scholarly journals The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at the SIRTA Atmospheric Observatory

2006 ◽  
Vol 134 (3) ◽  
pp. 897-918 ◽  
Author(s):  
M. Chiriaco ◽  
R. Vautard ◽  
H. Chepfer ◽  
M. Haeffelin ◽  
J. Dudhia ◽  
...  

Abstract The ability of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate midlatitude ice clouds is evaluated. Model outputs are compared to long-term meteorological measurements by active (radar and lidar) and passive (infrared and visible fluxes) remote sensing collected at an atmospheric observatory near Paris, France. The goal is to understand which of four microphysical schemes is best suited to simulate midlatitude ice clouds. The methodology consists of simulating instrument observables from the model outputs without any profile inversion, which allows the authors to use fewer assumptions on microphysical and optical properties of ice particles. Among the four schemes compared in the current study, the best observation-to-simulations scores are obtained with Reisner et al. provided that the particles’ sedimentation velocity from Heymsfield and Donner is used instead of that originally proposed. For this last scheme, the model gives results close to the measurements for clouds with medium optical depth of typically 1 to 3, whatever the season. In this configuration, MM5 simulates the presence of midlatitude ice clouds in more than 65% of the authors’ selection of observed cloud cases. In 35% of the cases, the simulated clouds are too persistent whatever the microphysical scheme and tend to produce too much solid water (ice and snow) and not enough liquid water.

2019 ◽  
Vol 58 (6) ◽  
pp. 1219-1232
Author(s):  
Yu-Fen Huang ◽  
Yi-Leng Chen

AbstractThe seasonal variations of rainfall over the island of Hawaii are studied using the archives of the daily model run from the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) from June 2004 to February 2010. Local effects mainly drive the rainfall on the Kona coast in the early morning and the lower slopes in the afternoon. During the summer, the incoming trade winds are more persistent and moister than in winter. The moisture content in the wake zone is higher than open-ocean values because of the convergent airflow associated with dual counterrotating vortices. As the westerly reversed flow moves toward the Kona coast, it decelerates with increasing moisture and a moisture maximum over the coastal area, especially in the afternoon hours in summer months. The higher afternoon rainfall on the Kona lower slopes in summer than in winter is caused by a moister (>6 mm) westerly reversed flow bringing moisture inland and merging with a stronger upslope flow resulting from solar heating. Higher nocturnal rainfall off the Kona coast in summer than in winter is caused by the low-level convergence between a moister westerly reversed flow and offshore flow. On the windward slopes, the simulated rainfall accumulation in winter is higher because of frequently occurring synoptic disturbances during the winter storm season. Nevertheless, early morning rainfall along the windward coast and afternoon rainfall over the windward slopes of the Kohala Mountains is lower in winter because the incoming trades are drier.


2006 ◽  
Vol 63 (1) ◽  
pp. 19-42 ◽  
Author(s):  
Scott A. Braun ◽  
Michael T. Montgomery ◽  
Zhaoxia Pu

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is used to simulate Hurricane Bonnie at high resolution (2-km spacing) in order to examine how vertical wind shear impacts the distribution of vertical motion in the eyewall on both the storm and cloud scale. As in many previous studies, it is found here that the shear produces a wavenumber-1 asymmetry in the time-averaged vertical motion and rainfall. Several mechanisms for this asymmetry are evaluated. The vertical motion asymmetry is qualitatively consistent with an assumed balance between horizontal vorticity advection by the relative flow and stretching of vorticity, with relative asymmetric inflow (convergence) at low levels and outflow (divergence) at upper levels on the downshear side of the eyewall. The simulation results also show that the upward motion portion of the eyewall asymmetry is located in the direction of vortex tilt, consistent with the vertical motion that required to maintain dynamic balance. Variations in the direction and magnitude of the tilt are consistent with the presence of a vortex Rossby wave quasi mode, which is characterized by a damped precession of the upper vortex relative to the lower vortex. While the time-averaged vertical motion is characterized by ascent in a shear-induced wavenumber-1 asymmetry, the instantaneous vertical motion is typically associated with deep updraft towers that generally form on the downtilt-right side of the eyewall and dissipate on the downtilt-left side. The updrafts towers are typically associated with eyewall mesovortices rotating cyclonically around the eyewall and result from an interaction between the shear-induced relative asymmetric flow and the cyclonic circulations of the mesovortices. The eyewall mesovortices may persist for more than one orbit around the eyewall and, in these cases, can initiate multiple episodes of upward motion.


