Microphysical Parameterization Schemes Research Articles

Numerical Modeling of Ice Fog in Interior Alaska Using the Weather Research and Forecasting Model

An ice microphysics parameterization scheme has been modified to better describe and understand ice fog formation. The modeling effort is based on observations in the Sub-Arctic Region of Interior Alaska, where ice fog occurs frequently during the cold season due to abundant water vapor sources and strong inversions existing near the surface at extremely low air temperatures. The microphysical characteristics of ice fog are different from those of other ice clouds, implying that the microphysical processes of ice should be changed in order to generate ice fog particles. Ice fog microphysical characteristics were derived with the NCAR Video Ice Particle Sampler during strong ice fog cases in the vicinity of Fairbanks, Alaska, in January and February 2012. To improve the prediction of ice fog in the Weather Research and Forecasting model, observational data were used to change particle size distribution properties and gravitational settling rates, as well as to implement a homogeneous freezing process. The newly implemented homogeneous freezing process compliments the existing heterogeneous freezing scheme and generates a higher number concentration of ice crystals than the original Thompson scheme. The size distribution of ice crystals is changed into a Gamma distribution with the shape factor of 2.0, using the observed size distribution. Furthermore, gravitational settling rates are reduced for the ice crystals since the crystals in ice fog do not precipitate in a similar manner when compared to the ice crystals of cirrus clouds. The slow terminal velocity plays a role in increasing the time scale for the ice crystals to settle to the surface. Sensitivity tests contribute to understanding the effects of water vapor emissions as an anthropogenic source on the formation of ice fog.

Evaluating the Performance of Planetary Boundary Layer and Cloud Microphysical Parameterization Schemes in Convection-Permitting Ensemble Forecasts Using Synthetic GOES-13 Satellite Observations

Abstract In this study, the ability of several cloud microphysical and planetary boundary layer parameterization schemes to accurately simulate cloud characteristics within 4-km grid-spacing ensemble forecasts over the contiguous United States was evaluated through comparison of synthetic Geostationary Operational Environmental Satellite (GOES) infrared brightness temperatures with observations. Four double-moment microphysics schemes and five planetary boundary layer (PBL) schemes were evaluated. Large differences were found in the simulated cloud cover, especially in the upper troposphere, when using different microphysics schemes. Overall, the results revealed that the Milbrandt–Yau and Morrison microphysics schemes tended to produce too much upper-level cloud cover, whereas the Thompson and the Weather Research and Forecasting Model (WRF) double-moment 6-class (WDM6) microphysics schemes did not contain enough high clouds. Smaller differences occurred in the cloud fields when using different PBL schemes, with the greatest spread in the ensemble statistics occurring during and after daily peak heating hours. Results varied somewhat depending upon the verification method employed, which indicates the importance of using a suite of verification tools when evaluating high-resolution model performance. Finally, large differences between the various microphysics and PBL schemes indicate that large uncertainties remain in how these schemes represent subgrid-scale processes.

Multi-Physics ensemble prediction of tropical cyclone movement over Bay of Bengal

Ensemble prediction methodology based on variations in physical process parameterizations in tropical cyclone track prediction has been assessed. Advanced Research Weather Research and Forecasting model with 30-km resolution was used to make 5-day simulation of the movement of Orissa super cyclone (1999), one of the most intense tropical cyclones over the North Indian Ocean. Altogether 36 ensemble members with all possible combinations of three cumulus convection, two planetary boundary layer and six cloud microphysics parameterization schemes were produced. A comparison of individual members indicated that Kain–Fritsch cumulus convection scheme, Mellor–Yamada–Janjic planetary boundary layer scheme and Purdue Lin cloud microphysics scheme showed better performance. The best possible ensemble formulation is identified based on SPREAD and root mean square error (RMSE). While the individual members had track errors ranging from 96–240 km at 24 h to 50–803 km at 120 h, most of the ensemble predictions show significant betterment with mean errors less than 130 km up to 120 h. The convection ensembles had large spread of the cluster, and boundary layer ensembles had significant error disparity, indicating their important roles in the movement of tropical cyclones. Six-member ensemble predictions with cloud microphysics schemes of LIN, WSM5, and WSM6 produce the best predictions with least of RMSE, and large SPREAD indicates the need for inclusion of all possible hydrometeors in the simulation and that six-member ensemble is sufficient to produce the best ensemble prediction of tropical cyclone tracks over Bay of Bengal.

