Raindrop Number Concentration Research Articles

Spatial Variability of Raindrop Size Distribution at Beijing City Scale and Its Implications for Polarimetric Radar QPE

Understanding the characteristics of the raindrop size distribution (DSD) is crucial to improve our knowledge of the microphysical processes of precipitation and to improve the accuracy of radar quantitative precipitation estimation (QPE). In this study, the spatial variability of DSD in different regions of Beijing and its influence on radar QPE are analyzed using 11 disdrometers. The DSD data are categorized into three regions: Urban, suburban, and mountainous according to their locations. The DSD exhibits evidently different characteristics in the urban, suburban, and mountain regions of Beijing. The average raindrop diameter is smaller in the urban region compared to the suburban region. The average rain rate and raindrop number concentration are lower in the mountainous region compared to both urban and suburban regions. The difference in DSD between urban and suburban regions is due to the difference in DSD for the same precipitation types, while the difference in DSD between mountain and plains (i.e., urban and suburban regions) is the combined effect of the convection/stratiform ratio and the difference of DSD for the same precipitation types. Three DSD-based polarimetric radar QPE estimators were retrieved and estimated. Among these three QPE estimators, R(ZH), R(Kdp), and R(Kdp, ZDR), R(Kdp, ZDR) performs best, followed by R(Kdp), and R(ZH) performs worst. R(Kdp) is more sensitive to the representative parameters, while R(ZH) and R(Kdp, ZDR) are more sensitive to observational error and systematic bias (i.e., calibration).

The Impact of Autoconversion Parameterizations of Cloud Droplet to Raindrop on Numerical Simulations of a Meiyu Front Heavy Rainfall Event

This study analyzes the different impacts of autoconversion of cloud droplets to raindrops (ACR) in a Meiyu front rainfall event by comparing two simulations using different parameterizations (KK00 and LD04) in the Weather Research and Forecasting (WRF) model. The Meiyu frontal clouds are further classified into stratiform and deep-convective cloud categories, and the precipitation and microphysical characteristics of the two simulations are compared with a budget analysis of raindrops. The simulated precipitation, radar composite reflectivity distribution, and rain rate evolution are overall consistent with observations while precipitation is overestimated, especially in the rainfall centers. The intensity and vertical structure of the ACR process between the two simulations are significantly different. The ACR rate in LD04 is larger than that in KK00 and there are two peak heights in LD04 but only one in KK00. Accretion of droplets by raindrops (CLcr), melting of ice-phase particles (ML), evaporation of raindrops (VDrv), and accretion of raindrops by ice-phase particles (CLri) are the dominant pathways to raindrop production. Limited distributional differences can be found in both the deep-convective and stratiform clouds between the two simulations during the growth stage of the Meiyu event. Stronger ACR in LD04 results in less cloud droplet content (Lc), more raindrop content (Lr), and larger raindrop number concentration (Nr) and the effect of ACR on Nr is greater than that on Lr. The ACR process also impacts other microphysical processes indirectly, and the influences vary in the two cloud categories. Less CLcr (especially), ML, and VDrv content, caused by stronger ACR, lead to less raindrop production in the LD04 deep-convective clouds, which is different from stratiform clouds, and finally correct the overestimated rainfall center to better match the observations.

Do Double‐Moment Microphysics Schemes Make Reliable Predictions on the Raindrop Number Concentration?: A Squall‐Line Case Study

AbstractUtilizing raindrop size distribution observations in the evaluation of a cloud microphysics scheme helps identifying systematic deficiencies of the scheme and improving it. In this study, we evaluate the performance of seven different double‐moment bulk microphysics schemes in predicting raindrop number concentration Nr in squall‐line simulations using ground‐based disdrometer observations. While all seven schemes show good performances in the prediction of rainwater mass, they show significant biases from the observation and severe discrepancies from each other in the prediction of Nr. The Thompson, Thompson aerosol‐aware, and Weather Research and Forecasting double moment 6‐class (WDM6) schemes, where the main source of Nr is melting of snow and graupel, overestimate Nr by four times, which may be caused by overestimation of Nr production via melting. The Morrison and predicted particle properties (P3) schemes, where the autoconversion of cloud droplets into raindrops is an Nr source that is as important as melting, exhibit negative biases of Nr, which may be attributed to insufficient collisional breakup of raindrops. The P3_Nc scheme, the P3 scheme that prognoses cloud droplet number concentration, shows two prominent modes in Nr distribution, one of which consists of overestimated Nr produced by overly active autoconversion. The ice‐spheroids habit model with aspect‐ratio evolution scheme overestimates Nr but not as much as the two Thompson schemes and WDM6 scheme, showing the most realistic prediction of mean raindrop diameter. The high uncertainty in Nr prediction needs to be reduced by carefully selecting parameterizations for important microphysical processes, in order to maximize the advantage of using double‐moment microphysics schemes.

