Cloud Water Content Research Articles

An airborne study of the aerosol effect on the dispersion of cloud droplets in a drizzling marine stratocumulus cloud over eastern China

Detailed airborne measurements were carried out to explore aerosol-cloud interactions and cloud microphysical properties in a drizzling marine stratocumulus cloud deck over eastern China. Results show that the collision-coalescence of cloud droplets, the condensation of small droplets, and the collision-induced break-up of drizzle were the dominant microphysical processes in the sampled water cloud parcel. The region in the vicinity of the cloud's lateral boundary was spatially divided into sub-regions to better understand aerosol and droplet interactions. Relationships between the relative dispersion (ε) and the cloud’'s microphysical and dynamical characteristics were also examined. A negative relation was found between ε and the cloud droplet number concentration, with ε showing a close relationship with the liquid water content (LWC) and updraft velocity. When LWC was greater than ~0.75 g kg−1, the range of ε values narrowed, and updrafts dominated. By introducing ε in the cloud droplet effect radius (Re) parameterization, we find that ε can further affect indirect forcing by changing the Re distribution for the cloud examined in this study. The dispersion effect (DE) was estimated using the effective radius ratio and the specific cloud water content. An in-depth analysis indicates that DE may offset the Twomey effect by ~12%. Two different methods of estimating the indirect effect (IE) yielded close values (0.084 and 0.077), suggesting that introducing DE into the estimation had a small influence on the IE calculation in the drizzling marine stratocumulus cloud of this study. Note that the estimated IE has a large uncertainty, given the large biases in the cloud properties measured.

Improvement of inorganic aerosol component in PM2.5 by constraining aqueous-phase formation of sulfate in cloud with satellite retrievals: WRF-Chem simulations

High concentrations of PM2.5 in China have caused severe visibility degradation and health problems. However, it is still challenging to accurately predict PM2.5 and its chemical components in numerical models. In this study, we compared the inorganic aerosol components of PM2.5 (sulfate, nitrate, and ammonium (SNA)) simulated by the Weather Research and Forecasting model fully coupled with chemistry (WRF-Chem) model with in-situ data in a heavy haze-fog event during November 2018 in Nanjing, China. Comparisons show that the model underestimates sulfate concentrations by 81% and fails to reproduce the significant increase of sulfate from early morning to noon, which corresponds to the timing of fog dissipation that suggests the model underestimates the aqueous-phase formation of sulfate in clouds. In addition, the model overestimates both nitrate and ammonium concentrations by 184% and 57%, respectively. These overestimates contribute to the simulated SNA being 77.2% higher than observed. However, cloud water content is also underestimated which is a pathway for important aqueous-phase reactions. Therefore, we constrained the simulated cloud water content based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Liquid Water Path observations. Results show that the simulation with MODIS-corrected cloud water content increases the sulfate by a factor of 3, decreases the Normalized Mean Bias (NMB) by 53.5%, and reproduces its diurnal cycle with the peak concentration occurring at noon. The improved sulfate simulation also improves the simulation of nitrate, which decreases the simulated nitrate bias by 134%. Although the simulated ammonium is still higher than the observations, corrected cloud water content leads to a decrease of the modelled bias in SNA from 77.2% to 14.1%. The strong sensitivity of simulated SNA concentration to the cloud water content provides an explanation for the simulated SNA bias. Hence, uncertainties in cloud water content can contribute to model biases in simulating SNA which are less frequently explored from a process-level perspective and can be reduced by constraining the model with satellite observations.

