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Steven M. Lazarus
,
Carol M. Ciliberti
,
John D. Horel
, and
Keith A. Brewster

Abstract

Several mesoscale data analysis systems are reviewed, of which one is then adapted and applied to the complex terrain of northwest Utah and the western United States. The analysis system relies on the simple, but computationally efficient, successive correction methodology. Near-real-time three-dimensional mesoscale analyses are produced hourly over northwest Utah at 1-km horizontal resolution while analyses are produced every 15 min for surface fields over northwest Utah and the western United States. Surface analyses over the western United States are also generated at 0000 and 1200 UTC to help to initialize 36-h mesoscale model forecasts. Comparisons between the 1-km three-dimensional analyses and the background three-dimensional analysis provided by the National Centers for Environmental Prediction Rapid Update Cycle, version 2 (RUC-2), indicate that, where surface and upper-air observations are abundant, the local analysis adds information beyond that of simply interpolating the background (RUC-2) data to the high-resolution analysis grid.

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Taylor A. McCorkle
,
John D. Horel
,
Alexander A. Jacques
, and
Trevor Alcott

Abstract

The High-Resolution Rapid Refresh–Alaska (HRRR-AK) modeling system provides 3-km horizontal resolution and 0–36-h forecast guidance for weather conditions over Alaska. This study evaluated the experimental version of the HRRR-AK system available from December 2016 to June 2017, prior to its operational deployment by the National Centers for Environmental Prediction in July 2018. Surface pressure observations from 158 National Weather Service (NWS) stations assimilated during the model’s production cycle and pressure observations from 101 USArray Transportable Array (TA) stations that were not assimilated were used to evaluate 265 complete 0–36-h forecasts of the altimeter setting (surface pressure reduced to sea level). The TA network is the largest recent expansion of Alaskan weather observations and provides an independent evaluation of the model’s performance during this period. Throughout the study period, systematic differences in altimeter setting between the HRRR-AK 0-h forecasts were larger relative to the unassimilated TA observations than relative to the assimilated NWS observations. Upon removal of these initial biases from each of the subsequent 1–36-h altimeter setting forecasts, the model’s 36-h forecast root-mean-square errors at the NWS and TA locations were comparable. The model’s treatment of rapid warming and downslope winds that developed in the lee of the Alaska Range during 12–15 February is examined. The HRRR-AK 0-h forecasts were used to diagnose the synoptic and mesoscale conditions during this period. The model forecasts underestimated the abrupt increases in the temperature and intensity of the downslope winds with smaller errors as the downslope wind events evolved.

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Bryan G. White
,
Jan Paegle
,
W. James Steenburgh
,
John D. Horel
,
Robert T. Swanson
,
Louis K. Cook
,
Daryl J. Onton
, and
John G. Miles

Abstract

The short-term forecast accuracy of six different forecast models over the western United States is described for January, February, and March 1996. Four of the models are operational products from the National Centers for Environmental Prediction (NCEP) and the other two are research models with initial and boundary conditions obtained from NCEP models. Model resolutions vary from global wavenumber 126 (∼100 km equivalent horizontal resolution) for the Medium Range Forecast model (MRF) to about 30 km for the Meso Eta, Utah Local Area Model (Utah LAM), and Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Version 5 (MM5). Forecast errors are described in terms of bias error and mean square error (mse) as computed relative to (i) gridded objective analyses and (ii) rawinsonde observations. Bias error and mse fields computed relative to gridded analyses show considerable variation from model to model, with the largest errors produced by the most highly resolved models. Using this approach, it is impossible to separate real forecast errors from possibly correct, highly detailed forecast information because the forecast grids are of higher resolution than the observations used to generate the gridded analyses. Bias error and mse calculated relative to rawinsonde observations suggest that the Meso Eta, which is the most highly resolved and best developed operational model, produces the most accurate forecasts at 12 and 24 h, while the MM5 produces superior forecasts relative to the Utah LAM. At 36 h, the MRF appears to produce superior mass and wind field forecasts. Nevertheless, a preliminary validation of precipitation performance for fall 1997 suggests the more highly resolved models exhibit superior skill in predicting larger precipitation events. Although such results are valid when skill is averaged over many simulations, forecast errors at individual rawinsonde locations, averaged over subsets of the total forecast period, suggest more variability in forecast accuracy. Time series of local forecast errors show large variability from time to time and generally similar maximum error magnitudes among the different models.