Estimation of raindrop size distribution and rain rate with infrared surveillance camera in dark conditions

Abstract. This study estimated raindrop size distribution (DSD) and rainfall intensity with an infrared surveillance camera in dark conditions. Accordingly, rain streaks were extracted using a k-nearest-neighbor (KNN)-based algorithm. The rainfall intensity was estimated using DSD based on a physical optics analysis. The estimated DSD was verified using a disdrometer for the two rainfall events. The results are summarized as follows. First, a KNN-based algorithm can accurately recognize rain streaks from complex backgrounds captured by the camera. Second, the number concentration of raindrops obtained through closed-circuit television (CCTV) images had values between 100 and 1000 mm−1 m−3, and the root mean square error (RMSE) for the number concentration by CCTV and PARticle SIze and VELocity (PARSIVEL) was 72.3 and 131.6 mm−1 m−3 in the 0.5 to 1.5 mm section. Third, the maximum raindrop diameter and the number concentration of 1 mm or less produced similar results during the period with a high ratio of diameters of 3 mm or less. Finally, after comparing with the 15 min cumulative PARSIVEL rain rate, the mean absolute percent error (MAPE) was 49 % and 23 %, respectively. In addition, the differences according to rain rate are that the MAPE was 36 % at a rain rate of less than 2 mm h−1 and 80 % at a rate above 2 mm h−1. Also, when the rain rate was greater than 5 mm h−1, MAPE was 33 %. We confirmed the possibility of estimating an image-based DSD and rain rate obtained based on low-cost equipment during dark conditions.

Characteristics of two different types of thunderstorms in summer over the Nagqu area in China

To investigate further the characteristics of thunderstorms on the Qinghai–Tibet plateau, a plateau vortex (PV) thunderstorm and a local thermoconvective (TC) thunderstorm over the Nagqu area are analyzed using cloud-radar, microwave-radiometer, and raindrop-spectrometer data, and their macrophysical and microphysical evolution characteristics are discussed in terms of thermodynamic processes, microphysical processes, and lightning activities. The results show the following. 1) The cloud layer was deeper in the PV thunderstorm, but the TC thunderstorm had a stronger short-time updraft with a radial velocity exceeding 10 m/s, and the warming from the strong updraft action and latent heat release from the hydromorphic phase change was about twice that of the PV thunderstorm. 2) The water vapor density increased significantly when the thunderstorm cloud passed, and the liquid water content in the middle and lower layers exceeded 4 g/m3. The maximum ice water content in the TC thunderstorm was twice bigger than that in the PV thunderstorm. The trends of raindrop number concentration and rain intensity of the PV thunderstorm were similar, and the average particle size of raindrops was smaller than that of the TC thunderstorm. 3) Both types of thunderstorms accounted for more than 90% of negative cloud-to-ground (CG) lightning, and the regions with black-body temperature (TBB) less than −40 °C and a larger TBB gradient were more favorable for the occurrence of CG lightning. 4) Thermodynamic fields bring water vapor and lift for microphysical processes, and microphysical changes release latent heat to enhance the dynamic effects, which together promote the development of lightning activities. The peak radial velocity and ice-phase particle concentration were more than 10 min ahead of the active peak of the CG lightning. This study reveals the macrophysical and microphysical evolution characteristics of different types of thunderstorms and provides a certain scientific basis for disaster prevention and mitigation regarding thunderstorms over the Nagqu area.

