Midlatitude Continental Convective Clouds Experiment Research Articles

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

The Impact of Constrained Data Assimilation on the Forecasts of Three Convection Systems during the ARM MC3E Field Campaign

Abstract A constrained data assimilation (CDA) system based on the ensemble variational (EnVar) method and physical constraints of mass and water conservations is evaluated through three convective cases during the Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program. Compared to the original data assimilation (ODA), the CDA is shown to perform better in the forecasted state variables and simulated precipitation. The CDA is also shown to greatly mitigate the loss of forecast skills in observation denial experiments when radar radial winds are withheld in the assimilation. Modifications to the algorithm and sensitivities of the CDA to the calculation of the time tendencies in the constraints are described.

A Multi-Platform In Situ Kinematic and Microphysical Analysis of a Hybrid Parallel–Trailing Stratiform Mesoscale Convective System

Abstract Parallel stratiform–type mesoscale convective systems (MCS) have been found to comprise less than 20% of the central U.S. MCSs, but parallel stratiform MCSs have been reviewed by few studies and only a handful have been sampled using airborne platforms. This study conducts a detailed review of the 11 May 2011 MCS that was observed during the Midlatitude Continental Convective Clouds Experiment. In situ data from the University of North Dakota Cessna Citation II Weather Research Aircraft and the Oklahoma Mesonet are used in conjunction with radar reflectivity data and a multiple-Doppler wind retrieval to present an in-depth analysis of the kinematic and microphysical processes within this hybrid parallel–trailing stratiform MCS. Results suggest the MCS started with parallel stratiform characteristics and then developed trailing stratiform features over the course of a couple of hours such as leading line convection and the presence of rear inflow, which is a feature not observed in previous studies of parallel stratiform MCSs. Based on surface observations and multi-Doppler wind field retrievals, the cold pool influenced the 11 May 2011 MCS and may have helped it to transition toward the trailing stratiform mode. Within the stratiform region, in situ measurements show hydrometeor aggregation and sublimation occurring above the melting layer via a faster rate of decline in total hydrometer concentration compared to the total water content, the presence of a bimodal droplet size spectra, and increasing dispersion and decreasing slope, with respect to increasing temperature in both the unimodal and bimodal gamma distributions. Significance Statement The purpose of this study is to investigate the wind pattern of a nontypical type of thunderstorm complex. The wind pattern is found to be a combination of features from both a common type of thunderstorm complex and another less common type. The behavior of snowflakes as they fall through this thunderstorm was also investigated. The snowflakes in this storm grew bigger by linking up with other snowflakes as they fell down, and then melted before they reached the ground. It is hoped that results from this study are useful to future work to improve weather prediction.

A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application

AbstractData assimilation (DA) at mesoscales is important for severe weather forecasts, yet the techniques of data assimilation at this scale remain a challenge. This study introduces dynamical constraints in the Gridpoint Statistical Interpolation (GSI) three-dimensional ensemble variational (3D-EnVar) data assimilation algorithm to enable the use of high-resolution surface observations of precipitation to improve atmospheric analysis at mesoscales. The constraints use the conservations of mass and moisture. Mass constraint suppresses the unphysical high-frequency oscillation, while moisture conservation constrains the atmospheric states to conform with the observed high-resolution precipitation. We show that the constrained data assimilation (CDA) algorithm significantly reduced the spurious residuals of the mass and moisture budgets compared to the original data assimilation (ODA). A case study is presented for a squall line over the Southern Great Plains on 20 May 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program by using ODA or CDA analysis as initial condition of forecasts. The state variables, and the location and intensity of the squall line are better simulated in the CDA experiment. Results show how surface observation of precipitation can be used to improve atmospheric analysis through data assimilation by using the dynamical constraints of mass and moisture conservations.

