Liquid Water Content Values Research Articles

Vortex Structure of Head Bubble in Convective Cloud Starting Plume

Abstract A developing cumulus cloud (Cu) was modeled, and dynamic, thermodynamic, and microphysical properties of an ascending head bubble reproducing the upper part of a developing Cu were investigated. The data for analysis are taken from 10-m-resolution LES of trade wind Cu under BOMEX conditions. The detection of a rising bubble is carried out using wavelet filtering of the velocity fields and microphysical fields, while a low-frequency signal of the filtering is associated with the convective-scale structure of cloud. We substantiate and discuss the representation of the bubble as a vortex ring, and estimate the parameters of this vortex ring. The simplest Hill’s vortex was chosen as a model of a vortex ring inside cloud. Analytical approximations of the radial profiles of the vertical velocity and of conservative quantities (such as total water mixing ratio and liquid water potential temperature inside and outside the bubble) are obtained. The spatial structure of these quantities is investigated using analytical expressions. Analytical models for spatial distributions of liquid water content (LWC) and adiabatic fraction (AF) are also designed and analyzed. The results demonstrate the existence of a cloud core with high values of LWC and AF up to the height of 1800 m. The horizontally averaged value of the adiabatic fraction, calculated analytically using the Hill’s vortex concept, is evaluated as 0.39, which is the typical AF value in the upper parts of such Cu. The vertical profiles of different important quantities characterizing cloud structure are presented. The analysis performed in this study allows us to conclude that a rising vortex ring plays the dominating role in formation of the thermodynamic and microphysical structure of developing Cu. Significance Statement 1) Dynamic and thermodynamic fields of a developing cumulus cloud simulated by high-resolution LES with spectral bin microphysics are separated into convective and turbulent components by means of the wavelet technique. 2) The analysis of convective component of the cloud revealed the existence of a vortex ring at the developing stage of the cloud and evaluate its parameters. 3) The analysis performed in this study allows us to conclude that a rising vortex ring plays the important role in formation of the thermodynamic and microphysical structure of developing Cu. 4) The study provides a novel insight into the cloud–environment interaction. 5) The approximating equations describing the vortex ring can be usefully applied for developing new schemes of convective parameterization.

Analysis of the Taquari Megafan through radiometric indices

The complex landscapes of tropical monsoonal lowlands make water resource estimates difficult, given sparsely distributed monitoring networks. Satellite radiometry has facilitated increased access to environmental data. Here, we use radiometric indices to analyze the Taquari megafan and identify features of the Pantanal subregions that characterize it. Recent periods of strong droughts and floods were selected in the region for statistical analysis using the following radiometric indices: NDWI-Gao, NDWI-McFeeters and MNDWI. The behavior of the NDWI-Gao showed that the Paiaguás and Nhecolândia subregions had similar vegetation moisture values in 2011 and 2012, but surprisingly, the two subregions did not attain maximum values of vegetation moisture higher than values in the Taquari subregion during severe flooding in 2011. The Paiaguás and Nhecolândia subregions were more correlated in terms of vegetation moisture than open water features. The MNDWI analysis of the Taquari subregion, however, revealed the highest levels of liquid water in the vegetation and the highest values for water bodies/courses. The permanently flooded state of the Taquari subregion may explain why the vegetation appears to be moister in the NDWI-Gao. The NDWI-Gao data were consistent for dry vegetation in 2020, recording values of −0.7, while other dry periods such as 2010 and 2013 recorded values of −0.4. The vegetation responded quickly to the alternation of drought/flood cycles, registering high values of liquid water content in the period 2011–2012 and reduced values in 2012–2013.

Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

Abstract. Aerosol-aware microphysics parameterisation schemes are increasingly being introduced into numerical weather prediction models, allowing for regional and case-specific parameterisation of cloud condensation nuclei (CCN) and cloud droplet interactions. In this paper, the Thompson aerosol-aware microphysics scheme, within the Weather Research and Forecasting (WRF) model, is used for two fog cases during September 2017 over Namibia. Measurements of CCN and fog microphysics were undertaken during the AErosols, RadiatiOn and CLOuds in southern Africa (AEROCLO-sA) field campaign at Henties Bay on the coast of Namibia during September 2017. A key concept of the microphysics scheme is the conversion of water-friendly aerosols to cloud droplets (hereafter referred to as CCN activation), which could be estimated from the observations. A fog monitor 100 (FM-100) provided cloud droplet size distribution, number concentration (Nt), liquid water content (LWC), and mean volumetric diameter (MVD). These measurements are used to evaluate and parameterise WRF model simulations of Nt, LWC, and MVD. A sensitivity analysis was conducted through variations to the initial CCN concentration, CCN radius, and the minimum updraft speed, which are important factors that influence droplet activation in the microphysics scheme of the model. The first model scenario made use of the default settings with a constant initial CCN number concentration of 300 cm−3 and underestimated the cloud droplet number concentration, while the LWC was in good agreement with the observations. This resulted in droplet size being larger than the observations. Another scenario used modelled data as CCN initial conditions, which were an order of magnitude higher than other scenarios. However, these provided the most realistic values of Nt, LWC, MVD, and droplet size distribution. From this, it was concluded that CCN activation of around 10 % in the simulations is too low, while the observed appears to be higher reaching between 20 % and 80 %, with a mean (median) of 0.55 (0.56) during fog events. To achieve this level of activation in the model, the minimum updraft speed for CCN activation was increased from 0.01 to 0.1 m s−1. This scenario provided Nt, LWC, MVD, and droplet size distribution in the range of the observations, with the added benefit of a realistic initial CCN concentration. These results demonstrate the benefits of a dynamic aerosol-aware scheme when parameterised with observations.

Response of Mixed-Phase Cloud Microphysical Properties to Cloud-Seeding Near Cloud Top Over Hebei, China

On November 29, 2019, an aircraft observation during the period of cloud-seeding was carried out for a mixed-phase cloud over Xingtai, Hebei Province, China. This study investigates the response of mixed-phase cloud microphysical properties to cloud-seeding near cloud top. Before cloud seeding, the cloud droplet concentration from fast cloud droplet probe (NC_FCDP) presented a multi-peak vertical distribution structure, with a maximum concentration of 192 cm−3 at a height of 3,322 m; the maximum concentration of ice crystals from cloud imaging probe (NC_CIP) was 10 L−1, which appeared at 4,500 m in the upper part of cloud; and the peak value of liquid water content (LWC) in the cloud also appeared at 4,500 m, with a value of 0.15 g/m3. The coexistence of supercooled liquid water and ice crystals implies that they are particularly suitable for cloud seeding at the height of 4,550 m. About 7–8 min later after cloud seeding at this height, the average NC_FCDP decreased from 160.3 to 129 cm−3, and the average NC_CIP increased from 7.1 to 10 L−1. Moreover, after cloud seeding, high NC_CIP as well as larger and more ice crystals appeared almost in the same areas within the cloud, and LWC presented an obvious decreasing trend. In contrast, the concentration of small cloud droplets and LWC decreased obviously after seeding. The findings suggest that the cloud microphysical properties showed obvious responses to the artificial introduction of silver iodide, which is important for human weather modification.

