Advanced Regional Prediction System Research Articles

A Numerical Study of Smoke Concentration Distribution near Low-Intensity Fires: Sensitivity to Vertical Canopy Structure and Fire Heat Source Strength

Abstract Broadly speaking, prediction of the negative impacts of prescribed fire on air quality is limited by gaps in our understanding of the underlying fire, fuels, and atmospheric processes. These knowledge gaps hinder our ability to accurately predict smoke concentration distributions, leading to unintended smoke intrusions into nearby communities and subsequent threats to public health and safety. In this study, numerical simulations are performed using the Flexible Particle Weather Research and Forecasting (FLEXPART-WRF) Model, a Lagrangian particle dispersion model, with particle motion driven by output from a full-physics atmospheric model with a forest canopy submodel and 10-m horizontal grid spacing [Advanced Regional Prediction System (ARPS)-CANOPY], to address two research questions. First, what is the relationship between near-fire (within ∼50–150 m of fire) smoke concentration distribution and (i) vertical canopy structure and (ii) fire heat source strength? Second, what roles do mean transport (i.e., transport by the mean wind) and turbulent diffusion play in shaping the near-fire smoke concentration distribution? To address these questions, simulations are run with 25 combinations of plant area density profile and fire sensible heat flux magnitude, and smoke is represented by particles with diameters ≤ 2.5 μm (PM2.5). Results show that near-fire PM2.5 concentration distribution is primarily controlled by vertical canopy structure, with fire heat source strength primarily controlling the PM2.5 concentration magnitude. Analysis of the underlying ARPS-CANOPY variables driving the FLEXPART-WRF particle dispersion helps elucidate the roles of mean transport and turbulent diffusion. In total, the study findings suggest that the vertical distribution of canopy vegetation and fire heat source strength are important factors influencing PM2.5 dispersion and concentration distribution near low-intensity fires.

Factors Affecting the Rapid Recovery of CAPE on 31 March 2016 during VORTEX-Southeast

Abstract In this study, we analyze various sources of CAPE in the environment and their contributions to its time tendency that will complement forecast models and operational analyses that are relatively temporally (∼1 h) coarse. As a case study, the relative roles of direct insolation and near-surface moisture advection in the recovery CAPE on 31 March 2016 in northern Alabama are examined using VORTEX-Southeast (VORTEX-SE) observations and numerical simulations. In between rounds of nontornadic morning storms and tornadic evening storms, CAPE over the VORTEX-SE domain increased from near zero to at least 500 J kg−1. A timeline of the day’s events is provided with a focus on the evolution of the lower levels of the atmosphere. We focus on its responses to solar insolation and moisture advection, which we hypothesize as the main mechanisms behind the recovery of CAPE. Data from the University of Massachusetts S-Band frequency-modulated, continuous-wave (FMCW) radar and NOAA National Severe Storms Laboratory (NSSL) Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS), and high-resolution EnKF analyses from the Advanced Regional Prediction System (ARPS) are used to characterize the boundary layer evolution in the pre-tornadic storm environment. It is found that insolation-driven surface diabatic heating was the primary driver of rapid CAPE recovery on this day. The methodology developed in this case can be applied in other scenarios to diagnose the primary drivers of CAPE development. Significance Statement The mechanisms by which atmospheric instability recovers can vary widely and are often a source of uncertainty in forecasting. We want to understand how and why the environment destabilized enough to produce an evening tornado following morning storms on 31 March 2016. To do this, we used model data and observations from a collocated radar and profiler. It was found that heating from the sun at the surface was the primary cause of destabilization in the environment.

Dynamical Analyses of a Supercell Tornado in Eastern China Based on a Real-Data Simulation

Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a Meiyu frontal system. To investigate the dynamical process of the tornado, a numerical simulation was performed using four one-way nested grids within the Advanced Regional Prediction System (ARPS). Data from a nearby operational S-band Doppler radar are assimilated using a 4D ensemble Kalman filter (4DEnKF) at 5 min intervals. Forecasts are run with a nested 50 m grid, capturing the tornado embedded within the supercell storm with a reasonable agreement with observations. The tornadogenesis processes within the simulation results are analyzed in detail, including the three-dimensional evolution of the tornado vortex. It is found that a cold surge within the rear flank downdraft region plays a key role in instigating tornadogenesis when the leading edge of the cold surge approaches a near-ground convergence center located underneath the main updraft, and the enhancement of the convergence center caused by the descending of the low-level mesocyclone is the direct cause of the rapid increase in tornado vorticity. Backward trajectories are calculated based on model output, and the origins of the parcels feeding the intensifying tornado vortex are identified. It is found that parcels from the mid-level of the rear flank downdraft region follow the cold surge, descending to the ground under the influence of the downdraft in the cold surge, and then entering the convergence center, merging into the core of the tornado and being lifted up. Vertical profiles of the mass and vorticity fluxes into the core of the tornado vortex are examined, and it is found that the near-ground airflow contributes significantly to the growth of the tornado vorticity, with the contribution increasing as it gets closer to the ground.

