High resolution simulations of a tornadic storm affecting Sydney

Effect of the better representation of the cloud ice-nucleation in WRF microphysics schemes: A case study of a severe storm in India

Abstract. In the present study, we have used the Weather Research and Forecasting (WRF) model to simulate the features associated with a severe thunderstorm observed over Gadanki (13.5° N, 79.2° E), over southeast India, on 21 May 2008 and examined its sensitivity to four different microphysical (MP) schemes (Thompson, Lin, WSM6 and Morrison). We have used the WRF model with three nested domains with the innermost domain of 2 km grid spacing with explicit convection. The model was integrated for 36 h with the GFS initial conditions of 00:00 UTC, 21 May 2008. For validating simulated features of the thunderstorm, we have considered the vertical wind measurements made by the Indian MST radar installed at Gadanki, reflectivity profiles by the Doppler Weather Radar at Chennai, and automatic weather station data at Gadanki. There are major differences in the simulations of the thunderstorm among the MP schemes, in spite of using the same initial and boundary conditions and model configuration. First of all, all the four schemes simulated severe convection over Gadanki almost an hour before the observed storm. The DWR data suggested passage of two convective cores over Gadanki on 21 May, which was simulated by the model in all the four MP schemes. Comparatively, the Thompson scheme simulated the observed features of the updraft/downdraft cores reasonably well. However, all the four schemes underestimated strength and vertical extend of the updraft cores. The MP schemes also showed problems in simulating the downdrafts associated with the storm. While the Thompson scheme simulated surface rainfall distribution closer to observations, the other three schemes overestimated observed rainfall. However, all the four MP schemes simulated the surface wind variations associated with the thunderstorm reasonably well. The model simulated reflectivity profiles were consistent with the observed reflectivity profile, showing two convective cores. These features are consistent with the simulated condensate profiles, which peaked around 5–6 km. As the results are dependent on initial conditions, in simulations with different initial conditions, different schemes may become closer to observations. The present study suggests not only large sensitivity but also variability of the microphysical schemes in the simulations of the thunderstorm. The study also emphasizes the need for a comprehensive observational campaign using multi-observational platforms to improve the parameterization of the cloud microphysics and land surface processes over the Indian region.

Assessment of wind resources in two parts of Northeast Brazil with the use of numerical models

This study utilized the Weather Research and Forecast (WRF) model to forecast hail induced by the hailstorms on 17 March 2020 in western North Vietnam, using two microphysical schemes: the Thompson and Morrison schemes. Assessment of the WRF skill in predicting hail coverage and intensity was done for two predicted indices, namely UH (Updraft Helicity) and CTG (Column Total Integrated Graupel). Two predicted variables are DTh (hail diameter given by WRF using the Thompson Hail Algorithm) and DHc (hail diameter given by the HAILCAST submodel in WRF). The predicted hail coverage and intensity were compared with the products given by the Pha Din radar's Hail Size Discrimination Algorithm (HSDA) for three categories: small, large, and giant hail size. Using the Morrison scheme, the WRF model indicates that the hail-coverage forecast skills of UH, CTG, and DHc are highest, with an insignificant difference at the horizontal scale more significant than 60 km. However, the DHc variable given by the Morrison scheme provides the most successful forecast for both hail size and coverage compared with the HSDA products and field reports. This is because HAILCAST considers kinematic and microphysical processes to predict maximum hail size at the surface. The predicted hailstorms could occur in environments with moderate convective available potential energy but require robust moisture flux convergence over high mountains.