Spatiotemporal Variations in Liquid Water Content in a Seasonal Snowpack: Implications for Radar Remote Sensing

Radar instruments have been widely used to measure snow water equivalent (SWE) and Interferometric Synthetic Aperture Radar is a promising approach for doing so from spaceborne platforms. Electromagnetic waves propagate through the snowpack at a velocity determined by its dielectric permittivity. Velocity estimates are a significant source of uncertainty in radar SWE retrievals, especially in wet snow. In dry snow, velocity can be calculated from relations between permittivity and snow density. However, wet snow velocity is a function of both snow density and liquid water content (LWC); the latter exhibits high spatiotemporal variability, there is no standard observation method, and it is not typically measured by automated stations. In this study, we used ground-penetrating radar (GPR), probed snow depths, and measured in situ vertically-averaged density to estimate SWE and bulk LWC for seven survey dates at Cameron Pass, Colorado (~3120 m) from April to June 2019. During this cooler than average season, median LWC for individual survey dates never exceeded 7 vol. %. However, in June, LWC values greater than 10 vol. % were observed in isolated areas where the ground and the base of the snowpack were saturated and therefore inhibited further meltwater output. LWC development was modulated by canopy cover and meltwater drainage was influenced by ground slope. We generated synthetic SWE retrievals that resemble the planned footprint of the NASA-ISRO L-band InSAR satellite (NISAR) from GPR using a dry snow density model. Synthetic SWE retrievals overestimated observed SWE by as much as 40% during the melt season due to the presence of LWC. Our findings emphasize the importance of considering LWC variability in order to fully realize the potential of future spaceborne radar missions for measuring SWE.

Effect of Rain on the Aerodynamic Performance of a Horizontal Axis Wind Turbine – A Computational Study

This paper analyzes numerically the impact of rainfall on the aerodynamic performance of a three-bladed Horizontal Axis Wind Turbine, with blades constructed by NACA 4418 airfoil. The simulations were conducted by the help of the commercial Computational Fluid Dynamics code, ANSYS Fluent. Firstly, the optimum geometry of the blade was designed with an application based on Blade Element Momentum theory. The Moving Reference Frame Model was applicated to simulate the rotation of the blades and the k-ω shear-stress transport turbulence model was added as well. The simulation of rain was accomplished by the Discrete Phase Model and the Taylor Analogy Breakup model was enabled to simulate droplets breakup. Three different rainfall conditions were studied, corresponding to Liquid Water Contents of 10g/m³, 30g/m³ and 60g/m³. The influence of droplet diameter on the aerodynamic performance of the blade was also examined. The results showed that the aerodynamic performance of the wind turbine is degraded in rain conditions, and the degradation is greater for higher values of Liquid Water Content and for larger diameter of water droplets.

Investigating Wintertime Cloud Microphysical Properties and Their Relationship to Air Mass Advection at Ny-Ålesund, Svalbard Using the Synergy of a Cloud Radar–Ceilometer–Microwave Radiometer

This study investigates the relationship of cloud properties and radiative effects with air mass origin during the winter (November–February, 2016–2020) at Ny-Ålesund, Svalbard, through a combination of cloud radar, ceilometer, and microwave radiometer measurements. The liquid cloud fraction (CF) was less than 2%, whereas the ice CF predominantly exceeded 10% below 6 km. The liquid water content (LWC) of mixed-phase clouds (LWCmix), which predominantly exist in the boundary layer (CFmix: 10–30%), was approximately four times higher than that of liquid clouds (LWCliq). Warm air mass advection (warmadv) cases were closely linked with strong southerly/southwesterly winds, whereas northerly winds brought cold and dry air masses (coldadv) to the study area. Elevated values of LWC and ice water content (IWC) during warmadv cases can be explained by the presence of mixed-phase clouds in the boundary layer and ice clouds in the middle troposphere. Consistently, the re of ice particles in warmadv cases was approximately 5–10 μm larger than that in coldadv cases at all altitudes. A high CF and cloud water content in warmadv cases contributed to a 33% (69 W m−2) increase in downward longwave (LW) fluxes compared to cloud-free conditions.

