scholarly journals Evaluation of Snow Depth and Soil Temperatures Predicted by the Hydro–Thermodynamic Soil–Vegetation Scheme Coupled with the Fifth-Generation Pennsylvania State University–NCAR Mesoscale Model

2005 ◽  
Vol 44 (12) ◽  
pp. 1827-1843 ◽  
Author(s):  
Balachandrudu Narapusetty ◽  
Nicole Mölders
Keyword(s):  
Soil Temperature ◽  
Snow Depth ◽  
Coupled Model ◽  
State University ◽  
Baltic Region ◽  
Pennsylvania State University ◽  
Fifth Generation ◽  
Soil Temperatures ◽  
The Baltic ◽  
Better Than

Abstract The Hydro–Thermodynamic Soil–Vegetation Scheme (HTSVS) coupled in a two-way mode with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Meteorological Model (MM5) is evaluated for a typical snowmelt episode in the Baltic region by means of observations at 25 soil temperature, 355 snow-depth, and 344 precipitation sites that have, in total, 1000, 1775, and 1720 measurements, respectively. The performance with respect to predicted near-surface meteorological fields is evaluated using reanalysis data. Snow depth depends on snow metamorphism, sublimation, and snowfall. Because in the coupled model these processes are affected by the predicted surface radiation fluxes and cloud and precipitation processes, sensitivity studies are performed with two different cloud microphysical schemes and/or radiation schemes. Skill scores are calculated as a quality measure for the coupled model’s performance for a typical forecast range of 120 h for a typical spring (snowmelt) weather situation in the Baltic region. Discrepancies between predicted and observed snow-depth changes relate to the coupling. Enhanced water supply to the atmosphere, which results from water that was assumed to be open in MM5 but was actually ice covered in nature, finally leads to an overestimation of snowfall (input to HTSVS) and changes in snow depth (output). The resolution-dependent discrepancies between the terrain height in the model and real world also lead to snowfall where none occurred. For heavy snowfall the performance of the coupled model with respect to predicted snow-depth changes becomes nearly independent of the choice of the cloud microphysical and radiation schemes. As compared with observed changes in snow depth, the coupled model simulation using the Schultz scheme in conjunction with the radiation scheme from the Community Climate Model, version 2, (CCM2) predicts snow-depth changes of less than 2.5 mm considerably better than the other combinations that were tested. For thick snowpacks, the accuracy of the snow-depth decrease resulting from metamorphism strongly depends on the initial value of snow density. The coupled model acceptably captures the soil temperature diurnal cycles, the observed soil temperature increase with time, and the soil temperature behavior with depth. In general, discrepancies between simulated and observed soil temperatures decrease with soil depth. Simulations performed with the so-called CLOUD radiation scheme capture soil temperature minima and maxima better than do simulations performed with the CCM2 scheme.

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.

The effect of soil temperature and light on sprouting and rooting of root cuttings of hybrid aspen clones

2005 ◽  
Vol 35 (11) ◽  
pp. 2671-2678 ◽  
Author(s):  
N Stenvall ◽  
T Haapala ◽  
S Aarlahti ◽  
P Pulkkinen
Keyword(s):  
Soil Temperature ◽  
Populus Tremuloides ◽  
Hybrid Aspen ◽  
Light Conditions ◽  
Dark Treatment ◽  
Sand Mixture ◽  
Negative Effect ◽  
Soil Temperatures ◽  
Time Required ◽  
Better Than

Root cuttings from five clones of hybrid aspen (Populus tremula L. × Populus tremuloides Michx.) obtained from 2-year-old stock plants were grown in a peat–sand mixture (soil) at four soil temperatures (18, 22, 26, and 30 °C). Half of the cuttings were grown in light and the rest in darkness. The root cuttings that were grown at the highest soil temperature sprouted and rooted significantly better than the cuttings grown at the lower temperatures. Light did not affect the sprouting of root cuttings but did have a negative effect on their rooting. Moreover, the clones varied significantly in sprouting and rooting percentages, as well as in the time required for sprouting. In general, higher soil temperatures hastened sprouting of the cuttings. Sprouting was also faster in the light than in the dark treatment. Differences in soil temperature, light conditions, or clone had no significant effect on rooting time.

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 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.

scholarly journals High-Resolution Simulation of Hurricane Bonnie (1998). Part I: The Organization of Eyewall Vertical Motion

2006 ◽  
Vol 63 (1) ◽  
pp. 19-42 ◽  
Author(s):  
Scott A. Braun ◽  
Michael T. Montgomery ◽  
Zhaoxia Pu
Keyword(s):  
High Resolution ◽  
Mesoscale Model ◽  
Dynamic Balance ◽  
Vertical Wind Shear ◽  
Vertical Motion ◽  
State University ◽  
Upward Motion ◽  
Pennsylvania State University ◽  
Fifth Generation ◽  
Hurricane Bonnie

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.

scholarly journals Objective Bias Correction for Improved Skill in Forecasting Diurnal Cycles of Temperature over Multiple Locations: The Summer Case

2011 ◽  
Vol 26 (1) ◽  
pp. 26-43 ◽  
Author(s):  
P. Goswami ◽  
S. Mallick
Keyword(s):  
Bias Correction ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Numerical Models ◽  
State University ◽  
Pennsylvania State University ◽  
Diurnal Cycles ◽  
Fifth Generation ◽  
Comprehensive Development ◽  
Environmental Prediction

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.

scholarly journals The Sensitivity of Idealized Hurricane Structure and Development to the Distribution of Vertical Levels in MM5

2006 ◽  
Vol 134 (7) ◽  
pp. 1987-2008 ◽  
Author(s):  
Sytske K. Kimball ◽  
F. Carroll Dougherty
Keyword(s):  
Mesoscale Model ◽  
Numerical Models ◽  
Potential Temperature ◽  
Surface Fluxes ◽  
State University ◽  
Pennsylvania State University ◽  
Fifth Generation ◽  
Intense Storm ◽  
Moderate Rate ◽  
Vertical Level

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.

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