scholarly journals On Improving 4-km Mesoscale Model Simulations

2006 ◽  
Vol 45 (3) ◽  
pp. 361-381 ◽  
Author(s):  
Aijun Deng ◽  
David R. Stauffer
Keyword(s):  
Mesoscale Model ◽  
Vertical Mixing ◽  
Horizontal Resolution ◽  
Tracer Experiment ◽  
State University ◽  
Model Errors ◽  
Low Level ◽  
Medium Range Forecast ◽  
Pbl Scheme ◽  
Four Dimensional Data Assimilation

Abstract A previous study showed that use of analysis-nudging four-dimensional data assimilation (FDDA) and improved physics in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) produced the best overall performance on a 12-km-domain simulation, based on the 18–19 September 1983 Cross-Appalachian Tracer Experiment (CAPTEX) case. However, reducing the simulated grid length to 4 km had detrimental effects. The primary cause was likely the explicit representation of convection accompanying a cold-frontal system. Because no convective parameterization scheme (CPS) was used, the convective updrafts were forced on coarser-than-realistic scales, and the rainfall and the atmospheric response to the convection were too strong. The evaporative cooling and downdrafts were too vigorous, causing widespread disruption of the low-level winds and spurious advection of the simulated tracer. In this study, a series of experiments was designed to address this general problem involving 4-km model precipitation and gridpoint storms and associated model sensitivities to the use of FDDA, planetary boundary layer (PBL) turbulence physics, grid-explicit microphysics, a CPS, and enhanced horizontal diffusion. Some of the conclusions include the following: 1) Enhanced parameterized vertical mixing in the turbulent kinetic energy (TKE) turbulence scheme has shown marked improvements in the simulated fields. 2) Use of a CPS on the 4-km grid improved the precipitation and low-level wind results. 3) Use of the Hong and Pan Medium-Range Forecast PBL scheme showed larger model errors within the PBL and a clear tendency to predict much deeper PBL heights than the TKE scheme. 4) Combining observation-nudging FDDA with a CPS produced the best overall simulations. 5) Finer horizontal resolution does not always produce better simulations, especially in convectively unstable environments, and a new CPS suitable for 4-km resolution is needed. 6) Although use of current CPSs may violate their underlying assumptions related to the size of the convective element relative to the grid size, the gridpoint storm problem was greatly reduced by applying a CPS to the 4-km grid.

scholarly journals The Importance of the Boundary Layer Parameterization in the Prediction of Low-Level Convergence Lines

2008 ◽  
Vol 136 (6) ◽  
pp. 2173-2185 ◽  
Author(s):  
Gerald L. Thomsen ◽  
Roger K. Smith
Keyword(s):  
Boundary Layer ◽  
Mesoscale Model ◽  
State University ◽  
Pennsylvania State University ◽  
Low Level ◽  
Surface Pressure Distribution ◽  
Fifth Generation ◽  
Medium Range Forecast ◽  
The Arid Regions ◽  
Better Than

Abstract The importance of the boundary layer parameterization in the numerical prediction of low-level convergence lines over northeastern Australia is investigated. High-resolution simulations of convergence lines observed in one event during the 2002 Gulf Lines Experiment are carried out using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Calculations using five different parameterizations are compared with observations to determine the optimum scheme for capturing these lines. The schemes that give the best agreement with the observations are the three that include a representation of countergradient fluxes and a surface layer scheme based on Monin–Obukhov theory. One of these, the Medium-Range Forecast scheme, is slightly better than the other two, based on its ability to predict the surface pressure distribution. The findings are important for the design of mesoscale forecasting systems for the arid regions of Australia and elsewhere.

scholarly journals Evolution of a Cold Front Encountering Steep Quasi-2D Terrain: Coordinated Aircraft Observations on 8–9 December 2001 during IMPROVE-2

2005 ◽  
Vol 62 (10) ◽  
pp. 3559-3579 ◽  
Author(s):  
N. A. Bond ◽  
B. F. Smull ◽  
M. T. Stoelinga ◽  
C. P. Woods ◽  
A. Haase
Keyword(s):  
Doppler Radar ◽  
Mesoscale Model ◽  
Liquid Water Content ◽  
Horizontal Resolution ◽  
Second Phase ◽  
State University ◽  
Microphysical Properties ◽  
The Pacific ◽  
Aircraft Observations ◽  
Research Aircraft

