Microphysical Parameterization Schemes Research Articles

Evaluating the performances of cloud microphysical parameterizations in WRF for the heavy rainfall event of Kerala (2018)

This study evaluates the performances of four different cloud microphysical parameterization (CMP) schemes of the Weather Research and Forecasting (WRF) model at 3 km horizontal resolution (lead time up to 96 h) for the Heavy Rainfall Event (HRE) over Kerala in August 2018. The goal is to identify the major drivers for rain making mechanism and evaluate the ability of CMPs to accurately simulate the event with special emphasis on rainfall. It is found that the choice of CMP has a considerable impact on the rainfall forecast characteristics and associated convection. Results are validated against the India Meteorological Department (IMD) station data and Global Precipitation Measurement (GPM) observations and found that, among the four CMP schemes, viz., Milbrandt (MIL), Thompson Aerosol Aware (TAA), WRF double-moment 6-class scheme (WDM6) and WRF single-moment 6-class scheme (WSM6); WDM6 is the best performing scheme in terms of rainfall. It is noted that mixed phase processes are dominant in this scenario and the inability (ability) of MIL and TAA (WDM6 and WSM6) to predict the frozen hydrometeors, and thus simulating the cold rain processes realistically led to large (small) errors in the rainfall forecast. The moisture convergence was prominent in the foothills of the Western Ghats and highly influential in facilitating orography driven lifting of moisture. The moisture budget results suggest that horizontal moisture flux convergence (MFC) was the major driver of convection with WDM6 predicting the peaks of MFC most consistently with the observed Tropical Rainfall Measuring Mission (TRMM) rainfall product. Additionally, from Contiguous Rain Area analysis it is also found that the WDM6 has the least volumetric error. This is to highlight that hydrometeor distributions are strongly modulated by MFC, which further impacts the latent heat generation and rainfall over the region. Overall results infer the substantial influence of CMPs on the forecast of the Heavy Rainfall Event. The findings of this study will be highly useful for operational forecasting agencies and disaster management authorities for mitigation of damages caused by this kind of severe HREs in the future.

Impact of initial conditions and cloud parameterization on the heavy rainfall event of Kerala (2018)

In Aug 2018, the extreme precipitation event had created devastation over Kerala's state for 1 week and led to more than 483 deaths, and destructions of properties cost more than 50,000 Crore rupees. We simulated the event with the Advanced Research Weather Research and Forecasting model (WRF-ARW). Two most popular initial conditions (ICs), i.e., the National Centre for Environment Prediction (NCEP-FNL) and European Centre for Medium-range Weather Forecasting (ECMWF-ERA5), have been used to investigate the impacts of ICs on the forecast skills (up to day1) with particular reference to rainfall. Using these ICs, the study simulated the event with four cloud microphysics parameterization schemes (CMPS), namely, Milbrandt–Yau, Thompson, Aerosol aware Thompson, and WDM6. The study examined the role of ICs in modulating the cloud microphysical properties and associated mechanisms impacting the rainfall characteristics, hydrometeor formation, and related convective mechanism over the region. A total of 24 simulations (2 ICs × 4 CMPS × 3 initial days 13–15 Aug 2018) are conducted. Results show that the ERA5 IC with Milbrandt–Yau CMPS has performed best among all the simulations. Nevertheless, in general, there is an underestimation of rainfall in the model. It is found that though an ample amount of moisture available at the lower levels of the troposphere in the model, however, due to the lack of intense updraft, this moisture could not reach the middle levels, resulting in robust dryness at these levels and adversely impacting the convection and rainfall. This process shows a deficiency in the formation of frozen hydrometeors in the model's upper levels, leading to the lack of cloud heating and weakly developed vertical pressure gradient. These chain processes resulted in weak convection and reduced rainfall in the model experiments. These findings are highly relevant to understand the limitations of the model, influences of ICs, and cloud microphysical parameterizations to forecast extreme rainfall events accurately.

Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) over the Middle and Lower Reaches of the Yangtze River in 2020

Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) was conducted over the middle and lower reaches of the Yangtze River during the period 16 June to 19 July 2020. This paper provides a brief overview of the IMFRE-II field campaign, including the multiple ground-based remote sensors, aircraft probes, and their corresponding measurements during the 2020 mei-yu period, as well as how to use these numerous datasets to answer scientific questions. The highlights of IMFRE-II are: (1) to the best of our knowledge, IMFRE-II is the first field campaign in China to use ground-based, airborne, and spaceborne platforms to conduct comprehensive observations over the middle and lower reaches of the Yangtze River; and (2) seven aircraft flights were successfully carried out, and the spectra of ice particles, cloud droplets, and raindrops at different altitudes were obtained. These in-situ measurements will provide a “cloud truth” to validate the ground-based and satellite-retrieved cloud and precipitation properties and quantitatively estimate their retrieval uncertainties. They are also crucial for the development of a warm (and/or cold) rain conceptual model in order to better understand the cloud-to-rain conversion and accretion processes in mei-yu precipitation events. Through an integrative analysis of ground-based, aircraft, and satellite observations and model simulations, we can significantly improve our cloud and precipitation retrieval algorithms, investigate the microphysical properties of cloud and precipitation, understand in-depth the formation and dissipation mechanisms of mei-yu frontal systems, and improve cloud microphysics parameterization schemes and model simulations.

Impact of WRF Parameterization Schemes on Track and Intensity of Extremely Severe Cyclonic Storm “Fani”

Weather Research and Forecasting (WRF) model version 4.1.3 is configured in the present study to understand the impact of microphysical parameterization schemes on the track and intensity of extremely severe cyclonic storm (ESCS) “Fani” that occurred during 26 April to 4 May 2019 in the Bay of Bengal. The model is customized with six different microphysical parameterization schemes along with Kain–Fritsch cumulus for convection and the Yonsei University planetary boundary-layer scheme for computation of heat and moisture transport. The simulations are conducted at 27-km horizontal resolution with 41 levels in the vertical for 150 h (00UTC 28 April to 06UTC 4 May 2019). Model-simulated features such as the track, track error, minimum central sea-level pressure (MSLP), maximum sustained surface wind (MSW), and precipitation are validated against India Meteorological Department (IMD) and Tropical Rainfall Measuring Mission (TRMM) observation data. Although all the schemes predict track patterns similar to observation, the MP3 scheme shows the least track error even after landfall, and its track length is maximum in comparison with other schemes, albeit less than the observed track. The MP3 scheme exhibits a better track for “Fani,” followed by MP14. The lowest mean direct position error (along-track error) of 85 km (68.5 km) is noted for the MP3 scheme, followed by 112.5 km (82.3 km) for the MP8 scheme. Analysis of the MSLP and MSW using the t-test suggests that the MP2 scheme has better forecast ability, followed by MP6. Analysis of the quantitative/spatial matching of the rainfall forecasts and TRMM observations using the Method for Object-Based Diagnostic Evaluation (MODE) tool suggests that the MP8 (MP14) scheme is capable of simulating the rainfall beyond (up to) 48 h. Analysis of the zonal cross-section of horizontal and vertical winds shows that intense convection is well simulated by the MP2, MP3, and MP4 schemes during the change of intensity from cyclonic storm to severe cyclonic storm (SCS), by MP6 and MP14 from SCS to very severe cyclonic storm (VSCS) and from VSCS to ESCS, and by MP8 at ESCS level. All the schemes can capture the eyewall and simulate the westerly that allowed the system to move north-northeastwards. The synoptic flow at different pressure levels is reproduced by all the schemes. However, assessing the impact of the microphysics parameterizations on the synoptic flow of “Fani” at low resolution was difficult. Analysis of Qc and Qr indicates definite impacts of the microphysical parameterizations on the vertical structure of “Fani” in producing rainfall. The MP3 scheme exhibits a better cloud pattern up to upper troposphere level, followed by the MP2 scheme. Analysis of the latent heat flux predicted using the different microphysics schemes suggests that the latent heat flux release at VSCS intensity level or above contributes to further intensification of the TC, and this feature is very well simulated by the MP2 scheme.