2011 ◽  
Vol 26 (1) ◽  
pp. 26-43 ◽  
Author(s):  
P. Goswami ◽  
S. Mallick

Abstract One factor that limits skill of the numerical models is the bias in the model forecasts with respect to observations. Similarly, while the mesoscale models today can support horizontal grid spacing down to a few kilometers or fewer, downscaling of model forecasts to arrive at station-scale values will remain a necessary step for many applications. While generic improvement in model skill requires parallel and comprehensive development in model and other forecast methodology, one way of achieving skill in station-scale forecasts without (intensive effort) calibration of the model is to implement an objective bias correction (referred to as debiasing). This study shows that a nonlinear objective debiasing can transform zero-skill forecasts from a mesoscale model [fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)] to forecasts with significant skill. Twelve locations over India, representing urban sites in different geographical conditions, during May–August 2009 were considered. The model MM5 was integrated for 24 h with initial conditions from the National Centers for Environmental Prediction Global Forecast System (final) global gridded analysis (FNL) for each of the days of May–August 2009 in a completely operational setting (without assuming any observed information on dynamics beyond the time of the initial condition). It is shown that for all the locations and the four months, the skill of the debiased forecast is significant against essentially zero skill of raw forecasts. The procedure provides an applicable forecast strategy to attain realizable significant skill in station-scale forecasts. Potential skill, derived using in-sample data for calibrating the debiasing parameters, shows promise of further improvement with large samples.


2006 ◽  
Vol 134 (7) ◽  
pp. 1987-2008 ◽  
Author(s):  
Sytske K. Kimball ◽  
F. Carroll Dougherty

Abstract In the course of studying the development of hurricanes using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), a relationship between storm intensity and the distribution of vertical levels became apparent, even when the same total number of sigma levels was used. A specific case of an idealized hurricane, on an f plane, in a quiescent environment, with constant and uniform SST of 28°C, was used to study the sensitivity of hurricane structure and evolution to the distribution of sigma levels. The distribution of vertical levels in the inflow, outflow, and middle layers of the atmosphere clearly affects the intensity, size, and structure of the storms, causing certain physical processes to be under- or overresolved. A well-resolved outflow layer is found to be necessary for proper storm intensification, while a well-resolved inflow layer does not necessarily correspond to an intense storm. In fact, when a well-resolved inflow layer is coupled with a poorly resolved outflow layer, a particularly weak storm evolves. When too few levels are assigned to the upper layer, the storm’s outflow is restricted, causing the eyewall column to become statically stable until surface fluxes can replenish low-level equivalent potential temperature content. Convection in the eyewall and compensating subsidence in the eye occur at a moderate rate and weak storms evolve. However, too few levels in the planetary boundary layer (PBL) can cause a storm to overintensify because of overestimated surface fluxes. When such a PBL is coupled with a poorly resolved outflow, the excessive surface fluxes can compensate for the stifled secondary circulation. Hence, this storm may develop to an expected intensity, but for the wrong reasons. Better guidelines for vertical-level distribution in numerical models, perhaps developed from observations of real-case hurricanes, are required.


2006 ◽  
Vol 23 (3) ◽  
pp. 424-436 ◽  
Author(s):  
Frank H. Ruggiero ◽  
John Michalakes ◽  
Thomas Nehrkorn ◽  
George D. Modica ◽  
Xiaolei Zou

Abstract Updated versions of the Tangent Linear Model (TLM) and adjoint of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) have been developed and are now available to the meteorological community. The previous version of the MM5 TLM and adjoint were designed for single-processor computer architectures, based on version 1 of MM5, and were hand coded, which made it difficult to maintain up-to-date versions of the TLM and the adjoint as MM5 evolved. The new TLM and adjoint are based on version 3 of MM5 and run efficiently on multiple-processor computers. The TLM and adjoint were developed with the aid of the Tangent Linear and Adjoint Model Compiler (TAMC) automatic code generator. While some manual intervention is still necessary, the use of the automatic code generator can significantly speed code development and lower code maintenance costs. The new TLM and adjoint contain most of the physics packages and observation operators that were available in the MM5 version 1 TLM and adjoint. The new adjoint has been combined with the MM5 version 3 nonlinear model and an updated minimization module in a four-dimensional variational data assimilation analysis configuration. Accuracy of the new TLM and adjoint has been verified by individual unit and system tests as well as comparisons with the adjoint from MM5 version 1. Timing tests showed substantial decreases in time to solution when increasing the number of processors devoted to the problem.


