Cloud Microphysical Parameters Research Articles

Cloud Microphysical Factors Affecting Simulations of Deep Convection During the Presummer Rainy Season in Southern China

AbstractThe sensitivity of subtropical deep convection to the parameterization of cloud microphysics is elucidated through high‐resolution modeling of extreme presummer rainfall over southern China. An ensemble of physics configuration experiments is used to identify several drivers of model errors in comparison to radar observations from the South China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of cloud, precipitation, and radiation from satellites in the A‐train constellation. The benefits of increasing the number of prognostic variables in the microphysics scheme is assessed, relative to the effects of the parameterization of cloud microphysical properties and cloud fraction diagnosis. By matching individual parameterizations between the microphysical configurations, it is shown that a small subset of the parameterization changes can reproduce most of the dependence of model performance on physics configuration. In particular, biases that are due to the low‐level clouds and rain are strongly influenced by cloud fraction diagnosis and raindrop size distribution, whereas variations in the effects of high clouds are strongly influenced by differences in the parameterization of ice crystal sedimentation. Hence, for the case studied here, these parameterizations give more insight into the causes of variability in model performance than does the number of model prognostics per se.

Development of neural network retrievals of liquid cloud properties from multi-angle polarimetric observations

We present a neural network (NN) based algorithm for the retrieval of liquid low-level marine stratocumulus cloud microphysical property parameters (cloud optical depth, cloud droplet size effective radius and variance) from airborne multi-angle polarimetric measurements. We establish our retrieval method for the Research Scanning Polarimeter (RSP) airborne instrument, which measures both polarized and total reflectance in the spectral range of 410–2260 nm, scanning along the flight track at ∼150 viewing zenith angles spanning the angular range between −60° and 60°. In this study, we present the development of the algorithm, including the optimization and selection of input parameters and the network architecture. We perform a sensitivity study to test the effect of random and correlated instrument noise on the retrieval performance, and to assess which of the measured radiometric quantities (i.e., total reflectance, polarized reflectance, degree of linear polarization and combinations thereof) are best suited for marine stratocumulus liquid cloud property retrievals using simulated RSP data. Finally, we show the application of this method to airborne observations from the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) 2016 field campaign, which primarily encountered low altitude marine clouds. Retrieved cloud optical depth compares favorably (r2 = 0.96) to standard algorithms, but cloud droplet size effective radius less so (r2 = 0.45), providing an assessment of the NN approach strengths and limitations. Specifically, the latter seemed to be affected by the cloud macro-structure and the liquid cloud droplet vertical distribution.

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

AbstractRegional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.

The effects of ice microphysics on the inner core thermal structure of the hurricane boundary layer

The effects of five cloud microphysics parameterizations on the mean thermal structure of the tropical cyclone boundary layer (TCBL) are examined by numerical experiments with an axisymmetric, non-hydrostatic model. It is shown that although the radial and azimuthal velocity remains “slaved” to the gradient flow above the TCBL, the strength of the boundary layer updrafts (and downdrafts) and the location of the cloud base (which is connected to the location of the stable layer within the TCBL) depend sensitively on the microphysics parameterization. From an analysis of the potential temperature and water vapor mixing ratio budgets, it is found that latent heat release within the eyewall above the cloud base is balanced by the strong cooling tendency due to vertical advection above the cloud base. Below the cloud base, it is found that the downward flux of high θ is largely balanced by rain evaporation. Near the surface, it is shown that warm rain microphysical parameterizations enhance near-surface evaporation rates compared to their ice microphysics counterparts (which affect the thermal structure of the surface layer). Finally, it is shown that diagnostic TCBL models generally underestimate rainwater evaporation rates compared to the full non-hydrostatic model.