Large-eddy simulation of the urban boundary layer using drag-porosity modeling

This work details the assessment of the performance of the drag-porosity model implemented in ARPS (Advanced Regional Prediction System) atmospheric Large-Eddy Simulation (LES) solver for simulating the atmospheric boundary layer developing over the urban canopy with comparison with literature. The flow within and above an idealized urban canopy consisting of a staggered array of cubes with various packing densities modeled with the drag-porosity approach immersed into a neutral, Coriolis-free atmospheric boundary layer at high Reynolds is investigated. Besides one-points statistics, particular interest was given to the ability of the model to reproduce the turbulent coherent structures and their characteristic scales. A detailed analysis of one-point statistics, one- and two-dimensional spectra and two-point correlation functions revealed the presence of typical structures and features found in wall-bounded turbulent flows (two-scale behavior in the roughness sublayer, ejections, sweeps, self-similar wall-attached large scale streaky motions, canopy-independent very large scale motions). Further investigation to identify the interaction mechanisms between large and small scales based on spectral filtering highlighted an interaction mechanism that resembles an amplitude modulation process, as observed in literature on wall-bounded flows. These findings therefore show that the proposed approach is able to reproduce all the key features of the flow developing over urban terrain.

Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs

AbstractThe radiative‐convective equilibrium (RCE) of two models exhibiting convective aggregation has been compared. The goal of the work, following the suggestion from the RCE Model Intercomparison Project (RCEMIP), is to identify key parameters controlling self‐aggregation in RCE for both models, to discuss the processes controlled by these parameters and to underline the models similarities and differences. The two cloud resolving models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), present similar statistics concerning precipitation, but different warming, and drying of the atmosphere, within the spread of the RCEMIP values. On the other hand, the two models show different strengths of the moisture feedback, due to the different saturation of the sub‐cloud layer. A saturated sub‐cloud layer in ARPS (which was not artificially imposed in the numerical setup) allows the localization of convection in moist regions, by weakening the negative influence of cold pools. Such a mechanism leads to a lower degree of aggregation (based on three organization metrics) and a weaker effect of the organized state on the average domain statistics in ARPS. Stronger cold pools in SAM, instead, help the creation of shallow clouds in dry regions, increasing the longwave feedback responsible for their expansion; while delocalizing convection in moist regions and therefore opposing high‐cloud radiative‐feedback. Further experiments are needed to generalize such findings to other RCEMIP models, also investigating the role of microphysics and turbulence schemes in regulating such mechanisms.

Atmospheric dispersion of hydrogen sulfide using a modified ARPS model: a case study.

Exposure to disgusting smells constitutes a type of atmospheric pollution from industrial and human activities. Complaints stemming from various sources of unpleasant odors have become a serious concern in both sparsely and densely populated countries. Hydrogen sulfide is a compound characterized by its disgusting odor. In this work, a new chemical reaction was incorporated to Advanced Regional Prediction System (ARPS) model, to calculate the H2S air concentrations. A turbulent boundary layer flow is computed using the LES code ARPS 4.5.2. A LES coupled with a Lagrangian stochastic model has been applied to the study of reactive scalar dispersion downwind of a localized source of H2S. The study case corresponds to the H2S emission of cellulose mill. Two bad odor event was evaluating in order to compare the result of the model with the measured concentrations. The results of this model application provides good description of the plumes for two event of bad odor records in the zone. The values resulting from the analysis of the air samples are within the concentration range estimated by the model. The model is a valid and useful tool to simulate atmospheric pollution episodes that involve non-conservative pollutants, that is, chemical species that, when in contact with the atmospheric components, react, and giving rise to the formation of secondary compounds. It is possible used the developed modeling system in cases of diagnosis and prognosis of real situations and even emergencies, with an appropriate level of precision for studies of this type.

