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Patricia M. Pauley and Steven J. Nieman

Abstract

Large-scale departures from quasigeostrophic vertical motions are diagnosed for a model simulation of the QE II storm (9–11 September 1978). The simulation was performed by the Limited-Area Mesoscale Prediction System (LAMPS), initialized at 1200 UTC 9 September 1978. The model cyclone intensified from a central pressure of 1003 mb to 976 mb in 24 h, considerably short of the 59 mb (24 h)−1 observed deepening but reasonable in comparison to other model simulations of this storm. This diagnosis centers on a hydrostatic generalized omega equation, which scales to the quasigeostiophic omega equation for small Rossby number. Vertical motions were computed both from this generalized omega equation and the quasigeostrophic omega equation in order to examine the importance of nonquasigeostrophic effects. The high correlation of vertical motions from a control experiment (using most of the terms in the generalized omega equation) with the vertical motions predicted by the model establishes the validity of the method. A further comparison against satellite imagery also shows that these computed vertical motions portray a pattern similar to the satellite cloud shield. However, the pattern and magnitude of the quasigeostrophic vertical motions are quite different from those of the generalized vertical motions. An evaluation of individual terms in the generalized equation shows that although additional terms in omega placed on the left-hand side significantly affect the magnitude of the vertical motion, the greatest nonquasigeostrophic effects are provided by the diabatic term and the ageostrophic advections. Latent heating greatly enhances the upward motion in the cyclone’s cloud shield, while ageostrophic advections both suppress downward motion behind the cold front and enhance upward motion near the warm front.

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Steven J. Nieman, Johannes Schmetz, and W. Paul Menzel

Abstract

Satellite-derived cloud-motion vector (CMV) production has been troubled by inaccurate height assignment of cloud tracers, especially in thin semitransparent clouds. This paper presents the results of an intercomparison of current operational height assignment techniques. Currently, heights are assigned by one of three techniques when the appropriate spectral radiance measurements are available. The infrared window (IRW) technique compares measured brightness temperatures to forecast temperature profiles and thus infers opaque cloud levels. In semitransparent or small subpixel clouds, the carbon dioxide (CO2) technique uses the ratio of radiances from different layers of the atmosphere to infer the correct cloud height. In the water vapor (H2O) technique, radiances influenced by upper-tropospheric moisture and IRW radiances are measured for several pixels viewing different cloud amounts, and their linear relationship is used to extrapolate the correct cloud height. The results presented in this paper suggest that the H2O technique is a viable alternative to the CO2 technique for inferring the heights of semitransparent cloud elements. This is important since future National Environmental Satellite, Data, and Information Service (NESDIS) operations will have to rely on H20-derived cloud-height assignments in the wind field determinations with the next operational geostationary satellite. On a given day, the heights from the two approaches compare to within 60–110 hPa rms; drier atmospheric conditions tend to reduce the effectiveness of the H2O technique. By inference one can conclude that the present height algorithms used operationally at NESDIS (with the C02 technique) and at the European Satellite Operations Center (ESOC) (with their version of the H20 technique) are providing similar results. Sample wind fields produced with the ESOC and NESDIS algorithms using Meteosat-4 data show good agreement.

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Filippo Giorgi, Gary T. Bates, and Steven J. Nieman

As part of the development effort of a regional climate model (RCM) for the southern Great Basin, this paper presents a validation analysis of the climatology generated by a high-resolution RCM driven by observations. The RCM is a version of the National Center for Atmospheric Research/Pennsylvania State University mesoscale model, version 4 (MM4), modified for application to regional climate simulation. Two multiyear simulations, for the periods 1 January 1982 to 31 December 1983 and 1 January 1988 to 25 April 1989, were performed over the western United States with the RCM driven by European Centre for Medium-Range Weather Forecasts analyses of observations. The model resolution is 60 km. This validation analysis is the first phase of a project to produce simulations of future climate scenarios over a region surrounding Yucca Mountain, Nevada, the only location currently being considered as a potential high-level nuclear-waste repository site.

Model-produced surface air temperatures and precipitation were compared with observations from five southern Nevada stations located in the vicinity of Yucca Mountain. The seasonal cycles of temperature and precipitation were simulated well. Monthly and seasonal temperature biases were generally negative and largely explained by differences in elevation between the observing stations and the model topography. The model-simulated precipitation captured the extreme dryness of the Great Basin. Average yearly precipitation was generally within 30% of observed and the range of monthly precipitation amounts was the same as in the observations. Precipitation biases were mostly negative in the summer and positive in the winter. The number of simulated daily precipitation events for various precipitation intervals was within factors of 1.5–3.5 of observed. Overall, the model tended to overestimate the number of light precipitation events and underestimate the number of heavy precipitation events. At Yucca Mountain, simulated precipitation, soil moisture content, and water infiltration below the root zone (top 1 m) were maximized in the winter. Evaporation peaked in the spring after temperatures began to increase.

The conclusion drawn from this validation analysis is that this high-resolution RCM simulates the regional surface climatology of the southern Great Basin reasonably well when driven by meteorological fields derived from observations.