Atlantic Hurricanes and Climate Change. Part I: Experimental Design and Isolation of Thermodynamic Effects

Abstract The Weather Research and Forecasting (WRF) model is used in a downscaling experiment to simulate a portion of the Atlantic hurricane season both in present-day conditions and with modifications to include future thermodynamic changes. Temperature and moisture changes are derived from an ensemble of climate simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) A1B scenario and added to analyzed initial and lateral boundary conditions, leaving horizontal temperature gradients and vertical wind shear unaltered. This method of downscaling excludes future changes in shear and incipient disturbances, thereby isolating the thermodynamic component of climate change and its effect on tropical cyclone (TC) activity. The North Atlantic basin is simulated with 18- and 6-km grid spacing, and a four-member physics ensemble is composed by varying microphysical and boundary layer parameterization schemes. This ensemble is used in monthly simulations during an active (2005) and inactive (2009) season, and the simulations are able to capture the change in activity between the different years. TC frequency is better reproduced with use of 6-km grid spacing and explicitly simulated convection, relative to simulations with 18-km grid spacing. A detailed comparison of present-day and future ensemble results is provided in a companion study.

Comparison between Dual-Doppler and EnKF Storm-Scale Wind Analyses: The 29–30 May 2004 Geary, Oklahoma, Supercell Thunderstorm

Abstract Kinematical analyses of storm-scale mobile radar observations are critical to advancing our understanding of supercell thunderstorms. Maximizing the accuracy of these analyses, and characterizing the uncertainty in ensuing conclusions about storm structure and processes, requires knowledge of the error characteristics of different retrieval techniques under different observational scenarios. Using storm-scale mobile radar observations of a tornadic supercell, this study examines the impacts on ensemble Kalman filter (EnKF) wind analyses of the number of available radars (one versus two), uncertainty in the model-initialization sounding, the sophistication of the microphysical parameterization scheme (double versus single moment), and assimilating reflectivity observations. The relative accuracy of three-dimensional variational data assimilation (3DVAR) dual-Doppler wind retrievals and single- and dual-radar EnKF wind analyses of the supercell is also explored. The results generally reinforce the findings of a previous study that used observing system simulation experiments to explore the same issues. Both studies suggest that single-radar EnKF wind analyses can be very useful once enough data have been assimilated, but that subsequent analyses that operate on the retrieved wind field gradients should be interpreted with caution. In the present study, severe errors appear to occur in computed Lagrangian circulation time series, imperiling interpretation of the underlying dynamics. This result strongly suggests that dual- and multiple-Doppler radar deployment strategies continue to be used in mobile field campaigns.

天气预报模式WRFV3.3在三峡库区的应用及参数敏感性试验研究

为实现长江三峡库区的高精度降水预报，利用新一代天气预报模式WRFV3.3对三峡库区两场典型降水过程进行模拟试验，并采用TS评分与极差分析法分析其不同参数化方案组合对降水模拟的影响，以评估WRF模式在三峡库区的区域适用性以及物理过程参数敏感性。结果表明，WRFV3.3能够较好地模拟三峡库区典型降水过程，且当WRF模式中微物理过程为Lin et al.方案、积云对流参数化方案为Simplified Arakawa-Schubert方案时，比其他参数化方案组合能得到更好的模拟效果；通过极差分析法比较发现，对于小雨和暴雨量级的降水，微物理过程方案和积云对流参数化方案的影响度接近，但对于中雨和大雨量级的降水，微物理过程方案的影响占主导地位。 In order to achieve high accuracy for precipitation forecast in the Three Gorges Reservoir area, a new generation of numerical weather model WRFV3.3 was applied to simulate two typical precipitation events in the Three Gorges Reservoir area, for evaluating WRF’s applicability in the research area. The im-pacts of different parameterization schemes combination on precipitation simulation were studied by adopt-ing TS and variance analysis, for analyzing sensitivity of the physical process parameterization schemes. The results indicate that WRFV3.3 can simulate typical precipitation events well in the Three Gorges Reservoir area. When the micro-physical process scheme is Lin et al. and the cumulus convective parameterization scheme is Simplified Arakawa-Schubert, the simulation of WRF is better than other parameterization scheme combinations. Comparison of variance analysis shows that the impact of the micro-physical process parame-terization schemes on precipitation is similar as the cumulus convective parameterization schemes when rain grade is 0.1 mm and 50 mm, while impact of the micro-physical process parameterization schemes is domi-nating when rain grade is 10 mm and 25 mm.

