Nonhydrostatic Mesoscale Model Research Articles

The occurrence of a tornado in Serbia on 31 march 2013

Tornado occurs very rarely in the territory of Serbia. The occurrence of a tornado above Torda (Vojvodina, Serbia) on 31 March 2013 indicted the importance of monitoring such a dangerous weather phenomenon, knowing its characteristics and forecasting it. This paper analyzes the synoptic conditions and vertical structure of the atmosphere that prevailed during the development of a supercell with a tornado. Changes in temperature and air pressure are presented on mesoscale maps. The analysis was performed by using the Nonhydrostatic Mesoscale Model (NMM). The tornado occurrence was monitored via satellite images and radar characteristics of a supercell. The cause of tornadogenesis has been ascertained. According to the EF scale, the tornado reached F0 intensity. Damages to roofs, power lines, trees and cars caused by the wind (>35ms-1) are also presented.

Verification and Calibration of Neighborhood and Object-Based Probabilistic Precipitation Forecasts from a Multimodel Convection-Allowing Ensemble

Abstract Neighborhood and object-based probabilistic precipitation forecasts from a convection-allowing ensemble are verified and calibrated. Calibration methods include logistic regression, one- and two-parameter reliability-based calibration, and cumulative distribution function (CDF)-based bias adjustment. Newly proposed object-based probabilistic forecasts for the occurrence of a forecast object are derived from the percentage of ensemble members with a matching object. Verification and calibration of single- and multimodel subensembles are performed to explore the effect of using multiple models. The uncalibrated neighborhood-based probabilistic forecasts have skill minima during the afternoon convective maximum. Calibration generally improves the skill, especially during the skill minima, resulting in positive skill. In general all calibration methods perform similarly, with a slight advantage of logistic regression (one-parameter reliability based) calibration for 1-h (6 h) accumulations. The uncalibrated object-based probabilistic forecasts are, in general, less skillful than the uncalibrated neighborhood-based probabilistic forecasts. Object-based calibration also results in positive skill at all lead times. For object-based calibration the skill is significantly different among the calibration methods, with the logistic regression performing the best and CDF-based bias adjustment performing the worst. For both the neighborhood and object-based probabilistic forecasts, the impact of using 10 or 25 days of training data for calibration is generally small and is most significant for the two-parameter reliability-based method. An uncalibrated Advanced Research Weather Research and Forecasting Model (ARW-WRF) subensemble is significantly more skillful than an uncalibrated WRF Nonhydrostatic Mesoscale Model (NMM) subensemble. The difference is reduced by calibration. The multimodel subensemble only shows an advantage for the neighborhood-based forecasts beyond 1-day lead time and shows no advantage for the object-based forecasts.

Numerical simulation of severe local storms over east India using WRF-NMM mesoscale model

A common feature of the weather during the pre-monsoon season (March–May) over the east and northeast India is the outburst of severe local storms which have significant socio-economic impact due to loss of lives and properties. Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal scales and the inherent non-linearity of their dynamics and physics. In the present study, an attempt has been made to simulate severe local storms that occurred over east India during STORM field experiments 2007, 2009 and 2010, using Non-hydrostatic Mesoscale Model (NMM) and validate the model results with observation. This study shows that the NMM model holds better promise for prediction of thunderstorm with reasonable accuracy. The intensity of rainfall rates is in good agreement with the observation. The model has well captured the stability indices, which act as indicators of severe convective activity. The surface temperature and relative humidity over Kolkata are reasonably well simulated by the NMM model even though one hour time lag or lead exists. The model simulated well the updraft and downdraft over Kolkata, which is an important phenomenon related to thunderstorm life cycle. From the model simulated spatial plots of composite radar reflectivity and cloud top temperature, we can see that the model has also been able to capture the movement of thunder squall. The results of these analyses determined that the 3km WRF-NMM model has good skill when it comes to the thunderstorm simulation.

