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Mark T. Stoelinga
,
Peter V. Hobbs
,
Clifford F. Mass
,
John D. Locatelli
,
Brian A. Colle
,
Robert A. Houze Jr.
,
Arthur L. Rangno
,
Nicholas A. Bond
,
Bradley F. Smull
,
Roy M. Rasmussen
,
Gregory Thompson
, and
Bradley R. Colman

Despite continual increases in numerical model resolution and significant improvements in the forecasting of many meteorological parameters, progress in quantitative precipitation forecasting (QPF) has been slow. This is attributable in part to deficiencies in the bulk microphysical parameterization (BMP) schemes used in mesoscale models to simulate cloud and precipitation processes. These deficiencies have become more apparent as model resolution has increased. To address these problems requires comprehensive data that can be used to isolate errors in QPF due to BMP schemes from those due to other sources. These same data can then be used to evaluate and improve the microphysical processes and hydrometeor fields simulated by BMP schemes. In response to the need for such data, a group of researchers is collaborating on a study titled the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE). IMPROVE has included two field campaigns carried out in the Pacific Northwest: an offshore frontal precipitation study off the Washington coast in January–February 2001, and an orographic precipitation study in the Oregon Cascade Mountains in November–December 2001. Twenty-eight intensive observation periods yielded a uniquely comprehensive dataset that includes in situ airborne observations of cloud and precipitation microphysical parameters; remotely sensed reflectivity, dual-Doppler, and polarimetric quantities; upper-air wind, temperature, and humidity data; and a wide variety of surface-based meteorological, precipitation, and microphysical data. These data are being used to test mesoscale model simulations of the observed storm systems and, in particular, to evaluate and improve the BMP schemes used in such models. These studies should lead to improved QPF in operational forecast models.

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UNDERSTANDING UTAH WINTER STORMS

The Intermountain Precipitation Experiment

David M. Schultz
,
W. James Steenburgh
,
R. Jeffrey Trapp
,
John Horel
,
David E. Kingsmill
,
Lawrence B. Dunn
,
W. David Rust
,
Linda Cheng
,
Aaron Bansemer
,
Justin Cox
,
John Daugherty
,
David P. Jorgensen
,
José Meitín
,
Les Showell
,
Bradley F. Smull
,
Keli Tarp
, and
Marilu Trainor

Winter storms and their prediction are of increasing importance throughout the region of the United States with the fastest growing population, the Intermountain West. Such storms can produce heavy orographic snowfall, lake-effect snowbands, and even lightning. Unfortunately, precipitation forecast skill is lower over the Intermountain West than other regions of the country because of the complex topography, the lack or limited utility of upstream and in situ data, and insufficient understanding of storm and precipitation processes.

The Intermountain Precipitation Experiment (IPEX) is a research program designed to improve the understanding, analysis, and prediction of precipitation over the complex topography of the Intermountain West. The field phase of this research program was held in northern Utah in February 2000. During this time, seven storms were observed, including the heaviest snowfall to strike the Wasatch Mountains in two years, a tornadic bow echo associated with a strong cold front, a mesoscale snowband in Tooele Valley, and three other storms with locally heavy orographic snowfall and complex mesoscale circulations. Some of these storms were electrified and produced lightning.

This paper reviews the weather of the Intermountain West, describes the experimental setup and the outreach activities of IPEX, and presents preliminary results from the field phase. Finally, lessons learned in planning and executing this field program are discussed.

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