Evaluation of Microphysics Parameterization for Convective Clouds in the NCAR Community Atmosphere Model CAM5

Abstract A physically based two-moment microphysics parameterization scheme for convective clouds is implemented in the NCAR Community Atmosphere Model version 5 (CAM5) to improve the representation of convective clouds and their interaction with large-scale clouds and aerosols. The explicit treatment of mass mixing ratio and number concentration of cloud and precipitation particles enables the scheme to account for the impact of aerosols on convection. The scheme is linked to aerosols through cloud droplet activation and ice nucleation processes and to stratiform cloud parameterization through convective detrainment of cloud liquid/ice water content (LWC/IWC) and droplet/crystal number concentration (DNC/CNC). A 5-yr simulation with the new convective microphysics scheme shows that both cloud LWC/IWC and DNC/CNC are in good agreement with observations, indicating the scheme describes microphysical processes in convection well. Moreover, the microphysics scheme is able to represent the aerosol effects on convective clouds such as the suppression of warm rain formation and enhancement of freezing when aerosol loading is increased. With more realistic simulations of convective cloud microphysical properties and their detrainment, the mid- and low-level cloud fraction is increased significantly over the ITCZ–southern Pacific convergence zone (SPCZ) and subtropical oceans, making it much closer to the observations. Correspondingly, the serious negative bias in cloud liquid water path over subtropical oceans observed in the standard CAM5 is reduced markedly. The large-scale precipitation is increased and precipitation distribution is improved as well. The long-standing precipitation bias in the western Pacific is significantly alleviated because of microphysics–thermodynamics feedbacks.

Impact of Physics Representations in the HWRFX on Simulated Hurricane Structure and Pressure–Wind Relationships

Abstract A series of idealized experiments with the NOAA Experimental Hurricane Weather Research and Forecasting Model (HWRFX) are performed to examine the sensitivity of idealized tropical cyclone (TC) intensification to various parameterization schemes of the boundary layer (BL), subgrid convection, cloud microphysics, and radiation. Results from all the experiments are compared in terms of the maximum surface 10-m wind (VMAX) and minimum sea level pressure (PMIN)—operational metrics of TC intensity—as well as the azimuthally averaged temporal and spatial structure of the tangential wind and its material acceleration. The conventional metrics of TC intensity (VMAX and PMIN) are found to be insufficient to reveal the sensitivity of the simulated TC to variations in model physics. Comparisons of the sensitivity runs indicate that (i) different boundary layer physics parameterization schemes for vertical subgrid turbulence mixing lead to differences not only in the intensity evolution in terms of VMAX and PMIN, but also in the structural characteristics of the simulated tropical cyclone; (ii) the surface drag coefficient is a key parameter that controls the VMAX–PMIN relationship near the surface; and (iii) different microphysics and subgrid convection parameterization schemes, because of their different realizations of diabatic heating distribution, lead to significant variations in the vortex structure. The quantitative aspects of these results indicate that the current uncertainties in the BL mixing, surface drag, and microphysics parameterization schemes have comparable impacts on the intensity and structure of simulated TCs. The results also indicate that there is a need to include structural parameters in the HWRFX evaluation.