The Characteristics of Raindrop Size Distribution at Windward and Leeward Side over Mountain Area

To analyze the difference in the microphysical development characteristics of orographic rainfall, several Parsivel disdrometers were installed along the windward and leeward slope of a mountain. There were differences in the raindrop size distribution according to the difference in height and distance from the center of the mountain. In low-altitude coastal areas and adjacent areas, the number concentration of raindrops smaller than 1 mm was relatively lower than in mountainous areas, and the rain rate increased with the growth in the size of the raindrops. On the other hand, a higher rain rate was observed as the number concentration of raindrops smaller than 1 mm increased in the hillside area. The increase in the number concentration of small raindrops was evident at the LCL (lifting condensation level) altitude. The main factors affecting the increase in the rain rate on the windward and leeward slopes were the concentration of raindrops and the growth of raindrops, which showed regional differences. As a result of a PCA (principal component analysis), it was found that raindrop development by vapor deposition and weak convection were the main rainfall development characteristics on the windward and leeward slopes, respectively. The difference in regional precipitation development characteristics in mountainous areas affects the parameters of the rainfall estimation relational expression. This means that the rainfall relation calculated through the disdrometer observation data observed in a specific mountainous area can cause spatial and quantitative errors.

A new warm-cloud collection and breakup parameterization scheme for weather and climate models

Microphysical process rates in bulk microphysics schemes have been parameterized in simple forms which may inadequately represent their complicated dependencies on hydrometeor quantities. In this study, we develop a bulk warm rain microphysics scheme that includes physically based parameterizations of collection and breakup. The parameterizations are derived from the stochastic collection and breakup equations by approximating the collection and breakup kernels in elaborate forms and analytically evaluating the integrals in those equations. Although the new scheme performs relatively complicated calculations, it is computationally not too expensive to be used in weather and climate models. We first evaluate the raindrop self-collection and collisional breakup (RSCB) parameterizations developed in this study using a box model. Under the intrinsic limitation of bulk schemes, they generally yield the equilibrium raindrop size distributions closest to those from a bin-based solver. We then evaluate the new scheme through the simulations of shallow cumuli field and a single warm convective cloud. In the simulation of shallow cumuli field, the new scheme quite well reproduces the observed cloud properties. Compared to two other bulk schemes, the new scheme yields somewhat different rainwater mass and raindrop number concentration, which is largely attributable to the differences in autoconversion parameterizations. In the simulation of a single warm convective cloud where RSCB plays a major role, the rate of raindrop number depletion by RSCB and the time of precipitation onset predicted by the new scheme are close to those predicted by a bin scheme used as the reference.

Microphysics of Stratiform and Convective Precipitation During Meiyu Season in Eastern China

AbstractThe microphysical structure of Meiyu precipitation in Eastern China is investigated using two‐dimensional video disdrometer (2DVD) and S‐band polarimetric radar observations. The constrained‐gamma raindrop size distribution (DSD) model derived from 2DVD observations performs well in representing Meiyu DSDs. The vertical variability of polarimetric variables and retrieved DSD parameters are then investigated. The results show different patterns of vertical behavior for convective and stratiform rain due to different ice‐phase and precipitation microphysical processes. The radar reflectivity of stratiform rain presents a distinct bright band (with an average echo top between 6 and 7 km). In contrast, the convective rain shows a larger reflectivity with a relatively higher echo top at 8 km. Polarimetric signatures of convective rain above the 0°C isotherm imply the coexistence of rimed particles and aggregates, which is indispensable for the intense precipitation on the ground. However, with a bulk precipitation formed below the melting layer, warm rain processes are still critical pathways for the growth of raindrops and the subsequent generation of heavy rainfall. Furthermore, both convective and stratiform rain is dominated by raindrops <4 mm, and the increase in their rain intensity can mostly be attributed to the increase in raindrop concentration. The identified maritime nature of convective rain has a much higher (roughly more than two times) number concentration of raindrops than that of convection in a similar climate region. This study provides a more comprehensive picture of Meiyu precipitation microphysics in Eastern China.

The characteristics of RSDs before and after the landing Typhoon Meranti

The characteristics of raindrop size distribution during Typhoon Meranti, determined using disdrometer (LPA10) data collected from 14 to Sep. 15, 2016 in Fujian Province, China, were associated with different parts of the storm. From the front side of the rain band to the central region and then to the rear side or to the residual clouds of Typhoon Meranti, the top of the radar echo, reflectivity, raindrop number concentration and spectrum width all increased when Meranti moved close and then decreased as it moved away. Moreover, precipitation was produced from the stratiform to the oceanic convective and then to the oceanic convective-stratiform mixed clouds or to the stratiform.

