Evaluation of Simulated Winter Precipitation Using WRF-ARW during the ICE-POP 2018 Field Campaign

AbstractThis study evaluates the performance of several cloud microphysics parameterizations in simulating surface precipitation for two snowstorm cases during the International Collaborative Experiment held at the PyeongChang 2018 Olympics and Winter Paralympic Games (ICE-POP 2018) field campaign. We compared four different schemes in the Weather Research and Forecasting (WRF) Model, namely the double-moment 6-class (WDM6), the WRF single-moment 6-class (WSM6), and Thompson and Morrison parameterizations. Both WSM6 and WDM6 overestimated the precipitation amount for the shallow precipitation system because of the substantial amount of cloud ice, mostly generated by the deposition process. The simulated precipitation amount and distribution for the deep precipitation system showed no noticeable differences in the different cloud microphysics parameterizations. However, the simulated hydrometeor type at the surface using WSM6 and WDM6 showed good agreement with observations for all cases. The accuracy of the mean mass-weighted terminal velocity of cloud ice applied in WSM6 and WDM6 is ±20%. The number concentration of cloud ice and the ice microphysics processes are newly retrieved with 1.2 times increased . For the shallow snowstorm, the precipitation amount was reduced by approximately 8% because of the inefficient deposition and its effects on the subsequent ice microphysical processes, such as the accretion of cloud ice by snow and the conversion from cloud ice to snow.

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Expanding the Goddard CSH Algorithm for GPM: New Extratropical Retrievals

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-18-0215.1 ◽

2019 ◽

Vol 58 (5) ◽

pp. 921-946 ◽

Cited By ~ 2

Author(s):

W.-K. Tao ◽

T. Iguchi ◽

S. Lang

Keyword(s):

High Latitude ◽

Wrf Model ◽

Tropical Rainfall Measuring Mission ◽

Consistency Check ◽

New Classification ◽

Surface Precipitation ◽

Winter Conditions ◽

Simulated Precipitation ◽

Combined Algorithm ◽

Self Consistency

AbstractThe Goddard convective–stratiform heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model to simulate LH profiles to build lookup tables (LUTs). However, the current LUTs in the CSH algorithm are not suitable for retrieving LH profiles at high latitudes or winter conditions that are needed for GPM. The NASA Unified-Weather Research and Forecasting (NU-WRF) Model is used to simulate three eastern continental U.S. (CONUS) synoptic winter and three western coastal/offshore events. The relationship between LH structures (or profiles) and other precipitation properties (radar reflectivity, freezing-level height, echo-top height, maximum dBZ height, vertical dBZ gradient, and surface precipitation rate) is examined, and a new classification system is adopted with varying ranges for each of these precipitation properties to create LUTs representing high latitude/winter conditions. The performance of the new LUTs is examined using a self-consistency check for one CONUS and one West Coast offshore event by comparing LH profiles retrieved from the LUTs using model-simulated precipitation properties with those originally simulated by the model. The results of the self-consistency check validate the new classification and LUTs. The new LUTs provide the foundation for high-latitude retrievals that can then be merged with those from the tropical CSH algorithm to retrieve LH profiles over the entire GPM domain using precipitation properties retrieved from the GPM combined algorithm.

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Assessing the Effects of Microphysical Scheme on Convective and Stratiform Characteristics in a Mei-Yu Rainfall Combining WRF Simulation and Field Campaign Observations

Advances in Meteorology ◽

10.1155/2020/8231320 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Lin Liu ◽

Chunze Lin ◽

Yongqing Bai ◽

Dengxin He

Keyword(s):

