Cloud Microphysics Parameterization Schemes Research Articles

Combining effects of cloud microphysical and planetary boundary layer parameterization schemes on the prediction of tropical cyclone intensity

The numerical simulation of tropical cyclone (TC) can be affected by the choices in physics parameterization schemes. These effects can be from the single scheme or the combination of multiple ones due to closely linked physical processes. Previous studies have discussed the roles of different schemes in TC simulation, but the roles of scheme combinations still remain to be explored. To investigate the combining effects of cloud microphysical (MP) and planetary boundary layer (PBL) parameterization schemes on the prediction of TC intensity, two Single-Moment MP schemes, WRF 6-class (WSM6) and Goddard 4ice, and two PBL schemes, non-local closure Yonsei University (YSU) and local closure Quasi-normal Scale Elimination (QNSE), were selected for the cloud-resolving simulations of both real and idealized cases using the Weather Research and Forecasting (WRF) model.Results showed that the experiments combining the PBL scheme with different MP schemes had different performances in reproducing TC intensity. The local QNSE PBL scheme, compared with non-local YSU, simulated larger surface sensible, latent, and moisture fluxes, while not necessarily leading to a stronger TC. When used in conjunction with the Goddard MP scheme, the QNSE scheme can simulate a stronger TC than the YSU scheme, but when used with the WSM6 MP scheme, there was little difference in their intensity. Goddard 4ice scheme adding hail class, compared with WSM6, simulated a better-organized eyewall, more latent heat release and convective bursts, leading to the formation of a clear warm core in the upper troposphere and thus contributing to the intensification of TC. Only with the coupling of MP and PBL schemes, did the simulation generate a compact and erect eyewall, which further enhanced TC intensity via stronger convergence airflow and more water vapor supply at the lower layer. Idealized experiments were consistent with those in real cases, demonstrating the TC sensitivity responding to different combinations while the uncertainties remained in the selection of these schemes.

Study on the Vertical Structure and the Evolution of Precipitation Particle Spectrum Parameters of Stratocumulus Clouds over North China Based on Aircraft Observation

The understanding of the macro- and micro-structure, particle spectrum parameters, and their evolutions in different parts of stratocumulus clouds based on aircraft observation data, is important basic data for the development of cloud microphysical parameterization schemes and the quantitative retrieval of cloud-precipitation by radar and satellite detections. In this study, a total of ten vertical measurements during three aircraft observations were selected to analyze the vertical distribution of cloud microphysical properties in different parts of stratocumulus clouds in Hebei, North China. It was found that the downdraft in the cumulus cloud area was stronger than that in the stratiform cloud area, with the temperature at the same height higher than that in the stratiform cloud area, and the height of the 0 °C layers was correspondingly higher. In terms of particle spectrum parameters, the intercept and slope parameters of particle spectrum below melting levels in the cumulus part were higher than those in stratiform clouds area in the same weather process. In different vertical detection, it was found that the ice particles have begun to melt in the negative temperature layer near 0 °C level, and there might be sublimation, fragmentation, and aggregation in the melting process of ice phase particles. In addition, the melting process changed the spectral parameters greatly and also changed the correlation between the intercept and slope of the particle spectrum. The slope below the 0 °C level increased with the increase of intercept, which was greater than that above the 0 °C level. The relationship obtained between the intercept parameter of the particle’s spectrum and temperature, and the correlation between the maximum diameter and slope parameter of the particle spectrum, have certain reference significance for cloud physical parameterization and the quantitative retrieval of cloud precipitation by radar and satellite in North China and similar climate background areas.

Sensitivity of Real‐Time Forecast for Typhoons Around Korea to Cumulus and Cloud Microphysics Schemes

AbstractIn numerical weather prediction models, the typhoon track and intensity forecast performances are highly sensitive to physics parameterization schemes. To investigate the impact of physics parameterization schemes on the real‐time short‐term forecasts, we simulated six typhoons which directly/indirectly affected the South Korea region in recent years using the Weather Research and Forecasting (WRF) model. Three cumulus parameterization schemes (CPSs) of Kain‐Fritsch (KF), Betts‐Miller‐Janjić (BMJ), modified Tiedtke (TDK), and two cloud microphysics parameterization schemes (MPSs) of WRF‐single‐moment‐microphysics class 6 (WSM6), Predicted Particle Properties (P3) 1‐category were selected for the sensitivity experiment. The results showed that there was a significant difference in simulated typhoon track and intensity performances depending on the physics schemes. On average, the typhoon forecast performances were improved when applying the KF scheme for CPS and WSM6 scheme for MPS in our experimental setup. The BMJ‐applied runs showed the worst performances, which simulated westward shifted typhoon tracks compared to other runs. Overall, the typhoon track and intensity spreads tended to be more sensitive to CPSs and MPSs, respectively. We conducted additional sensitivity experiments using the BMJ scheme with modified reference and temperature profiles. The result showed that the overactivity of the BMJ scheme at low latitudes was reasonably reduced, leading to the improved simulation of typhoons and synoptic fields.