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

The objective of this work is to evaluate GOES-R (Geostationary Operational Environmental Satellites-R series) data-based fog conditions which occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. The C-FOG campaign was designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve predictability. The project took place along coastlines and open water environments of eastern Canada (Nova Scotia, and the Island of Newfoundland) during August−October of 2018 where environmental conditions play an important role for late season fog formation. During the C-FOG field campaign, coastal instruments were mainly located at the Ferryland supersite, Newfoundland, with two main sites, and five satellite sites, as well as on the Research Vessel Hugh R. Sharp. Key in-situ measurement instruments included microphysical, meteorological, radiation, and aerosol sensors. A fog spectral probe was used for measuring droplet spectra from 1–50 µm at the Ferryland supersite. A laser precipitation monitor with 100 µm to 10 mm size range and an optical particle counter with 0.3–17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms, e.g. profiling microwave radiometer, ceilometer, microwave rain radar, lidar, meteorological towers, tethered balloons, and GOES-R products for fog coverage, and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and the profiling microwave radiometer are comparable to ground-based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short-term local fog predictions.

Measuring Atmospheric Icing Rate in Mixed-Phase Clouds Using Filtered Particle Data

In-cloud icing of objects is caused by supercooled microscopic water droplets carried by the wind. To estimate the icing rate of objects in such conditions, the liquid water content (LWC) of the icing cloud and the median volume diameter (MVD) of the droplets are measured. Mixed-phase clouds also contain ice crystals that must be ruled out in order to avoid the overestimation of the icing rate. Typically, cloud droplet instruments are not able to do this. A particle imaging instrument icing condition evaluation method (ICEMET) was used to observe in-cloud icing conditions. This lensless device uses a computational imaging method to reconstruct the shadow images of the microscopic objects. The size, position, and shape descriptors of each particle are measured. These data are then used to filter out the ice crystals. The droplet size distribution and the size of the measurement volume are used to determine the LWC and MVD. The performance of the instrument was tested under mixed-phase icing conditions in a wind tunnel and on a wind turbine. The measured LWC and MVD values were used to model the ice accretion on a cylinder-shaped object according to the ISO 12494:2017 icing standard. In the wind tunnel, the modeled ice mass was compared with the weighed ice mass collected by a cylinder. According to our results, ice accretion rates were overestimated by 65.6% on average without filtering out the ice crystals. Thus, the ability to distinguish between droplets and ice crystals is essential for estimating the icing rate properly.

Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China During the Meiyu Seasons

AbstractThe rain parameters derived from the laser OTT second‐generation Particle Size Velocity (Parsivel2), the two‐dimensional video disdrometer (2DVD), and DZZ5 tipping‐bucket rain gauge (RG) during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE) in summer 2018 are compared. The total rainfall amounts observed by Parsivel, 2DVD, and RG during IMFRE were 178.07, 176.76, and 182.5 mm, while their total rainy hours were 113, 113, and 90. The mean Dm (mass‐weighted mean diameter) and LWC (liquid water content) values derived from Parsivel and 2DVD were 1.03 and 1.01 mm and 0.247 and 0.223 g m−3. The rainy samples from six Parsivel sites over the middle reaches of the Yangtze River during the 2016–2018 Meiyu seasons have been collected and analyzed. The occurrence frequencies for rain rates (RR) < 5 and >10 mm hr−1 were 83.9% and 7.4%, respectively, but they contributed 30.5% and 52.1% of the total accumulated rainfall. Compared with the results over the lower reaches of the Yangtze River, the total accumulated rainfall percentages for RR < 5 mm hr−1 and RR > 10 mm hr−1 observed at XN site were higher and lower, respectively. The stratiform rain (SR) raindrop size increases with RR over both the middle and lower reaches, whereas the Nw values over the middle reaches are much higher. Opposite to the SR results, the convective rain (CR) raindrops from this study are larger, while their Nw values are similar to one another. For gamma‐type‐size distribution, the μ − λ and Z − R relations are strongly dependent on geographical location.