Evaluation of Simulated Drop Size Distributions and Microphysical Processes Using Polarimetric Radar Observations for Landfalling Typhoon Matmo (2014)

AbstractThe Morrison (Morr), Thompson (Thom), Thompson aerosol‐aware (ThomA), and WRF double‐moment 6‐class (WDM6) microphysics schemes within the WRF model are used to simulate landfalling Typhoon Matmo (2014) and evaluated against polarimetric radar observations in terms of raindrop size distribution (RSD) and microphysical processes. Focus is placed on the inner rainband convection. Only ThomA is able to reproduce observed RSD characteristics having even smaller mean raindrop sizes and larger number concentrations than those of typical maritime convection, when measured in terms of mass‐weighted mean diameter and normalized RSD intercept parameter. The diagnoses of microphysical transfer terms show that warm rain processes are dominant in all experiments. The accretion and autoconversion processes dominate the production of rainwater content and raindrop number concentration, respectively. Examinations of vertical profiles of hydrometeor masses and number concentrations as well as rainwater‐related microphysical transfer rates suggest that raindrop total number concentration NTr near the freezing level, mainly produced by the autoconversion process, plays an important role in determining the near‐surface RSD characteristics. Morr and Thom assume fixed values of cloud droplet number concentration NTc that are much larger than those predicted by ThomA, leading to much smaller NTr near the freezing level produced by the autoconversion process. Sensitivity experiments using much reduced NTc substantially increase predicted NTr, mainly through invigoration of autoconversion. These results indicate that adequately predicting NTc is very important for capturing the right RSD characteristics for landfalling typhoons over East China where Typhoon Matmo is one of the representative examples.

Microphysical Properties of Rainwater in Typhoon Usagi (2013): A Numerical Modeling Study

A 2-km resolution simulation using the Weather Research and Forecasting model with Morrison microphysics was employed to investigate the rainwater microphysical properties during different stages of Typhoon Usagi (2013) in the inner-core and outer region. The model reproduced the track, intensity, and overall structure of Usagi (2013) reasonably. The simulated raindrop size distribution showed a rapid increase in small-size raindrop concentration but an oscillated decrease in large-size ones in the inner-core region, corresponding well with the upward motion. It was found that there existed two levels (1.25 and 5.25 km) of maximum number concentration of raindrops. The ice-related microphysics at high levels was stronger than the warm-rain processes at low levels. The larger raindrops formed by self-collection in the inner-core suffered from significant breakup, but the raindrops outside the eyewall did not experience evident breakup. Model results indicated that the dominant terms in the water vapor budget were the horizontal moisture flux convergence (HFC) and local condensation and deposition. The evaporation from the ocean surface (PBL) was ∼10% of the HFC in the inner core, but up to 40% in the outer region as the air therein was far from saturation. Furthermore, water vapor in the outer region was obtained equally through evaporation from the cloud and inward transportation from the environment. An earlier start of cloud microphysical processes in the inner-core region was evident during the intensification stage, and the continuous decreasing of condensation in both the inner-core and outer regions might imply the beginning of the storm weakening.

Analysis of Dual-Polarimetric Radar Variables and Quantitative Precipitation Estimators for Landfall Typhoons and Squall Lines Based on Disdrometer Data in Southern China

Typhoon rainstorms often cause disasters in southern China. Quantitative precipitation estimation (QPE) with the use of polarimetric radar can improve the accuracy of precipitation estimation and enhance typhoon defense ability. On the basis of the observed drop size distribution (DSD) of raindrops, a comparison is conducted among the DSD parameters and the polarimetric radar observation retrieved from DSD in five typhoon and three squall line events that occurred in southern China from 2016 to 2017. A new piecewise fitting method (PFM) is used to develop the QPE estimators for landfall typhoons and squall lines. The performance of QPE is evaluated by two fitting methods for two precipitation types using DSD data collected. Findings indicate that the number concentration of raindrops in typhoon precipitation is large and the average diameter is small, while the raindrops in squall line rain have opposite characteristics. The differential reflectivity (ZDR) and specific differential phase (KDP) in these two precipitation types increase slowly with the reflectivity factor (ZH), whereas the two precipitation types have different ZDR and KDP in the same ZH. Thus, it is critical to fit the rainfall estimator for different precipitation types. Enhanced estimation can be obtained using the estimators for specific precipitation types, whether the estimators are derived from the conventional fitting method (CFM) or PFM, and the estimators fitted using the PFM can produce better results. The estimators for the developed polarimetric radar can be used in operational QPE and quantitative precipitation foresting, and they can improve disaster defense against typhoons and heavy rains.

Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study

This study incorporated the Weather Research and Forecasting (WRF) model double-moment 6-class (WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso). A rainfall event that occurred during 3–5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme (WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warm-rain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei (CCN) number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration (Nc) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration (Nr), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event.

Impact of Drizzle-Sized Cloud Particles on Production of Precipitation in Hailstorms: A Sensitivity Study

This sensitivity study examined the impact of drizzle on hailstorm characteristics and precipitation on the ground. A cloud-resolving mesoscale model with a two-moment bulk microphysical scheme is modified by introducing mixing ratio and number concentration of drizzle. Therefore, the cloud model integrates the mixing ratio and number concentration of the eight microphysical particles: cloud droplets, drizzle, raindrops, cloud ice, snowflakes, graupel, frozen raindrops and hailstones. We compared two microphysical schemes depending on whether drizzle particles are present or not. It can be noted that the presence of drizzle category slows the development of the rain in the hailstorm and its appearance on the ground. The increased values of radar reflectivity factor in simulations with drizzle are a result of significantly higher values of raindrop number concentration rather than their sizes and indicate the presence of hail as well. There are prominent decreases of the radar reflectivity factor in simulations with drizzle. The occurrence of heavy showers does not exist in results without drizzle. The absence of drizzle category leads to greater accumulations of rain and a wider area of downdrafts. The alternate case produces both weaker downdrafts and smaller area of downdraft cells due to a slower autoconversion of drizzle to rain and a smaller rain evaporation. A smaller amount of surface hail is expected in the non-drizzle case.

Microphysical characteristics of rainfall during different seasons over a coastal tropical station using disdrometer

AbstractDrop size distribution (DSD) over the tropical region exhibit pronounced variations during different monsoon seasons. Measurements from an impact type Joss–Waldovgel disdrometer is used for characterization of drop size distribution and its integral parameters over a tropical coastal station (Thiruvananthapuram, 8.31°N, 76.54°E, 20 m asl). Rain events were identified during the winter, premonsoon, summer monsoon and postmonsoon seasons from 8 years, computed rain duration (min) and accumulated rain water (mm). Rain intensity (mm h−1), mean drop diameter (Dm, mm) and total number concentration of raindrops (NT, m−3) were calculated on each sampling interval and classified in to different bins.The different range bins of rain intensity and their relative contributions towards total rainfall are different for different seasons. Maximum events were reported on the R2 (heavy drizzle/light rain) type, but the contribution of rainfall (mm) is mainly registered on R4 (heavy rain) type. Similarly, the NT and Dm are also showing different characteristics during different monsoon seasons. Frequency of occurrence of Dm is higher in Dm2 (1–2 mm) followed by Dm1 (Dm < 1 mm) and then Dm3 (2–3 mm) with difference in magnitudes for different seasons. On analysing relative rainfall contribution from different mean diameter bins, it can be observed that Dm2 and Dm3 (1–3 mm) are the major contributors to the total rainfall. In the case of NT, both frequency and accumulated water are almost same or comparable for the different bins during all the seasons. The Dm and NT are positively related with different intensity bins. The lower rainfall intensity bins show higher duration during the summer monsoon season and lower duration during the premonsoon season, the higher intensity range bins show lower duration for the premonsoon season and higher duration for the postmonsoon season.

Characteristics of the raindrop distributions in RICO shallow cumulus

Abstract. The physical properties of rain spectra are generally modeled using an analytical distribution. It is common for the gamma distribution and, to a lesser extent, the lognormal distribution to be used. The majority of studies in the literature focusing on the characterization of raindrop distribution are based on deep convective cloud observations, mostly at ground level. This study focuses on shallow-cumulus rain distributions throughout the depth of the cloud layer and subcloud layer using airborne in situ measurements made with both the Particle Measuring Systems (PMS) Optical Array Probe 260X (OAP-260-X) and the PMS two-Dimensional Precipitation (2DP) instruments during the Rain in Cumulus over the Ocean (RICO) field experiment. Sampled spectra analyzed on the scale of large-eddy simulation resolution (100 m) are found to be relatively broad, with values of the shape parameter – υ for the gamma law and σg for the lognormal law – on the order of 1–3 and 1.5–2, respectively. The dependence of the shape parameters on the main rain variables (number concentration, water content, mean volume diameter, sedimentation fluxes and radar reflectivity) is examined, and a parameterization of the shape parameters υ and σg as a function of a power law of the rainwater content and raindrop number concentration is proposed.

