• Atmosphere
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• v.29 no.2
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• pp.227-239
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• 2019

This paper reviews various bulk-type cloud microphysics parameterizations (BCMPs). BCMP, predicting the moments of size distribution of hydrometeors, parameterizes the grid-resolved cloud and precipitation processes in atmospheric models. The generalized gamma distribution is mainly applied to represent the hydrometeors size distribution in BCMPs. BCMP can be divided in three different methods such as single-moment, double-moment, and triple-moment approaches depending on the number of prognostic variables. Single-moment approach only predicts the hydrometeors mixing ratio. Double-moment approach predicts not only the hydrometeors mixing ratio but also the hydrometeors number concentration. Triple-moment approach predicts the dispersion parameter of hydrometeors size distribution through the prognostic reflectivity, together with the number concentrations and mixing ratios of hydrometeors. Triple-moment approach is the most time expensive method because it has the most number of prognostic variables. However, this approach can allow more flexibility in representing hydrometeors size distribution relative to single-moment and double-moment approaches. At the early stage of the development of BMCPs, warm rain processes were only included. Ice-phase categories such as cloud ice, snow, graupel, and hail were included in BCMPs with prescribed properties for densities and sedimentation velocities of ice-phase hydrometeors since 1980s. Recently, to avoid fixed properties for ice-phase hydrometeors and ad-hoc category conversion, the new approach was proposed in which rimed ice and deposition ice mixing ratios are predicted with total ice number concentration and volume.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.2
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• pp.135-151
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• 2013

This study has been carried out to analyze the sensitivity of ozone concentrations by employing different options of cumulus parameterization schemes (CPSs) and microphysics schemes in MM5 models. These sensitivity tests were applied to long-range transport case of higher ozone over Northeast Asia. Employed CPS schemes are Betts-Miller (BM), Grell (GR), Kain-Fritsch2 (KF2), Anthes-Kuo (AK), None scheme (grid scale physics only), and four microphysics used here are Simple ice, Reisner1, Reisner2, Schultz scheme in MM5. We chose two cases of high ozone long range transport case by employing both concentrations ozone level and backward trajectory model. The results showed that modeled ozone concentrations indicated about 10% differences among CPSs. Of the all options, GR and KF2 (for CPS), and Rersiner-1 and Resiner-2 (for microphysics) showed relatively good and stable variations against ensemble mean values. For both CPS and microphysics schemes, the difference of precipitation arising from different parameterization schemes was significant by itself, but the resultant ozone variations showed only marginal. But the cloud fraction differences arising from different parameterization schemes showed better correlation with ozone variations than precipitation differences, indicating that the photochemical ozone generation variations is more dominant by cloud fraction than wet removal process for high and long-ranged transported ozone cases over Northeast Asia.

• Atmosphere
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• v.16 no.3
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• pp.203-213
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• 2006

The objective of this paper is to investigate the effects of physical parameterization on the simulation of a snowfall event over Korea caused by air-mass transformation by using the PSU/NCAR MM5. A heavy snowfall event over Korea during 3-5 January 2003 is selected. In addition to the control experiments employing simple-ice microphysics scheme, MRF PBL scheme, and original surface layer process, three consequent physics sensitivity experiments are performed. Each experiment exchanges microphysics (Reisner Graupel), boundary layer (YSU PBL) schemes, and revised surface layer process with a reduced thermal roughness length for the control run. The control run reproduces an overall pattern of snowfall over Korea, but with a high bias by a factor of about 2. As revealed in the previous studies, the cloud microphysics and PBL parameterizations do not show a significant sensitivity for the case of snowfall. A more sophisticated cloud processes does not reveal a discernible effect on the simulated snowfall. Further, high bias in snowfall is exaggerated when a more realistic PBL scheme is employed. On the other hand, it is found that the revised surface layer process plays a role in improving the prediction of snowfall by reducing it. Thus, it is found that a realistic design of surface layer physics in mesoscale models is an important factor to the reduction of systematic bias of the snowfall over Korea that is caused by air-mass transformation over the Yellow sea.

• Atmosphere
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• v.27 no.1
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• pp.17-28
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• 2017

The sensitivity of the typhoon track and intensity simulation to physics schemes of the global model are examined for the typhoon Bolaven and Tembin cases by using the Global/Regional Integrated Model System-Global Model Program (GRIMs-GMP) with the physics package version 2.0 of the Korea Institute of Atmospheric Prediction Systems. Microphysics, Cloudiness, and Planetary boundary Layer (PBL) parameterizations are changed and the impact of each scheme change to typhoon simulation is compared with the control simulation and observation. It is found that change of microphysics scheme from WRF Single-Moment 5-class (WSM5) to 1-class (WSM1) affects to the typhoon simulation significantly, showing the intensified typhoon activity and increased precipitation amount, while the effect of the prognostic cloudiness and PBL enhanced mixing scheme is not noticeable. It appears that WSM1 simulates relatively unstable and drier atmospheric structure than WSM5, which is induced by the latent heat change and the associated radiative effect due to not considering ice cloud. And WSM1 results the enhanced typhoon intensity and heavy rainfall simulation. It suggests that the microphysics is important to improve the capability for typhoon simulation of a global model and to increase the predictability of medium range forecast.