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Neil P. Lareau
,
Erik Crosman
,
C. David Whiteman
,
John D. Horel
,
Sebastian W. Hoch
,
William O. J. Brown
, and
Thomas W. Horst

The Persistent Cold-Air Pool Study (PCAPS) was conducted in Utah's Salt Lake valley from 1 December 2010 to 7 February 2011. The field campaign's primary goal was to improve understanding of the physical processes governing the evolution of multiday cold-air pools (CAPs) that are common in mountain basins during the winter. Meteorological instrumentation deployed throughout the Salt Lake valley provided observations of the processes contributing to the formation, maintenance, and destruction of 10 persistent CAP episodes. The close proximity of PCAPS field sites to residences and the University of Utah campus allowed many undergraduate and graduate students to participate in the study.

Ongoing research, supported by the National Science Foundation, is using the PCAPS dataset to examine CAP evolution. Preliminary analyses reveal that variations in CAP thermodynamic structure are attributable to a multitude of physical processes affecting local static stability: for example, synoptic-scale processes impact changes in temperatures and cloudiness aloft while variations in boundary layer forcing modulate the lower levels of CAPs. During episodes of strong winds, complex interactions between the synoptic and mesoscale f lows, local thermodynamic structure, and terrain lead to both partial and complete removal of CAPs. In addition, the strength and duration of CAP events affect the local concentrations of pollutants such as PM2.5.

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Manuel S. F. V. De Pondeca
,
Geoffrey S. Manikin
,
Geoff DiMego
,
Stanley G. Benjamin
,
David F. Parrish
,
R. James Purser
,
Wan-Shu Wu
,
John D. Horel
,
David T. Myrick
,
Ying Lin
,
Robert M. Aune
,
Dennis Keyser
,
Brad Colman
,
Greg Mann
, and
Jamie Vavra

Abstract

In 2006, the National Centers for Environmental Prediction (NCEP) implemented the Real-Time Mesoscale Analysis (RTMA) in collaboration with the Earth System Research Laboratory and the National Environmental, Satellite, and Data Information Service (NESDIS). In this work, a description of the RTMA applied to the 5-km resolution conterminous U.S. grid of the National Digital Forecast Database is given. Its two-dimensional variational data assimilation (2DVAR) component used to analyze near-surface observations is described in detail, and a brief discussion of the remapping of the NCEP stage II quantitative precipitation amount and NESDIS Geostationary Operational Environmental Satellite (GOES) sounder effective cloud amount to the 5-km grid is offered. Terrain-following background error covariances are used with the 2DVAR approach, which produces gridded fields of 2-m temperature, 2-m specific humidity, 2-m dewpoint, 10-m U and V wind components, and surface pressure. The estimate of the analysis uncertainty via the Lanczos method is briefly described. The strength of the 2DVAR is illustrated by (i) its ability to analyze a June 2007 cold temperature pool over the Washington, D.C., area; (ii) its fairly good analysis of a December 2008 mid-Atlantic region high-wind event that started from a very weak first guess; and (iii) its successful recovery of the finescale moisture features in a January 2010 case study over southern California. According to a cross-validation analysis for a 15-day period during November 2009, root-mean-square error improvements over the first guess range from 16% for wind speed to 45% for specific humidity.

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A. Gannet Hallar
,
Steven S. Brown
,
Erik Crosman
,
Kelley C. Barsanti
,
Christopher D. Cappa
,
Ian Faloona
,
Jerome Fast
,
Heather A. Holmes
,
John Horel
,
John Lin
,
Ann Middlebrook
,
Logan Mitchell
,
Jennifer Murphy
,
Caroline C. Womack
,
Viney Aneja
,
Munkhbayar Baasandorj
,
Roya Bahreini
,
Robert Banta
,
Casey Bray
,
Alan Brewer
,
Dana Caulton
,
Joost de Gouw
,
Stephan F.J. De Wekker
,
Delphine K. Farmer
,
Cassandra J. Gaston
,
Sebastian Hoch
,
Francesca Hopkins
,
Nakul N. Karle
,
James T. Kelly
,
Kerry Kelly
,
Neil Lareau
,
Keding Lu
,
Roy L. Mauldin III
,
Derek V. Mallia
,
Randal Martin
,
Daniel L. Mendoza
,
Holly J. Oldroyd
,
Yelena Pichugina
,
Kerri A. Pratt
,
Pablo E. Saide
,
Philip J. Silva
,
William Simpson
,
Britton B. Stephens
,
Jochen Stutz
, and
Amy Sullivan

Abstract

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

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