Sensitivity of tropical cyclone Jal simulations to physics parameterizations

In this study, the sensitivity of numerical simulations of tropical cyclones to physics parameterizations is carried out with a view to determine the best set of physics options for prediction of cyclones originating in the north Indian Ocean. For this purpose, the tropical cyclone Jal has been simulated by the advanced (or state of science) mesoscale Weather Research and Forecasting (WRF) model on a desktop mini super computer CRAY CX1 with the available physics parameterizations. The model domain consists of one coarse and two nested domains. The resolution of the coarse domain is 90 km while the two nested domains have resolutions of 30 and 10 km, respectively. The results from the inner most domain have been considered for analyzing and comparing the results. Model simulation fields are compared with corresponding analysis or observation data. The track and intensity of simulated cyclone are compared with best track estimates provided by the Joint Typhoon Warning Centre (JTWC) data. Two sets of experiments are conducted to determine the best combination of physics schemes for track and intensity and it is seen that the best set of physics combination for track is not suitable for intensity prediction and the best combination for track prediction overpredicts the intensity of the cyclone. The sensitivity of the results to orography and level of nesting has also been studied. Simulations were also done for the cyclone Aila with (i) best set of physics and (ii) randomly selected physics schemes. The results of the Aila case show that the best set of physics schemes has more prediction skill than the randomly selected schemes in the case of track prediction. The cumulus (CPS), planetary boundary layer (PBL) and microphysics (MP) parameterization schemes have more impact on the track and intensity prediction skill than the other parameterizations employed in the mesoscale model.

Impact of cloud parameterization on the numerical simulation of a super cyclone

Abstract. This study examines the role of parameterization of convection and explicit moisture processes on the simulated track, intensity and inner core structure of Orissa super cyclone (1999) in Bay of Bengal (north Indian Ocean). Sensitivity experiments are carried out to examine the impact of cumulus parameterization schemes (CPS) using MM5 model (Version 3.7) in a two-way nested domain (D1 and D2) configuration at horizontal resolutions (45–15 km). Three different cumulus parameterization schemes, namely Grell (Gr), Betts-Miller (BM) and updated Kain Fritsch (KF2), are tested. It is noted that track and intensity both are very sensitive to CPS and comparatively, KF2 predicts them reasonably well. Particularly, the rapid intensification phase of the super cyclone is best simulated by KF2 compared to other CPS. To examine the effect of the cumulus parameterization scheme at high resolution (5 km), the three-domain configuration (45-15-5 km resolution) is utilized. Based on initial results, KF2 scheme is used for both the domains (D1 and D2). Two experiments are conducted: one in which KF2 is used as CPS and another in which no CPS is used in the third domain. The intensity is well predicted when no CPS is used in the innermost domain. The sensitivity experiments are also carried out to examine the impact from microphysics parameterization schemes (MPS). Four cloud microphysics parameterization schemes, namely mixed phase (MP), Goddard microphysics with Graupel (GG), Reisner Graupel (RG) and Schultz (Sc), are tested in these experiments. It is noted that the tropical cyclone tracks and intensity variation have considerable sensitivity to the varying cloud microphysical parameterization schemes. The MPS of MP and Sc could very well capture the rapid intensification phase. The final intensity is well predicted by MP, which is overestimated by Sc. The MPS of GG and RG underestimates the intensity.

Numerical simulation of cloud burst event on August 05, 2010, over Leh using WRF mesoscale model

Localized deep cumulus convective clouds have a capability of giving enormous amount of rainfall over a limited horizontal area, within a short span of time. Such types of extreme rainfall events are most common over the high elevated areas of Northern India during the Southwest monsoon season which causes widespread damage to the property and lives. Therefore, it is necessary to predict such extreme events accurately to avoid damage associated with them. The numerical mesoscale model Weather Research and Forecasting has been used to simulate the cloud burst event of Leh on August 05, 2010, so as to capture the main characteristics of the various parameters associated with this localized mesoscale phenomenon. The model has been integrated with four nested domains keeping Leh and its adjoining area as center. Two cloud microphysics parameterization schemes namely WSM3 and WSM6 have been used for the sensitivity experiments and results have been analyzed to examine the performance of both the schemes in capturing such extreme localized heavy rainfall events. Results show that the WSM6 microphysics was able to simulate the precipitation near to the observation. WSM3 microphysics simulated the location of the circulation near to the observation. In addition, the results also show that the maximum magnitudes of meridional and vertical wind as simulated with WSM3 microphysics are 12 and 4 m/s, respectively.