• Korean Journal of the Atmospheric Sciences
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• v.78 no.5
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• pp.1629-1645
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• 2021

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part I of this study addressed collision-coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision-coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

• Atmosphere
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• v.26 no.3
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• pp.435-444
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• 2016

In spite of considerable progress in the recent decades, there still remain large uncertainties in numerical cloud models. In this study, effects of uncertainty in terminal velocity of graupel on cloud simulation are investigated. For this, a two-dimensional bin microphysics cloud model is employed, and deep convective clouds are simulated under idealized environmental conditions. In the sensitivity experiments, the terminal velocity of graupel is changed to twice and half the velocity in the control experiment. In the experiment with fast graupel terminal velocity, a large amount of graupel mass is present in the lower layer. On the other hand, in the experiment with slow graupel terminal velocity, almost all graupel mass remains in the upper layer. The graupel size distribution exhibits that as graupel terminal velocity increases, in the lower layer, the number of graupel particles increases and the peak radius in the graupel mass size distribution decreases. In the experiment with fast graupel terminal velocity, the vertical velocity is decreased mainly due to a decrease in riming that leads to a decrease in latent heat release and an increase in evaporative cooling via evaporation, sublimation, and melting that leads to more stable atmosphere. This decrease in vertical velocity causes graupel particles to fall toward the ground easier. By the changes in graupel terminal velocity, the accumulated surface precipitation amount differs up to about two times. This study reveals that the terminal velocity of graupel should be estimated more accurately than it is now.

• Atmosphere
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• v.28 no.2
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• pp.175-185
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• 2018

Characteristics of precipitation response to enhanced aerosols have been investigated during the severe haze events observed in Korea for 2011 to 2016. All 6-years haze events are classified into long-range transported haze (LH: 31%), urban haze (UH: 28%), and yellow sand (YS: 18%) in order. Long-range transported one is mainly discussed in this study. Interestingly, both LH (68%) and YS (87%) appear to be more frequently accompanied with precipitation than UH (48%). We also found out the different timing of precipitation for LH and YS, respectively. The variations of precipitation frequency for the LH event tend to coincide with aerosol variations specifically in terms of temporal covariation, which is in contrast with YS. Increased aerosol loadings following precipitation for the YS event seems to be primarily controlled by large scale synoptic forcing. Meanwhile, aerosols for the LH event may be closely associated with precipitation longevity through changes in cloud microphysics such that enhanced aerosols can increase smaller cloud droplets and further extend light precipitation at weaker rate. Notably, precipitation persisted longer than operational weather forecast not considering detailed aerosol-cloud interactions, but the timescale was limited within a day. This result demonstrates active interactions between aerosols and meteorology such as probable modifications of cloud microphysics and precipitation, synoptic-induced dust transport, and precipitation-scavenging in Korea. Understanding of aerosol potential effect on precipitation will contribute to improving the performance of numerical weather model especially in terms of precipitation timing and location.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.

• Atmosphere
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• v.34 no.3
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• pp.305-317
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• 2024

The study examines the effects of parameters that define the characteristics of raindrops on the simulated precipitation during the summer season over Korea using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) cloud microphysics scheme. Prescribed parameters, defining the characteristics of hydrometeors in the WDM6 scheme such as a_R, b_R, and f_R in the fall velocity (V_R) - diameter (D_R) relationship and shape parameter (𝜇_R) in the number concentration (N_R) - D_R relationship, presents different values compared to the observed data from Two-Dimensional Video Disdrometer (2DVD) at Boseong standard meteorological observatory during 2018~2019. Three experiments were designed for the heavy rainfall event on August 8, 2022 using WRF version 4.3. These include the control (CNTL) experiment with original parameters in the WDM6 scheme; the MUR experiment, adopting the 50th percentile observation value for 𝜇_R; and the MEDI experiment, which uses the same 𝜇_R as MUR, but also includes fitted values for a_R, b_R, and f_R from the 50th percentile of the observed V_R - D_R relationship. Both sensitivity experiments show improved precipitation simulation compared to the CNTL by reducing the bias and increasing the probability of detection and equitable threat scores. In these experiments, the raindrop mixing ratio increases and its number concentration decreases in the lower atmosphere. The microphysics budget analysis shows that the increase in the rain mixing ratio is due to enhanced source processes such as graupel melting, vapor condensation, and accretion between cloud water and rain. Our study also emphasizes that applying the solely observed 𝜇_R produces more positive impact in the precipitation simulation.

• Atmosphere
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• v.22 no.1
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• pp.73-85
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• 2012

The collision efficiency data for collision between graupel or hail particles and cloud drops that take into account the differences of particle density are applied to the Takahashi cloud model. The original setting assumes that graupel or hail collision efficiency is the same as that of the cloud drops of the same volume. The Takahashi cloud model is run with the new collision efficiency data and the results are compared with those with the original. As an initial condition, a thermodynamic profile that can initiate strong convection is provided. Three different CCN concentration values and therefore three initial cloud drop spectra are prescribed that represent maritime (CCN concentration = 300 $cm^{-3}$), continental (1000 $cm^{-3}$) and extreme continental (5000 $cm^{-3}$) air masses to examine the aerosol effects on cloud and precipitation development. Increase of CCN concentration causes cloud drop sizes to decrease and cloud drop concentrations to increase. However, the concentration of ice particles decreases with the increase of CCN concentration because small drops are difficult to freeze. These general trends are well captured by both model runs (one with the new collision efficiency data and the other with the original) but there are significant differences: with the new data, the development of cloud and raindrop formation are delayed by (1) decrease of ice collision efficiency, (2) decrease of latent heat from riming process and (3) decrease of ice crystals generated by ice multiplication. These results indicate that the model run with the original collision efficiency data overestimates precipitation rates.