Sensitivity of Microphysical Schemes on the Simulation of Post-Monsoon Tropical Cyclones over the North Indian Ocean

Tropical Cyclones (TCs) are the most disastrous natural weather phenomenon, that have a significant impact on the socioeconomic development of the country. In the past two decades, Numerical Weather Prediction (NWP) models (e.g., Advanced Research WRF (ARW)) have been used for the prediction of TCs. Extensive studies were carried out on the prediction of TCs using the ARW model. However, these studies are limited to a single cyclone with varying physics schemes, or single physics schemes to more than one cyclone. Hence, there is a need to compare different physics schemes on multiple TCs to understand their effectiveness. In the present study, a total of 56 sensitivity experiments are conducted to investigate the impact of seven microphysical parameterization schemes on eight post-monsoon TCs formed over the North Indian Ocean (NIO) using the ARW model. The performance of the Ferrier, Lin, Morrison, Thompson, WSM3, WSM5, and WSM6 are evaluated using error metrics, namely Mean Absolute Error (MAE), Mean Square Error (MSE), Skill Score (SS), and average track error. The results are compared with Indian Meteorological Department (IMD) observations. From the sensitivity experiments, it is observed that the WSM3 scheme simulated the cyclones Nilofar, Kyant, Daye, and Phethai well, whereas the cyclones Hudhud, Titli, and Ockhi are best simulated by WSM6. The present study suggests that the WSM3 scheme can be used as the first best scheme for the prediction of post-monsoon tropical cyclones over the NIO.

Assessment of WRF-ARW model parameterization schemes for extreme heavy precipitation events associated with atmospheric rivers over West Coast of India

This study attempts to investigate the simulation of heavy precipitation events (HPEs) over the West Coast of India associated with atmospheric rivers (ARs) using the Advanced Research Weather Research and Forecasting (ARW-WRF) model. The study evaluates the sensitivity of five microphysical (Lin, WSM6, Goddard, Thompson, and Morrison) and cumulus (KF, BMJ, Grell3D, Tidtke, and GD) parameterization schemes to explore the capability to reproduce the AR associated HPEs. The model simulations were reasonably successful at reproducing key structural and synoptic characteristics of atmospheric rivers, including well-defined corridors of strong water vapor transport, meteorological variables and circulation features. Deviations in Rainfall and Wind profiles were observed in simulations among the different parameterization schemes. The model better simulated the AR related precipitation using the Lin, Thompson MP and KF, Grell3D CU schemes when compared to observations, and attributed to the moisture laden tendency of the schemes. Nonetheless, differences in precipitation distribution and overestimation of winds among the model runs using different microphysical and cumulus physics schemes were noted. The study highlights that simulation of AR associated HPEs using high-resolution mesoscale mode with suitable representations of physical parameterization schemes are useful for disaster management and to minimize the loss of fatalities and property.

Sensitivity studies of cloud microphysical schemes of WRF-ARW model in the simulation of trailing stratiform squall lines over the Gangetic West Bengal region

In this paper an attempt has been made to investigate the impact of different microphysical (MP) parameterization schemes in simulation of leading convective line with trailing stratiform (TS) squall lines observed over the Gangetic West Bengal (GWB) region of India during the pre-monsoon season of March–May using Advanced Research Weather Research and Forecasting (WRF-ARW). The model is employed to study the features associated with three TS squall line (May 15, 2009, May 5, 2010 and May 7, 2010) observed over the study region. The model sensitivity is evaluated with four different microphysics schemes of the model (Goddard, WDM6, Thompson and Morrison). Model simulations are carried out with three two-way nested domains with horizontal resolution of 18, 6 and 2 km grid spacing and explicit convection in the innermost domain. The model simulated results are compared with available observations (Surface data, rainfall, hydrometeors and Doppler Weather Radar products). The analysis demonstrates that the simulation of TS squall lines are very sensitive to the parameterization of microphysical processes of different MP schemes, in spite of using similar initial and boundary conditions and model configuration. The model provides better simulations of rainfall, maximum reflectivity and vertical profiles of hydrometeors with the Morrison MP Scheme. The study reveals that snow and graupel particles has significant impacts on the simulation of stratiform precipitation region of the TS squall line. The study suggests that simulation of TS squall lines using a high-resolution mesoscale model with suitable cloud microphysics scheme is useful for the prediction of such severe events.