Understanding irrigation impacts on low-level jets over the Great Plains

Low-level jets (LLJs) over the Great Plains are well-known for their importance in transporting moisture from the Gulf of Mexico and forming precipitation in the Central US. However, the impact of irrigation practice on LLJs is rarely studied. To understand the irrigation impact on the Great Plains LLJs, the Weather Research and Forecasting (WRF) model is employed with and without an irrigation scheme. The simulated wind fields are evaluated against the observed wind from the Midlatitude Continental Convective Clouds Experiment (MC3E) as well as the North America Regional Reanalysis dataset. The results show that adding irrigation improves the simulated wind, especially at altitudes below 800 hPa. Irrigation reduces the LLJ frequency over the Great Plains, mainly by reducing the intense LLJ frequency. The reduced LLJ frequency is caused by the irrigation-induced weakening of meridional wind. The favorable conditions for LLJs have been identified by examining the mechanism associated with LLJs: a ridge-like pattern with weak and calm synoptic-scale conditions in the mid-levels and a strong west–east temperature gradient at lower levels that promote meridional winds. Irrigation-induced cooling leads to a baroclinic pattern with high pressure at lower altitudes over the irrigation region and low pressure in the mid- and upper levels in the downstream region, resulting in a northerly component that hinders the formation of LLJs. Low-level surface cooling also decreases the west–east temperature gradient and hence weakens the thermal wind forcing. The irrigation-induced mid-level low and weaker west–east temperature gradient are responsible for the reduced meridional winds and the reduced LLJ frequencies.

Simulating a Mesoscale Convective System Using WRF With a New Spectral Bin Microphysics: 1: Hail vs Graupel

AbstractA modified Fast Spectral Bin Microphysics scheme (FSBM‐2) embedded into the Weather Research and Forecasting (WRF) model is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM‐2 uses modified source codes as compared to the current FSBM (FSBM‐1). In contrast to FSBM‐1, FSBM‐2 can simulate hail of several centimeters in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall‐line structures in both the convective and stratiform regions. In contrast, if graupel particles are used to represent high‐density hydrometeors in convective areas, the ratio of convective‐to‐stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM‐2 show a good agreement with observations. The regeneration of cloud condensational nuclei (CCN) by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8‐ to 9‐km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification.

Effects of Under-Resolved Convective Dynamics on the Evolution of a Squall Line

Abstract Simulations of a squall line observed on 20 May 2011 during the Midlatitude Continental Convective Clouds Experiment (MC3E) using 750- and 250-m horizontal grid spacing are performed. The higher-resolution simulation has less upshear-tilted deep convection and a more elevated rear inflow jet than the coarser-resolution simulation in better agreement with radar observations. A stronger cold pool eventually develops in the 250-m run; however, the more elevated rear inflow counteracts the cold pool circulation to produce more upright convective cores relative to the 750-m run. The differing structure in the 750-m run produces excessive midlevel front-to-rear detrainment, reinforcing excessive latent cooling and rear inflow descent at the rear of the stratiform region in a positive feedback. The contrasting mesoscale circulations are connected to early stage deep convective draft differences in the two simulations. Convective downdraft condensate mass, latent cooling, and downward motion all increase with downdraft area similarly in both simulations. However, the 750-m run has a relatively greater number of wide and fewer narrow downdrafts than the 250-m run averaged to the same 750-m grid, a consequence of downdrafts being under-resolved in the 750-m run. Under-resolved downdrafts in the 750-m run are associated with under-resolved updrafts and transport mid–upper-level zonal momentum downward to low levels too efficiently in the early stage deep convection. These results imply that under-resolved convective drafts in simulations may vertically transport air too efficiently and too far vertically, potentially biasing buoyancy and momentum distributions that impact mesoscale convective system evolution.

Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework

AbstractIce microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so‐called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass‐size (m‐D) relationship (m=aDb) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m‐D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m‐D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ‐IWP relationship variability is nonexistent using the deterministic m‐D ensemble. Additional sensitivity tests are performed in which the fallspeed‐size relationship (V=cDd) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small‐amplitude noise added to the potential temperature field.

