Two-Dimensional Idealized Simulations of the Impact of Multiple Windward Ridges on Orographic Precipitation

2008 ◽  
Vol 65 (2) ◽  
pp. 509-523 ◽  
Author(s):  
Brian A. Colle
Keyword(s):  
Mesoscale Model ◽  
Two Dimensional ◽  
State University ◽  
Mountain Waves ◽  
Freezing Level ◽  
Fifth Generation ◽  
Warm Rain ◽  
Windward Slope ◽  
The Impact ◽  
Precipitation Enhancement

Abstract This paper presents two-dimensional (2D) idealized simulations at 1-km grid spacing using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in order to illustrate how a series of ridges along a broad windward slope can impact the precipitation distribution and simulated microphysics. The number of windward ridges for a 2000-m mountain of 50-km half-width is varied from 0 to 16 over a 150-km distance using different stratifications, freezing levels, uniform ambient flows, and ridge amplitudes. A few (200–400 m) windward ridges can enhance the precipitation locally over each ridge crest by a factor of 2–3. Meanwhile, a series of 8–16 ridges that are 200–400 m in height can increase the net precipitation averaged over the windward slope by 10%–35%. This average precipitation enhancement is maximized when the ridge spacing is relatively small (<20 km), since there is less time for subsidence drying within the valleys and the mountain waves become more evanescent, which favors a simple upward and downward motion couplet over each ridge. In addition, small ridge spacing is shown to have a synergistic effect on precipitation over the lower windward slope, in which an upstream ridge helps increase the precipitation over the adjacent downwind ridge. There is little net precipitation enhancement by the ridges for small moist Froude numbers (Fr < 0.8), since flow blocking limits the flow up and over each ridge. For a series of narrow ridges (∼10 km wide), the largest precipitation enhancement for a 500-mb freezing level occurs over lower windward slope of the barrier through warm-rain processes. In contrast, a 1000-mb freezing level has the largest precipitation enhancement over the middle and upper portions of a barrier for a series of narrow (∼10 km wide) ridges given the horizontal advection of snow aloft.

The Impact of Assimilating Dropwindsonde Data Deployed at Different Sites on Typhoon Track Forecasts

2013 ◽  
Vol 141 (8) ◽  
pp. 2669-2682 ◽  
Author(s):  
Boyu Chen ◽  
Mu Mu ◽  
Qin Xiaohao
Keyword(s):  
Mesoscale Model ◽  
Three Dimensional ◽  
Weather Research And Forecasting ◽  
Surveillance Program ◽  
State University ◽  
Optimal Perturbation ◽  
Fifth Generation ◽  
Typhoon Track ◽  
Adaptive Observation ◽  
The Impact

Abstract This study investigates the impacts on typhoon track forecasting by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and its three-dimensional variational data assimilation (3DVAR) system of assimilating dropwindsonde observational data acquired from different sites. All of the sonde data were obtained between 2004 and 2009 in the typhoon surveillance program Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR). Experiments were conducted to test the model's response to five scenarios involving differing dropwindsonde data inputs: 1) no dropwindsonde data, 2) all available dropwindsonde data, 3) data gathered in sensitive regions identified by the conditional nonlinear optimal perturbation (CNOP) approach, 4) data gathered in sensitive regions identified by the first singular vector (FSV) approach, and 5) several sondes selected at random. The results show that using dropwindsonde data based on CNOP sensitivity can lead to improvements in typhoon track forecasting similar to, and occasionally better than, those achieved by assimilating all of the available data. Both approaches offered greater benefits than the other three alternatives averagely. It is proposed that CNOP provides a suitable approach to determining sensitive regions during adaptive observation of typhoons. Similar results may be obtained if the sensitivity products developed using MM5 are employed in the Weather Research and Forecasting Model (WRF), suggesting that it is applicable to utilize sensitivity produced by MM5 in WRF.

scholarly journals Digital Filter Initialization for MM5

2006 ◽  
Vol 134 (4) ◽  
pp. 1222-1236 ◽  
Author(s):  
Min Chen ◽  
Xiang-Yu Huang
Keyword(s):  
Digital Filter ◽  
Mesoscale Model ◽  
Heavy Rain ◽  
State University ◽  
Initial Model ◽  
Pennsylvania State University ◽  
Fifth Generation ◽  
Beijing Institute ◽  
The Impact

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.

scholarly journals A Comparison of Two Tropical Cyclone Bogussing Schemes

2008 ◽  
Vol 23 (1) ◽  
pp. 194-204 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Ying Zhao ◽  
Bin Wang
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Vortex Structure ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Negative Impact ◽  
Initial Structure ◽  
State University ◽  
Fifth Generation ◽  
The Impact