Role of convective and microphysical processes on the simulation of monsoon intraseasonal oscillation

The study explores the role of ice-phase microphysics and convection for the better simulation of Indian summer monsoon rainfall (ISMR) and monsoon intraseasonal oscillation (MISO). Sensitivity experiments have been performed with coupled climate model- CFSv2 using different microphysics (with and without ice phase processes) and convective [Simple Arakawa Schubert (SAS), new SAS (NSAS)] parameterization schemes. Results reveal that the ice phase microphysics parameterization scheme performs better in the simulation of active and break composites of the ISMR as compared to ice-free runs. The difference between ice (ICE) and ice-free run (NOICE) can be attributed to the availability of copious cloud condensate at the upper level. Better representation of upper-level cloud condensate in ICE run (i.e., with ice phase microphysics) leads to correct representation of specific humidity in active and break spells. Proper depiction of upper-level cloud condensate further leads to realistic modulation of atmospheric circulation and better simulation of convection (as represented by OLR) in active and break spells of ICE run. As a result, better simulation of active and break occurs in the ICE run. In contrast, NOICE run (i.e., with warm phase microphysics) fails to depict upper-level cloud condensate in the active phase. It leads to an improper representation of specific humidity. Circulation features are also unrealistic, and convection is suppressed in the active phase. As a result, the active phase is not adequately simulated in the NOICE run. NOICE run composites during active spells depict the overestimation of the ascending branch of Hadley circulation as compared to MERRA reanalysis, which is relatively better in ICE run. NOICE run composites during active spells depict the overestimation of the ascending branch of Walker circulation as compared to MERRA reanalysis, which is further improved in ICE runs. The north–south space–time spectra of daily rainfall anomaly are also better captured by ICE run as compared to NOICE run. Results indicate that ice-phase processes are more important for capturing the difference between active and break composites, while convection parameterization is relatively more important for the intraseasonal variance analyses. Further improvements in ice microphysics parameterization with better convection schemes in models will be helpful for the betterment of MISO and will lead to the improved simulation of monsoon.

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics.

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

Novel Thunderstorm Alert System (NOTHAS)

A “Novel Thunderstorm Alert System” (NOTHAS) has been developed and extensively tested for forecast and warnings of mid-latitude and tropical convective events. The design of the system showed some potential advantages compared to earlier alert systems, mainly in reducing uncertainties in predictions by taking the given maximum hourly local-scale signal. It represents a dynamic tool which allows the use of the probability concept of multivariate distribution and integrating it into general function by taking all convective parameters. It utilizes the latest developed microphysical parameterization scheme using a scale and aerosol awareness convective scheme and the sharpest criteria for mid-latitude storms. NOTHAS shows consistency and some kind of flexibility in post-processing applications, regardless of different parameterizations used in the ensemble or deterministic forecasts. The scientific verification shows a high level of accuracy in all significant scores which indicates that severe weather outlooks produced by NOTHAS for several hours ahead are in good alignment with observed thunderstorm activity. This novel tool shows a good performance which has sufficient merit for further additional testing and system evaluation of different severe mid-latitude and tropical storms, tropical cyclones and other severe weather cases across regions.