Comparison of microphysics parameterization schemes on cloud macrophysics forecasts for mixed convective-stratiform cloud events

In this study, the performances and uncertainties of cloud microphysics parameterization (MP) schemes for simulating cloud macrophysics associated with mixed convective-stratiform cloud (MCSC) events are investigated. MCSC system is the primary object of cloud seeding for the purpose of rain enhancement in North China. Understanding the forecast uncertainties of cloud macrophysics, such as cloud top temperature (CTT), cloud base height (CBH), and cloud optical thickness (COT), is of great significance for cloud seeding operations. Simulations of cloud macrophysics are verified using cloud data retrieved from the Feng-Yun-2F geostationary meteorological satellite, radiosondes and Moderate Resolution Imaging Spectroradiometer (MODIS) products. The performances of several MP schemes to accurately simulate cloud macrophysics within ensemble forecasts is explored using both grid-wise and object-based metrics. Large differences are found among schemes in simulated cloud macrophysics compared with similar performances in simulated precipitation. In most cases, the ensemble mean simulates more realistically than each single scheme. The ensemble spread varies somewhat according to the simulated variables. For CBH, the ensemble shows adequate ensemble spread, while relative underdispersion occurs for CTT and COT. Detailed COT comparisons of reveal that COT bias mainly comes from the contribution of cloud droplets and snow. The causes of COT bias are further investigated by a detailed comparison of the cloud water path (CWP) and cloud effective radius (EFFR). The study establishes a baseline for ensemble forecasting of cloud macrophysics.

Demonstration of the Temporal Evolution of Tropical Cyclone “Phailin” Using Gray-Zone Simulations and Decadal Variability of Cyclones over the Bay of Bengal in a Warming Climate

The intensity and frequency variability of cyclones in the North Indian Ocean (NIO) have been amplified over the last few decades. The number of very severe cyclonic storms (VSCSs) over the North Indian Ocean has increased over recent decades. “Phailin”, an extreme severe cyclonic storm (ESCS), occurred during 8–13 October 2013 over the Bay of Bengal and made landfall near the Gopalpur coast of Odisha at 12 UTC on 12 October. It caused severe damage here, as well as in the coastal Odisha, Andhra Pradesh, and adjoining regions due to strong wind gusts (~115 knot/h), heavy precipitation, and devastating storm surges. The fidelity of the WRF model in simulating the track and intensity of tropical cyclones depends on different cloud microphysical parameterization schemes. Thus, four sensitivity simulations were conducted for Phailin using double-moment and single-moment microphysical (MP) parameterization schemes. The experiments were conducted to quantify and characterize the performance of such MP schemes for Phailin. The simulations were performed by the advanced weather research and forecasting (WRF-ARW) model. The model has two interactive domains covering the entire Bay of Bengal and adjoining coastal Odisha on 25 km and 8.333 km resolutions. Milbrandt–Yau (MY) double-moment and WRF single-moment microphysical schemes, with 6, 5, and 3 classes of hydrometeors, i.e., WSM6, WSM5, and WSM3, were used for the simulation. Experiments for Phailin were conducted for 126 h, starting from 00 UTC 08 October to 06 UTC 13 October 2013. It was found that the track, intensity, and structure of Phailin are highly sensitive to the different microphysical parameterization schemes. Further, the precipitation and cloud distribution were studied during the ESCS stage of Phailin. The microphysics schemes (MY, WSM3, WSM5, WSM6), along with Grell–Devenyi ensemble convection scheme predicted landfall of Phailin over the Odisha coast with significant track errors. Supply of moisture remains a more crucial component than SST and wind shear for rapid intensification of the Phailin 12 h before landfall over the Bay of Bengal. Finally, the comparison of cyclone formation between two decades 2001–2010 and 2011–2020 over the Bay of Bengal inferred that the increased numbers of VSCS are attributed to the supply of abundant moisture at low levels in the recent decade 2011–2020.

Influence of cloud microphysical parameterization on the characteristics of monsoon depressions over the Indian region