Abstract The impact of two bogussing schemes on tropical cyclone (TC) forecasts is compared. One scheme for bogussing TCs into the initial conditions of the nonhydrostatic version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is proposed by NCAR and the Air Force Weather Agency (AFWA), and four-dimensional variational data assimilation technology is employed for the other bogus data assimilation (BDA) scheme. The initial vortex structure adjusted by the NCAR–AFWA (N–A) scheme is more physically realistic, while the BDA scheme produces an initial vortex structure that is more consistent with the model. The results from 41 forecasts of TCs occurring over the western North Pacific (WNP) in 2002 suggest that the adjustment of the initial structure in the BDA scheme produces a greater benefit to the subsequent track and intensity forecasts, and the improvements in the track and intensity forecasts are significant using the BDA scheme. It seems that when using a model with 45-km grid length, the N–A scheme has a negative impact on the track forecasts for the recurving TCs and on the intensity predictions after 24 h.

scholarly journals Wavelet Support Vector Machines for Forecasting Precipitation in Tropical Cyclones: Comparisons with GSVM, Regression, and MM5

2012 ◽  
Vol 27 (2) ◽  
pp. 438-450 ◽  
Author(s):  
Chih-Chiang Wei
Keyword(s):  
Statistical Models ◽  
Mesoscale Model ◽  
Gaussian Kernel ◽  
Support Vector ◽  
State University ◽  
Rainfall Prediction ◽  
Fifth Generation ◽  
Shihmen Reservoir ◽  
Reservoir Watershed ◽  
Lag Times

Abstract This study presents two support vector machine (SVM) based models for forecasting hourly precipitation during tropical cyclone (typhoon) events. The two SVM-based models are the traditional Gaussian kernel SVMs (GSVMs) and the advanced wavelet kernel SVMs (WSVMs). A comparison between the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and statistical models, including SVM-based models and linear regressions (regression), was made in terms of performance of rainfall prediction at the Shihmen Reservoir watershed in Taiwan. Data from 73 typhoons affecting the Shihmen Reservoir watershed were included in the analysis. This study designed six attribute combinations with different lag times for the forecast target. The modified RMSE, bias, and estimated threat score (ETS) results were employed to assess the predicted outcomes. Results show that better attribute combinations for typhoon climatologic characteristics and typhoon precipitation predictions occurred at 0-h lag time with modified RMSE values of 0.288, 0.257, and 0.296 in GSVM, WSVM, and the regression, respectively. Moreover, WSVM having average bias and ETS values close to 1.0 gave better predictions than did the GSVM and regression models. In addition, Typhoons Zeb (1998) and Nari (2001) were selected for comparison between the MM5 model output and the developed statistical models. Results showed that the MM5 tended to overestimate the peak and cumulative rainfall amounts while the statistical models were inclined to yield underestimations.

scholarly journals Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Mesoscale Model ◽  
State University ◽  
Motion Vectors ◽  
Geostationary Meteorological Satellite ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Data Assimilation Technique ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

scholarly journals Numerical Simulations of Seasonal Variations of Rainfall over the Island of Hawaii

2019 ◽  
Vol 58 (6) ◽  
pp. 1219-1232
Author(s):  
Yu-Fen Huang ◽  
Yi-Leng Chen
Keyword(s):  
Seasonal Variations ◽  
Mesoscale Model ◽  
Early Morning ◽  
State University ◽  
Pennsylvania State University ◽  
Reversed Flow ◽  
Trade Winds ◽  
Fifth Generation ◽  
Offshore Flow ◽  
Wake Zone

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.

scholarly journals A High-Resolution Simulation of Typhoon Rananim (2004) with MM5. Part I: Model Verification, Inner-Core Shear, and Asymmetric Convection

2008 ◽  
Vol 136 (7) ◽  
pp. 2488-2506 ◽  
Author(s):  
Qingqing Li ◽  
Yihong Duan ◽  
Hui Yu ◽  
Gang Fu
Keyword(s):  
High Resolution ◽  
Inner Core ◽  
Mesoscale Model ◽  
Lower Troposphere ◽  
Model Verification ◽  
Vertical Shear ◽  
State University ◽  
Surface Winds ◽  
Fifth Generation ◽  
Divergence Pattern