The Importance of the Ice-Phase Microphysics Parameterization for Simulating the Effects of Changes to CCN Concentrations in Deep Convection

AbstractSimulations of a well-observed squall line that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) were conducted using a mesoscale model with a horizontal grid spacing of 1 km to examine the importance of parameterized ice-phase processes to changes in concentrations of activated cloud condensation nuclei (CCN) in a detailed two-moment bulk microphysics scheme. Numerical experiments showed that the simulated squall-line structure was sensitive to changes in activated CCN concentration not only from the direct impacts on cloud droplet sizes and autoconversion rates, but also because of changes in the growth rates and spatial distribution of ice-phase condensate. A microphysical budget analysis highlighted the importance of graupel in rain production and the sensitivity of graupel growth rates on changes to CCN concentrations. Sensitivity tests on the level of detail in the representation of graupel, specifically the treatment of its bulk density and the number of prognostic moments, indicated that changes in the reflectivity and precipitation structure of the simulated storm due to changes in CCN were sensitive to the graupel parameterization. The results suggest that the proper representation of graupel and possibly other ice-phase categories in microphysics schemes may be crucial for correctly simulating the effects of changes to CCN concentrations for continental deep convective systems.

A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E

Abstract. Mass–dimension (m–D) relationships determining bulk microphysical properties such as total water content (TWC) and radar reflectivity factor (Z) from particle size distributions are used in both numerical models and remote sensing retrievals. The a and b coefficients representing m=aDb relationships, however, can vary significantly depending on meteorological conditions, particle habits, the definition of particle maximum dimension, the probes used to obtain the data, techniques used to process the cloud probe data, and other unknown reasons. Thus, considering a range of a,b coefficients may be more applicable for use in numerical models and remote sensing retrievals. Microphysical data collected by two-dimensional optical array probes (OAPs) installed on the University of North Dakota (UND) Citation aircraft during the Mid-latitude Continental Convective Clouds Experiment (MC3E) were used in conjunction with TWC data from a Nevzorov probe and ground-based S-band radar data to determine a and b using a technique that minimizes the chi-square difference between the TWC and Z derived from the OAPs and those directly measured by a TWC probe and radar. All a and b values within a specified tolerance were regarded as equally plausible solutions. Of the 16 near-constant-temperature flight legs analyzed during the 25 April, 20 May, and 23 May 2011 events, the derived surfaces of solutions on the first 2 days where the aircraft-sampled stratiform cloud had a larger range in a and b for lower temperature environments that correspond to less variability in N(D), TWC, and Z for a flight leg. Because different regions of the storm were sampled on 23 May, differences in the variability in N(D), TWC, and Z influenced the distribution of chi-square values in the (a,b) phase space and the specified tolerance in a way that yielded 2.8 times fewer plausible solutions compared to the flight legs on the other dates. These findings show the importance of representing the variability in a,b coefficients for numerical modeling and remote sensing studies, rather than assuming fixed values, as well as the need to further explore how these surfaces depend on environmental conditions in clouds containing ice hydrometeors.

Investigation of Liquid Cloud Microphysical Properties of Deep Convective Systems: 2. Parameterization of Raindrop Size Distribution and its Application for Convective Rain Estimation

AbstractThe liquid cloud microphysical properties for stratiform rain (SR) have been investigated in Part 1 of this series. Since convective rain (CR) has characteristics in raindrop size distribution (DSD) and precipitation that are distinct from SR, we investigate the CR properties in this study by using 20 hr of CR samples collected by 17 Automatic Parsivel Units disdrometers during the Midlatitude Continental Convective Clouds Experiment over the Atmospheric Radiation Measurement Southern Great Plains site. A full spectrum of DSD is constructed based on a total of 23 size channels (0.321 to 9.785 mm), and both Gamma and Exponential fitted functions are applied to extract the DSD shape parameters. Compared to SR properties, CR has distinct features including broader size range and narrower exponential slope parameter (λE). These results indicate that the assumption of constant exponential intercept parameter (N0E) is inappropriate for CR rain rate estimates. Additionally, the subsetting scheme of the CR DSD spectra also has a strong impact on the Gamma/Exponential functions. Therefore, a new CR DSD parameterization scheme is developed by choosing the appropriate spectra subset with the constraint of rain rate and using the constant λE instead of constant N0E. With the input of the radar reflectivity at the lowest observed height, the newly calculated CR rain rates match well with the collocated surface rain gauge measurements (127 Mesonet stations and 17 Automatic Parsivel Units), while the rain rates calculated using traditional Z‐R relationship are 3–4 times larger, indicating that constant λE is a better assumption for CR DSD.