Abstract Research aircraft observations from the 8–9 December 2001 case of the second phase of the Improvement of Microphysical Parameterization through Operational Verification Experiment (IMPROVE-2) describe the evolution of a wide cold-frontal rainband (WCFR) during its eastward advance from the Pacific coastline to a point 200 km inland over the Cascade Mountains of Oregon. This analysis has two objectives: first, to illustrate the rapid weakening of the circulation associated with a landfalling WCFR and the relationship of these changes to terrain-induced airflow modifications, and second, to quantify the degree to which this weakening impacted cloud microphysical properties such as liquid water content, ice particle concentrations, and precipitation rate. The kinematic structure of the WCFR is detailed using Doppler radar observations from a NOAA P-3 aircraft, while some concomitant cloud microphysical properties are documented using flight-level measurements from the University of Washington Convair-580 aircraft. An accompanying the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) control simulation (nested to a horizontal resolution of 4 km over the IMPROVE-2 domain) provides a mesosynoptic context and thermodynamic information to complement the aircraft observations. To the authors’ knowledge, this case study represents the most complete documentation obtained to date of the rapid modifications that may occur when a frontal rainband progresses from coastal waters into a region of prominent terrain.

On the Role of Sloping Terrain in the Forcing of the Great Plains Low-Level Jet

2010 ◽  
Vol 67 (8) ◽  
pp. 2690-2699 ◽  
Author(s):  
Thomas R. Parish ◽  
Larry D. Oolman
Keyword(s):  
Great Plains ◽  
Mesoscale Model ◽  
Horizontal Resolution ◽  
Inertial Oscillation ◽  
Western Boundary ◽  
Boundary Current ◽  
Wind Maximum ◽  
Low Level ◽  
Low Level Jet ◽  
Sloping Terrain

Abstract The summertime Great Plains low-level jet (LLJ) has been the subject of numerous investigations during the past several decades. Characteristics of the LLJ include nighttime development of a pronounced wind maximum of typically 15–20 m s−1 at levels 300–800 m above the surface and a clockwise rotation of the wind maximum during the course of the night. Maximum frequency of occurrence of the LLJ is found in the southern Great Plains. Theories proposed to explain the diurnal wind maximum of the Great Plains LLJ include inertial oscillation of the ageostrophic wind, the diurnal oscillation of the horizontal pressure field associated with heating and cooling of the sloping terrain, and the western boundary current interpretations. A simple equation system and output from the 12-km horizontal resolution Weather Research and Forecasting Nonhydrostatic Mesoscale Model (NAM) for July 2008 are used to provide evidence as to the importance of the Great Plains topography in driving the LLJ. Summertime heating of the sloping terrain is critical in establishing the climatological position for the Great Plains LLJ. Heating enhances the background geostrophic flow associated with the Bermuda high, resulting in a maximum low-level mean summertime flow over the Great Plains region. Maximum geostrophic winds in the NAM are found during late afternoon, providing a large background wind on which frictional decoupling can act. The nighttime LLJ maximum is the result of an inertial oscillation of the unbalanced components that arise fundamentally from frictional decoupling. Diurnal heating of the sloping terrain forces a cycle in the geostrophic wind that is out of phase with the wind maximum.

scholarly journals The Tornadic Supercell on the Kanto Plain on 6 May 2012: Polarimetric Radar and Surface Data Assimilation with EnKF and Ensemble-Based Sensitivity Analysis

2016 ◽  
Vol 144 (9) ◽  
pp. 3133-3157 ◽  
Author(s):  
Sho Yokota ◽  
Hiromu Seko ◽  
Masaru Kunii ◽  
Hiroshi Yamauchi ◽  
Hiroshi Niino
Keyword(s):  
Sensitivity Analysis ◽  
Relative Humidity ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Radar Data ◽  
Horizontal Resolution ◽  
Horizontal Wind ◽  
Spatial Density ◽  
Low Level