AbstractIndian summer monsoon (ISM) low‐pressure systems are considered as the lifeline for seasonal monsoon rainfall over the Indian region. However, the current models have limitations in predicting their characteristics and rainfall. This study assesses the influence of five cloud microphysical parameterization Schemes (MP) on simulations of 14 monsoon deep depressions (DD) using the weather research and forecasting (WRF) model. The simulations are carried out with a lead time up to 96 hr in a nested domain resolution of 27, 9, and 3 km. The five cloud microphysical parameterizations, that is, WRF Double moment (WDM6), WRF single moment (WSM6), Milbrandt (MIL), Thompson (THOM), and Aerosol Aware Thompson (AAT), are considered in this study, leading to a total of 70 simulations. The results are validated through composite analysis at a radial distance of 300 km from the respective storm centres. The choice of MP significantly impacts the key characteristics of the monsoon DDs such as rainfall, wind, temperature, moisture, humidity, hydrometeors, and associated convective processes. In terms of rainfall, it is found that WDM6 (AAT) has the best (worst) performance with a lead time up to day‐4. Besides, WDM6 has simulated the best result in terms of temperature and specific humidity. Examining the hydrometeors distribution around the storm intense convective region (i.e., 300 km), it is noted that frozen hydrometeors (i.e., ice, snow, and graupel) are mainly modulating the rainfall. There is a general tendency to overestimate snow and graupel among MP except WDM6. Further, ice hydrometeors are well represented in WDM6 compared with others leading to better rainfall forecast. The moisture flux convergence and absolute vorticity are two major mechanisms determining the convection within the storm's core zone, and WDM6 stands out the best among these schemes. The findings of this study are relevant and have direct consequences to the operational applications.

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 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 Investigations of Atmospheric Rivers and the Rain Shadow over the Santa Clara Valley

This study investigated precipitation distribution patterns in association with atmospheric rivers (ARs). The Weather Research and Forecasting (WRF) model was employed to simulate two strong atmospheric river events. The precipitation forecasts were highly sensitive to cloud microphysics parameterization schemes. Thus, radar observed and simulated Z H and Z D R were evaluated to provide information about the drop-size distribution (DSD). Four microphysics schemes (WSM-5, WSM-6, Thompson, and WDM-6) with nested simulations (3 km, 1 km, and 1/3 km) were conducted. One of the events mostly contained bright-band (BB) rainfall and lasted less than 24 h, while the other contained both BB and non-bright-band (NBB) rainfall, and lasted about 27 h. For each event, there was no clear improvement in the 1/3 km model, over the 1 km model. Overall, the WDM-6 microphysics scheme best represented the rainfall and the DSD. It appears that this scheme performed well, due to its relative simplicity in ice and mixed-phase microphysics, while providing double-moment predictions of warm rain microphysics (i.e., cloud and rain mixing ratio and number concentration). The other schemes tested either provided single-moment predictions of all classes or double-moment predictions of ice and rain (Thompson). Considering the shallow nature of precipitation in atmospheric rivers and the high-frequency of the orographic effect enhancing the warm rain process, these assumptions appear to be applicable over the southern San Francisco Bay Area.

A Study of Characteristics of the Cloud Microphysical Parameterization Schemes in Mesoscale Models and Its Applicability to China

A Study of Characteristics of the Cloud Microphysical Parameterization Schemes in Mesoscale Models and Its Applicability to China

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.

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.

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.

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.

Sensitivity of Numerical Simulation of Early Rapid Intensification of Hurricane Emily (2005) to Cloud Microphysical and Planetary Boundary Layer Parameterizations

Abstract An advanced research version of the Weather Research and Forecasting (ARW) Model is used to simulate the early rapid intensification of Hurricane Emily (2005) using grids nested to high resolution (3 km). A series of numerical simulations is conducted to examine the sensitivity of the simulation to available cloud microphysical (CM) and planetary boundary layer (PBL) parameterization schemes. Results indicate that the numerical simulations of the early rapid intensification of Hurricane Emily are very sensitive to the choice of CM and PBL schemes in the ARW model. Specifically, with different CM schemes, the simulated minimum central sea level pressure (MSLP) varies by up to 29 hPa, and the use of various PBL schemes has resulted in differences in the simulated MSLP of up to 19 hPa during the 30-h forecast period. Physical processes associated with the above sensitivities are investigated. It is found that the magnitude of the environmental vertical wind shear is not well correlated with simulated hurricane intensities. In contrast, the eyewall convective heating distributions and the latent heat flux and high equivalent potential temperature (θe) feeding from the ocean surface are directly associated with the simulated intensities. Consistent with recognized facts, higher latent heat release in stronger eyewall convection, stronger surface energy, and high θe air feeding from the ocean surface into the hurricane eyewall are evident in the more enhanced convection and intense storms. The sensitivity studies in this paper also indicate that the contributions from the CM and PBL processes can only partially explain the slow intensification in the ARW simulations. Simulation at 1-km grid resolution shows a slight improvement in Emily’s intensity forecast, implying that the higher resolution is somewhat helpful, but still not enough to cause the model to reproduce the real intensity of the hurricane.

Numerical comparison study of cloud microphysical parameterization schemes for a moderate snowfall event in North China

A moderate snowfall event in North China is simulated using the high-resolution mesoscale model MM5. A fourfold-nest experiment, with a minimum horizontal grid size of 2 km, is run. In order to study the cloud microphysics processes associated with the snowfall, two experiments were conducted in two inner domains, one using the Goddard scheme (Goddard experiment), and the other using the Reisner scheme (Reisner experiment). The analysis focused on the comparison of the cloud microphysics processes which occurred in the experiments.