Representing low-intensity fire sensible heat output in a mesoscale atmospheric model with a canopy submodel: a case study with ARPS-CANOPY (version 5.2.12)

Abstract. Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2–200 km, although they are also applied to microscale phenomena with horizontal scales of less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion byproducts (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model–observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1 min mean observed heat flux averaged across the flux towers, and an e-folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models.

Assessing the Impact of Non-Conventional Radar and Surface Observations on High-Resolution Analyses and Forecasts of a Severe Hailstorm

A 2009 National Research Council study recommended that new mesoscale observing networks be integrated with existing networks to form a nationwide “network of networks”. The report also recommended that research testbeds be established, such as the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) DFW Testbed, to ascertain the potential benefit of proposed observing systems. In this work, we use various conventional and non-conventional observing systems from the DFW Testbed in a series of observing system experiments (OSEs). Of special interest are radar data from Terminal Doppler Weather Radars and CASA X-band radars, as well as novel surface observations. The Advanced Regional Prediction System (ARPS) model is used to perform OSEs that are designed to assess the impact of these observing systems. A three-dimensional variational analysis system and companion complex cloud analysis are used to produce analysis increments, which are assimilated in ARPS using Incremental Analysis Updating. Experiments are performed on a supercell thunderstorm case from 11 April 2016 that produced large, damaging hail. The analysis includes quantitative comparisons of model-derived hail with radar-observed hail, along with verification of surface fields. The CASA radial velocity data benefited the forecasted storm structure, as it positively affected subsequent storm morphology and model-derived hail forecasts. Of note in surface observation impacts, the dewpoint measurements from the non-conventional Earth Networks and CWOP networks slightly degrade the forecasted dewpoint field compared to independent standard observations, but did not prevent the successful prediction of hail.

Investigating the Impacts of Assimilating Surface Observations on High-Resolution Forecasts of the 15 May 2013 Tornado Event

In this study, the Advanced Regional Prediction System (ARPS), and its associated three-dimensional variational analysis (3DVAR) package are used to simulate a tornadic supercell at 400-m grid spacing. This storm produced an EF3 tornado in Johnson County, TX during the evening of 15 March 2013. Data from Doppler radar, satellite, aircraft, radiosondes, profilers, and surface observations are assimilated in this work. We show that the assimilation of non-conventional surface observations from three networks: the Citizen Weather Observer Program (CWOP), Global Science and Technology (GST) and Automated Weather Stations (AWS) operated by EarthNetworks, in and around the storm inflow, were fundamentally important to the development of an intense low-level mesocyclone. Simulations that did not incorporate this non-conventional data either developed a weak mesocyclone that was displaced to the east of the actual tornado track, or were unable to develop a defined mesocyclone in the first place. In particular, the assimilation of thermodynamic variables (temperature, pressure and moisture) from a subset of AWS observations near the storm’s inflow environment leads to the most accurate simulation of the low-level mesocyclone.

Numerical Simulation Study on the Microphysical Processes of Typhoon Wipha Using a New Moisture Conditioning Method

Yang, W.X.; Hu, Z.X.; Lei, H.C., and Li, B.D., 2020. Numerical simulation study on the microphysical processes of Typhoon Wipha using a new moisture conditioning method. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 156–159. Coconut Creek (Florida), ISSN 0749-0208.With the non-static mesoscale model ARPS (Advanced Regional Prediction System), by using the NCEP/ NCAR global final analysis data, and the global surface and sounding data under MICAPS (Meteorological Information Comprehensive Analysis and Process System) assimilated in 4 dimensions as the initial field and lateral boundary conditions, the initial moisture field is adjusted according to the surface accumulated rain of each 6 h, and the triple nested simulation is conducted to produce 3 dimensional high time -spatial (Wipha) are analysed. The results are significant for understanding the cloud structure and the precipitation forming mechanisms of the Typhoon storm. It is found that the ice phase microphysical processes are the key storm mechanisms in different periods. The melting graupel confirms that the rain is the most important mechanism. The intensity of the production of graupel varies in accordance with the Typhoon.