A tornadic supercell and associated low-level mesocyclone (LMC) observed on the Kanto Plain, Japan, on 6 May 2012 were predicted with a nonhydrostatic mesoscale model with a horizontal resolution of 350 m through assimilation of surface meteorological data (horizontal wind, temperature, and relative humidity) of high spatial density and C-band Doppler radar data (radial velocity and rainwater estimated from reflectivity and specific differential phase) with a local ensemble transform Kalman filter. With assimilation of both surface and radar data, a strong LMC was successfully predicted near the path of the actual tornado. When either surface or radar data were not assimilated, however, the LMC was not predicted. Therefore, both surface and radar data were essential for successful LMC forecasts. The factors controlling the strength of the predicted LMC, defined as a low-level maximum vertical vorticity, were clarified by an ensemble-based sensitivity analysis (ESA), which is a new approach for analyzing LMC intensification. The ESA showed that the strength of the LMC was sensitive to low-level convergence forward of the storm and to low-level relative humidity in the rear of the storm. Therefore, the correction of these low-level variables by assimilation of dense observations was found to be particularly important for forecasting and monitoring the LMC in the present case.

scholarly journals Evaluation of the Summertime Low-Level Winds Simulated by MM5 in the Central Valley of California

2010 ◽  
Vol 49 (11) ◽  
pp. 2230-2245 ◽  
Author(s):  
Sara A. Michelson ◽  
Irina V. Djalalova ◽  
Jian-Wen Bao
Keyword(s):  
Large Scale ◽  
Mesoscale Model ◽  
Central Valley ◽  
State University ◽  
Low Level ◽  
Fifth Generation ◽  
Southern Central ◽  
The Difference ◽  
Upper Level ◽  
And Control

Abstract A season-long set of 5-day simulations between 1200 UTC 1 June and 1200 UTC 30 September 2000 are evaluated using the observations taken during the Central California Ozone Study (CCOS) 2000 experiment. The simulations are carried out using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), which is widely used for air-quality simulations and control planning. The evaluation results strongly indicate that the model-simulated low-level winds in California’s Central Valley are biased in speed and direction: the simulated winds tend to have a stronger northwesterly component than observed. This bias is related to the difference in the observed and simulated large-scale, upper-level flows. The model simulations also show a bias in the height of the daytime atmospheric boundary layer (ABL), particularly in the northern and southern Central Valley. There is evidence to suggest that this bias in the daytime ABL height is not only associated with the large-scale, upper-level bias but also linked to apparent differences in the surface forcing.

scholarly journals Regional Model Simulations of the Bodélé Low-Level Jet of Northern Chad during the Bodélé Dust Experiment (BoDEx 2005)

2008 ◽  
Vol 21 (5) ◽  
pp. 995-1012 ◽  
Author(s):  
Martin C. Todd ◽  
Richard Washington ◽  
Srivatsan Raghavan ◽  
Gil Lizcano ◽  
Peter Knippertz
Keyword(s):  
Diurnal Cycle ◽  
Climate Models ◽  
Mesoscale Model ◽  
Regional Climate ◽  
Dust Emission ◽  
Horizontal Resolution ◽  
Emission Model ◽  
Low Level ◽  
Low Level Jet ◽  
Key Features

Abstract The low-level jet (LLJ) over the Bodélé depression in northern Chad is a newly identified feature. Strong LLJ events are responsible for the emission of large quantities of mineral dust from the depression, the world’s largest single dust source, and its subsequent transport to West Africa, the tropical Atlantic, and beyond. Accurate simulation of this key dust-generating atmospheric feature is, therefore, an important requirement for dust models. The objectives of the present study are (i) to evaluate the ability of regional climate models (RCMs) and global analyses/reanalyses to represent this feature, and (ii) to determine the driving mechanisms of the LLJ and its strong diurnal cycle. Observational data obtained during the Bodélé Dust Experiment (BoDEx 2005) are utilized for comparison. When suitably configured, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) RCM can represent very accurately many of the key features of the jet including the structure, diurnal cycle, and day-to-day variability. Surface winds are also well reproduced, including the peak winds, which activate dust emission. Model fidelity is, however, strongly dependent on the boundary layer parameterization scheme, surface roughness, and vertical resolution in the lowest layers. A model horizontal resolution of a few tens of kilometers is sufficient to resolve most of the key features of the LLJ, while in global analyses/reanalyses many features of the LLJ are not adequately represented. Idealized RCM simulations indicate that under strong synoptic forcing the surrounding orography of the Tibesti and Ennedi Mountains acts to focus the LLJ onto the Bodélé and to accelerate the jet by ∼40%. From the RCM experiments it is diagnosed that the pronounced diurnal cycle of the Bodélé LLJ is largely a result of varying eddy viscosity, with elevated heating/cooling over the Tibesti Mountains to the north as a second-order contribution.

