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Stanley G. Benjamin
and
Patricia A. Miller

Abstract

A method for station or grid point reduction of surface pressure to sea level or some other level is presented that shows improvement over the standard reduction method in the western United States. This method (MAPS SLP-Mesoscale Analysis and Prediction System sea level pressure) uses the 700 hPa temperature to estimate an “effective” surface temperature from which the temperature of the hypothetical layer beneath the ground is estimated. The use of this “effective” temperature instead of the observed surface temperature is responsible for the improved reduction since it varies more smoothly over space and time and is more representative of the temperature variation found above the boundary layer.

The MAPS SLP reduction was compared with the standard reduction and altimeter setting reduction in statistical comparisons of geostrophic wind estimates with observed winds and in a case study. A 21-month comparison between geostrophic and observed winds was made over different geographical regions, times of day, rotation angles and seasons. The results showed that the MAPS SLP reduction performed better than the standard reduction in the western United States, but not in other regions with generally low elevation. In general, the correlation between sea level geostrophic winds and observed winds was found to be dependent on the Froude number. A statistical comparison using a smaller sample between MAPS SLP and the Sangster geostrophic wind, which is not a station reduction, showed similar skill over the western United States. The case study also showed that the pattern over the western United States was more coherent and less anomalous with MAPS SLP that with the other reductions.

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Patricia A. Miller
and
Stanley G. Benjamin

Abstract

An assimilation system is presented that was designed to provide timely, detailed, and coherent analyses of surface data, even when the data are collected in rough terrain where station elevations differ widely and observations are often subject to local effects. Analyses with improved spatial continuity are obtained from these data through careful choice of analysis method and variables. The analysis method has the ability to handle varying data density, and the analysis variables, when possible, were chosen in such a way as to cancel out the effects of elevation differences. In addition, the method accounts for physical blocking and channeling by mountainous terrain by incorporating elevation and potential temperature differences in its horizontal correlation functions. The correlation functions also enable the method to move accurately represent surface gradients.

An hourly analysis cycle is used in which each analysis uses as a background the previous hourly analysis (a 1-h persistence forecast). The cycling is important in providing temporal continuity between analyses.

Detailed explanations of the analysis variables and method are given, along with a discussion of the objective quality-control procedures necessary to ensure reliable analyses in an operational environment. The assimilation system has been used experimentally by National Weather Service forecasters since 1996. Quality-control statistics summarizing the observational errors of surface stations across the 48 contiguous states are also presented.

The effects of variable terrain on the analyses are demonstrated in examples. Sample analyses are presented, including diagnosed fields, for a severe-storm case. Overall, the surface analyses described here allow better temporal and spatial resolution than the current operational National Meteorolegical Center surfaces analyses.

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Patricia A. Miller
and
Michael J. Falls

Abstract

Results of radiometer temperature profile simulations are analyzed in order to examine the hypothesis that knowledge of temperature inversion parameters obtained from other instruments would substantially improve the accuracy of radiometric temperature profiles. Five variations of a statistical retrieval method are used to produce radiometric temperature profiles. These profiles are then compared with radiosonde data under both inversion and noninversion conditions. The best algorithm yields consistently better results than the traditional (pure radiometric) technique, but still fails to correctly reproduce the radiosonde inversions.

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Patricia A. Miller
,
Thomas W. Schlatter
,
Douglas W. van de Kamp
,
Michael F. Barth
, and
Bob L. Weber

Abstract

The National Oceanic and Atmospheric Administration has completed the installation of a 30-site demonstration network of wind-profiling radars in the central United States. The network is being used to demonstrate and assess the utility of wind profiler technology in a quasi-operational environment and to help define operational requirements for possible future national networks.

This paper reviews the cause of velocity folding and presents the unfolding method recently implemented for the NOAA Wind Profiler Demonstration Network. The method uses a simple median cheek to dealias (unfold) radial velocities quickly and effectively in real time. Cast study examples and statistical evaluation of the method's performance are also presented.

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David J. Stensrud
,
Nusrat Yussouf
,
Michael E. Baldwin
,
Jeffery T. McQueen
,
Jun Du
,
Binbin Zhou
,
Brad Ferrier
,
Geoffrey Manikin
,
F. Martin Ralph
,
James M. Wilczak
,
Allen B. White
,
Irina Djlalova
,
Jian-Wen Bao
,
Robert J. Zamora
,
Stanley G. Benjamin
,
Patricia A. Miller
,
Tracy Lorraine Smith
,
Tanya Smirnova
, and
Michael F. Barth

The New England High-Resolution Temperature Program seeks to improve the accuracy of summertime 2-m temperature and dewpoint temperature forecasts in the New England region through a collaborative effort between the research and operational components of the National Oceanic and Atmospheric Administration (NOAA). The four main components of this program are 1) improved surface and boundary layer observations for model initialization, 2) special observations for the assessment and improvement of model physical process parameterization schemes, 3) using model forecast ensemble data to improve upon the operational forecasts for near-surface variables, and 4) transfering knowledge gained to commercial weather services and end users. Since 2002 this program has enhanced surface temperature observations by adding 70 new automated Cooperative Observer Program (COOP) sites, identified and collected data from over 1000 non-NOAA mesonet sites, and deployed boundary layer profilers and other special instrumentation throughout the New England region to better observe the surface energy budget. Comparisons of these special datasets with numerical model forecasts indicate that near-surface temperature errors are strongly correlated to errors in the model-predicted radiation fields. The attenuation of solar radiation by aerosols is one potential source of the model radiation bias. However, even with these model errors, results from bias-corrected ensemble forecasts are more accurate than the operational model output statistics (MOS) forecasts for 2-m temperature and dewpoint temperature, while also providing reliable forecast probabilities. Discussions with commerical weather vendors and end users have emphasized the potential economic value of these probabilistic ensemble-generated forecasts.

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