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.

Modeling Rapid Intensification of Typhoon Saomai (2006) with the Weather Research and Forecasting Model and Sensitivity to Cloud Microphysical Parameterizations

Typhoon Saomai (2006) was one of the most severe typhoon landfalls in China from 1956 to 2010. The rapid intensification process of Typhoon Saomai is simulated with the advanced research version of the Weather Research and Forecasting (ARW) modeling system using different cloud microphysical parameterization schemes. The horizontal spacing of the finest nested mesh is 1.5 km. The intensity, precipitation, and inner-core structures of the simulated typhoons are verified against the observations. The performances of various cloud microphysical parameterization schemes are compared. It is found that varying the microphysics scheme generates little sensitivity in track, but results in pronounced deviations in intensity and inner-core structures. The results indicate the condensation and depositional growth of graupel or snow of the suitable cloud microphysical parameterization scheme enhances the diabatic heat releasing in the inner core region. The released diabatic heating determines the intensity and inner-core structures of typhoon. Furthermore, a positive feedback associated with the diabatic heating plays an important role in the intensification of the simulated storm with a suitable cloud microphysical parameterization scheme.

A New Bulk Microphysical Scheme That Includes Riming Intensity and Temperature-Dependent Ice Characteristics

Abstract A new bulk microphysical parameterization (BMP) scheme is presented that includes a diagnosed riming intensity and its impact on ice characteristics. As a result, the new scheme represents a continuous spectrum from pristine ice particles to heavily rimed particles and graupel using one prognostic variable [precipitating ice (PI)] rather than two separate variables (snow and graupel). In contrast to most existing parameterization schemes that use fixed empirical relationships to describe ice particles, general formulations are proposed to consider the influences of riming intensity and temperature on the projected area, mass, and fall velocity of PI particles. The proposed formulations are able to cover the variations of empirical coefficients found in previous observational studies. The new scheme also reduces the number of parameterized microphysical processes by ∼50% as compared to conventional six-category BMPs and thus it is more computationally efficient. The new scheme (called SBU-YLIN) has been implemented in the Weather Research and Forecasting (WRF) model and compared with three other schemes for two events during the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) over the central Oregon Cascades. The new scheme produces surface precipitation forecasts comparable to more complicated BMPs. The new scheme reduces the snow amounts aloft as compared to other WRF schemes and compares better with observations, especially for an event with moderate riming aloft. Sensitivity tests suggest both reduced snow depositional growth rate and more efficient fallout due to the contribution of riming to the reduction of ice water content aloft in the new scheme, with a larger impact from the partially rimed snow and fallout.

Microphysics parameterization for convective clouds in a global climate model: Description and single-column model tests

[1] An efficient two-moment microphysics parameterization scheme for convective clouds is developed to improve the representation of convective clouds and its interactions with stratiform clouds and aerosol in global climate models (GCMs). The scheme explicitly treats mass mixing ratio and number concentration of four hydrometeor species (cloud water, cloud ice, rain, and snow) and describes several microphysical processes, including autoconversion, self-collection, collection between hydrometeor species, freezing, cloud ice nucleation, droplet activation, and sedimentation. Thus this physically based scheme is suitable for investigating the interaction between convection and aerosol and the indirect aerosol effect on climate. An evaluation of the scheme in the single-column version of NCAR Community Atmospheric Model version 3.5 (CAM3.5) with the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) data shows that the simulation of cloud microphysical properties in convective core is significantly improved, indicating that the new parameterization describes the microphysical processes in convection reasonably well. The contribution from convective detrainment to large-scale cloud ice and liquid water budgets is enhanced greatly. With more realistic convective cloud microphysical properties and their detrainment, the surface stratiform precipitation, which is seriously underestimated in the model, is increased by a factor of roughly 2.5, and therefore is much closer to the observations. In addition, the simulations of net surface shortwave radiation flux, OLR, specific humidity, and temperature are also improved to some extent. Sensitivity experiments show that the microphysics scheme is moderately sensitive to model vertical resolution, updraft vertical velocity, and numerics, but less so to the lower boundary conditions of hydrometeor budget equations. The experiments with climatological aerosol distribution show that convective precipitation is suppressed with increasing aerosol amount, consistent with some available observations.