Abstract In this study, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is used to simulate Typhoon Rananim (2004) at high resolution (2-km grid size). The simulation agrees well with a variety of observations, especially for intensification, maintenance, landfall, and inner-core structures, including the echo-free eye, the asymmetry in eyewall convection, and the slope of the eyewall during landfall. The asymmetric feature of surface winds is also captured reasonably well by the model, as well as changes in surface winds and pressure near the storm center. The shear-induced vortex tilt and storm-relative asymmetric winds are examined to investigate how vertical shear affects the asymmetric convection in the inner-core region. The inner-core vertical shear is found to be nonunidirectional, and to induce a nonunidirectional vortex tilt. The distribution of asymmetric convection is, however, inconsistent with the typical downshear-left pattern for a deep-layer shear. Qualitative agreement is found between the divergence pattern and the storm-relative flow, with convergence (divergence) generally associated with asymmetric inflow (outflow) in the eyewall. The collocation of the inflow-induced lower-level convergence in the boundary layer and the lower troposphere and the midlevel divergence causes shallow updrafts in the western and southern parts of the eyewall, while the deep and strong upward motion in the southeastern portion of the eyewall is due to the collocation of the net convergence associated with the strong asymmetric flow in the midtroposphere and the inflow near 400 hPa and its associated divergence in the outflow layer above 400 hPa.

scholarly journals The Same-Source Parallel MM5

2000 ◽  
Vol 8 (1) ◽  
pp. 5-12 ◽  
Author(s):  
John Michalakes
Keyword(s):  
Shared Memory ◽  
Distributed Memory ◽  
Mesoscale Model ◽  
State University ◽  
Parallel Performance ◽  
Hybrid Parallelization ◽  
Beowulf Clusters ◽  
Penn State ◽  
Library Support ◽  
The Impact

Beginning with the March 1998 release of the Penn State University/NCAR Mesoscale Model (MM5), and continuing through eight subsequent releases up to the present, the official version has run on distributed -memory (DM) parallel computers. Source translation and runtime library support minimize the impact of parallelization on the original model source code, with the result that the majority of code is line-for-line identical with the original version. Parallel performance and scaling are equivalent to earlier, hand-parallelized versions; the modifications have no effect when the code is compiled and run without the DM option. Supported computers include the IBM SP, Cray T3E, Fujitsu VPP, Compaq Alpha clusters, and clusters of PCs (so-called Beowulf clusters). The approach also is compatible with shared-memory parallel directives, allowing distributed-memory/shared-memory hybrid parallelization on distributed-memory clusters of symmetric multiprocessors.

scholarly journals Influences of Asymmetric Heating on Hurricane Evolution in the MM5

2005 ◽  
Vol 62 (11) ◽  
pp. 3974-3992 ◽  
Author(s):  
J. Dominique Möller ◽  
Lloyd J. Shapiro
Keyword(s):  
Diabatic Heating ◽  
Mesoscale Model ◽  
State University ◽  
Short Term ◽  
Term Change ◽  
Passive Response ◽  
Tangential Wind ◽  
Small Change ◽  
The Impact

Abstract While previous idealized studies have demonstrated the importance of asymmetric atmospheric features in the intensification of a symmetric tropical cyclone vortex, the role of convectively generated asymmetries in creating changes in the azimuthally averaged cyclone is not well understood. In the present study the full-physics nonhydrostatic fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) is used to evaluate the influence of such asymmetries. Rather than adding winds and temperatures in balance with a specified potential vorticity (PV) asymmetry, or temperature perturbations themselves, to a symmetric vortex as in previous studies, a diabatic heating asymmetry is imposed on a spunup model hurricane. The impact of short-duration eyewall-scale monochromatic azimuthal wavenumber diabatic heating on the short- and long-term evolution of the azimuthally averaged vortex is evaluated, and a tangential wind budget is made to determine the mechanisms responsible for the short-term impact. It is found that the small eddy kick created by the additional diabatic heating asymmetry leads to a substantially amplified long-term change in the azimuthally averaged vortex, with episodes of strong relative weakening and strengthening following at irregular intervals. This behavior is diabatically controlled. It is also found that the symmetric secondary circulation can be active in creating short-term changes in the vortex, and is not simply a passive response as in previous studies with dry physics. A central conclusion of the study is that the structure of the spunup hurricane vortex, in particular preexisting asymmetric features, can have a substantial influence on the character of the response to an additional diabatic heating asymmetry. The results also imply that a small change in the factors that control convective activity will have a substantial lasting consequence for the intensification of a hurricane.

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 ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Sedimentation Velocity ◽  
State University ◽  
Pennsylvania State University ◽  
Ice Clouds ◽  
Water Ice ◽  
Fifth Generation ◽  
Profile Inversion ◽  
Selection Of

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.

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