scholarly journals Assimilation of DMSP and TOVS Satellite Soundings in a Mesoscale Model

2000 ◽  
Vol 39 (10) ◽  
pp. 1727-1741 ◽  
Author(s):  
Jordan G. Powers ◽  
Kun Gao
Keyword(s):  
Satellite Data ◽  
Mesoscale Model ◽  
Forecast Error ◽  
Model Performance ◽  
State University ◽  
Error Statistics ◽  
Infrared Observation ◽  
Fifth Generation ◽  
Defense Meteorological Satellite Program ◽  
Four Dimensional Data Assimilation

Abstract A modeling investigation explores the impacts of the assimilation of satellite-retrieved soundings on forecast error in the Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Simulations of the period of the U.S. Air Force’s Contrail Experiment (18–29 September 1995) vary the initialization method and datasets assimilated, the performance of first-guess reanalysis, the imposition of quality control (QC) on the satellite data, and the frequency of the model update cycle. MM5 experiments employing four-dimensional data assimilation (FDDA) are compared with a control experiment without FDDA. In the former, combinations of conventional surface and radiosonde observations and retrieved temperature and moisture soundings from the Defense Meteorological Satellite Program (DMSP) and Television and Infrared Observation Satellite Operational Vertical Sounder (TOVS) satellite instruments are assimilated. Forecast error statistics for the experiments are computed and analyzed. It is found that for retrieved temperatures the DMSP and TOVS sounding datasets used have similar, reasonable accuracy, but for retrieved dewpoints they display significant, and more differing, errors. Overall, the TOVS retrievals obtained are of poorer quality than are the DMSP retrievals. Sensitivity tests reveal that imposing a QC filter on the satellite data prior to assimilation does improve the resultant MM5 simulations. With such QC, it is found that assimilating DMSP and TOVS soundings with the methods used can significantly improve the forecasts of both temperature and moisture variables in the MM5. Model performance, however, can still reflect the relative quality of the satellite retrievals assimilated, with the lower-error DMSP data yielding better simulations than do the TOVS data. Tests exploring the reanalysis of first-guess fields obtained from FDDA show that it does benefit the short-term (0–12 h) forecast but that significant gains diminish thereafter.

A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part II: Application and Evaluation in a Mesoscale Meteorological Model

2007 ◽  
Vol 46 (9) ◽  
pp. 1396-1409 ◽  
Author(s):  
Jonathan E. Pleim
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Atmospheric Boundary Layer ◽  
Mesoscale Model ◽  
Evaluation Studies ◽  
Vertical Mixing ◽  
Model Performance ◽  
State University ◽  
Meteorological Model ◽  
Wind Profilers

Abstract A new combined local and nonlocal closure atmospheric boundary layer model called the Asymmetric Convective Model, version 2, (ACM2) was described and tested in one-dimensional form and was compared with large-eddy simulations and field data in Part I. Herein, the incorporation of the ACM2 into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is described. Model simulations using the MM5 with the ACM2 are made for the summer of 2004 and evaluated through comparison with surface meteorological measurements, rawinsonde profile measurements, and observed planetary boundary layer (PBL) heights derived from radar wind profilers. Overall model performance is as good as or better than similar MM5 evaluation studies. The MM5 simulations with the ACM2 compare particularly well to PBL heights derived from radar wind profilers during the afternoon hours. The ACM2 is designed to simulate the vertical mixing of any modeled quantity realistically for both meteorological models and air quality models. The next step, to be described in a subsequent article, is to incorporate the ACM2 into the Community Multiscale Air Quality (CMAQ) model for testing and evaluation.

