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J. D. Horel

Abstract

Complex principal component (CPC) analysis is shown to be a useful method for identifying traveling and standing waves in geophysical data sets. Combinations of simple progressive and standing oscillations are used to examine the properties of this technique. These examples illustrate that although CPC analysis allows for the identification of traveling waves, many of the drawbacks associated with conventional principal component analysis remain, and sometimes become worse; e.g. the interpretation of CPC solutions is more difficult since both amplitude and phase relationships must be considered. A method for linearly transforming complex principal components was devised in order to identify regional relationships within large geophysical data sets. The errors in CPC analysis resulting from limited sample sizes are discussed.

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J. C. Doran
,
J. D. Fast
, and
J. Horel

A month-long meteorological field campaign sponsored by the Department of Energy's Environmental Meteorology Program was conducted during October 2000 in the Salt Lake Valley to study vertical transport and mixing (VTMX) processes. The goals of the program are to increase the understanding of these processes, to improve the ability to measure and characterize them, and to incorporate that improved knowledge into conceptual and numerical models that can be used to describe and predict them. The program is currently concentrating on nocturnal stable periods and morning and evening transition periods, and it is further focused on urban areas located in valleys, basins, or other settings affected by nearby elevated terrain. Approximately 75 people participated in the campaign. The campaign featured a wide range of remote sensing and in situ measurements, including those from 6 radar wind profilers, 6 sodars, 5 radio acoustic sounding systems, a Doppler lidar, 2 aerosol lidars, and a water vapor lidar, as many as 22 rawinsonde soundings per intensive observing period (IOP), and the simultaneous release of up to 7 perfluorocarbon tracers. Preliminary results show the existence of strong cold pools forming over the valley center with significant wind shear aloft and intermittent turbulence close to the surface, a heat island over the downtown area at night and areas with substantially cooler temperatures nearby, regions of strong convergence and divergence affected by a narrow jet through a gap in the mountains to the south and flows out of the canyons to the east, and extensive wave activity.

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H. M. Van Den Dool
and
J. D. Horel

Abstract

An attempt is made to estimate the thermal inertia of the upper ocean, relevant to climatic change. This is done by assuming that the annual variation in sea surface temperature (SST) can, to a first-order approximation, be described by a simple energy-balance equation. From the observed climatological annual variation in SST and in absorbed solar radiation we can estimate then a typical value of the heat capacity (C) of the active layer of the ocean. Also we can estimate how fast the SST is damped towards an equilibrium value (damping coefficient b). Within the same theoretical framework the decay time of SST anomalies allows us to estimate the seasonality of C/b.

The method is first tested on SST at six ocean weather ships and two coastal stations. The calculated depth of the active layer looks reasonable though somewhat small and it is encouraging that the seasonality in C/b, derived from daily SST data at one station, is similar to the observed seasonality in mixed layer depth. One of the problems seems to be that we need rather precise observations concerning solar radiation reaching the earth's surface. At many places such knowledge is not available. The spatial distribution of calculated active layer depth over the North Pacific is very similar to that of observed annual mean mixed layer depth but the mixed layer seems to be twice as deep as the active layer. Also the effective mixed layer defined and used by Manabe and Stouffer is substantially deeper than our calculated active layer.

The results are discussed in the context of both the surface energy balance and the vertically averaged energy balance. One of the interesting findings of this study is that the layer of the ocean involved in the annual cycle should be taken as 20–50 m rather than the more customary 60–80 m. Another conclusion is that the SST seems to damp (towards equilibrium) at least five times faster than the vertically integrated energy content of the climate system as a whole (including the ocean!).

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Kevin J. Dougherty
,
John D. Horel
, and
Jason E. Nachamkin

Abstract

Precipitation forecasts from the High-Resolution Rapid Refresh model (HRRR) of the National Centers for Environmental Prediction (NCEP) and the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) are examined during heavy precipitation periods in California. Precipitation forecast discrepancies between the two models are examined during a recent heavy winter precipitation episode in California from 6 to 8 December 2019. The skill of initial 12-h precipitation forecasts is examined objectively from 1 December 2018 to 28 February 2019 from the HRRR, COAMPS, and NCEP’s North American Mesoscale Forecast System (NAM-3km). The HRRR exhibited lower seasonal biases and higher skill based on several metrics applied to a sample of 48 12-h periods during California’s second wettest winter season during the past 20 years. Overall, the NAM-3km and COAMPS exhibited a large wet bias over the interior mountain regions while the HRRR model indicated a dry bias along the northern coastal region. All models tended to underestimate precipitation along the coastal mountains of Northern California. To highlight the regional and localized nature of forecast skill, the fraction skill score (FSS) metric is applied across ranges of spatial scales and precipitation values. For the domain as a whole, the HRRR had higher precipitation forecast skill compared to the other two models, particularly within radial distances of 20–30 km and moderate (10–50 mm) precipitation totals. FSS computed locally highlights the HRRR’s overall higher skill as well as enhanced skill in the southern half of the state.

Open access
J. Horel
,
T. Potter
,
L. Dunn
,
W. J. Steenburgh
,
M. Eubank
,
M. Splitt
, and
J. Onton

The 2002 Winter Olympic and Paralympic Games will be hosted by Salt Lake City, Utah, during February–March 2002. Adverse weather during this period may delay sporting events, while snow and ice-covered streets and highways may impede access by the athletes and spectators to the venues. While winter snowstorms and other large-scale weather systems typically have widespread impacts throughout northern Utah, hazardous winter weather is often related to local terrain features (the Wasatch Mountains and Great Salt Lake are the most prominent ones). Examples of such hazardous weather include lake-effect snowstorms, ice fog, gap winds, down-slope windstorms, and low visibility over mountain passes.

A weather support system has been developed to provide weather information to the athletes, games officials, spectators, and the interested public around the world. This system is managed by the Salt Lake Olympic Committee and relies upon meteorologists from the public, private, and academic sectors of the atmospheric science community. Weather forecasting duties will be led by National Weather Service forecasters and a team of private weather forecasters organized by KSL, the Salt Lake City NBC television affiliate. Other government agencies, commercial firms, and the University of Utah are providing specialized forecasts and support services for the Olympics. The weather support system developed for the 2002 Winter Olympics is expected to provide long-term benefits to the public through improved understanding, monitoring, and prediction of winter weather in the Intermountain West.

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J. Horel
,
M. Splitt
,
L. Dunn
,
J. Pechmann
,
B. White
,
C. Ciliberti
,
S. Lazarus
,
J. Slemmer
,
D. Zaff
, and
J. Burks

Meteorological data from over 2800 automated environmental monitoring stations in the western United States are collected, processed, archived, integrated, and disseminated as part of the MesoWest program. MesoWest depends upon voluntary access to provisional observations from environmental monitoring stations installed and maintained by federal, state, and local agencies and commercial firms. In many cases, collection and transmission of these observations are facilitated by NWS forecast offices, government laboratories, and universities. MesoWest augments the Automated Surface Observing System (ASOS) network maintained by the NWS, Federal Aviation Administration, and Department of Defense. MesoWest increases the coverage of observations in remote locations and helps capture many of the local and mesoscale weather phenomena that impact the public.

The primary goal of MesoWest is to improve timely access to automated observations for NWS forecasters at offices throughout the western United States. In addition, integration of the observations into analyses of surface conditions at high spatial and temporal resolution provides additional tools for nowcasts and forecast verification. MesoWest observations are being used for many other applications, including input to operational and research models and research and education on weather processes in the western United States.

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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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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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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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