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  • Author or Editor: Roy M. Rasmussen x
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Troy J. Zaremba
,
Robert M. Rauber
,
Samuel Haimov
,
Bart Geerts
,
Jeffrey R. French
,
Coltin Grasmick
,
Kaylee Heimes
,
Sarah A. Tessendorf
,
Katja Friedrich
,
Lulin Xue
,
Roy M. Rasmussen
,
Melvin L. Kunkel
, and
Derek R. Blestrud

Abstract

Vertical motions over the complex terrain of Idaho’s Payette River basin were observed by the Wyoming Cloud Radar (WCR) during 23 flights of the Wyoming King Air during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) field campaign. The WCR measured radial velocity Vr , which includes the reflectivity-weighted terminal velocity of hydrometeors Vt , vertical air velocity w, horizontal wind contributions as a result of aircraft attitude deviations, and aircraft motion. Aircraft motion was removed through standard processing. To retrieve vertical radial velocity W, Vr was corrected using rawinsonde data and aircraft attitude measurements; w was then calculated by subtracting the mean W ( W ¯ ) at a given height along a flight leg long enough for W ¯ to equal the mean reflectivity-weighted terminal velocity V t ¯ at that height. The accuracy of the w and V t ¯ retrievals were dependent on satisfying assumptions along a given flight leg that the winds at a given altitude above/below the aircraft did not vary, the vertical air motions at a given altitude sum to 0 m s−1, and V t ¯ at a given altitude did not vary. The uncertainty in the w retrieval associated with each assumption is evaluated. Case studies and a projectwide summary show that this methodology can provide estimates of w that closely match gust probe measurements of w at the aircraft level. Flight legs with little variation in equivalent reflectivity factor at a given height and large horizontal echo extent were associated with the least retrieval uncertainty. The greatest uncertainty occurred in regions with isolated convective turrets or at altitudes where split cloud layers were present.

Free access
Lulin Xue
,
Jiwen Fan
,
Zachary J. Lebo
,
Wei Wu
,
Hugh Morrison
,
Wojciech W. Grabowski
,
Xia Chu
,
István Geresdi
,
Kirk North
,
Ronald Stenz
,
Yang Gao
,
Xiaofeng Lou
,
Aaron Bansemer
,
Andrew J. Heymsfield
,
Greg M. McFarquhar
, and
Roy M. Rasmussen

Abstract

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

Full access
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.

Full access
John Kochendorfer
,
Michael Earle
,
Roy Rasmussen
,
Craig Smith
,
Daqing Yang
,
Samuel Morin
,
Eva Mekis
,
Samuel Buisan
,
Yves-Alain Roulet
,
Scott Landolt
,
Mareile Wolff
,
Jeffery Hoover
,
Julie M. Thériault
,
Gyuwon Lee
,
Bruce Baker
,
Rodica Nitu
,
Luca Lanza
,
Matteo Colli
, and
Tilden Meyers

Abstract

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

Full access
Sarah A. Tessendorf
,
Jeffrey R. French
,
Katja Friedrich
,
Bart Geerts
,
Robert M. Rauber
,
Roy M. Rasmussen
,
Lulin Xue
,
Kyoko Ikeda
,
Derek R. Blestrud
,
Melvin L. Kunkel
,
Shaun Parkinson
,
Jefferson R. Snider
,
Joshua Aikins
,
Spencer Faber
,
Adam Majewski
,
Coltin Grasmick
,
Philip T. Bergmaier
,
Andrew Janiszeski
,
Adam Springer
,
Courtney Weeks
,
David J. Serke
, and
Roelof Bruintjes

Abstract

The Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) project aims to study the impacts of cloud seeding on winter orographic clouds. The field campaign took place in Idaho between 7 January and 17 March 2017 and employed a comprehensive suite of instrumentation, including ground-based radars and airborne sensors, to collect in situ and remotely sensed data in and around clouds containing supercooled liquid water before and after seeding with silver iodide aerosol particles. The seeding material was released primarily by an aircraft. It was hypothesized that the dispersal of the seeding material from aircraft would produce zigzag lines of silver iodide as it dispersed downwind. In several cases, unambiguous zigzag lines of reflectivity were detected by radar, and in situ measurements within these lines have been examined to determine the microphysical response of the cloud to seeding. The measurements from SNOWIE aim to address long-standing questions about the efficacy of cloud seeding, starting with documenting the physical chain of events following seeding. The data will also be used to evaluate and improve computer modeling parameterizations, including a new cloud-seeding parameterization designed to further evaluate and quantify the impacts of cloud seeding.

Full access
Francina Dominguez
,
Roy Rasmussen
,
Changhai Liu
,
Kyoko Ikeda
,
Andreas Prein
,
Adam Varble
,
Paola A. Arias
,
Julio Bacmeister
,
Maria Laura Bettolli
,
Patrick Callaghan
,
Leila M. V. Carvalho
,
Christopher L. Castro
,
Fei Chen
,
Divyansh Chug
,
Kwok Pan (Sun) Chun
,
Aiguo Dai
,
Luminita Danaila
,
Rosmeri Porfírio da Rocha
,
Ernani de Lima Nascimento
,
Erin Dougherty
,
Jimy Dudhia
,
Trude Eidhammer
,
Zhe Feng
,
Lluís Fita
,
Rong Fu
,
Julian Giles
,
Harriet Gilmour
,
Kate Halladay
,
Yongjie Huang
,
Angela Maylee Iza Wong
,
Miguel Ángel Lagos-Zúñiga
,
Charles Jones
,
Jorge Llamocca
,
Marta Llopart
,
J. Alejandro Martinez
,
J. Carlos Martinez
,
Justin R. Minder
,
Monica Morrison
,
Zachary L. Moon
,
Ye Mu
,
Richard B. Neale
,
Kelly M. Núñez Ocasio
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Sujan Pal
,
Erin Potter
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German Poveda
,
Franciano Puhales
,
Kristen L. Rasmussen
,
Amanda Rehbein
,
Rosimar Rios-Berrios
,
Christoforus Bayu Risanto
,
Alan Rosales
,
Lucia Scaff
,
Anton Seimon
,
Marcelo Somos-Valenzuela
,
Yang Tian
,
Peter Van Oevelen
,
Daniel Veloso-Aguila
,
Lulin Xue
, and
Timothy Schneider
Open access