The low-echo centroid (LEC) storm, characterized by the dominance of warm-rain processes and high precipitation efficiency (Vitale & Ryan, 2013), is generally associated with high-intensity rainfall events in tropical and subtropical regions (Hamada et al. 2015). While many double-moment microphysical parameterization schemes are primarily designed for deep convection or cold-rain processes, research on their performance in simulating LEC warm-cloud precipitation systems is limited. In this study, we investigate an extreme rainfall case that occurred on 20 July 2016 in northern China, resulting in over 600 mm of maximum 24-hour accumulated rainfall. According to radar observations, the case is characterized by LEC structure. Using the Weather Research and Forecasting (WRF) model with 4 km grid spacing, we simulate this event employing the Morrison, Thompson, and Milbrandt-Yau double-moment microphysics schemes. Evaluation based on simulated infrared brightness temperature (BT) using a radiative transfer model and simulated reflectivity reveals that while different microphysics schemes generally predict rainfall amount, location, and propagation accurately, they fail to replicate the three-dimensional cloud structures. The simulated convective cores (>35dBZ) are higher than -10 °C, indicating active cold-cloud processes, while the observed LEC suggests the dominance of warm-cloud processes. The model produces an excessive number of upper-level clouds and overshooting clouds, also overpredict the cloud-top height. Sensitivity experiments show that simulated brightness temperatures are primarily influenced by the concentration of cloud ice particles. Morrison and Milbrandt-Yau microphysics schemes produces an overabundance of cloud ice particles in the upper layer, leading to the overproduction of uppe-level cloud and incorrect representation of cloud top height. Warm-rain processes are not fully developed, and the cold-rain processes are not effectively restrained, resulting in unrealistic cloud structure. By adjusting microphysical processes in the schemes, such as increasing cloud water number concentration, the simulated convective cores align more closely with the observed ones. In summary, while the current microphysics schemes effectively simulate rainfall intensity and propagation, there is a clear need for improvement in simulating the cloud particle distribution and vertical structure of LEC storms. Our findings underscore the importance of refining microphysical parameterization schemes for accurate simulation of extreme rainfall events.

The weather research and Forecasting (WRF) model in an atmospheric simulation system, which is designed for both operational and research use. This common tool aspect promotes closer ties between research and operational communities. It contains a lot a different physics and dynamics options reflecting the experience and input of the broad scientific community. The WRF physics categories and microphysics, cumulus parametrization, planetary boundary layer, land-surface model and radiation. Explicitly resolved water vapor, cloud and precipitation processes are included in microphysics. Several bulk water microphysics schemes are available within the Weather Research and Forecasting (WRF) model, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University (SBU-YLIN) microphysics scheme is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In this paper, we develop an efficient graphics processing unit (GPU) based SBU-YLIN scheme. WRF computation domain is 3D grid layed over the earth. SBU-YLIN performs the same computation for each spatial position in the whole domain. This repletion of the same computation on different data sets allows using GPU's Single Instruction Multiple Dataset (SIMD) architecture. The GPU-based SBUYLIN scheme will be compared to a CPU-based single-threaded counterpart. The implementation achieves 213x speedup with I/O compared to a Fortran implementation running on a CPU. Without I/O the speedup is 896x.

Dynamic downscaling over western Himalayas: Impact of cloud microphysics schemes

Idealized three-dimensional supercell simulations were performed using the two-moment bulk microphysics schemes of Morrison and Milbrandt–Yau in the Weather Research and Forecasting (WRF) model. Despite general similarities in these schemes, the simulations were found to produce distinct differences in storm structure, precipitation, and cold pool strength. In particular, the Morrison scheme produced much higher surface precipitation rates and a stronger cold pool, especially in the early stages of storm development. A series of sensitivity experiments was conducted to identify the primary differences between the two schemes that resulted in the large discrepancies in the simulations. Different approaches in treating graupel and hail were found to be responsible for many of the key differences between the baseline simulations. The inclusion of hail in the baseline simulation using the Milbrant–Yau scheme with two rimed-ice categories (graupel and hail) had little impact, and therefore resulted in a much different storm than the baseline run with the single-category (hail) Morrison scheme. With graupel as the choice of the single rimed-ice category, the simulated storms had considerably more frozen condensate in the anvil region, a weaker cold pool, and reduced surface precipitation compared to the runs with only hail, whose higher terminal fall velocity inhibited lofting. The cold pool strength was also found to be sensitive to the parameterization of raindrop breakup, particularly for the Morrison scheme, because of the effects on the drop size distributions and the corresponding evaporative cooling rates. The use of a more aggressive implicit treatment of drop breakup in the baseline Morrison scheme, by limiting the mean–mass raindrop diameter to a maximum of 0.9 mm, opposed the tendency of this scheme to otherwise produce large mean drop sizes and a weaker cold pool compared to the hail-only run using the Milbrandt–Yau scheme.

Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment

Abstract. This study examines how different microphysical parameterization schemes influence orographically induced precipitation and the distributions of hydrometeors and water vapour for midlatitude summer conditions in the Weather Research and Forecasting (WRF) model. A high-resolution two-dimensional idealized simulation is used to assess the differences between the schemes in which a moist air flow is interacting with a bell-shaped 2 km high mountain. Periodic lateral boundary conditions are chosen to recirculate atmospheric water in the domain. It is found that the 13 selected microphysical schemes conserve the water in the model domain. The gain or loss of water is less than 0.81% over a simulation time interval of 61 days. The differences of the microphysical schemes in terms of the distributions of water vapour, hydrometeors and accumulated precipitation are presented and discussed. The Kessler scheme, the only scheme without ice-phase processes, shows final values of cloud liquid water 14 times greater than the other schemes. The differences among the other schemes are not as extreme, but still they differ up to 79% in water vapour, up to 10 times in hydrometeors and up to 64% in accumulated precipitation at the end of the simulation. The microphysical schemes also differ in the surface evaporation rate. The WRF single-moment 3-class scheme has the highest surface evaporation rate compensated by the highest precipitation rate. The different distributions of hydrometeors and water vapour of the microphysical schemes induce differences up to 49 W m−2 in the downwelling shortwave radiation and up to 33 W m−2 in the downwelling longwave radiation.

This study examines the influence of Purdue-Lin microphysical parameterization scheme (Lin et al.,1983) on quantitative precipitation for pre-monsoon/monsoon conditions over southern peninsular India in the Weather Research and Forecasting (WRF) model. An ideal microphysical scheme has to describe the formation, growth of cloud droplets and ice crystals and fall out as precipitation. Microphysics schemes can be broadly categorized into two types: bin and bulk particle size distribution (Morrison, 2010). Bulk schemes predict one or more bulk quantities and assume some functional form for the particle size distribution. For better parameterization, proper interpretation of these hydrometeors (Cloud Droplets, Raindrops, Ice Crystals and Aggregates, Rimed Ice Particles, Graupel, Hail) and non-hydrometeors (Aerosols vs. Condensation Nuclei vs. Cloud Condensation Nuclei vs. Ice Nuclei) is very important. The Purdue-Lin scheme is a commonly used microphysics scheme in WRF model utilizing the “bulk” particle size distribution, meaning that a particle size distribution is assumed. The intercept parameter ( N 0 ) is, in fact, turns out to be independent of the density. However, in situ observations suggest (Haddad et al., 1996, 1997) that the mass weighted mean diameter is correlated with water content per unit volume ( q ), leading to the fact that N0 depends on it. Here, in order to analyze the correlation of droplet size distribution with the convection, we have carried out simulations by implementing a consistent methodology to enforce a correlation between N0 and q in the Purdue-Lin microphysics scheme in WRF model. The effect of particles in Indian Summer Monsoon has been examined using frequency distribution of rainfall at surface, daily rainfall over the domain and convective available potential energy and convective inhibition. The simulations are conducted by analyzing the maximum rainfall days in the pre-monsoon/monsoon seasons using Tropical Rainfall Measuring Mission (TRMM) accumulated rainfall data for 24 hours.