What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

Comparison of three microphysics parameterization schemes in the WRF model for an extreme rainfall event in the coastal metropolitan City of Guangzhou, China

Abstract An extreme rainfall event in the coastal metropolitan city of Guangzhou, China is simulated by the Weather Research and Forecasting (WRF) model using three bulk microphysics schemes to explore the capability to reproduce the observed precipitation features by these schemes and their differences. The detailed comparison among the three runs in terms of radar reflectivity, precipitation, thermodynamic fields and microphysical processes are conducted. Results show that all the simulations can reproduce the two main heavy rainfall centers in Guangzhou and the first convection initiation. The accumulated precipitation in the simulation using the WSM6 scheme performs better than the others in terms of intensity and distribution compared to observations. The weaker accumulated precipitation in the second heavy rainfall center in the simulations using the Thompson and Morrison schemes result from their more dispersed precipitation distributions dominated by the cold pool intensity and distribution. The latent heating from the water vapor condensation dominates the convection initiation and storm development. The latent cooling from the rain water evaporation dominates the cold pool intensity and distribution, which influences the storm moving and subsequent convection propagation, and finally the intensity and distribution of surface precipitation. Sensitivity experiments of the latent heat confirm the dominant roles of latent heating/cooling, especially the water vapor condensation heating and rain water evaporation cooling, in the differences of the thermodynamic fields, storm development, convection propagation and surface precipitation among the three simulations.

Impact of Different Cloud Microphysics Parameterization Schemes on Typhoon Intensity and Structure

The impact of different cloud microphysics parameterization schemes on the intensity and structure of the Super-strong Typhoon Rammasun (1409) in 2014 is investigated using the Weather Research and Forecasting model version 3.4 with eight cloud microphysics parameterization schemes. Results indicate that the uncertainty of cloud microphysics schemes results in typhoon forecast uncertainties, which increase with forecast time. Typhoon forecast uncertainty primarily affects intensity predictions, with significant differences in predicted typhoon intensity using various cloud microphysics schemes. Typhoon forecast uncertainty also affects the predicted typhoon structure. Greater typhoon intensity is accompanied by smaller vortex width, tighter vortex structure, stronger wind in the middle and lower troposphere, greater height of the strong wind region, smaller thickness of the eyewall and the outward extension of the eyewall, and a warmer warm core at upper levels of the eye. The differences among the various cloud microphysics schemes lead to different amounts and distributions of water vapor and hydrometeors in clouds. Different hydrometeors have different vertical distributions. In the radial direction, the maxima for the various hydrometeors forecast by a single cloud microphysics scheme are collocated with each other and with the center of maximum precipitation. When the hydrometeor concentration is high and hydrometeors exist at lower altitudes, more precipitation often occurs. Both the vertical and horizontal winds are the strongest at the location of maximum precipitation. Results also indicate that typhoon intensities forecast by cloud microphysics schemes containing graupel processes are noticeably greater than those forecast by schemes without graupel processes. Among the eight cloud microphysics schemes investigated, typhoon intensity forecasts using the WRF Single-Moment 6-class and Thompson schemes are the most accurate.

Numerical Rainfall Simulation of Different WRF Parameterization Schemes with Different Spatiotemporal Rainfall Evenness Levels in the Ili Region

To obtain high-precision precipitation simulation results, different types of rainfall events in the Ili Region are simulated by using the Weather Research and Forecasting (WRF) model with different physical parameterization schemes. According to the spatiotemporal distribution of rainfall evenness, six rainfall events in the Ili Region are divided into four types. Six microphysical parameterization (MP) schemes, five planetary boundary layer (PBL) schemes, and five cumulus (CU) schemes are combined into 14 parameterization members to simulate the rainfall events. It is worth noting that the simulation result sequence of the WRF model (from best to worst) is as follows: type I (events 3 and 5) > type II (events 1 and 6) > type III (event 2) > type IV (event 4). This finding would imply that the WRF model has the best performance for rainfall events with even spatiotemporal distributions, while it is hard to achieve good simulation results for rainfall events with highly uneven spatial and temporal distributions. The results suggest that no single combination of parameterization members provides the best performance for all rainfall events. According to the overall scheme rankings, d, n, and j are the optimal parameterization combination members that accurately describe the spatiotemporal characteristics of the six rainfall events. The study provides guidance for the selection of the physical parameters for the accurate simulation of different types of rainfall events in the arid region of northwestern China.