Comparative evaluation of the impact of WRF–NMM and WRF–ARW meteorology on CMAQ simulations for O3 and related species during the 2006 TexAQS/GoMACCS campaign

In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related precursors has been comparatively evaluated over the eastern United States using surface network (AIRNow) data and over the Texas area with the intensive observations obtained by NOAA aircraft P–3 flights and ship during the 2006 TexAQS/GoMACCS campaign. The NMM–CMAQ and ARW–CMAQ models were run on the basis of their original grid structures of the meteorological models. The results at the AIRNow surface sites showed that the model performance for ARW–CMAQ and NMM–CMAQ models was similar and reasonable for the high maximum 8–hr O3 concentration range (>40ppbv) with slightly better performance for ARW–CMAQ [the normalized mean bias (NMB) values of ARW–CMAQ and NMM–CMAQ are 8.1 and 9.4%, respectively]. The results of the evaluation using aircraft observations over the Houston–Galveston–Brazoria and Dallas metropolitan areas revealed that both models had similar performances for different chemical species (O3, CO, PAN, NO2, NO, NOX, HNO3, NOY and ethylene) as both models use the same chemical mechanism and emissions. Both models reproduced the vertical variation patterns of the observed air temperature and water vapor well with the slightly lower values for the ARW–CMAQ model. The evaluation results with ship observations over the Gulf of Mexico showed that both models captured, with a good deal of accuracy, the temporal variations and broad synoptic change seen in the observed O3, NOY, CO and O3+NO2 with the mean NMB value <25% most of the time.

The diagnosis of severe thunderstorms with high-resolution WRF model

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’westers’(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region.

Characteristics of the asymmetric flow of Tropical Cyclone Shanshan (2006) during its turning and intensification period

In this paper, characteristics of the asymmetric flow of Tropical Cyclone (TC) Shanshan (2006) during its turning and intensification period over the oceanic area east of Taiwan are investigated, based on the simulation results from the nonhydrostatic mesoscale model WRF (Weather Research and Forecasting). It is found that the symmetric flow strengthened as the TC intensified, whereas the amplitude of the asymmetric flow of wavenumber 2 increased more significantly, which was strong enough to be comparable with or even exceed that of wavenumber 1, becoming the main part of the asymmetric flow sometimes. The asymmetric waves rotated around the TC center mainly counterclockwise. The closer to the center, the faster the asymmetric waves rotated. Moreover, the asymmetric flow rotated rapidly (slowly) during the slow (rapid) intensification of the TC, and the radial wavenumber showed an increase during the TC intensification. Furthermore, because of the superposition of intensified symmetric flow with the positive perturbation of the asymmetric flow, the maximum wind speed of TC Shanshan became larger. During the merger of the double eyewalls of Shanshan, the symmetric flow showed less increase in strength and the intensification of maximum wind speed was mainly related to the energy accumulation caused by the phase change of the asymmetric waves. The energy accumulation was realized when the asymmetric waves altered the strength and distribution of the inner and outer maximum wind cores, leading to the combination of the inner and outer eyewalls and eventually resulting in the intensification of the TC.

Object-Based Evaluation of a Storm-Scale Ensemble during the 2009 NOAA Hazardous Weather Testbed Spring Experiment

Abstract Object-based verification of deterministic forecasts from a convection-allowing ensemble for the 2009 NOAA Hazardous Weather Testbed Spring Experiment is conducted. The average of object attributes is compared between forecasts and observations and between forecasts from subensembles with different model dynamics. Forecast accuracy for the full ensemble and the subensembles with different model dynamics is also evaluated using two object-based measures: the object-based threat score (OTS) and the median of maximum interest (MMI). Forecast objects aggregated from the full ensemble are generally more numerous, have a smaller average area, more circular average aspect ratio, and more eastward average centroid location than observed objects after the 1-h lead time. At the 1-h lead time, forecast objects are less numerous than observed objects. Members using the Advanced Research Weather Research and Forecasting Model (ARW) have fewer objects, more linear average aspect ratio, and smaller average area than members using the Nonhydrostatic Mesoscale Model (NMM). The OTS aggregated from the full ensemble is more consistent with the diurnal cycles of the traditional equitable threat score (ETS) than the MMI because the OTS places more weight on large objects, while the MMI weights all objects equally. The group of ARW members has higher OTS than the group of NMM members except at the 1-h lead time when the group of NMM members has more accurate maintenance and evolution of initially present precipitation systems provided by radar data assimilation. The differences between the ARW and NMM accuracy are more pronounced with the OTS than the MMI and the ETS.