2009 ◽  
Vol 137 (2) ◽  
pp. 505-524 ◽  
Author(s):  
Hyun Mee Kim ◽  
Byoung-Joo Jung

Abstract In this study, the structure and evolution of total energy singular vectors (SVs) of Typhoon Usagi (2007) are evaluated using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) and its tangent linear and adjoint models with a Lanczos algorithm. Horizontal structures of the initial SVs following the tropical cyclone (TC) evolution suggest that, relatively far from the region of TC recurvature, SVs near the TC center have larger magnitudes than those in the midlatitude trough. The SVs in the midlatitude trough region become dominant as the TC passes by the region of recurvature. Increasing magnitude of the SVs over the midlatitude trough regions is associated with the extratropical transition of the TC. While the SV sensitivities near the TC center are mostly associated with warming in the midtroposphere and inflow toward the TC along the edge of the subtropical high, the SV sensitivities in the midlatitude are located under the upper trough with upshear-tilted structures and associated with strong baroclinicity and frontogenesis in the lower troposphere. Given the results in this study, sensitive regions for adaptive observations of TCs may be different following the TC development stage. Far from the TC recurvature, sensitive regions near TC center may be important. Closer to the TC recurvature, effects of the midlatitude trough become dominant and the vertical structures of the SVs in the midlatitude are basically similar to those of extratropical cyclones.


2006 ◽  
Vol 134 (4) ◽  
pp. 1222-1236 ◽  
Author(s):  
Min Chen ◽  
Xiang-Yu Huang

Abstract In this paper several configurations of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), which is implemented at Beijing Institute of Urban Meteorology in China, are used to demonstrate the initial noise problem caused either by interpolating global model fields onto an MM5 grid or by using MM5 objective analysis schemes. An implementation of a digital filter initialization (DFI) package to MM5 is then documented. A heavy rain case study and intermittent data assimilation experiments are used to assess the impact of DFI on MM5 forecasts. It is shown that DFI effectively filters out the noise and produces a balanced initial model state. It is also shown that DFI improves the spinup aspects for precipitation, leading to better scores for short-range precipitation forecasts. The issues related to the initialization of variables that are not observed and/or analyzed, in particular those for nonhydrostatic quantities, are discussed.


2008 ◽  
Vol 136 (6) ◽  
pp. 2173-2185 ◽  
Author(s):  
Gerald L. Thomsen ◽  
Roger K. Smith

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.


2005 ◽  
Vol 133 (12) ◽  
pp. 3517-3526 ◽  
Author(s):  
Martin Stuefer ◽  
Xiande Meng ◽  
Gerd Wendler

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is being used for forecasting the atmospheric layers of aircraft condensation trail (contrail) formation. Contrail forecasts are based on a conventional algorithm describing the adiabatic mixing of aircraft exhaust with environmental air. Algorithm input data are MM5-forecasted temperature and humidity values at defined pressure or sigma levels, and an aircraft-relevant contrail factor that is derived statistically from a contrail observation database. For comparison purposes a mean overlap (MO), which is a parameter quantifying the overlap between forecasted contrail layers and contrail layers derived from radiosonde measurements, is introduced. Mean overlap values are used to test for the altitude and thickness of forecasted contrail layers. Contrail layers from Arctic MM5 and Air Force Weather Agency (AFWA) MM5 models agree well with contrail layers derived from corresponding radiosonde measurements for certain forecast periods; a steady decrease of the MO shows a decrease of contrail forecast accuracy with the increasing forecast period. Mean overlaps around 82% indicate reasonable results for the 48-h forecasts. Verification of MM5 with actual contrail observations shows a slightly better performance of Arctic MM5. A possible dry bias might occur in humidity measurements at low temperature levels due to temperature-dependence errors of the humidity sensor polymer, which might also affect forecasts of humidity of the upper troposphere or lower stratosphere. Despite this fact, this contrail verification study shows hit rates higher than 82% within forecast periods up to 36 h using Arctic MM5.


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