Variable Raindrop Size Distributions in Different Rainbands Associated With Typhoon Fitow (2013)

AbstractThe microphysical characteristics of rain may vary in different rain regions of a tropical cyclone (TC), but few studies have demonstrated the differences in raindrop size distributions (RSDs) of convective rain in different rainbands of a specific TC. This study examines the RSD characteristics and evolution of convective rain within outer rainbands and a coastal‐front‐like rainband associated with Typhoon Fitow, based on observational data from a disdrometer at Shibo station in Shanghai, China, during 6–7 October 2013. Considering the fast passage of convective TC rainbands over the disdrometer and the low rain rate of stratiform rain in the outer area, this study proposes a modified rain‐type classification method based on the disdrometer data. This study indicates that convective outer‐rainband rain (ORR) and coastal‐front rain (CFR) have different rain parameters, three parameters of the gamma model, radar reflectivity–rain rate (Z‐R), and shape–slope (μ‐Λ) relationships. The convective ORR has higher concentrations at all drop sizes than the convective CFR as well as larger spectral width, leading to the greater rainfall rate. The different Z‐R relationships suggest the necessity of a variable relationship for quantitative precipitation estimation (QPE) in different rain regions of the TC. This study also demonstrates for the first time that the RSD evolution with increasing rain rate is different in various convective rainbands associated with Fitow, suggesting that different microphysical parameterization schemes may be required for different rainbands in TC models.

The Potential for Discriminating Microphysical Processes in Numerical Weather Forecasts Using Airborne Polarimetric Radio Occultations

Accurate representation of cloud microphysical processes in numerical weather and climate models has proven challenging, in part because of the highly specialized instrumentation required for diagnosing errors in simulated distributions of hydrometeors. Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a promising new technique that is sensitive to hydrometeors and has the potential to help address these challenges by providing microphysical observations that are relevant to larger spatial scales, especially if this type of observing system can be implemented on aircraft that can target heavy precipitation events. Two numerical experiments were run using a mesoscale model configured with two different microphysical parameterization schemes for a very intense atmospheric river (AR) event that was sampled by aircraft deploying dropsondes just before it made landfall in California, during the CalWater 2015 field campaign. The numerical experiments were used to simulate profiles of airborne polarimetric differential phase delay observations. The differential phase delay due to liquid water hydrometeors below the freezing level differed significantly in the two experiments, as well as the height of the maximum differential phase delay due to all hydrometeors combined. These results suggest that PRO observations from aircraft have the potential to contribute to validating and improving the representation of microphysical processes in numerical weather forecasts once these observations become available.

Sensitivity of Summer Precipitation Simulation to Microphysics Parameterization Over Eastern China: Convection‐Permitting Regional Climate Simulation

AbstractWith a six‐year (2009–2014) summer climate simulation using the Weather Research and Forecasting model at convection‐permitting resolution (4‐km grid spacing), the effects of microphysics parameterization (MP) schemes on precipitation characteristics are investigated in this study. The convection‐permitting simulations employ three popular MP schemes, namely, Lin (single‐moment bulk MP), Weather Research and Forecasting Single‐Moment 5‐class (one‐moment and mixed‐phased MP), and Thompson (two‐moment and mixed‐phase MP) scheme. By evaluating the simulations against the CMORPH, rain gauge (Station), and ERA‐Interim data, it is found that the convection‐permitting model reproduce well the summer precipitation amount and the associated large‐scale atmospheric circulations, which are insensitive to the choice of MP schemes. The simulations with three MP schemes overestimate the precipitation amount, especially over the Yangtze‐Huaihe River Valley. The overestimations may be due to the systematic biases, and cannot be significantly reduced by using different MP schemes. Moreover, all simulations capture well the major features of precipitation diurnal variations and their transition characteristics, but they significantly overestimate the precipitation frequency while underestimate the precipitation intensity. The analysis on the microphysical hydrometeors shows that the model‐simulated precipitation amount is considerably affected by the vertical profiles of solid hydrometeors, especially the snow and graupel particles. The Thompson scheme creates more snow particles and less graupel than the other schemes, while produces the least precipitation amount that best matches the CMORPH.