The Initiation and Organization of a Severe Hail‐Producing Mesoscale Convective System in East China: A Numerical Study

AbstractThe initiation and organization of a long‐duration hail‐producing mesoscale convective system (MCS) in eastern China are investigated using convection‐allowing simulations at 3‐km grid spacing with the Advanced Regional Prediction System. The lifecycle of this MCS is characterized by two stages. In the first stage, a series of convective storms are initiated along the northwest border of Jiangsu Provinces. These storms organize into a northwest southeast line as they moved southeastward, eventually organizing into an eastward moving bow‐echo structure during the second stage. Our analyses show that the storms initiate along a northwest‐southeast oriented convergence boundary set up between two low‐level mesoscale vortices, one to the northwest of Jiangsu Province and one over the East China Sea. Comparisons between the fake‐dry and control simulations show that the rearward (westward) spreading of a cold pool from another MCS proceeding the hail‐producing MCS plays a key role in generating and enhancing the vortex over Eastern China Sea. The tilting of baroclinically generated horizontal vorticity along the edge of the cold outflow creates a cyclonic and anticyclonic vortex couplet. The cyclonic vortex becomes the dominant East China Sea vortex as it is superposed onto the background cyclonic circulation. This cold outflow‐induced vortex also has strong impacts on the later organization of the hail‐producing MCS, leading to the eventual establishment of a bow‐echo structure. Finally, a three‐stage conceptual model for the initiation and organization of the long‐lasting multicellular MCS is proposed, and the understanding on the complex interactions between two MCSs will be helpful to operational forecasters.

A Multiscale Numerical Modeling Study of Smoke Dispersion and the Ventilation Index in Southwestern Colorado

The ventilation index (VI) is an index that describes the potential for smoke or other pollutants to disperse from a source. In this study, a Lagrangian particle dispersion model was utilized to examine smoke dispersion and the diagnostic value of VI during a September 2018 prescribed fire in southwestern Colorado. Smoke dispersion in the vicinity of the fire was simulated using the FLEXPART-WRF particle dispersion model, driven by meteorological outputs from Advanced Regional Prediction System (ARPS) simulations of the background (non-fire) conditions. Two research questions are posed: (1) Is a horizontal grid spacing of 4 km comparable to the finest grid spacing currently used in operational weather models and sufficient to capture the spatiotemporal variability in wind and planetary boundary layer (PBL) structure during the fire? (2) What is the relationship between VI and smoke dispersion during the prescribed fire event, as measured by particle residence time within a given horizontal or vertical distance from each particle’s release point? The ARPS no-fire simulations are shown to generally reproduce the observed variability in weather variables, with greatest fidelity to observations found with horizontal grid spacing of approximately 1 km or less. It is noted that there are considerable differences in particle residence time (i.e., dispersion) at different elevations, with VI exhibiting greater diagnostic value in the southern half of the domain, farthest from the higher terrain across the north. VI diagnostic value is also found to vary temporally, with diagnostic value greatest during the mid-morning to mid-afternoon period, and lowest during thunderstorm outflow passage in the late afternoon. Results from this study are expected to help guide the application of VI in complex terrain, and possibly inform development of new dispersion potential metrics.

Large-Eddy Simulation of Erosion and Deposition over Multiple Two-Dimensional Gaussian Hills in a Turbulent Boundary Layer

We investigate the effects of one or more hills on the solid-particle saltation layer, and focus on the effect of the recirculation zone that plays an important role in solid-particle erosion or entrapment. The aerodynamic features of the flow have been presented previously (Huang et al. in Environ Fluid Mech 18:581–609, 2018) and the influence of hill separation was discussed in light of the classification deduced from the urban canopy scheme of Oke (Energy Build 11:103–113, 1988). Here, large-eddy simulations (LES) coupled with Lagrangian tracking of solid particles over multiple two-dimensional Gaussian hills in a turbulent boundary layer are performed using the atmospheric Advanced Regional Prediction System. Models for the interaction of particles with the soil are used, especially for take-off and rebound, and the boundary layer at different external velocities is first simulated. Numerical results are compared with experiments performed in our laboratory (Simoens et al. in Procedia IUTAM 17:110–118, 2015) to collect particle concentration and velocity profiles, with the different forces acting on the particles at the wall analyzed. Accumulation and erosion zones are investigated regarding the shear velocity, and different fluxes as function of the Shields number are defined and discussed. Lower momentum transfer and exchange between the recirculation region and the mixing zone in the wake-flow regime result in an increase in the number of trapped particles compared with the skimming-flow regime.