A Regression-Free Rainfall Estimation Algorithm for Dual-Polarization Radars

AbstractIn this study a new radar rainfall estimation algorithm—rainfall estimation using simulated raindrop size distributions (RESID)—was developed. This algorithm development was based upon the recent finding that measured and simulated raindrop size distributions (DSDs) with matching triplets of dual-polarization radar observables (i.e., horizontal reflectivity, differential reflectivity, and specific differential phase) produce similar rain rates. The RESID algorithm utilizes a large database of simulated gamma DSDs, theoretical rain rates calculated from the simulated DSDs, the corresponding dual-polarization radar observables, and a set of cost functions. The cost functions were developed using both the measured and simulated dual-polarization radar observables. For a given triplet of measured radar observables, RESID chooses a suitable cost function from the set and then identifies nine of the simulated DSDs from the database that minimize the value of the chosen cost function. The rain rate associated with the given radar observable triplet is estimated by averaging the calculated theoretical rain rates for the identified simulated DSDs. This algorithm is designed to reduce the effects of radar measurement noise on rain-rate retrievals and is not subject to the regression uncertainty introduced in the conventional development of the rain-rate estimators. The rainfall estimation capability of our new algorithm was demonstrated by comparing its performance with two benchmark algorithms through the use of rain gauge measurements from the Midlatitude Continental Convective Clouds Experiment (MC3E) and the Olympic Mountains Experiment (OLYMPEx). This comparison showed favorable performance of the new algorithm for the rainfall events observed during the field campaigns.

Comparisons of Ice Water Path in Deep Convective Systems Among Ground‐Based, GOES, and CERES‐MODIS Retrievals

AbstractRetrievals of convective cloud microphysical properties based on passive satellite imagery are difficult. To help quantify their uncertainties, ice water paths (IWPs) retrieved from the NASA Clouds and the Earth's Radiant Energy System project using Geostationary Operational Environmental Satellite (GOES) and Terra/Aqua MODerate‐resolution Imaging Spectroradiometer observations are compared with IWPs retrieved from Next‐Generation Radar (NEXRAD) observations over a large domain (32°N to 40°N and 105°W to 91°W) during the 2011 Midlatitude Continental Convective Clouds Experiment field campaign. Based on comparisons of pixel‐level (4 km × 4 km) daytime IWP retrievals from NEXRAD and GOES, it is found that NEXRAD‐ and GOES‐retrieved mean IWPs are 2.03 and 1.83 kg m−2, respectively, for ice‐phase cloud in thick anvil area. Their mean difference of 0.20 kg m−2 (with 95% confidence interval: 0.14–0.26 kg m−2) is within the uncertainty of NEXRAD retrievals. However, the low correlation between pixel‐to‐pixel comparisons indicates a large variation in GOES‐retrieved IWP. For mixed‐phase clouds in thick anvil areas, in addition to IWPs, total water paths (TWPs, sum of ice and liquid water path) are estimated with aid of aircraft measurements for NEXRAD retrievals and corrected using a TWP parameterization for GOES retrievals. The mean values of estimated TWPs from NEXRAD (corrected using aircraft in situ measurements) and GOES are similar. GOES and Clouds and the Earth's Radiant Energy System‐MODerate‐resolution Imaging Spectroradiometer‐retrieved IWPs/TWPs generally do not exceed 5 kg m−2. Large differences and low correlations exist between satellite and NEXRAD retrievals in stratiform rain areas. Possible reasons for the differences between retrievals are discussed.

Aerosol properties and their impacts on surface CCN at the ARM Southern Great Plains site during the 2011 Midlatitude Continental Convective Clouds Experiment

Aerosol particles are of particular importance because of their impacts on cloud development and precipitation processes over land and ocean. Aerosol properties as well as meteorological observations from the Department of Energy Atmospheric Radiation Measurement (ARM) platform situated in the Southern Great Plains (SGP) are utilized in this study to illustrate the dependence of continental cloud condensation nuclei (CCN) number concentration (NCCN) on aerosol type and transport pathways. ARM-SGP observations from the 2011 Midlatitude Continental Convective Clouds Experiment field campaign are presented in this study and compared with our previous work during the 2009–10 Clouds, Aerosol, and Precipitation in the Marine Boundary Layer field campaign over the current ARM Eastern North Atlantic site. Northerly winds over the SGP reflect clean, continental conditions with aerosol scattering coefficient (σsp) values less than 20 Mm−1 and NCCN values less than 100 cm−3. However, southerly winds over the SGP are responsible for the observed moderate to high correlation (R) among aerosol loading (σsp < 60 Mm−1) and NCCN, carbonaceous chemical species (biomass burning smoke), and precipitable water vapor. This suggests a common transport mechanism for smoke aerosols and moisture via the Gulf of Mexico, indicating a strong dependence on air mass type. NASA MERRA-2 reanalysis aerosol and chemical data are moderately to highly correlated with surface ARM-SGP data, suggesting that this facility can represent surface aerosol conditions in the SGP, especially during strong aerosol loading events that transport via the Gulf of Mexico. Future long-term investigations will help to understand the seasonal influences of air masses on aerosol, CCN, and cloud properties over land in comparison to over ocean.