Wrf Model ◽

Cloud Microphysics ◽

Middle Level ◽

Weather Research And Forecasting ◽

Field Campaign ◽

Microphysical Properties ◽

Double Moment ◽

Storm Dynamics ◽

Precipitation Structure ◽

Upper Level

Microphysics parameterization becomes increasingly important as the model grid spacing increases toward convection-resolving scales. Using observations from a field campaign for Mei-Yu rainfall in China, four bulk cloud microphysics schemes in the Weather Research and Forecasting (WRF) model were evaluated with respect to their ability to simulate precipitation, structure, and cloud microphysical properties over convective and stratiform regimes. These are the Thompson (THOM), Morrison graupel/hail (MOR_G/H), Stony Brook University (SBU_YLIN), and WRF double-moment six-class microphysics graupel/hail (WDM6_G/H). All schemes were able to predict the rain band but underestimated the total precipitation by 23%–35%. This is mainly attributed to the underestimation of stratiform precipitation and overestimation of convective rain. For the vertical distribution of radar reflectivity, many problems remain, such as lower reflectivity values aloft in both convective and stratiform regions and higher reflectivity values at middle level. Each bulk scheme has its advantages and shortcomings for different cloud regimes. Overall, the discrepancies between model output and observations mostly exist in the midlevel to upper level, which results from the inability of the model to accurately represent the particle size distribution, ice processes, and storm dynamics. Further observations from major field campaigns and more detailed evaluation are still necessary.

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Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-17-0034.1 ◽

2017 ◽

Vol 74 (10) ◽

pp. 3145-3166 ◽

Cited By ~ 11

Author(s):

K. Gayatri ◽

S. Patade ◽

T. V. Prabha

Keyword(s):

Size Distribution ◽

Cloud Condensation Nuclei ◽

Wrf Model ◽

Cloud Droplet ◽

Liquid Water Content ◽

Cloud Microphysics ◽

Large Area ◽

Surface Precipitation ◽

Aerosol Cloud ◽

Bin Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

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A Comparative Study of Bin and Bulk Cloud Microphysics Schemes in Simulating a Heavy Precipitation Case

Atmosphere ◽

10.3390/atmos9120475 ◽

2018 ◽

Vol 9 (12) ◽

pp. 475 ◽

Cited By ~ 2

Author(s):

Hyunho Lee ◽

Jong-Jin Baik

Keyword(s):

Heat Release ◽

Latent Heat ◽

Wrf Model ◽

Heavy Precipitation ◽

Cloud Microphysics ◽

Latent Heat Release ◽

Microphysics Scheme ◽

Surface Precipitation ◽

Double Moment ◽

Bin Microphysics

Comparisons between bin and bulk cloud microphysics schemes are conducted by simulating a heavy precipitation case using a bin microphysics scheme and four double-moment bulk microphysics schemes in the Weather Research and Forecasting (WRF) model. For this, we implemented an updated bin microphysics scheme in the WRF model. All of the microphysics schemes underestimate observed strong precipitation, but the bin microphysics scheme yields the result that is closest to observations. The differences among the schemes are more pronounced in terms of hydrometeor number concentration than in terms of hydrometeor mixing ratio. In this case, the bin scheme exhibits remarkably more latent heat release by deposition and riming than the bulk schemes. This causes stronger updrafts and more upward transport of water vapor, which leads to more deposition, and again, increases the latent heat release. An additional simulation using the bin scheme but excluding the riming of cloud droplets on ice crystals, which is not or poorly treated in the examined bulk schemes, shows that surface precipitation is slightly weakened and moved farther downwind compared to that of the control simulation. This implies that the more appropriate representation of microphysical processes in the bin microphysics scheme contributes to the more accurate prediction of precipitation in this case.

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Evaluating Warm and Cold Rain Processes in Cloud Microphysical Schemes Using OLYMPEX Field Measurements

Monthly Weather Review ◽

10.1175/mwr-d-19-0092.1 ◽

2020 ◽

Vol 148 (5) ◽

pp. 2163-2190

Author(s):

Aaron R. Naeger ◽

Brian A. Colle ◽

Na Zhou ◽

Andrew Molthan

Keyword(s):