Modeling Aerosol Impacts on Convective Storms in Different Environments

Abstract Aerosols are known to have both direct and indirect effects on clouds through their role as cloud condensation nuclei. This study examines the effects of differing aerosol concentrations on convective storms developing under different environments. The Regional Atmospheric Modeling System (RAMS), a cloud-resolving model with sophisticated microphysical and aerosol parameterization schemes, was used to achieve the goals of this study. A sounding that would produce deep convection was chosen and consistently modified to obtain a variety of CAPE values. Additionally, the model was initiated with varying concentrations of aerosols that were available to act as cloud condensation nuclei. Each model run produced long-lived convective storms with similar storm development, but they differed slightly based on the initial conditions. Runs with higher initial CAPE values produced the strongest storms overall, with stronger updrafts and larger amounts of accumulated surface precipitation. Simulations initiated with larger concentrations of aerosols developed similar storm structures but showed some distinctive dynamical and microphysical changes because of aerosol indirect effects. Many of the changes seen because of varying aerosol concentrations were of either the same order or larger magnitude than those brought about by changing the convective environment.

An EOF‐based comparison and evaluation of simulated passive microwave signatures to observations over tropical oceans

Bayesian algorithms are a common method of retrieving cloud properties from a set of observed passive microwave brightness temperature (TB) measurements. In practice, such methods often use predefined databases from cloud‐resolving models to perform the retrieval. Successful performance in these types of Bayesian retrievals is greatly affected by the similarity of TBs between observed and predefined databases. Here empirical orthogonal function (EOF) analysis methods were used to illustrate the importance of predefined simulation databases on the ability to retrieve known regional variability in cloud structures across different parts of the tropical oceans and to provide insight on the relative impact of environmental conditions to limitations in cloud model microphysical parameterizations in retrieving different types of cloud structures. The spatial distributions of EOF coefficients in EOF space showed that there were both underrepresentation and overrepresentation between manifolds of the predefined and observed databases. Moreover, there was poor alignment in the frequency distribution between observed and simulated clouds structures. Additionally, the ability to retrieve known regional variability in convective cloud structure was dependent on the environmental conditions used to generate the simulated data set more so than limitations in the model microphysical parameterizations. The opposite was true for stratiform rain, as the dominant EOF patterns of the radiation indices for the predefined databases exhibit overproduction of large‐sized high‐density ice‐phase hydrometeors for a given rain content in comparison to the observations. Improvements to microphysical parameterization schemes appear to be necessary to produce radiance index vectors that are consistent with observations.

Impact of physical parameterization schemes on numerical simulation of super cyclone Gonu