A Field Study of Footprint-Scale Variability of Raindrop Size Distribution

Abstract A network of seven two-dimensional video disdrometers (2DVD), which were operated during the Midlatitude Continental Convective Clouds Experiment (MC3E) in northern Oklahoma, are employed to investigate the spatial variability of raindrop size distribution (DSD) within the footprint of the dual-frequency precipitation radar (DPR) on board the National Aeronautics and Space Administration’s Global Precipitation Measurement (GPM) mission core satellite. One-minute 2DVD DSD observations were interpolated uniformly to 13 points distributed within a nearly circular DPR footprint through an inverse distance weighting method. The presence of deep continental showers was a unique feature of the dataset resulting in a higher mean rain rate R with respect to previous studies. As a measure of spatial variability for the interpolated data, a three-parameter exponential function was applied to paired correlations of three parameters of normalized gamma DSD, R, reflectivity, and attenuation at Ka- and Ku-band frequencies of DPR (Z_Ka, Z_Ku, k_Ka, and k_Ku, respectively). The symmetry of the interpolated sites allowed quantifying the directional differences in correlations at the same distance. The correlation distances d0 of R, k_Ka, and k_Ku were approximately 10 km and were not sensitive to the choice of four rain thresholds used in this study. The d0 of Z_Ku, on the other hand, ranged from 29 to 20 km between different rain thresholds. The coefficient of variation (CV) remained less than 0.5 for most of the samples for a given physical parameter, but a CV of greater than 1.0 was also observed in noticeable samples, especially for the shape parameter and Z_Ku.

The Microphysical Roles of Lower-Tropospheric versus Midtropospheric Aerosol Particles in Mature-Stage MCS Precipitation

Abstract Simulations of two leading-line, trailing-stratiform mesoscale convective system (MCS) events that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) have been used to understand the relative microphysical impacts of lower- versus midtropospheric aerosol particles (APs) on MCS precipitation. For each MCS event, four simulations were conducted in which the initial vertical location and concentrations of cloud droplet nucleating APs were varied. These simulations were used to determine the precipitation response to AP vertical location. Importantly, the total integrated number and mass of the initial aerosol profiles used in the sensitivity simulations remained constant, such that differences in the simulations could be directly attributable to changes in the vertical location of cloud droplet nucleating APs. These simulations demonstrate that lower-tropospheric APs largely influenced the precipitation response directly rearward of the leading cold pool boundary. However, farther rearward in the MCS, the relative impact of lower- versus midtropospheric APs largely depended on the MCS structure, which varied between the two events because of differences in line-normal wind shear. Midtropospheric APs were able to activate new cloud droplets in the midtropospheric levels of convective updrafts and to enhance mixed-phase precipitation through increased cloud riming, and this microphysical pathway had a more significant impact on mixed-phase precipitation in weaker line-normal wind shear conditions. This result exposes the importance of properly representing midtropospheric APs when assessing aerosol effects on clouds. This study also demonstrates the utility of assessing aerosol effects within the different regions of MCSs.