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

A tornado that occurred in eastern China on June 23, 2016 was simulated with the Weather Research and Forecasting (WRF) model (version 3.9) using three different microphysical schemes (WRF single‐moment 6‐class [WSM6] scheme, Morrison double‐moment scheme, and Milbrandt–Yau [MY] scheme). The results showed that the Morrison scheme's simulation result was the best among the three schemes. The Morrison scheme simulated a better structure of three layers, including a cold pool near the ground, thick heating layer in the middle levels, and cooling again above 14 km. From the microphysical processes, the possible formation mechanism was that the convective activity was first evoked by the near‐ground cold pool, and then the horizontal vortex tube was raised and vertically stretched before turning in the vertical direction by the release of latent heat caused by the water vapor condensation. Thereafter, the vortex tube was cut off by the downward movement caused by the cloud water evaporation and the snow melting in the front of the convection system, causing the violent vertical lift of the rear vortex tube, forming the tornado.

Abstract. Regions with high ice water content (HIWC), composed of mainly small ice crystals, frequently occur over convective clouds in the tropics. Such regions can have median mass diameters (MMDs) <300 µm and equivalent radar reflectivities <20 dBZ. To explore formation mechanisms for these HIWCs, high-resolution simulations of tropical convective clouds observed on 26 May 2015 during the High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) international field campaign based out of Cayenne, French Guiana, are conducted using the Weather Research and Forecasting (WRF) model with four different bulk microphysics schemes: the WRF single‐moment 6‐class microphysics scheme (WSM6), the Morrison scheme, and the Predicted Particle Properties (P3) scheme with one- and two-ice options. The simulations are evaluated against data from airborne radar and multiple cloud microphysics probes installed on the French Falcon 20 and Canadian National Research Council (NRC) Convair 580 sampling clouds at different heights. WRF simulations with different microphysics schemes generally reproduce the vertical profiles of temperature, dew-point temperature, and winds during this event compared with radiosonde data, and the coverage and evolution of this tropical convective system compared to satellite retrievals. All of the simulations overestimate the intensity and spatial extent of radar reflectivity by over 30 % above the melting layer compared to the airborne X-band radar reflectivity data. They also miss the peak of the observed ice number distribution function for 0.1<Dmax<1 mm. Even though the P3 scheme has a very different approach representing ice, it does not produce greatly different total condensed water content or better comparison to other observations in this tropical convective system. Mixed-phase microphysical processes at −10 ∘C are associated with the overprediction of liquid water content in the simulations with the Morrison and P3 schemes. The ice water content at −10 ∘C increases mainly due to the collection of liquid water by ice particles, which does not increase ice particle number but increases the mass/size of ice particles and contributes to greater simulated radar reflectivity.

This study aims to investigate how assimilating GOES‐16 ABI infrared brightness temperature (BT) with different microphysics schemes affects the convection‐allowing analysis and prediction of the 3 May 2020 bow echo case. The Gridpoint Statistical Interpolation‐based Ensemble Kalman Filter (GSI‐EnKF) system and Weather Research and Forecasting (WRF) model are utilized to conduct data assimilation (DA) experiments using Thompson, WDM6, NSSL, and Morrison microphysics schemes. Correlation structures between BT and model state variables indicate that assimilating infrared BT can adjust bowing MCS dynamics via latent cooling and the rear inflow jet. Such corrections during DA cycling enhance the rear inflow jet and bow echo size, primarily for microphysics schemes featuring faster hydrometeor fall velocity and stronger latent cooling. The improved analyses lead to better forecasts of the bow echo's shape, size, timing of the bowing process, and wind speeds. Substituting a larger microphysics‐dependent effective radius for a constant default value increases prior BT, the magnitude of BT innovations, and accumulated impact on the rear inflow jet, especially for the WDM6 and Morrison schemes. In the subsequent forecasts, incorporating microphysics‐dependent effective radius further improves the experiment using the Morrison scheme but degrades it when using the WDM6 scheme.