The objective of this study is to investigate in detail the sensitivity of cumulus, planetary boundary layer and explicit cloud microphysics parameterization schemes on intensity and track forecast of super cyclone Gonu (2007) using the Pennsylvania State University-National Center for Atmospheric Research Fifth-Generation Mesoscale Model (MM5). Three sets of sensitivity experiments (totally 11 experiments) are conducted to examine the impact of each of the aforementioned parameterization schemes on the storm’s track and intensity forecast. Convective parameterization schemes (CPS) include Grell (Gr), Betts–Miller (BM) and updated Kain–Fritsch (KF2); planetary boundary layer (PBL) schemes include Burk–Thompson (BT), Eta Mellor–Yamada (MY) and the Medium-Range Forecast (MRF); and cloud microphysics parameterization schemes (MPS) comprise Warm Rain (WR), Simple Ice (SI), Mixed Phase (MP), Goddard Graupel (GG), Reisner Graupel (RG) and Schultz (Sc). The model configuration for CPS and PBL experiments includes two nested domains (90- and 30-km resolution), and for MPS experiments includes three nested domains (90-, 30- and 10-km grid resolution). It is found that the forecast track and intensity of the cyclone are most sensitive to CPS compared to other physical parameterization schemes (i.e., PBL and MPS). The simulated cyclone with Gr scheme has the least forecast track error, and KF2 scheme has highest intensity. From the results, influence of cumulus convection on steering flow of the cyclone is evident. It appears that combined effect of midlatitude trough interaction, strength of the anticyclone and intensity of the storm in each of these model forecasts are responsible for the differences in respective track forecast of the cyclone. The PBL group of experiments has less influence on the track forecast of the cyclone compared to CPS. However, we do note a considerable variation in intensity forecast due to variations in PBL schemes. The MY scheme produced reasonably better forecast within the group with a sustained warm core and better surface wind fields. Finally, results from MPS set of experiments demonstrate that explicit moisture schemes have profound impact on cyclone intensity and moderate impact on cyclone track forecast. The storm produced from WR scheme is the most intensive in the group and closer to the observed strength. The possible reason attributed for this intensification is the combined effect of reduction in cooling tendencies within the storm core due to the absence of melting process and reduction of water loading in the model due to absence of frozen hydrometeors in the WR scheme. We also note a good correlation between evolution of frozen condensate and storm intensification rate among these experiments. It appears that the Sc scheme has some systematic bias and because of that we note a substantial reduction in the rain water formation in the simulated storm when compared to others within the group. In general, it is noted that all the sensitivity experiments have a tendency to unrealistically intensify the storm at the later part of the integration phase.

Comparison of Evaporation and Cold Pool Development between Single-Moment and Multimoment Bulk Microphysics Schemes in Idealized Simulations of Tornadic Thunderstorms

Abstract Idealized simulations of the 3 May 1999 Oklahoma tornadic supercell storms are conducted at various horizontal grid spacings ranging from 1 km to 250 m, using a sounding extracted from a prior 3-km grid spacing real-data simulation. A sophisticated multimoment bulk microphysics parameterization scheme capable of predicting up to three moments of the particle or drop size distribution (DSD) for several liquid and ice hydrometeor species is evaluated and compared with traditional single-moment schemes. The emphasis is placed on the impact of microphysics, specifically rain evaporation and size sorting, on cold pool strength and structure, and on the overall reflectivity structure of the simulated storms. It is shown through microphysics budget analyses and examination of specific processes within the low-level downdraft regions that the multimoment scheme has important advantages, which lead to a weaker and smaller cold pool and better reflectivity structure, particularly in the forward-flank region of the simulated supercells. Specifically, the improved treatment of evaporation and size sorting, and their effects on the predicted rain DSDs by the multimoment scheme helps to control the cold bias often found in the simulations using typical single-moment schemes. The multimoment results are more consistent with observed (from both fixed and mobile mesonet platforms) thermodynamic conditions within the cold pools of the discrete supercells of the 3 May 1999 outbreak.

Impacts of cloud‐system resolving regional modeling on the simulation of monsoon depressions

The impacts of high‐resolution (<10 km) and cloud‐system‐resolving regional modeling (CSRM) on the simulation of an intense south Asian monsoon depression (MD) were examined using the WRF‐ARW model. Spatial resolution in this range was necessary to realistically simulate the MD's propagation, intensity, and precipitation. Simulations were however highly sensitive to the moist convection and cloud microphysics. The best scenarios were created by the microphysics parameterization (MP) that generated the most robust post‐landfall condensation associated with the MD, alone or in combination with the cumulus parameterization that triggered vigorous convection overland in the coarser setup. A sensitivity study of the MP schemes in CSRM suggested that more sophisticated mixed‐phased schemes contributed to higher simulation fidelity. Insufficient condensation and weak convection overland might induce spurious low systems over the Bay of Bengal through low‐level moisture advection, which further interfered with the MD and degraded several simulations.