Wrf Model ◽

Field Measurements ◽

Weather Research And Forecasting ◽

Flow Conditions ◽

Surface Precipitation ◽

Particle Properties ◽

Warm Rain ◽

Simulated Precipitation ◽

Rain Fall ◽

Western Washington

Abstract Field observations from the Olympic Mountain Experiment (OLYMPEX) around western Washington State during two atmospheric river (AR) events in November 2015 were used to evaluate several bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) Model. These AR events were characterized by a prefrontal period of stable, terrain-blocked flow with an abundance of cold rain over the lowland region followed by less stable, unblocked flow with more warm rain, and a shift in the largest precipitation amounts to over the windward Olympic slopes. Our WRF simulations underpredicted the precipitation by 19%–36% in the Morrison (MORR) and Thompson (THOM) BMPs and 10%–23% in the predicted particle properties (P3) BMP, with the largest underpredictions over the windward slopes during the more convective, unblocked flow conditions. Several important processes related to the BMPs led to the differences in simulated precipitation. First, the prognostic single ice category parameterization in the P3 scheme promoted a more realistic evolution of rimed particles and larger cold rain production, which led to the lowest underpredictions in precipitation among the schemes. Second, efficient melting processes associated with the production of nonspherical ice and snow in the P3 and THOM BMPs, respectively, promoted a more realistic transition to rain fall speeds within the warm layer compared to the spherical snow assumption in MORR. Last, all BMPs underpredict the contribution of warm rain processes to the surface precipitation, particularly during the unblocked flow period, which may be partly explained by too weak condensational and collisional growth processes due to the neglect of turbulence parameterizations within the schemes.

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Revision of WDM7 Microphysics Scheme and Evaluation for Precipitating Convection over the Korean Peninsula

Remote Sensing ◽

10.3390/rs13193860 ◽

2021 ◽

Vol 13 (19) ◽

pp. 3860

Author(s):

Sungbin Jang ◽

Kyo-Sun Sunny Lim ◽

Jeongsu Ko ◽

Kwonil Kim ◽

GyuWon Lee ◽

...

Keyword(s):

Korean Peninsula ◽

Solid Phase ◽

Terminal Velocity ◽

Cloud Microphysics ◽

Probability Of Detection ◽

Fall Velocity ◽

Microphysics Scheme ◽

Simulated Precipitation ◽

Relationship Of ◽

The Impact

The Weather Research and Forecasting (WRF) Double-Moment 7-Class (WDM7) cloud microphysics scheme was developed to parameterize cloud and precipitation processes explicitly for mesoscale phenomena in the Korean Integrated Model system. However, the WDM7 scheme has not been evaluated for any precipitating convection system over the Korean peninsula. This study modified WDM7 and evaluated simulated convection during summer and winter. The suggested modifications included the integration of the new fall velocity–diameter relationship of raindrops and mass-weighted terminal velocity of solid-phase precipitable hydrometeors (the latter is for representing mixed-phase particles). The mass-weighted terminal velocity for snow and graupel has been suggested by Dudhia et al. (2008) to allow for a more realistic representation of partially rimed particles. The WDM7 scheme having an additional hail category does not apply this terminal velocity only for hail. Additionally, the impact of enhanced collision-coalescence (C-C) efficiency was investigated. An experiment with enhanced C-C efficiency overall improved the precipitation skill scores, such as probability of detection, equitable threat score, and spatial pattern correlation, compared with those of the control experiment for the summer and winter cases. With application of the new mass-weighted terminal velocity of solid-phase hydrometeors, the hail mixing ratio at the surface was considerably reduced, and rain shafts slowed down low-level winds for the winter convective system. Consequently, the simulated hydrometeors were consistent with observations retrieved via remote sensing. The fall velocity–diameter relationship of raindrops further reduced the cloud ice amount. The proposed modifications in our study improved the simulated precipitation and hydrometeor profiles, especially for the selected winter convection case.