Simulation of a heavy rainfall event over Chennai in Southeast India using WRF: Sensitivity to microphysics parameterization

Chennai City on the southeast coast of India experienced record heavy rainfall on 1 Dec 2015 during the Northeast Monsoon. In this study, numerical simulations of this event are performed using the Advanced Research and Weather Research and Forecasting (WRF-ARW) model, with a cloud-resolving grid resolution of 1 km. Five simulations are performed to study the model sensitivity to cloud microphysics parameterizations on the heavy rainfall prediction. Model results are compared with the available surface and Doppler weather radar (DWR) observations. Results show that the microphysics significantly influenced the rainfall simulation due to variation in mixing ratios of different hydrometeors and the associated dynamic and thermodynamic parameters. The Thompson scheme, followed by the Morrison scheme captured the location of maximum rainfall, its spatial distribution, and its time of occurrence in close agreement with the observations. All the other schemes simulated the event with lesser intensity and at a later time. Results suggest that the Thomson scheme captured the time evolution of different hydrometeors that led to produce the observed pattern of rainfall both spatially and temporally. It is also found that the Thompson scheme correctly produced high vertical motions associated with high instability, strong mid-level convergence and upper air divergence associated with strong cyclonic vorticity, which led to the observed feature of the intense precipitation over Chennai.

An Evaluation of WRF Microphysics Schemes for Simulating the Warm-Type Heavy Rain over the Korean Peninsula

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warm-type rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warm-type heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collision-coalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

Diurnal spatial distributions of aerosol optical and cloud micro-macrophysics properties in Africa based on MODIS observations

The diurnal spatial distribution of both natural and anthropogenic aerosols, as well as liquid and ice cloud micro-macrophysics have been evaluated over Africa using Terra and Aqua MODIS collection 6 products. The variability of aerosol optical depth (AOD), Ångström exponent (AE), liquid and ice cloud microphysics (Liquid cloud effective radius LCER, Ice cloud effective radius ICER) and cloud macrophysics (Liquid cloud optical thickness LCOT, Liquid cloud water path LCWP, Ice cloud optical thickness ICOT, Ice cloud water path ICWP) parameters were investigated from the morning to afternoon over Africa from 2010 to 2014. In both the morning (Terra) and afternoon (Aqua) heavy pollution (AOD ≥ 0.6) occurs in the coastal and central areas (between 120 N-170 N and 100 E-150 E) of West of Africa (WA), Central of Africa (CA) (0.50 S-70S and 100 E-250 E),. Moderate pollution (0.3 < AOD < 0.6) often occurs in West and North of Africa (between 50 N-270 N and 160 W-50E), and clean environmental (AOD < 0.3) conditions are common in South of Africa (SA), East of Africa (EA) and some regions in North of Africa (NA). The West-North of Africa (WNA) and Central-South of Africa (CSA) regions are dominated by dust (AE < 0.7) and biomass burning (AE > 1.2) aerosols. The mixture of dust and biomass burning aerosols (0.7 < AE < 1.2) are found at the coastal areas in West of Africa (CoWA) and Central of Africa (CA) (50 N-80N and 100 E-340 E), particularly in the morning and afternoon respectively. The LCER often decrease from the morning to the afternoon in all seasons, but an increase occur from the morning to the afternoon in CSA (50 S-220 S) in DJF, both CA (20 S-50N) and CoWA in JJA and SON. The ICER increase from the morning to afternoon in all seasons over Africa and decreases in South of Africa (50 S-200 S) in DJF. The LCOT increases from the morning to afternoon in NA and SA while a decrease occur in CA in all seasons. The LCWP increase in many regions of Africa in all seasons while a decrease occurs in CoWA during JJA. The ICOT and ICWP show a remarkable increase from the morning to afternoon in regions dominated by biomass burning (CSA) compared to regions dominated by dust (WNA) aerosols in DJF, MAM and SON. Dust aerosols are mainly distributed in WNA by northerly and westerly winds in both January and April, southerly and southwesterly winds in July, and southerly and southwesterly winds in October, while biomass burning aerosols are mainly distributed in CSA by the northerly and northeasterly winds in January, easterly winds in April, July and October. The diurnal variability of cloud parameters is associated with both convective processes and cloud types. The knowledge of interactions between natural and anthropogenic aerosols with liquid and ice cloud microphysics parameters could contribute to improve aerosol and cloud remote sensing retrieval.