A rotating holographic imager for stationary cloud droplet and ice crystal measurements

An optical cloud droplet and ice crystal measurement system ICEMET (icing condition evaluation method), designed for present icing condition monitoring in field conditions, is presented. The aim in this work has been to develop a simple but precise imaging technique to measure the two often missing parameters needed in icing rate calculations caused by icing clouds—the droplet size distribution (DSD) and the liquid water content (LWC) of the air. The measurement principle of the sensor is based on lens-less digital in-line holographic imaging. Cloud droplets and ice crystals are illuminated by a short laser light pulse and the resulting hologram is digitally sampled by a digital image sensor and the digital hologram is then numerically analyzed to calculate the present DSD and LWC values. The sensor has anti-icing heating power up to 500 W and it is freely rotating by the wind for an optimal sampling direction and aerodynamics. A volume of 0.5 cm3 is sampled in each hologram and the maximum sampling rate is 3 cm3/s. Laboratory tests and simulations were made to ensure the adequate operation of the measurement sensor. Computational flow dynamics simulations showed good agreement with droplet concentration distributions measured from an icing wind tunnel. The anti-icing heating of the sensor kept the sensor operational even in severe icing conditions; the most severe test conditions were the temperature − 15 °C, wind speed 20 m/s and the LWC 0.185 g/m3. The verification measurements made using NIST traceable monodisperse particle standard glass spheres showed that the ICEMET sensor measurement median diameter 25.54 µm matched well with 25.60 µm ± 0.70 µm diameter confidence level given by the manufacturer.

Surface temperature distribution on a spherical ice particle growing by accretion in wet growth regime

AbstractExperimental evidence has demonstrated that temperature on the surface of an ice particle growing by accretion is not uniform. This non‐uniformity is relevant because the ice particle surface temperature is an important microphysical parameter that influences the sign and magnitude of the charge transfer during ice particles collisions. In particular, when high values of ambient temperature and liquid water content are reached, the ice particle surface temperature is expected to reach 0 °C, which is known as wet growth regime. Previous experimental results have shown that wet growth is not uniformly reached on the ice particle surface and a surface temperature distribution is developed. In order to know the surface temperature distribution of a fixed ice particle growing by accretion of supercooled water, numerical calculations were carried out. It was found that the surface temperature distribution has a strong dependence on liquid water content, ambient temperature, airflow velocity and water droplet size. The stagnation point always reaches higher temperatures and, in many cases, its temperature is near 0 °C. For some values of the liquid water content, ambient temperature and airflow velocity, it was possible to determine temperature differences up to 7 °C between the stagnation point and the equator. This variation in the surface temperature implies that the region near the stagnation point would experience wet growth, while the rest of the ice particle surface would remain in dry growth regime, supporting the partial wet growth hypothesis. This could also explain the charge transfer reported during ice particles collisions under wet growth conditions.

Laboratory and numerical modeling of the formation of superfog from wildland fires

Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed “superfog” and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 μm and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m−3 or greater. The model successfully predicted previous superfog events.

Vertical distribution of microphysical properties of Arctic springtime low-level mixed-phase clouds over the Greenland and Norwegian seas

Abstract. This study aims to characterize the microphysical and optical properties of ice crystals and supercooled liquid droplets within low-level Arctic mixed-phase clouds (MPCs). We compiled and analyzed cloud in situ measurements from four airborne spring campaigns (representing 18 flights and 71 vertical profiles in MPCs) over the Greenland and Norwegian seas mainly in the vicinity of the Svalbard archipelago. Cloud phase discrimination and representative vertical profiles of the number, size, mass and shape of ice crystals and liquid droplets are established. The results show that the liquid phase dominates the upper part of the MPCs. High concentrations (120 cm−3 on average) of small droplets (mean values of 15 µm), with an averaged liquid water content (LWC) of 0.2 g m−3 are measured at cloud top. The ice phase dominates the microphysical properties in the lower part of the cloud and beneath it in the precipitation region (mean values of 100 µm, 3 L−1 and 0.025 g m−3 for diameter, particle concentration and ice water content (IWC), respectively). The analysis of the ice crystal morphology shows that the majority of ice particles are irregularly shaped or rimed particles; the prevailing regular habits found are stellars and plates. We hypothesize that riming and diffusional growth processes, including the Wegener–Bergeron–Findeisen (WBF) mechanism, are the main growth mechanisms involved in the observed MPCs. The impact of larger-scale meteorological conditions on the vertical profiles of MPC properties was also investigated. Large values of LWC and high concentration of smaller droplets are possibly linked to polluted situations and air mass origins from the south, which can lead to very low values of ice crystal size and IWC. On the contrary, clean situations with low temperatures exhibit larger values of ice crystal size and IWC. Several parameterizations relevant for remote sensing or modeling studies are also determined, such as IWC (and LWC) – extinction relationship, ice and liquid integrated water paths, ice concentration and liquid water fraction according to temperature.