All‐Sky Aerosol Direct Radiative Effects at the ARM SGP Site

AbstractAll‐sky aerosol direct radiative effect (DRE) was estimated for the first time at the Atmospheric Radiation Measurement Southern Great Plains site using multiyear ground‐based observations. The NASA Langley Fu‐Liou radiation model was employed. Observed inputs for the radiation model include aerosol and cloud vertical extinction profile from Raman lidar; spectral aerosol optical depth, single‐scattering albedo, and asymmetry factor from Aerosol Robotic Network; cloud water content profiles from radars; temperature and water vapor profiles from radiosondes; and surface shortwave spectral albedo from radiometers. A cloudy‐sky radiative closure experiment was performed. The relative mean differences between modeled and observed surface downwelling shortwave total fluxes were 6% (7%) for transparent (opaque) cloudy‐skies. The estimated annual mean all‐sky aerosol DRE is −2.130.54 W m−2 at the top of atmosphere (TOA) and −5.950.87 W m−2 at the surface, compared to −3.000.58 W m−2 and −6.851.00 W m−2, respectively, under clear‐sky conditions. The seasonal cycle of all‐sky aerosol DRE is similar to that of the clear‐sky, except with secondary influences of the clouds: The cloud radiative effect is strongest (most negative) in the spring, which reduces the all‐sky aerosol DRE. The relative uncertainties in all‐sky aerosol DRE due to measurement errors are generally comparable to those in clear‐sky conditions except for the aerosol single‐scattering albedo. The TOA all‐sky aerosol DRE relative uncertainty due to aerosol single‐scattering albedo uncertainty is larger than that in clear‐sky, leading to a larger total relative uncertainty. The measurement errors in cloud properties have small effects on the all‐sky aerosol DRE.

A machine learning-based method to account for 3D Short-Wave radiative effects in 1D satellite observation operators

Data assimilation of Short-Wave (SW, ≤ 4μm) satellite radiance in cloudy regions could potentially improve cloud forecasts. Operational SW observation operators neglect cloud 3D radiative effects, which may cause nonnegligible errors in some circumstances, for example, with large solar zenith angles or for broken clouds. This study introduced a machine learning (ML)-based method to include some cloud 3D radiative effects in a 1D observation operator based on liquid water cloud simulations by the Weather Research and Forecasting model and radiative transfer simulations by the Spherical Harmonics Discrete Ordinate Method. The inputs of the ML correction method include the reflectance simulated by a 1D observation operator at the targeting column, cloud top height, cloud water content, and effective particle size at its adjacent columns, and other ancillary information (sun-viewing geometries, water vapor conditions, etc.). Preliminary results were presented for the channel 3 (0.75 ∼ 0.90µm) of the Advanced Geostationary Radiation Imager (AGRI) onboard FY-4A. Compared with 1D simulations, the ML correction method could reduce the biases from 6.9% ∼ 11.7% to 2.0% ∼ 4.7% and the root mean square errors from 22.3% ∼ 34.8% to 15.4% ∼ 27.4%. The elapsed CPU time for the ML correction method is approximately the same or two times that of the 1D observation operators, depending on whether atmospheric gases are included or not. In general, the ML correction method is computationally more efficient than traditional 3D radiative transfer solver, and could be used to correct current 1D observation operators’ simulations.

Quality Assessment of Acquired GEDI Waveforms: Case Study over France, Tunisia and French Guiana

The Global Ecosystem Dynamics Investigation (GEDI) full-waveform (FW) LiDAR instrument on board the International Space Station (ISS) has acquired in its first 18 months of operation more than 25 billion shots globally, presenting a unique opportunity for the analysis of LiDAR data across multiple domains (e.g., forestry, hydrology). Nonetheless, not all acquired GEDI shots provide exploitable waveforms due to instrumental (e.g., transmitted energy, viewing angle) and atmospheric conditions (e.g., clouds, aerosols). In this study, we analyzed the quality of all available GEDI acquisitions over France, Tunisia, and French Guiana, in order to determine the extent of the impact of instrumental and climatic factors on the viability of these acquisitions. Results showed that with favorable acquisition conditions (i.e., cloud-free acquisitions), the factor with the highest impact on the viability of GEDI data is the acquisition time, as acquisitions around noon were the least viable due to higher solar noise. In addition to acquisition time, the viewing angle, the transmitted energy, and the aerosol optical depth all affected, to a lesser extent, the viability of GEDI data. Nonetheless, the percentage of exploitable cloud-free GEDI acquisitions ranged from 75 to 91% of all total acquisitions, depending on the acquisition site. The analysis of the quality of GEDI shots acquired in the presence of clouds showed that clouds have a greater impact on their exploitability, with sometimes as much as 69% of acquired data being unusable. For cloudy acquisitions, the two factors that mostly affect the LiDAR signal are the cloud optical depth (or cloud opacity) and cloud water content. Overall, nonviable GEDI data represent less than 50% of total acquisitions across the different instrumental, climatic, and environmental conditions.