A Lookup-Table-Based Approach to Estimating Surface Solar Irradiance from Geostationary and Polar-Orbiting Satellite Data

Incoming surface solar irradiance (SSI) is essential for calculating Earth’s surface radiation budget and is a key parameter for terrestrial ecological modeling and climate change research. Remote sensing images from geostationary and polar-orbiting satellites provide an opportunity for SSI estimation through directly retrieving atmospheric and land-surface parameters. This paper presents a new scheme for estimating SSI from the visible and infrared channels of geostationary meteorological and polar-orbiting satellite data. Aerosol optical thickness and cloud microphysical parameters were retrieved from Geostationary Operational Environmental Satellite (GOES) system images by interpolating lookup tables of clear and cloudy skies, respectively. SSI was estimated using pre-calculated offline lookup tables with different atmospheric input data of clear and cloudy skies. The lookup tables were created via the comprehensive radiative transfer model, Santa Barbara Discrete Ordinate Radiative Transfer (SBDART), to balance computational efficiency and accuracy. The atmospheric attenuation effects considered in our approach were water vapor absorption and aerosol extinction for clear skies, while cloud parameters were the only atmospheric input for cloudy-sky SSI estimation. The approach was validated using one-year pyranometer measurements from seven stations in the SURFRAD (SURFace RADiation budget network). The results of the comparison for 2012 showed that the estimated SSI agreed with ground measurements with correlation coefficients of 0.94, 0.69, and 0.89 with a bias of 26.4 W/m2, −5.9 W/m2, and 14.9 W/m2 for clear-sky, cloudy-sky, and all-sky conditions, respectively. The overall root mean square error (RMSE) of instantaneous SSI was 80.0 W/m2 (16.8%), 127.6 W/m2 (55.1%), and 99.5 W/m2 (25.5%) for clear-sky, cloudy-sky (overcast sky and partly cloudy sky), and all-sky (clear-sky and cloudy-sky) conditions, respectively. A comparison with other state-of-the-art studies suggests that our proposed method can successfully estimate SSI with a maximum improvement of an RMSE of 24 W/m2. The clear-sky SSI retrieval was sensitive to aerosol optical thickness, which was largely dependent on the diurnal surface reflectance accuracy. Uncertainty in the pre-defined horizontal visibility for ‘clearest sky’ will eventually lead to considerable SSI retrieval error. Compared to cloud effective radius, the retrieval error of cloud optical thickness was a primary factor that determined the SSI estimation accuracy for cloudy skies. Our proposed method can be used to estimate SSI for clear and one-layer cloud sky, but is not suitable for multi-layer clouds overlap conditions as a lower-level cloud cannot be detected by the optical sensor when a higher-level cloud has a higher optical thickness.

Processing method for the partial particles and its influence on the cloud microphysical parameters measured by the airborne cloud and precipitation image probe

As an important instrument for the cloud microphysics measurement, the airborne cloud and precipitation imaging probe plays a significant role in studying the cloud and precipitation physics and artificial weather modification. The particle image data recorded by the probe can be used to process, calculate and produce the cloud microphysical parameters, such as the cloud particle size spectra, cloud particle number concentration, cloud water content, etc. However, there are lots of partial particle images in the sampled data. This is due to the limited sample volume of the probe, the volume that contains only a part of the particles and is imaged by the probe. The number of partial particles in each sample is so large that the technique used to process these particles can have a great influence on the calculation of cloud microphysical parameters. However, there has been no perfect solution for dealing with these partial particles so far.&lt;br/&gt;The three existing processing methods-“All In” method, “Center In” method, and “Diameter Reconstruction” method for the partial particles, are introduced and analysed in this study. After analyzing the advantages and disadvantages of these existing methods, a new definition and a particle shape classification for the partial particle are given, which can discriminate the circularly symmetric particles and the non-circularly symmetric particles from the partials. Then a new partial particle processing method is introduced, which combines the partial particle shape recognition technique and the traditional techniques-“Center In” method and “Diameter Reconstruction” method. The circularly symmetric partial particles are processed with the “Diameter Reconstruction method” and the non-circularly symmetric partial particles are processed with the “Center In” method.&lt;br/&gt;Utilizing the historical airplane observation data from Shanxi Taiyuan, the new method presented in this study and the three traditional methods are used to calculate the cloud particle size spectra, cloud particle number concentration, and the ice water content by using the same data. The calculated results are analyzed and compared. It is found that in most cases the results from the new method are more consistent with those from the “Diameter Reconstruction” technique and can overcome the disadvantages of the existing methods, especially when the cloud has more column-shaped and needle-shaped particles, the result from the new method is more reasonable. Considering the fact that the column shape is one of the main shapes in the cloud, it is strongly recommended to use the new technique in this paper to process the data from the probes.