Derivation of aerosol profiles for MC3E convection studies and use in simulations of the 20 May squall line case

Abstract. Advancing understanding of deep convection microphysics via mesoscale modeling studies of well-observed case studies requires observation-based aerosol inputs. Here, we derive hygroscopic aerosol size distribution input profiles from ground-based and airborne measurements for six convection case studies observed during the Midlatitude Continental Convective Cloud Experiment (MC3E) over Oklahoma. We demonstrate use of an input profile in simulations of the only well-observed case study that produced extensive stratiform outflow on 20 May 2011. At well-sampled elevations between −11 and −23 °C over widespread stratiform rain, ice crystal number concentrations are consistently dominated by a single mode near ∼ 400 µm in randomly oriented maximum dimension (Dmax). The ice mass at −23 °C is primarily in a closely collocated mode, whereas a mass mode near Dmax ∼ 1000 µm becomes dominant with decreasing elevation to the −11 °C level, consistent with possible aggregation during sedimentation. However, simulations with and without observation-based aerosol inputs systematically overpredict mass peak Dmax by a factor of 3–5 and underpredict ice number concentration by a factor of 4–10. Previously reported simulations with both two-moment and size-resolved microphysics have shown biases of a similar nature. The observed ice properties are notably similar to those reported from recent tropical measurements. Based on several lines of evidence, we speculate that updraft microphysical pathways determining outflow properties in the 20 May case are similar to a tropical regime, likely associated with warm-temperature ice multiplication that is not well understood or well represented in models.

Wind Effects on the Shape of Raindrop Size Distribution

AbstractThe wind effects on the shape of drop size distribution (DSD) and the driving microphysical processes for the DSD shape evolution were investigated using the dataset from the Midlatitude Continental Convective Clouds Experiment (MC3E). The quality-controlled DSD spectra from MC3E were grouped for each of the rainfall events by considering the precipitation type (stratiform vs convective) and liquid water content for the analysis. The DSD parameters (e.g., mass-weighted mean diameter) and the fitted DSD slopes for these grouped spectra showed statistically significant trends with varying wind speed. Increasing wind speeds were observed to modify the DSD shapes by increasing the number of small drops and decreasing the number of large drops, indicating that the raindrop breakup process governs the DSD shape evolution. Both spontaneous and collisional raindrop breakup modes were analyzed to elucidate the process responsible for the DSD shape evolution with varying wind speed. The analysis revealed that the collisional breakup process controls the wind-induced DSD shape. The findings of this study are of importance in DSD parameterizations that are essential to a wide variety of applications such as radar rainfall retrievals and hydrologic models.

An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation.

Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CMIP5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition, Cloud and Climate Coupling (TC4), DOE ARM-NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small Particles in Cirrus (SPARTICUS) field campaigns. The new parameterization assumes a normalized gamma PSD with two novel developments: no explicit assumption for particle habit in the calculation of mass distributions, and a formulation for translating ice particle fall speeds as a function of maximum diameter into fall speeds as a function of melted-equivalent diameter. Two parameters (particle volume- and projected area-weighted equivalent diameter) are diagnosed as a function of temperature and IWC in the convective plume, and these parameters constrain the shape and scale of the normalized gamma PSD. The diagnosed fall speeds and PSDs are combined with the GCM's parameterized convective updraft vertical velocity to partition convective updraft condensate into precipitating and detrained components. A 5-yr prescribed sea surface temperature GCM simulation shows a 30%-50% decrease in upper-tropospheric deep convective IWC, bringing the tropical and global mean ice water path into closer agreement with CloudSat best estimates.

Aerosol effects on the anvil characteristics of mesoscale convective systems

AbstractSimulations of two mesoscale convective systems (MCSs) that occurred during the Midlatitude Continental Convective Clouds Experiment were performed to examine the impact of aerosol number concentration on the vertical distributions of liquid and ice condensate and the macrophysical, microphysical, and radiative properties of the cirrus‐anvil cloud shield. Analyses indicate that for an increase in aerosol concentration from a clean continental to a highly polluted state, there was an increase in the rime collection rate of cloud water, which led to less lofted cloud water. Aerosol‐induced trends in the cloud mixing ratio profiles were, however, nonmonotonic in the mixed phase region, such that a moderate increase in aerosol concentration produced the greatest reduction in cloud water. Generally, less lofted cloud water led to less anvil ice mixing ratio but more numerous, small ice crystals within the anvil. In spite of reduced anvil ice mixing ratio, the anvil clouds exhibited greater areal coverage, increased albedo, reduced cloud top cooling, and reduced net radiative flux, which led to an aerosol‐induced warming (reduced cooling) effect in these squall lines.