Catalytic manufacture and characteristic valuation of biodiesel-biojet achieved from Jatropha curcas and waste cooking oils over chemically modified montmorillonite clay

Montmorillonite clay was chemically modified by grafting of 3-mercaptopropyl trimethoxy silane on the clay surface, followed by sulfonation of the terminal thiol groups. The chemical structures and surface characteristics of the prepared catalysts were characterized by FTIR, XRD, TPD, and BET analysis. The catalytic pyrolysis of Jatropha curcas oil and waste cooking oil for the production of biofuels was stimulated using the prepared catalyst. The conversion of oils into biofuels was performed at 350 °C using different catalysts amounts (0.2–1%). The obtained biofuels were characterized using density, flash, pour, and cloud points, water, sulfur, and ash contents, in addition to kinematic viscosity, copper strip, and carbon residue. Furthermore, the obtained biofuels were fractionated at 250 °C to obtain the light hydrocarbon components, which were evaluated as biojet fuel. The physical and fuel properties of biodiesel-petroleum diesel blends (B10), and biojet-JET A-1 blends were following the ASTM and IP specifications. The most suitable catalyst ratio during the catalytic cracking process was monitored at 0.8%.

Dependence of Warm Season Cloud-to-Ground Lightning Polarity on Environmental Conditions over Sichuan, Southwest China

The effects of thermodynamic and moisture factors on cloud-to-ground (CG) lightning polarity in the warm season were discussed. Small convective available potential energy (CAPE) represents relatively shallow convection, which is beneficial to the generation of positive lightning. Large vertical wind shear results in the displacement of upper-level positive ice crystals and promotes the initiation of +CG lightning from positive ice crystals. The dry low- to midlevel troposphere and the high cloud base in the plateau region favor +CG lightning, while the strong thermodynamic conditions in the basin region offset the influence of these moisture factors. In the plateau region, due to the limited cloud thickness, high total column liquid water may mean high cloud water content in the warm cloud region rather than high liquid water content in the mixed-phase region, which is unfavorable for the middle-level positive graupel and thus is unfavorable for the initiation of +CG lightning. In the basin region, the cloud thickness is relatively thicker, the high total column liquid water means that the liquid water content in the warm cloud and the mixed-phase region is both high, which is conducive to the middle-level positive graupel and the +CG lightning.

Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations

Abstract. Understanding the coupling of clouds to large-scale circulation is one of the grand challenges for the global climate research community. In this context, realistically modelling the vertical structure of cloud radiative heating (CRH) and/or cooling in Earth system models is a key premise to understand this coupling. Here, we evaluate CRH in two versions of the European Community Earth System Model (EC-Earth) using retrievals derived from the combined radar and lidar data from the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. One model version is also used with two different horizontal resolutions. Our study evaluates large-scale intraseasonal variability in the vertical structure of CRH and cloud properties and investigates the changes in CRH during different phases of the El Niño–Southern Oscillation (ENSO), a process that dominates the interannual climate variability in the tropics. EC-Earth generally captures both the intraseasonal and meridional pattern of variability in CRH over the convectively active and stratocumulus regions and the CRH during the positive and negative phases of ENSO. However, two key differences between model simulations and satellite retrievals emerge. First, the magnitude of CRH, in the upper troposphere, over the convectively active zones is up to twice as large in the models compared to the satellite data. Further dissection of net CRH into its shortwave and longwave components reveals noticeable differences in their vertical structure. The shortwave component of the radiative heating is overestimated by all model versions in the lowermost troposphere and underestimated in the middle troposphere. These over- and underestimates of shortwave heating are partly compensated by an overestimate of longwave cooling in the lowermost troposphere and heating in the middle troposphere. The biases in CRH can be traced back to disagreement in cloud amount and cloud water content. There is no noticeable improvement of CRH by increasing the horizontal resolution in the model alone. Our findings highlight the importance of evaluating models with satellite observations that resolve the vertical structure of clouds and cloud properties.