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

Abstract. In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s−1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

Preliminary study on direct assimilation of cloud-affected satellite microwave brightness temperatures

Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational (3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm (including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters (cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong (2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

Ice-Phase Precipitation

AbstractIce-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

AbstractOver the past decade, the number of studies that investigate aerosol–cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of basic physical mechanisms of aerosol–cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud–aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol–cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap—for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed.

The effect of El Nino and La Nina on lightning activity: its relation with meteorological and cloud microphysical parameters

The decadal variation of lightning activity over Northeast India (NEI) from the year 2002 to 2011 is studied with the help of satellite-based lightning imaging sensor (LIS) data. An anomalous 56 % increase in lightning activity is observed in the year 2010 with respect to the previous years. To investigate the reason behind this increase, the LIS data are analyzed with several meteorological and cloud microphysical parameters. These parameters are convective sources of cloud ice, cloud top temperature, surface temperature, convective precipitation rate and total ice water content and convective available potential energy. On a synoptic scale, the period of anomalous lightning activity could be related to the development of an El Nino event at the middle of 2009 that broke down in the early months of the next year with a rapid transition to La Nina by August 2010. Analyses expose that El Nino Southern Oscillation might have diversely modified the local meteorological and cloud microphysical parameters. It comes out that this rapid transition from El Nino to La Nina condition could be the possible reason behind the dramatic increase in lightning activity, which was not previously documented over NEI.

Indirect forcing of black carbon on clouds over northeast India

Black carbon (BC) induced indirect radiative forcing and cloud albedo effect has been studied for the first time over northeast India. Measurements of BC and cloud microphysical parameters were carried out during Phase‐I of the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) over northeast India (Guwahati) in 2009. Liquid water path (LWP) in the cloud layers coherent with BC on different experimental days was found to be 206–327 g m−2 over the region. Black carbon aerosol indirect effect (BCIE) for fixed LWP is found to be 0.32–0.48 on different days of observations. The indirect forcing corresponding to this BCIE has been estimated using a radiative transfer model for fixed LWP by altering the derived BC‐AOD (aerosol optical depth from measured BC profiles) and cloud effective radius (Re) combinations. The estimated average BC‐induced indirect forcing (BCIF) was −24 to −37.1 W m−2 at the surface and +2.5 to +14.8 W m−2 at the top of the atmosphere (TOA). The average albedo due to BCIF at TOA was 0.49–0.61. BCIF is found to reduce the cloud reflection by 1.5–2% over the region. The sensitivities of cloud parameters to BCIF and the albedo effect are illustrated.

The response of clouds and aerosols to cosmic ray decreases

AbstractA method is developed to rank Forbush decreases (FDs) in the galactic cosmic ray radiation according to their expected impact on the ionization of the lower atmosphere. Then a Monte Carlo bootstrap‐based statistical test is formulated to estimate the significance of the apparent response in physical and microphysical cloud parameters to FDs. The test is subsequently applied to one ground‐based and three satellite‐based data sets. Responses (&gt;95%) to FDs are found in the following parameters of the analyzed data sets. AERONET: Ångström exponent (cloud condensation nuclei changes), SSM/I: liquid water content, International Satellite Cloud Climate Project (ISCCP): total, high, and middle, IR‐detected clouds over the oceans, Moderate Resolution Imaging Spectroradiometer (MODIS): cloud effective emissivity, cloud optical thickness, liquid water, cloud fraction, liquid water path, and liquid cloud effective radius. Moreover, the responses in MODIS are found to correlate positively with the strength of the FDs, and the signs and magnitudes of the responses agree with model‐based expectations. The effect is mainly seen in liquid clouds. An impact through changes in UV‐driven photo chemistry is shown to be negligible and an impact via UV absorption in the stratosphere is found to have no effect on clouds. The total solar irradiance has a relative decrease in connection with FDs of the order of 10−3, which is too small to have a thermodynamic impact on timescales of a few days. The results demonstrate that there is a real influence of FDs on clouds probably through ions.