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Filippo Giorgi, Gary T. Bates, and Steven J. Nieman

Abstract

This paper presents a validation analysis of the climatology of a version of the National Center for Atmospheric Research-Pennsylvania State University limited-area model (MM4) developed for application to regional climate simulation over the western United States. Two continuous multiyear simulations, for the periods 1 January 1982–31 December 1983 and 1 January 1988–25 April 1989, were performed over this region with the MM4 driven by ECMWF analyses of observations and run at a horizontal resolution of 60 km. The model used in these simulations includes horizontal diffusion on terrain-following σ coordinates, a Kuo-type cumulus parameterization, sophisticated radiative transfer and surface physics-soil hydrology packages, and a relaxation boundary- conditions procedure.

Model-produced surface air temperatures, precipitation, and snow depths were compared with observations from about 390 stations distributed throughout the western United States. The base-model run reproduced the seasonal cycle of temperature and precipitation well. Monthly and seasonal temperature biases were generally less than a few degrees. The effects of topography on the regional distribution of precipitation were also well reproduced, although local detail was in several instances poorly captured. When regionally averaged, absolute model-precipitation biases were mostly in the range of 10% –50% of observations. The model generally simulated precipitation better in the cold season than in the warm season, and over coastal regions than in the continental interior. The simulated seasonal cycles of snowpack formation and melting were realistic, although modeled and observed snow-depth values differed significantly locally.

Over the Rocky Mountain regions the model reproduced wintertime precipitation amounts well but overpredicted summertime precipitation. Because of this overprediction of summertime precipitation, a version of the model was also tested in a simulation from 30 May 1988–26 December 1988 in which the horizontal diffusion coefficients were reduced over topographical gradients and an inflow-outflow lateral boundary condition was implemented for water vapor. These modifications were found to provide an improved simulation of summer precipitation while not substantially altering wintertime precipitation.

This work shows that it is feasible to perform good quality, multiyear simulations with current limited-area models and, therefore, that it is feasible to apply such models to climate studies.

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Christopher S. Velden, Christopher M. Hayden, Steven J W. Nieman, W. Paul Menzel, Steven Wanzong, and James S. Goerss

The coverage and quality of remotely sensed upper-tropospheric moisture parameters have improved considerably with the deployment of a new generation of operational geostationary meteorological satellites: GOES-8/9 and GMS-5. The GOES-8/9 water vapor imaging capabilities have increased as a result of improved radiometric sensitivity and higher spatial resolution. The addition of a water vapor sensing channel on the latest GMS permits nearly global viewing of upper-tropospheric water vapor (when joined with GOES and Meteosat) and enhances the commonality of geostationary meteorological satellite observing capabilities. Upper-tropospheric motions derived from sequential water vapor imagery provided by these satellites can be objectively extracted by automated techniques. Wind fields can be deduced in both cloudy and cloud-free environments. In addition to the spatially coherent nature of these vector fields, the GOES-8/9 multispectral water vapor sensing capabilities allow for determination of wind fields over multiple tropospheric layers in cloud-free environments. This article provides an update on the latest efforts to extract water vapor motion displacements over meteorological scales ranging from subsynoptic to global. The potential applications of these data to impact operations, numerical assimilation and prediction, and research studies are discussed.

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Steven J. Nieman, W. Paul Menzei, Christopher M. Hayden, Donald Gray, Steven T. Wanzong, Christopher S. Velden, and Jaime Daniels

Cloud-drift winds have been produced from geostationary satellite data in the Western Hemisphere since the early 1970s. During the early years, winds were used as an aid for the short-term forecaster in an era when numerical forecasts were often of questionable quality, especially over oceanic regions. Increased computing resources over the last two decades have led to significant advances in the performance of numerical forecast models. As a result, continental forecasts now stand to gain little from the inspection or assimilation of cloud-drift wind fields. However, the oceanic data void remains, and although numerical forecasts in such areas have improved, they still suffer from a lack of in situ observations. During the same two decades, the quality of geostationary satellite data has improved considerably, and the cloud-drift wind production process has also benefited from increased computing power. As a result, fully automated wind production is now possible, yielding cloud-drift winds whose quality and quantity is sufficient to add useful information to numerical model forecasts in oceanic and coastal regions. This article will detail the automated cloud-drift wind production process, as operated by the National Environmental Satellite Data and Information Service within the National Oceanic and Atmospheric Administration.

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Tom H. Zapotocny, Steven J. Nieman, W. Paul Menzel, James P. Nelson III, James A. Jung, Eric Rogers, David F. Parrish, Geoffrey J. DiMego, Michael Baldwin, and Timothy J. Schmit

Abstract

A case study is utilized to determine the sensitivity of the Eta Data Assimilation System (EDAS) to all operational observational data types used within it. The work described in this paper should be of interest to Eta Model users trying to identify the impact of each data type and could benefit other modelers trying to use EDAS analyses and forecasts as initial conditions for other models.

The case study chosen is one characterized by strong Atlantic and Pacific maritime cyclogenesis, and is shortly after the EDAS began using three-dimensional variational analysis. The control run of the EDAS utilizes all 34 of the operational data types. One of these data types is then denied for each of the subsequent experimental runs. Differences between the experimental and control runs are analyzed to demonstrate the sensitivity of the EDAS system to each data type for the analysis and subsequent 48-h forecasts. Results show the necessity of various nonconventional observation types, such as aircraft data, satellite precipitable water, and cloud drift winds. These data types are demonstrated to have a significant impact, especially observations in maritime regions.

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