Sensitivity of snowfall forecast over North China to ice crystal deposition/sublimation parameterizations in the WSM6 cloud microphysics scheme

AbstractIce‐phase cloud microphysical processes are very complicated, and there are still many uncertainties in current microphysics parameterization schemes. In this study, two alternative ice crystal deposition/sublimation (ICDS) parameterizations, following the Harrington et al., Journal of the Atmospheric Sciences, 1995, 52, 4344–4366 and Koenig, Monthly Weather Review, 1972, 100, 417–423 methods, were implemented into the Weather Research and Forecast (WRF) Single‐Moment 6‐class Microphysics (WSM6) scheme in the Global/Regional Assimilation and Prediction System (GRAPES) regional operational model to investigate their impact on overestimation of snowfall over North China. The results show that the snowfall amount and cloud particle composition are very sensitive to the ICDS parameterization. Sensitivity tests with WSM6 using the Harrington and Koenig ICDSs, referred to as WSM6_H and WSM6_K, respectively, notably reduced overestimation of the snowfall amount and simulated more realistic supercooled cloud water content compared with ERA5 reanalysis data. The vertical distributions, intensities, and duration of radar echoes simulated by WSM6_H are the most consistent with millimeter‐wavelength cloud radar observations. There is competition for water vapor in WSM6 due to the sequential order in which processes are updated. This tends to weaken the deposition of snow and graupel and the condensation of cloud water when the deposition of ice crystals is too strong in a cold region. In both WSM6_H and WSM6_K, the deposition processes of ice crystals are reduced and the other microphysical transformation processes become more active compared with WSM6. Overall, the WSM6_H configuration improves the forecast performance as evaluated by Taylor diagrams for eight snowfall days over North China. The ICDS parameterizations must therefore be handled carefully due to their large uncertainties in the development of the cloud microphysics schemes.

Volcanic Aerosol Impacts on Hawai‘i Island Rainfall

AbstractIn recent decades, a significant rainfall decline over the island of Hawai‘i has been noted, with many hypothesizing that the drying is associated with the volcanic aerosols emitted from the Kīlauea volcano. While it is clear that volcanic emissions can create hazardous air quality for Hawaiian communities, the impacts on rainfall are less clear. Here we investigate the impact of volcanic aerosol emissions on Hawai‘i Island rainfall. Based on observed daily rainfall and SO2 emissions, it is found that days with high SO2 emissions have on average 8 mm day−1 less rainfall downstream of the Kīlauea volcano. Sensitivity studies with varying volcanic aerosol emission sources from the Kīlauea vent locations have also been conducted by the Weather Research and Forecasting (WRF) Model in order to examine the detailed physical processes. Consistent with SO2 air quality observations, it is found that the diurnal change in aerosol number concentration is strongly dependent on the diurnal variation of local circulations. The added aerosols are lofted into the orographic convection where they modify the microphysical properties of the warm clouds by increasing the cloud droplet number concentration, decreasing the cloud droplet size, increasing cloud water content, and enhancing cloud evaporation. The volcanic aerosols also delay precipitation production and modify the spatial distribution of rainfall on the downstream mountainside. The modification of precipitation on an island has far-reaching consequences. For this reason, we work to quantify the sensitivity of the orographic precipitation to volcanic aerosols and move beyond hypothesized relationships to work toward understanding the underlying problem.