Wildfire and the atmosphere: Modelling the chemical and dynamic interactions at the regional scale

Abstract Forest fires release significant amounts of trace gases and aerosols into the atmosphere. Depending on meteorological conditions, fire emissions can efficiently reduce air quality and visibility, even far away from emission sources. In 2005, an arson forest fire burned nearly 700 ha near Lancon-de-Provence, southeast France. This paper explores the impact of this Mediterranean fire on the atmospheric dynamics and chemistry downwind of the burning region. The fire smoke plume was observed by the MODIS-AQUA instrument several kilometres downwind of the burning area out of the Mediterranean coast. Signatures of the fire plume on air pollutants were measured at surface stations in southeastern France by the air quality network AtmoPACA. Ground-based measurements revealed unusually high concentrations of aerosols and a well marked depletion of ozone concentrations on the day of the fire. The Lancon-de-Provence fire propagation was successfully simulated by the semi-physical fire spread model ForeFire. ForeFire provided the burnt area at high temporal and spatial resolutions. The burnt areas were scaled to compute the fire heat and water vapour fluxes in the three-dimensional meso-scale non-hydrostatic meteorological model MesoNH. The simulated fire plume kept confined in the boundary layer with high values of turbulent kinetic energy. The plume was advected several kilometres downwind of the ignition area by the Mistral winds in accordance with the MODIS and AtmoPACA observations. The vertical plume development was found to be more sensitive to the sensible heat flux than to the fire released moisture. The burnt area information is also used to compute emissions of a fire aerosol-like tracer and gaseous pollutants, using emission factors for Mediterranean vegetation. The coupled model simulated high concentrations of the fire aerosol-like tracer downwind of the burning zone at the right timing compared to ground-based measurements. A chemical reaction mechanism was coupled on-line to the MesoNH model to account for gaseous chemistry evolution in the fire plume. High levels of ozone precursors (NO x , CO) were simulated in the smoke plume which led to the depletion of ozone levels above and downwind of the burning zone. This depletion of ozone was indeed observed at ground-based stations but with a higher impact than simulated. The difference may be explained by the simplified design of the model with no anthropogenic sources and no interaction of the smoke aerosols with the photolysis rates. Ozone production was modelled tens of kilometres downwind of the ignition zone out of the coast.

Impact of Parameterization of Physical Processes on Simulation of Track and Intensity of Tropical Cyclone Nargis (2008) with WRF-NMM Model

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

Atmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model – Part 1: Model description, annual simulations and evaluation

Abstract. We describe and evaluate the NMMB/BSC-Dust, a new dust aerosol cycle model embedded online within the NCEP Non-hydrostatic Multiscale Model (NMMB). NMMB is a further evolution of the operational Non-hydrostatic Mesoscale Model (WRF-NMM), which together with other upgrades has been extended from meso to global scales. Its unified non-hydrostatic dynamical core is prepared for regional and global simulation domains. The new NMMB/BSC-Dust is intended to provide short to medium-range weather and dust forecasts from regional to global scales and represents a first step towards the development of a unified chemical-weather model. This paper describes the parameterizations used in the model to simulate the dust cycle including sources, transport, deposition and interaction with radiation. We evaluate monthly and annual means of the global configuration of the model against the AEROCOM dust benchmark dataset for year 2000 including surface concentration, deposition and aerosol optical depth (AOD), and we evaluate the daily AOD variability in a regional domain at high resolution covering Northern Africa, Middle East and Europe against AERONET AOD for year 2006. The NMMB/BSC-Dust provides a good description of the horizontal distribution and temporal variability of the dust. Daily AOD correlations at the regional scale are around 0.6–0.7 on average without dust data assimilation. At the global scale the model lies within the top range of AEROCOM dust models in terms of performance statistics for surface concentration, deposition and AOD. This paper discusses the current strengths and limitations of the modeling system and points towards future improvements.

Simulation of tornado over Orissa (India) on March 31, 2009, using WRF–NMM model

A severe thunderstorm produced a tornado (F3 on the Fujita-Pearson scale), which affected Rajkanika block of Kendrapara district of Orissa in the afternoon of March 31, 2009. The devastation caused by the tornado consumed 15 lives and left several injured with huge loss of property. The meteorological conditions that led to this tornado have been analyzed. An attempt is also made to simulate this rare event using Non-hydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system with a spatial resolution of 4 km for a period of 24 h, starting at 0000 UTC of March 31, 2009. The atmospheric settings resulted from synoptic, surface, upper air, satellite and radar echo studies were favorable for the occurrence of a severe thunderstorm activity over Rajkanika. The model-simulated meteorological parameters are consistent with each other, and all are in good agreement with the observation in terms of the region of occurrence of the intense convective activity. The model has well captured the vertical motion. The core of the strongest winds is shown to be very close to the site of actual occurrence of the event. The wind speed is not in good agreement with the observation as it has shown the strongest wind of only 20 ms−1, against the estimated wind speed of 70 ms−1. The spatial distributions as well as intensity of rainfall rates are in good agreement with the observation as model simulated 35.4 mm against the observed rainfall of 41 mm over Chandbali. The results of these analyses demonstrated the capability of high-resolution WRF–NMM model in simulation of severe thunderstorm events.

Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

Abstract. The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.

Assessment of dynamic downscaling of the extreme rainfall over East Asia using a regional climate model

This study investigates the capability of the dynamic downscaling method (DDM) in an East Asian climate study for June 1998 using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research non-hydrostatic Mesoscale Model (MM5). Sensitivity experiments show that MM5 results at upper atmospheric levels cannot match reanalyses data, but the results show consistent improvement in simulating moisture transport at low levels. The downscaling ability for precipitation is regionally dependent. During the monsoon season over the Yangtze River basin and the pre-monsoon season over North China, the DDM cannot match observed precipitation. Over Northwest China and the Tibetan Plateau (TP), where there is high topography, the DDM shows better performance than reanalyses. Simulated monsoon evolution processes over East Asia, however, are much closer to observational data than reanalyses. The convection scheme has a substantial impact on extreme rainfall over the Yangtze River basin and the pre-monsoon over North China, but only a marginal contribution for Northwest China and the TP. Land surface parameterizations affect the locations and pattern of rainfall bands. The 10-day re-initialization in this study shows some improvement in simulated precipitation over some sub-regions but with no obvious improvement in circulation. The setting of the location of lateral boundaries (LLB) westward improves performance of the DDM. Including the entire TP in the western model domain improves the DDM performance in simulating precipitation in most sub-regions. In addition, a seasonal simulation demonstrates that the DDM can also obtain consistent results, as in the June case, even when another two months consist of no strong climate/weather events.

A numerical simulation of the effect of the number concentration of cloud droplets on Typhoon Chanchu

In recent years, an increase in the number of anthropogenic aerosol particles has raised the global mean content of aerosol particles in the atmosphere from that of preindustrial times. The indirect effects of aerosols on weather and climate cannot be ignored. In this paper, the fifth generation Pennsylvania State University (PSU)–National Center of Atmospheric Research (NCAR) Nonhydrostatic Mesoscale Model (MM5) is used to simulate Typhoon Chanchu (international designation: 0601), which affected the northwest Pacific. Simulations are conducted in three two-way nested domains with Mercator map projection. The horizontal grid resolutions of the three domains are 27, 9, and 3 km. A period of 60 h is simulated. Surface and rawinsonde conventional observation data and ocean wind data are additionally incorporated into the initialization data. A control (CTL) experiment is run to produce a reasonable forecast. We change the parameter of the cloud condensation nuclei (CCN) concentration (CNP) in the Reisner-2 scheme of the CTL experiment (the default value is 100 cm−3) to conduct two sensitivity experiments. They are the very clean marine (VCM) CNP experiment (CNP = 25 cm−3) and the severe contamination (SC) CNP experiment (CNP = 1,000 cm−3). We investigate the effects of the CNP on Typhoon Chanchu by comparing and analyzing the simulation results of the three experiments in terms of the track, intensity, precipitation, vertical structure, and microphysical processes. The main results show that Typhoon Chanchu slightly weakens as the CNP increases. Increasing the CCN to 1,000 cm−3 results in less graupel, rainwater, and cloud ice but more cloud water. However, the mixing ratio of snow does not distinctly change as the CNP changes. Increasing the CCN leads a rapid decrease in the autoconversion of cloud water to rainwater. There is no autoconversion of cloud water to rainwater in a seriously polluted continental air mass. As the CNP increases, there is more condensation, evaporation, accretion of cloud water by rainwater, and precipitation fallout. Finally, a seriously polluted continental air mass can result in distinctly lower precipitation efficiency.

A Comparison of HWRF, ARW and NMM Models in Hurricane Katrina (2005) Simulation

The life cycle of Hurricane Katrina (2005) was simulated using three different modeling systems of Weather Research and Forecasting (WRF) mesoscale model. These are, HWRF (Hurricane WRF) designed specifically for hurricane studies and WRF model with two different dynamic cores as the Advanced Research WRF (ARW) model and the Non-hydrostatic Mesoscale Model (NMM). The WRF model was developed and sourced from National Center for Atmospheric Research (NCAR), incorporating the advances in atmospheric simulation system suitable for a broad range of applications. The HWRF modeling system was developed at the National Centers for Environmental Prediction (NCEP) based on the NMM dynamic core and the physical parameterization schemes specially designed for tropics. A case study of Hurricane Katrina was chosen as it is one of the intense hurricanes that caused severe destruction along the Gulf Coast from central Florida to Texas. ARW, NMM and HWRF models were designed to have two-way interactive nested domains with 27 and 9 km resolutions. The three different models used in this study were integrated for three days starting from 0000 UTC of 27 August 2005 to capture the landfall of hurricane Katrina on 29 August. The initial and time varying lateral boundary conditions were taken from NCEP global FNL (final analysis) data available at 1 degree resolution for ARW and NMM models and from NCEP GFS data at 0.5 degree resolution for HWRF model. The results show that the models simulated the intensification of Hurricane Katrina and the landfall on 29 August 2005 agreeing with the observations. Results from these experiments highlight the superior performance of HWRF model over ARW and NMM models in predicting the track and intensification of Hurricane Katrina.