scholarly journals Adding Four Dimensional Data Assimilation by Analysis Nudging to the Model for Prediction Across Scales – Atmosphere (Version 4.0)

2017 ◽  
Author(s):  
Orren Russell Bullock Jr. ◽  
Hosein Foroutan ◽  
Robert C. Gilliam ◽  
Jerold A. Herwehe
Keyword(s):  
Data Assimilation ◽  
Mesoscale Model ◽  
Global Analysis ◽  
Analysis Data ◽  
Global Scale ◽  
Model Errors ◽  
Near Surface ◽  
Target Values ◽  
Four Dimensional Data Assimilation ◽  
Reference Fields

Abstract. The Model for Prediction Across Scales – Atmosphere (MPAS-A) has been modified to allow four dimensional data assimilation (FDDA) by the nudging of temperature, humidity and wind toward target values predefined on the MPAS-A computational mesh. The addition of nudging allows MPAS-A to be used as a global-scale meteorological driver for retrospective air quality modeling. The technique of analysis nudging developed for the Penn State / NCAR Mesoscale Model, and later applied in the Weather Research and Forecasting model, is implemented in MPAS-A with adaptations for its unstructured Voronoi mesh. Reference fields generated from 1° × 1° National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data were used to constrain MPAS-A simulations on a 92–25 km variable-resolution mesh with refinement centered over the contiguous United States. Test simulations were conducted for January and July 2013 with and without FDDA, and compared to reference fields and near-surface meteorological observations. The results demonstrate that MPAS-A with analysis nudging has high fidelity to the reference data while still maintaining conservation of mass as in the unmodified model. The results also show that application of FDDA constrains model errors relative to 2 m temperature, 2 m water vapor mixing ratio, and 10 m wind speed such that they continue to be at or below the magnitudes found at the start of each test period.

scholarly journals Evaluation of Interregional Transport Using the MM5–SCIPUFF System

2004 ◽  
Vol 43 (12) ◽  
pp. 1864-1886 ◽  
Author(s):  
Aijun Deng ◽  
Nelson L. Seaman ◽  
Glenn K. Hunter ◽  
David R. Stauffer
Keyword(s):  
Mesoscale Model ◽  
Numerical Models ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Tracer Experiment ◽  
Plume Dispersion ◽  
State University ◽  
Wind Fields ◽  
The Impact ◽  
Horizontal Grid

Abstract Improved understanding of transport issues and source–receptor relationships on the interregional scale is dependent on reducing the uncertainties in the ability to define complex three-dimensional wind fields evolving in time. The numerical models used for this purpose have been upgraded substantially in recent years by introducing finer grid resolution, better representation of subgrid-scale physics, and practical four-dimensional data assimilation (FDDA) techniques that reduce the accumulation of errors over time. The impact of these improvements for interregional transport is investigated in this paper using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Second-Order Closure Integrated Puff (SCIPUFF) dispersion model to simulate the 1983 Cross-Appalachian Tracer Experiment (CAPTEX-83) episode 1 of 18–19 September 1983. Combining MM5 and SCIPUFF makes it possible to verify predicted tracer concentrations against observed surface concentrations collected during the CAPTEX-83 study. Conclusions from this study are as follows. 1) Not surprisingly, a baseline model configuration reflecting typical capabilities of the late 1980s (70-km horizontal grid, 15 vertical layers, older subgrid physics, and no FDDA) produced large meteorological errors that severely degraded the accuracy of the surface tracer concentrations predicted by SCIPUFF. 2) Improving the horizontal and vertical resolution of the MM5 to 12 km (typical for current operational model) and 32 layers led to some improvements in the statistical skill, but the further addition of more advanced physics produced much greater reductions of simulation errors. 3) The use of FDDA, along with 12-km resolution and improved physics, produced the overall best performance. 4) Further reduction of the horizontal grid size to 4 km had a detrimental effect on meteorological and plume-dispersion solutions in this case because of misrepresentation of convection associated with a cold front by the MM5's explicit moist physics.

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