Microphysical Process Comparison of Three Microphysics Parameterization Schemes in the WRF Model for an Idealized Squall-Line Case Study

Abstract Three bulk microphysics schemes with different complexities in the Weather Research and Forecasting Model are compared in terms of the individual microphysical process terms of the hydrometeor mass and number mixing ratio tendency equations in an idealized 2D squall-line case. Through evaluation of these process terms and of hydrometeor size distributions, it is shown that the differences in the simulated population characteristics of snow, graupel, and rainwater are the prominent factors contributing to the differences in the development of the simulated squall lines using these schemes. In this particular case, the gust front propagation speed produced by the Thompson scheme is faster than in the other two schemes during the first 2 h of the simulation because it has a larger dominant graupel size. After 2 h into the simulation, the initially less intense squall lines in the runs using the WSM6 and Morrison schemes start to catch up in intensity and development to the run using the Thompson scheme. Because the dominant size of graupel particles in the runs using the WSM6 and Morrison schemes is smaller, these particles take more time to fall below the freezing level and enhance the rainwater production and its evaporative cooling. In the run using the Thompson scheme, the graupel production slows down at later times while the snow particle growth increases, leading to more snow falling below the freezing level to melt and surpass graupel particle melting in the production of rainwater.

Evaluation of Cumulus and Microphysics Parameterizations in WRF across the Convective Gray Zone

Abstract This study evaluates the grid-length dependency of the Weather Research and Forecasting (WRF) Model precipitation performance for two cases in the Southern Great Plains of the United States. The aim is to investigate the ability of different cumulus and microphysics parameterization schemes to represent precipitation processes throughout the transition between parameterized and resolved convective scales (e.g., the gray zone). The cases include the following: 1) a mesoscale convective system causing intense local precipitation, and 2) a frontal passage with light but continuous rainfall. The choice of cumulus parameterization appears to be a crucial differentiator in convective development and resulting precipitation patterns in the WRF simulations. Different microphysics schemes produce very similar outcomes, yet some of the more sophisticated schemes have substantially longer run times. This suggests that this additional computational expense does not necessarily provide meaningful forecast improvements, and those looking to run such schemes should perform their own evaluation to determine if this expense is warranted for their application. The best performing cumulus scheme overall for the two cases studies here was the scale-aware Grell–Freitas cumulus scheme. It was able to reproduce a smooth transition from subgrid- (cumulus) to resolved-scale (microphysics) precipitation with increasing resolution. It also produced the smallest errors for the convective event, outperforming the other cumulus schemes in predicting the timing and intensity of the precipitation.

An Evaluation of Simulated Precipitation Characteristics during OLYMPEX

Abstract The OLYMPEX field campaign, which took place around the Olympic Mountains of Washington State during winter 2015/16, provided data for evaluating the simulated microphysics and precipitation over and near that barrier. Using OLYMPEX observations, this paper assesses precipitation and associated microphysics in the WRF-ARW model over the U.S. Pacific Northwest. Model precipitation from the University of Washington real-time WRF forecast system during the OLYMPEX field program (November 2015–February 2016) and an extended period (2008–18) showed persistent underprediction of precipitation, reaching 100 mm yr−1 over the windward side of the coastal terrain. Increasing horizontal resolution does not substantially reduce this underprediction. Evaluating surface disdrometer observations during the 2015/16 OLYMPEX winter, it was found that the operational University of Washington WRF modeling system using Thompson microphysics poorly simulated the rain drop size distribution over a windward coastal valley. Although liquid water content was represented realistically, drop diameters were overpredicted, and, consequently, the rain drop distribution intercept parameter was underpredicted. During two heavy precipitation periods, WRF realistically simulated environmental conditions, including wind speed, thermodynamic structures, integrated moisture transport, and melting levels. Several microphysical parameterization schemes were tested in addition to the Thompson scheme, with each exhibiting similar biases for these two events. We show that the parameterization of aerosols over the coastal Northwest offered only minor improvement.