Modeling the Effects of Explicit Urban Canopy Representation on the Development of Thunderstorms above a Tropical Mega City

The effects of an explicit three dimensional (3D) urban canopy representation on the development of convective thunderstorms were analyzed with the tropical town energy budget (tTEB) scheme integrated into the advanced regional prediction system (ARPS). The study provides a detailed description of the procedure to couple the system ARPS-tTEB and analyzed the simulation results of the 12 January 2015 sea-breeze event that developed a severe thunderstorm above the metropolitan area of São Paulo (MASP), Brazil. The simulation used realistic boundary and initial conditions from the Global Forecast System (GFS) and sea surface temperature (SST) from the Tropical Rainfall Measurement Mission (TRMM). The system ARPS-tTEB runs of up to 3 km horizontal resolution were carried out with high resolution topography features and land-use types currently available for Southeastern Brazil. The simulated spatial distribution of precipitation was verified against the Climate Prediction Center Morphing Technique (CMORPH), the Global Precipitation Measurement (GPM) and the São Paulo weather radar (SPWR) precipitation estimates by indexes scores. Time series of grid precipitation estimates (ARPS-tTEB and SPWR) and point measurements (rain gauges) were evaluated with a Bayesian statistical method. Results indicate that the urban area of the MASP modulates the precipitation spatial distribution over it. Furthermore, phase and amplitude precipitation accuracy increased with the 3D urban canyon and the urban energy budget scheme in relationship to control runs without urban environment effects.

Application of a Bayesian inflation approach to EnSRF radar data assimilation to improve the analysis and forecasting of an MCS

AbstractA spatially and temporally varying Bayesian inflation algorithm was applied to the assimilation of the real radar data of a mesoscale convective system (MCS), which occurred on May 8–9, 2007 in Oklahoma and Texas (USA), using the ensemble square root filter (EnSRF) within the advanced regional prediction system (ARPS). For comparison purposes, two radar data assimilation and forecast experiments using Bayesian inflation and regular multiplicative inflation algorithms were performed. Results indicated that the analysis reflectivity structure of the MCS using the Bayesian inflation method appeared better than when using the multiplicative inflation method. The Bayesian inflation method also reduced the root mean square innovations (RMSIs) and increased the ensemble spreads for reflectivity and radial velocity. Furthermore, the reduction of RMSIs was related to the higher Bayesian inflation parameter assigned to the background. The flow‐dependent characteristic of the Bayesian inflation parameter means it varies with space and model state variables. This successful analysis helped improve subsequent forecast reflectivity and precipitation, especially for stratiform precipitation. It also promoted the development of the MCS with a strong surface cold pool and outflow in the convective regions. Quantitative reflectivity and precipitation forecast skills were also improved in the Bayesian inflation experiment. These encouraging results demonstrated the greater potential of using the Bayesian inflation algorithm for EnSRF radar data assimilation compared with multiplicative inflation.

Explicit Prediction of Hail in a Long-Lasting Multicellular Convective System in Eastern China Using Multimoment Microphysics Schemes

Abstract During the afternoon of 28 April 2015, a multicellular convective system swept southward through much of Jiangsu Province, China, over about 7 h, producing egg-sized hailstones on the ground. The hailstorm event is simulated using the Advanced Regional Prediction System (ARPS) at 1-km grid spacing. Different configurations of the Milbrandt–Yau microphysics scheme are used, predicting one, two, and three moments of the hydrometeor particle size distributions (PSDs). Simulated reflectivity and maximum estimated size of hail (MESH) derived from the simulations are verified against reflectivity observed by operational S-band Doppler radars and radar-derived MESH, respectively. Comparisons suggest that the general evolution of the hailstorm is better predicted by the three-moment scheme, and neighborhood-based MESH evaluation further confirms the advantage of the three-moment scheme in hail size prediction. Surface accumulated hail mass, number, and hail distribution characteristics within simulated storms are examined across sensitivity experiments. Results suggest that multimoment schemes produce more realistic hail distribution characteristics, with the three-moment scheme performing the best. Size sorting is found to play a significant role in determining hail distribution within the storms. Detailed microphysical budget analyses are conducted for each experiment, and results indicate that the differences in hail growth processes among the experiments can be mainly ascribed to the different treatments of the shape parameter within different microphysics schemes. Both the differences in size sorting and hail growth processes contribute to the simulated hail distribution differences within storms and at the surface.