Understanding the condensation process of turbulent steam jet using the PDPA system

In the present study, we investigated condensation characteristics of water droplets in a turbulent steam jet with the Reynolds number from 78,400 to 140,700, such as Particle Size Distribution (PSD), Total Number Concentration (TNC), and Liquid Water Content (LWC) obtained from the Phase Doppler Particle Analyzer (PDPA) system and measured the temperature profile. The temperature decay rate and the temperature half width (rT, 0.5) were obtained for steam jets. The increased latent heat release due to condensation was found to have an effect on the decreased temperature decay rate and the increased spread rate with an increase of the steam jet's Reynolds number. Along the radial direction at z/d = 10, TNC and LWC increased up to the range within r / rT, 0.5 = 1.2, but the turbulence intensity continued to increase beyond the range. These results suggest that the evaporation effect started to occur due to the mixing with the surrounding air. Along the axial direction, we used the effective diameter in order to confirm the Reynolds number effect. As the Reynolds number became larger, particle formation started to occur further downstream along the axial direction. At the downstream of the peak position, the values of TNC and LWC were found to decrease due to the mixing process.

Drizzle formation in stratocumulus clouds: effects of turbulent mixing

Abstract. The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic and characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. It was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.

RACORO continental boundary layer cloud investigations: 2. Large‐eddy simulations of cumulus clouds and evaluation with in situ and ground‐based observations

AbstractA 60 h case study of continental boundary layer cumulus clouds is examined using two large‐eddy simulation (LES) models. The case is based on observations obtained during the RACORO Campaign (Routine Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations) at the ARM Climate Research Facility's Southern Great Plains site. The LES models are driven by continuous large‐scale and surface forcings and are constrained by multimodal and temporally varying aerosol number size distribution profiles derived from aircraft observations. We compare simulated cloud macrophysical and microphysical properties with ground‐based remote sensing and aircraft observations. The LES simulations capture the observed transitions of the evolving cumulus‐topped boundary layers during the three daytime periods and generally reproduce variations of droplet number concentration with liquid water content (LWC), corresponding to the gradient between the cloud centers and cloud edges at given heights. The observed LWC values fall within the range of simulated values; the observed droplet number concentrations are commonly higher than simulated, but differences remain on par with potential estimation errors in the aircraft measurements. Sensitivity studies examine the influences of bin microphysics versus bulk microphysics, aerosol advection, supersaturation treatment, and aerosol hygroscopicity. Simulated macrophysical cloud properties are found to be insensitive in this nonprecipitating case, but microphysical properties are especially sensitive to bulk microphysics supersaturation treatment and aerosol hygroscopicity.