Evaluating Arctic cloud radiative effects simulated by NICAM with A‐train

AbstractEvaluation of cloud radiative effects (CREs) in global atmospheric models is of vital importance to reduce uncertainties in weather forecasting and future climate projection. In this paper, we describe an effective way to evaluate CREs from a 3.5 km mesh global nonhydrostatic model by comparing it against A‐train satellite data. The model is the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), and its output is run through a satellite‐sensor simulator (Joint Simulator for satellite sensors) to produce the equivalent CloudSat radar, CALIPSO lidar, and Aqua Clouds and the Earth's Radiant Energy System (CERES) data. These simulated observations are then compared to real observations from the satellites. We focus on the Arctic, which is a region experiencing rapid climate change over various surface types. The NICAM simulation significantly overestimates the shortwave CREs at top of atmosphere and surface as large as 24 W m−2 for the month of June. The CREs were decomposed into cloud fractions and footprint CREs of cloud types that are defined based on the CloudSat‐CALIPSO cloud top temperature and maximum radar reflectivity. It turned out that the simulation underestimates the cloud fraction and optical thickness of mixed‐phase clouds due to predicting too little supercooled liquid and predicting overly large snow particles with too little mass content. This bias was partially offset by predicting too many optically thin high clouds. Offline sensitivity experiments, where cloud microphysical parameters, surface albedo, and single scattering parameters are varied, support the diagnosis. Aerosol radiative effects and nonspherical single scattering of ice particles should be introduced into the NICAM broadband calculation for further improvement.

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

Abstract. In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).

Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part III: Introduction of Multiple Free Categories

Abstract The predicted particle properties (P3) scheme introduced in Part I of this series represents all ice hydrometeors using a single “free” category, in which the bulk properties evolve smoothly through changes in the prognostic variables, allowing for the representation of any type of ice particle. In this study, P3 has been expanded to include multiple free ice-phase categories allowing particle populations with different sets of bulk properties to coexist, thereby reducing the detrimental effects of property dilution. The modified version of P3 is the first scheme to parameterize ice-phase microphysics using multiple free categories. The multicategory P3 scheme is described and its overall behavior is illustrated. It is shown using an idealized 1D kinematic model that the overall simulation of total ice mass, reflectivity, and surface precipitation converges with additional categories. The correct treatment of the rime splintering process, which promotes multiple ice modes, is shown to require at least two categories in order to be included without introducing problems associated with property dilution. Squall-line simulations using a 3D dynamical model with one, two, and three ice categories produce reasonable reflectivity structures and precipitation rates compared to radar observations. In the multicategory simulations, ice hydrometeors from different categories and with different bulk properties are shown to coexist at the same points, with effects on reflectivity structure and precipitation. The new scheme thus appears to work reasonably in a full 3D model and is ready to be tested more widely for research and operational applications.

A Bayesian Examination of Deep Convective Squall-Line Sensitivity to Changes in Cloud Microphysical Parameters

Abstract Deep convective cloud content, precipitation distribution and rate, dynamics, and radiative fluxes are known to be sensitive to the details of liquid- and ice-phase cloud microphysical processes. Previous studies have explored the multivariate convective response to changes in cloud microphysical parameter values in a framework that isolated the cloud and radiation schemes from the thermodynamic and dynamic environment. This study uses a Bayesian Markov chain Monte Carlo (MCMC) algorithm to generate sets of cloud microphysical parameters consistent with a specific storm environment in a three-dimensional cloud-system-resolving model. These parameter sets, and the corresponding large ensemble of model simulations, contain information about the univariate model sensitivity, as well as parameter–state and parameter–parameter interactions. Examination of the relationships between cloud parameters and in-cloud vertical motion and latent heat release provides information about the influence of microphysical processes on the in-cloud environment. Exploration of the joint dependence of microphysical properties and clear-air relative humidity and temperature allows an assessment of the influence of cloud microphysics on the near-cloud environment. Analysis of the MCMC results indicates the model output is sensitive to a small subset of the parameters. In addition, constraint of cloud microphysics using bulk observations of the hydrologic cycle and TOA radiative fluxes uniquely constrains vertical velocity, latent heat release, and the environmental temperature and relative humidity.