Simulation and Analysis of the Initiation of a Squall Line within a Meiyu Frontal System in East China

Based on the ARPS (Advanced Regional Prediction System) at 2 km grid spacing, the convective initiation (CI) of cells that evolved into a squall line on the southern flank of a Meiyu front in East China is investigated. The initiations of four convective cells, denoted CI-A through CI-D, are reasonably captured in the simulation. For CI-A and CI-B, locally enhanced convergence bands associated with boundary layer horizontal convective rolls (HCRs) play a crucial role in determining the exact locations of CIs, whereas a cold outflow boundary from earlier frontal precipitation contributes to additional convergence forcing. For CI-C, initiation occurs directly over the gust front, with the frontal convergence providing the main forcing. CI-D occurs south of and sufficiently far from the gust front, and is mainly forced by the HCR circulations. With surface heat flux turned off in the model, CI is much delayed. Therefore, surface heating increases the convective instability of air south of the front and causes the development of HCRs; it also enhances the gust front convergence by mixing higher southwesterly momentum toward the surface. When the condensation process is turned off, HCRs and/or gust frontal forcing are still able to lift the low-level air to super-saturation where CI is expected.

Analysis and prediction of a mesoscale convective system over East China with an ensemble square root filter radar data assimilation approach

A mesoscale convective system (MCS) over East China on June 5, 2009 was thoroughly analyzed using an Advanced Regional Prediction System (ARPS) ensemble square root filter (EnSRF) system. The analyzed reflectivity structure, location and intensity compared well with observation, and were substantially better than an experiment without radar data assimilation. The cold pool and wind speed in the convective regions were strengthened. With improved initial conditions, the impact of single‐moment (SM), double‐moment (DM) and triple‐moment (TM) microphysics parameterization (MP) schemes on ensemble forecasts of MCSs was evaluated. The use of multi‐moment (MM) MP schemes showed some improvements in neighborhood ensemble probability for reflectivity and precipitation. Quantitative reflectivity and precipitation forecast skills were also improved in MM forecasts, with those of the TM forecast the best.

The Impact of a Stochastically Perturbing Microphysics Scheme on an Idealized Supercell Storm

Abstract The concept of stochastic parameterization provides an opportunity to represent spatiotemporal errors caused by microphysics schemes that play important roles in supercell simulations. In this study, two stochastic methods, the stochastically perturbed temperature tendency from microphysics (SPTTM) method and the stochastically perturbed intercept parameters of microphysics (SPIPM) method, are implemented within the Lin scheme, which is based on the Advanced Regional Prediction System (ARPS) model, and are tested using an idealized supercell case. The SPTTM and SPIPM methods perturb the temperature tendency and the intercept parameters (IPs), respectively. Both methods use recursive filters to generate horizontally smooth perturbations and adopt the barotropic structure for the perturbation r, which is multiplied by tendencies or parameters from this parameterization. A double-moment microphysics scheme is used for the truth run. Compared to the multiparameter method, which uses randomly perturbed prescribed parameters, stochastic methods often produce larger ensemble spreads and better forecast the intensity of updraft helicity (UH). The SPTTM method better predicts the intensity by intensifying the midlevel heating with its positive perturbation r, whereas it performs worse in the presence of negative perturbation. In contrast, the SPIPM method can increase the intensity of UH by either positive or negative perturbation, which increases the likelihood for members to predict strong UH.

A Coastal Bay Summer Breeze Study, Part 2: High-resolution Numerical Simulation of Sea-breeze Local Influences

We complete the analysis of the data obtained during the experimental campaign around the semi circular bay of Quiberon, France, during two weeks in June 2006 (see Part 1). A reanalysis of numerical simulations performed with the Advanced Regional Prediction System model is presented. Three nested computational domains with increasing horizontal resolution down to 100 m, and a vertical resolution of 10 m at the lowest level, are used to reproduce the local-scale variations of the breeze close to the water surface of the bay. The Weather Research and Forecasting mesoscale model is used to assimilate the meteorological data. Comparisons of the simulations with the experimental data obtained at three sites reveal a good agreement of the flow over the bay and around the Quiberon peninsula during the daytime periods of sea-breeze development and weakening. In conditions of offshore synoptic flow, the simulations demonstrate that the semi-circular shape of the bay induces a corresponding circular shape in the offshore zones of stagnant flow preceding the sea-breeze onset, which move further offshore thereafter. The higher-resolution simulations are successful in reproducing the small-scale impacts of the peninsula and local coasts (breeze deviations, wakes, flow divergences), and in demonstrating the complexity of the breeze fields close to the surface over the bay. Our reanalysis also provides guidance for numerical simulation strategies for analyzing the structure and evolution of the near-surface breeze over a semi-circular bay, and for forecasting important flow details for use in upcoming sailing competitions.