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Improving High-Resolution Weather Forecasts Using the Weather Research and Forecasting (WRF) Model with an Updated Kain–Fritsch Scheme

Monthly Weather Review ◽

10.1175/mwr-d-15-0005.1 ◽

2016 ◽

Vol 144 (3) ◽

pp. 833-860 ◽

Cited By ~ 73

Author(s):

Yue Zheng ◽

Kiran Alapaty ◽

Jerold A. Herwehe ◽

Anthony D. Del Genio ◽

Dev Niyogi

Keyword(s):

High Resolution ◽

Initial Conditions ◽

Spatial Scales ◽

Wrf Model ◽

Cloud Microphysics ◽

Cumulus Parameterization ◽

Subgrid Scale ◽

Grid Spacing ◽

Dynamic Adjustment ◽

Surface Precipitation

Abstract Efforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale awareness for improving high-resolution short-term precipitation forecasts in the WRF Model. To address these issues, the authors introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain–Fritsch (KF) convective parameterization scheme in the WRF Model. These changes include subgrid-scale cloud–radiation interactions, a dynamic adjustment time scale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level–based entrainment methodology that includes scale dependency. A series of 48-h retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes, and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that 1) the source of initial conditions plays a key role in high-resolution precipitation forecasting, and 2) the authors’ updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, the study found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

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Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure

Monthly Weather Review ◽

10.1175/mwr-d-16-0385.1 ◽

2017 ◽

Vol 145 (12) ◽

pp. 4789-4812 ◽

Cited By ~ 22

Author(s):

Lulin Xue ◽

Jiwen Fan ◽

Zachary J. Lebo ◽

Wei Wu ◽

Hugh Morrison ◽

...

Keyword(s):

Mass Density ◽

Three Dimensional ◽

Wrf Model ◽

Terminal Velocity ◽

Squall Line ◽

Cold Pool ◽

Field Campaign ◽

Thermodynamic Structure ◽

Bin Microphysics ◽

The Impact

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

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Numerical Simulations of Airborne Glaciogenic Cloud Seeding Using the WRF Model with the Modified Morrison Scheme over the Pyeongchang Region in the Winter of 2016

Advances in Meteorology ◽

10.1155/2018/8453460 ◽

2018 ◽

Vol 2018 ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

Sanghee Chae ◽

Ki-Ho Chang ◽

Seongkyu Seo ◽

Jin-Yim Jeong ◽

Baek-Jo Kim ◽

...

Keyword(s):

Wrf Model ◽

Weather Conditions ◽

Cloud Microphysics ◽

Cloud Water ◽

Weather Research And Forecasting ◽

Cloud Seeding ◽

Wind Fields ◽

Liquid Water Path ◽

Microphysics Scheme ◽

Simulated Precipitation

A model was developed for simulating the effects of airborne silver iodide (AgI) glaciogenic cloud seeding using the weather research and forecasting (WRF) model with a modified Morrison cloud microphysics scheme. This model was used to hindcast the weather conditions and effects of seeding for three airborne seeding experiments conducted in 2016. The spatial patterns of the simulated precipitation and liquid water path (LWP) qualitatively agreed with the observations. Considering the observed wind fields during the seeding, the simulated spatiotemporal distributions of the seeding materials, AgI, and snowfall enhancements were found to be reasonable. In the enhanced snowfall cases, the process by which cloud water and vapor were converted into ice particles after seeding was also reasonable. It was also noted that the AgI residence time (>1 hr) above the optimum AgI concentration (105 m−3) and high LWP (>100 g m−2) were important factors for snowfall enhancements. In the first experiment, timing of the simulated snowfall enhancement agreed with the observations, which supports the notion that the seeding of AgI resulted in enhanced snowfall in the experiment. The model developed in this study will be useful for verifying the effects of cloud seeding on precipitation.

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Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development

Monthly Weather Review ◽

10.1175/mwr-d-15-0363.1 ◽

2016 ◽

Vol 144 (6) ◽

pp. 2395-2420 ◽

Cited By ~ 5

Author(s):

J.-W. Bao ◽

S. A. Michelson ◽

E. D. Grell

Keyword(s):

Tropical Cyclone ◽

Wrf Model ◽

Cloud Microphysics ◽

Weather Research And Forecasting ◽

Rapid Intensification ◽

Latent Heating ◽

Vertical Distributions ◽

Double Moment ◽

Microphysical Processes ◽

Definition Of

Abstract Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes.

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