The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions ; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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A Description of the Advanced Research WRF Version 3

Numerous modifications to the Kain‐Fritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly operational forecasters). The specific formulation of the modifications evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.

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The Kain–Fritsch Convective Parameterization: An Update

A Description of the Fifth-Generation Penn State/ NCAR Mesoscale Model (MM5), NCAR/TN-398+STR

Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

/pdf/a-description-of-the-fifth-generation-penn-state-ncar-4380gcr9if.pdf

A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5)

A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or “nudging” is tested using standard rawinsonde data in the Penn State/NCAR limited-area mesoscale model. It is imperative that we better understand these FDDA-generated datasets, which are widely used for model initialization and diagnostic analysis. The main hypothesis to be tested is that use of coarse-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can limit large-scale model error growth (amplitude and phase errors) while the model generates realistic mesoscale structures not resolved by the data. The main objective of this study is to determine what assimilation strategies and what meteorological fields (mass, wind or both) have the greatest positive impact via FDDA on the numerical simulators for two midlatitude, real-data cases using the full-physics version of a limited-area model. Seven experiments are performed for each case: one control experiment ...

Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model. Part I: Experiments with Synoptic-Scale Data

Four-dimensional data assimilation (FDDA) schemes capable of effectively analyzing asynoptic, near-continuous data streams art especially important on the mesobeta scale for both model initialization and dynamic analysis. A multiscale nudging approach that utilizes grid nesting is investigated for the generation of complete, dynamically consistent datasets for the mesobeta scale. These datasets are suitable for input into air quality models, but can also be used for other diagnostic purposes including model initialization. A multiscale nudging strategy is used here to simulate the wind flow for two cases over the Colorado Plateau and Grand Canyon region during the winter of 1990 when a special mesobeta-scale observing system was deployed in the region to study the canyon's visibility impairment problem. The special data included Doppler sodars, profilers rawinsondes, and surface stations. Combinations of these data and conventional mesoalpha-scale data were assimilated into a nested version of th...

Multiscale four-dimensional data assimilation

http://radiometrics.com/data/uploads/2012/11/seaman_AE-2000.pdf

Meteorological modeling for air-quality assessments

A comparison study of four cumulus parameterization schemes (CPSs), the Anthes‐Kuo, Betts‐Miller, Grell, and Kain‐Fritsch schemes, is conducted using The Pennsylvania State University‐National Center for Atmospheric Research mesoscale model. Performance of these CPSs is examined using six precipitation events over the continental United States for both cold and warm seasons. Grid resolutions of 36 and 12 km are chosen to represent current mesoscale research models and future operational models. The key parameters used to evaluate skill include precipitation, sea level pressure, wind, and temperature predictions. Precipitation is evaluated statistically using conventional skill scores (such as threat and bias scores) for different threshold values based on hourly rainfall observations. Rainfall and other mesoscale features are also evaluated by careful examination of analyzed and simulated fields, which are discussed in the context of timing, evolution, intensity, and structure of the precipitation systems. It is found that the general 6-h precipitation forecast skill for these schemes is fairly good in predicting four out of six cases examined in this study, even for higher thresholds. The forecast skill is generally higher for cold-season events than for warm-season events. There is an increase in the forecast skill in the 12-km model, and the gain is most obvious in predicting heavier rainfall amounts. The model’s precipitation forecast skill is better in rainfall volume than in either the areal coverage or the peak amount. The scheme with the convective available potential energy‐based closure assumption (Kain‐Fritsch scheme) appears to perform better. Some systematic behaviors associated with various schemes are also noted wherever possible. The partition of rainfall into subgrid scale and grid scale is sensitive to the particular parameterization scheme chosen, but relatively insensitive to either the model grid sizes or the convective environments. The prediction of mesoscale surface features in warm-season cases, such as mesoscale pressure centers, windshift lines (gust fronts), and temperature fields, strongly suggests that the CPSs with moist downdrafts are able to predict these surface features more accurately.

A Comparison Study of Convective Parameterization Schemes in a Mesoscale Model

A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or nudging has been developed and evaluated in the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Limited-Area Mesoscale Model. It was shown in Part I of this study that continuous assimilation of standard-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can successfully limit large model error growth (amplitude and phase errors) while the model maintains intervariable consistency and generates realistic mesoscale structures not resolved by the data. The purpose of this paper is to further refine the previously reported FDDA strategy used to produce “dynamic analyses” of the atmosphere by investigating the effects of data assimilation within the planetary boundary layer (PBL). The data used for assimilation include conventional synoptic-scale rawinsonde data and mesoalpha-scale surface data. The main objective of this study is ...

Nelson L. Seaman

Papers

Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model. Part I: Experiments with Synoptic-Scale Data

Multiscale four-dimensional data assimilation

Meteorological modeling for air-quality assessments

A Comparison Study of Convective Parameterization Schemes in a Mesoscale Model

Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model Part II: Effects of Data Assimilation within the Planetary Boundary Layer