002 through April 7, 2003. There were a total of 25.433 hours of
seeding at an average seeding rate of 5.92 grams of silver iodide (Agl) per
seeding hour. Summary information on independent evaluations of the OW
2002-2003 Program is at http://www.denverwater.orQ/couldseedinQ.html.

1.6 Colorado State University Regional Atmospheric Modeling System

The Regional Atmospheric Modeling System (RAMS) was developed at
Colorado State University (CSU). RAMS has been used at CSU for real-
time forecasting since 1991 (Cotton et aI., 1994). Gaudet and Cotton (1998)
showed that explicit bulk microphysics improved the forecasting of the areal
extent and maximum amount of precipitation, especially when compared to the
SNOTEL automatic pillow-sensor stations, which are found at locations more
representative of the model topography. For the month of April 1995, a series of
24-hour accumulated precipitation forecasts was generated with both the dump-
bucket and microphysics versions of the forecast model. Both sets of output
were compared to a set of 167 community-based station reports, and to a set of
32 SNOTEL stations. Climatological station precipitation forecasts were
improved on the average by correcting for the difference between a station's
actual elevation and the cell-averaged topography used by the model.

The model had more problems with the precise timing and geographical
location of the precipitation features, probably due in part to the influence of other
model physics, the failure of the model to resolve adequately wintertime
convection events, and lack of mesoscale detail in the initializations. Wetzel at al.
(2003) further demonstrated RAMS accuracy in predicting snowfall amounts in
high-mountain terrain, specifically the Park Range of Colorado. As in the Gaudet
and Cotton (1998) study, the best a9reement occurred at the higher elevation
sites and the worst in the valleys. This could be related to the inability of the
model to represent the valley features correctly since emphasis is placed on
getting the mountain high terrain forcing in the model. In addition, RAMS
exhibited a warm-temperature bias, which may be a consequence of using Eta
model forecast data for initialization and nudging: the Eta model is known to have
such a warm temperature bias.