Evaluation of boundary‐layer cloud forecasts over the Southern Ocean in a limited‐area numerical weather prediction system usingin situ, space‐borne and ground‐based observations

Near‐synchronized in situ, space‐borne (A‐Train) and ground‐based lidar observations are employed to evaluate the boundary‐layer clouds (BLCs) over Tasmania and the adjacent Southern Ocean (SO) simulated by the limited‐area version of Australian Community Climate and Earth System Simulator (ACCESS‐C). Two winter cases featuring BLCs associated with a post‐frontal environment and the leading side of a high‐pressure ridge are studied. Previous studies showed that these synoptic conditions contribute to the largest reflected short‐wave radiation biases simulated over the SO.Results of the simulations suggest that the ACCESS‐C model demonstrates an appreciable level of skill in simulating the macrophysical properties of the BLCs over the SO, generally consistent with the in situ and remote‐sensing observations. However, some notable challenges remain: the area cloud fraction of the marine BLCs is consistently underpredicted; the fine‐scale structure of the marine cumuli is poorly represented in the 4 km grid‐length simulations; the capping inversion over the marine boundary layer is generally too high, associated with the marine BLCs being predicted at the wrong altitude and temperature ranges; the liquid water content (LWC) of the BLCs is underestimated; and the model representation of drizzle production can be too efficient.Sensitivity studies are also conducted to test a newly developed autoconversion microphysics scheme and shear‐dominated planetary boundary‐level (PBL) scheme. These parametrizations show notable improvement in cloud prediction for CASE B (i.e. better area cloud fraction and better average and maximum values of LWC). However, none of these tests is able to improve the simulated marine PBL structure. Overall, the simulated cloud biases are jointly influenced by physical parametrizations, poor representations of large‐scale advection, surface fluxes and subsidence. More substantial observations are needed to improve our understanding of the origins and development of these biases and the relative contribution of these errors to the radiation budget over the SO.

An attempt to improve Kessler-type parameterization of warm cloud microphysical conversion processes using CloudSat observations

Improvements to the Kessler-type parameterization of warm cloud microphysical conversion processes (also called autoconversion) are proposed based on a large number of CloudSat observations between June 2006 and April 2011 over Asian land areas. The emphasis is given to the vertical distribution of liquid water content (LWC), particularly, the threshold values of LWC for autoconversion. The results warrant a new approach to the numerical parameterization of autoconversion in warm clouds. One feature of this new approach is that the autoconversion threshold, which has been treated as a constant in previous parameterization schemes, is diagnosed as a function of altitude by using a relationship between LWC and height (H) derived from CloudSat observations: $$LWC_{dig} = - 500.0\ln \left( {\frac{H} {{9492.2}}} \right)$$ . Under this framework, the threshold LWC decreases with increasing H, allowing autoconversion to occur in clouds with low LWC (approximately 0.3 g m−3) at levels above 5.5 km. Autoconversion rates calculated based on the new parameterization are compared to those calculated based on several commonly used parameterization schemes over a range of LWCs from 0.01 to 1.0 g m−3. The new scheme provides reasonable simulations of autoconversion at various vertical levels.

An integrated approach toward the incorporation of clouds in the temperature retrievals from microwave measurements

Abstract. In this paper, we address the characterization of clouds and its inclusion in microwave retrievals in order to study its effect on tropospheric temperature profiles measured by TEMPERA radiometer. TEMPERA is the first ground-based microwave radiometer that makes it possible to obtain temperature profiles in the troposphere and stratosphere at the same time. In order to characterize the clouds a multi-instrumental approach has been adopted. Cloud base altitudes were detected using ceilometer measurements while the integrated liquid water was measured by TROWARA radiometer. Both instruments are co-located with TEMPERA in Bern (Switzerland). Using this information and a constant Liquid Water Content value inside the cloud a liquid profile is provided to characterize the clouds in the inversion algorithm. Microwave temperature profiles have been obtained incorporating this water liquid profile in the inversion algorithm and also without considering the clouds, in order to assess its effect on the retrievals. The results have been compared with the temperature profiles from radiosondes which are launched twice a day at the aerological station of MeteoSwiss in Payerne (40 km W of Bern). Almost 1 year of data have been analysed and 60 non-precipitating cloud cases were studied. The statistical analysis carried out over all the cases evidenced that temperature retrievals improved in most of the cases when clouds were incorporated in the inversion algorithm.