Articulating and Stationary PARSIVEL Disdrometer Measurements in Conditions with Strong Winds and Heavy Rainfall

Abstract The influence of strong winds on the quality of optical Particle Size Velocity (PARSIVEL) disdrometer measurements is examined with data from Hurricane Ike in 2008 and from convective thunderstorms observed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) in 2010. This study investigates an artifact in particle size distribution (PSD) measurements that has been observed independently by six stationary PARSIVEL disdrometers. The artifact is characterized by a large number concentration of raindrops with large diameters (>5 mm) and unrealistic fall velocities (<1 m s−1). It is correlated with high wind speeds and is consistently observed by stationary disdrometers but is not observed by articulating disdrometers (instruments whose sampling area is rotated into the wind). The effects of strong winds are further examined with a tilting experiment, in which drops are dripped through the PARSIVEL sampling area while the instrument is tilted at various angles, suggesting that the artifact is caused by particles moving at an angle through the sampling area. Most of the time, this effect occurs when wind speed exceeds 20 m s−1, although it was also observed when wind speed was as low as 10 m s−1. An alternative quality control is tested in which raindrops are removed when their diameters exceed 8 mm and they divert from the fall velocity–diameter relationship. While the quality control does provide more realistic reflectivity values for the stationary disdrometers in strong winds, the number concentration is reduced compared to the observations with an articulating disdrometer.

A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

Abstract. A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.

Aerosol impacts on clouds and precipitation in eastern China: Results from bin and bulk microphysics

Using the Weather Research and Forecasting model coupled with a spectral‐bin microphysics (“SBM”) and measurements from the Atmospheric Radiation Measurement Mobile Facility field campaign in China (AMF‐China), the authors examine aerosol indirect effects (AIE) in the typical cloud regimes of the warm and cold seasons in Southeast China: deep convective clouds (DCC) and stratus clouds (SC), respectively. Comparisons with a two‐moment bulk microphysics (“Bulk”) are performed to gain insights for improving bulk schemes in estimating AIE in weather and climate simulations. For the first time, measurements of aerosol and cloud properties acquired in China are used to evaluate model simulations to better understand aerosol impact on clouds in the southeast of China. It is found that changes in cloud condensation nuclei (CCN) concentration significantly change the timing of storms, the spatial and temporal distributions of precipitation, the frequency distribution of precipitation rate, as well as cloud base and top heights for the DCC, but not for the SC. Increasing CCN increases cloud droplet number (Nc) and mass concentrations, decreases raindrop number concentration, and delays the onset of precipitation. Compared with SBM, Bulk predicts much higher Ncand the opposite CCN effects on convection and heavy rain, stemming from the fixed CCN prescribed in Bulk. CCN have a significant effect on ice microphysical properties with SBM but not Bulk and different condensation/deposition freezing parameterizations employed could be the main reason. This study provided insights to further improve the bulk scheme to better account for aerosol‐cloud interactions in regional and global climate simulations, which will be the focus for a follow‐on paper.

On the Parameterization of Evaporation of Raindrops as Simulated by a One-Dimensional Rainshaft Model

Abstract The process of evaporation of raindrops below cloud base is investigated by numerical simulations using a one-dimensional rainshaft model with bin microphysics. The simulations reveal a high variability of the shape of the raindrop size distributions, which has important implications for the efficiency of evaporation below cloud base. A new parameterization of the shape of the raindrop size distribution as a function of the mean volume diameter is suggested and applied in a two-moment microphysical scheme. In addition, the effect of evaporation on the number concentration of raindrops is parameterized. A comparison of results of the revised two-moment scheme and the bin microphysics rainshaft model shows that the two-moment scheme is able to reproduce the results of the reference model in a wide parameter range.