The genesis of tropical cyclone Bilis (2000) associated with cross-equatorial surges

The purpose of this paper is to explore how a tropical cyclone forms from a pre-existing large-scale depression which has been observed and associated with cross-equatorial surges in the western North Pacific. Tropical cyclone Bilis (2000) was selected as the case to study. The research data used are from the results of the non-hydrostatic mesoscale model (MM5), which has successfully simulated the transformation of a pre-existing weak large-scale tropical depression into a strong tropical storm. The scale separation technique is used to separate the synoptic-scale and sub-synoptic-scale fields from the model output fields.

Performance of the experimental HWRF in the 2008 Hurricane Season

In response to the needs of improving hurricane forecasts, we have built an experimental version of the operational Hurricane Weather Research and Forecasting Model (HWRF), which is based on the Weather Research and Forecasting Nonhydrostatic Mesoscale Model of the National Oceanic and Atmospheric Administration (NOAA). The experimental HWRF (HWRFx) is adopted to study the intensity change problem at the highest possible resolutions with the existing computing facility, using moving nests to focus the model resolution in the vicinity of the storms. Although this is at an early stage of development, results from real-time experiments in the 2008 hurricane season show that the HWRFx is generally comparable to the NOAA operational models, in terms of the accuracy of both track and intensity forecasts. The HWRFx, however, has a negative bias in the intensity forecasts as opposed to the positive biases of the NOAA operational models. We present in this article a brief description of the HWRFx and its performance during the 2008 hurricane season in comparison with the NOAA operational models.

Multiphysics superensemble forecast applied to Mediterranean heavy precipitation situations

Abstract. The high-impact precipitation events that regularly affect the western Mediterranean coastal regions are still difficult to predict with the current prediction systems. Bearing this in mind, this paper focuses on the superensemble technique applied to the precipitation field. Encouraged by the skill shown by a previous multiphysics ensemble prediction system applied to western Mediterranean precipitation events, the superensemble is fed with this ensemble. The training phase of the superensemble contributes to the actual forecast with weights obtained by comparing the past performance of the ensemble members and the corresponding observed states. The non-hydrostatic MM5 mesoscale model is used to run the multiphysics ensemble. Simulations are performed with a 22.5 km resolution domain (Domain 1 in http://mm5forecasts.uib.es) nested in the ECMWF forecast fields. The period between September and December 2001 is used to train the superensemble and a collection of 19~MEDEX cyclones is used to test it. The verification procedure involves testing the superensemble performance and comparing it with that of the poor-man and bias-corrected ensemble mean and the multiphysic EPS control member. The results emphasize the need of a well-behaved training phase to obtain good results with the superensemble technique. A strategy to obtain this improved training phase is already outlined.

Sensitivity of Typhoon Vamei (2001) Simulation to Planetary Boundary Layer Parameterization Using PSU/NCAR MM5

This paper investigates the sensitivity of the numerical simulations of a near equatorial Typhoon Vamei (2001) to various planetary boundary layer (PBL) parameterization schemes in the Pennsylvania State University (PSU)/National Centre for Atmospheric Research (NCAR) non-hydrostatic mesoscale model (MM5). The numerical simulations are conducted on two domains at 45 and 15 km grids nested in a one-way fashion. Four different PBL parameterization schemes including the Blackadar (BLK) scheme, the Burk–Thompson (BURKT) scheme, the NCEP Eta model scheme and the NCEP medium range forecast (MRF) model scheme are investigated. Results indicate that the intensity and propagation track of the simulated near equatorial typhoon system is not very sensitive to the different PBL treatments. The simulated minimum central pressures and the maximum surface wind speeds differ by only 5–6 hPa and 6–8 ms−1, respectively. Larger variations between the simulations occur during the weakening phase of the typhoon system. While all schemes simulated the typhoon with reasonable accuracy, the ETA scheme produces the strongest storm intensity with the largest heat exchanges over the marine environment and the highest warm moisture air content in the PBL around the core of the storm.

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

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.