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.

Vertical profile of atmospheric single scattering properties and assessment of the effects of temporal variability of cloud water content over Yaounde

This study discusses a method for deriving the vertical profiles of absorption and scattering coefficients in integrated atmospheric column for radiative models. It then presents these profiles in the case of cloudy layers using details of the distributions of cloud water content and the vertical description of other radiatively active atmospheric species in the shortwave spectrum for Yaounde (11°51′ E, 3°86′ N). It was shown that both quantities globally exhibit spatial and temporal variabilities and therefore should be used with caution in radiative transfer calculations. The proposed method duly incorporates these variabilities using existing knowledge on atmospheric optics and radiative constituents (gas, clouds and aerosols) for appropriate representation of the actual state of the atmosphere. The case study combines data of cloud water content and effective radius as described by Akana and Njomo (2010b) as well as HITRAM vertical profile for gas (Rothman et al., 2010) and aerosols vertical properties as proposed by Kneizys et al. (1996). From the present analysis, it was observed that the highest values obtained near the surface were followed by a decrease in altitude. The minima are obtained slightly above the mixed-phase cloud layer. The scattering coefficient close to the surface is globally smaller than the absorption coefficient but this tendency is reversed at mid-altitude in the mixed-phase cloud layer generally between 500 and 600 mbar. The single scattering albedo (SSA) deduced from these column-integrated profiles show very small values near the surface and gradual increase towards high altitudes with the smallest value (less than 0.15) found during rainy season. This increase is rapid in mixed-phase cloud where it reaches 0.79 at the upper limits. Assessing the impact of gases and aerosol on these profiles, it was observed that SSA increase by 153% in gas-free atmosphere while a drop of 3% was noticed in aerosol-free atmosphere close to the surface.

Simulation of Aerosol Indirect Effects on Cloud Streets Over the Northwestern Pacific Ocean

AbstractWe simulated aerosol effects on cloud streets formed during continental cold‐air outbreaks over the Northwestern Pacific using an aerosol‐sensitive cloud microphysical scheme coupled with the Weather Research and Forecast model. The micro‐ and macro‐scale responses were examined under a wide range of aerosol concentrations. The cloud streets generally remain in a transient state, indicating that the aerosol particles may significantly affect the cloud system's development. The simulation results revealed a clear Twomey effect, but they were contrary to some of the Albrecht effect, especially under relatively clean conditions. Such reversed Albrecht effects stem mainly from dynamic response to changes in atmospheric stability associated with drizzle evaporation in the sub‐cloud layer. The dynamic response works against thermal forcing from the large air‐sea temperature gradient in a cold‐air outbreak. As the aerosol increases, the drizzle mechanisms weaken, and the boundary layer becomes more convective, leading to stronger dry‐air entrainment from the free troposphere. In individual clouds, the effect of entrainment on cloud water content may be compensated by more substantial vertical vapor flux. These mechanisms lead to a reduction in the cloud amount. Furthermore, the reduced moisture flux from drizzle evaporation in the sub‐cloud layer, as well as the reduced sedimentation speed of the smaller cloud drops, tend to lessen cloud thickness. The overall reduction in cloud dimensions may offset the Twomey effect by up to 20% in cloud albedo.

Constraining Ice Water Content of Thin Antarctic Cirrus Clouds Using Ground-Based Lidar and Satellite Data

AbstractWe combine observations of optically thin cirrus clouds made by lidar at Davis, Antarctica (69°S, 78°E), during 14–15 June 2011 with a microphysical retrieval algorithm to constrain the ice water content (IWC) of these clouds. The cirrus clouds were embedded in a tropopause jet that flowed around a ridge of high pressure extending southward over Davis from the Southern Ocean. Cloud optical depths were 0.082 ± 0.001, and subvisual cirrus were present during 11% of the observation period. The macrophysical cirrus cloud properties obtained during this case study are consistent with those previously reported at lower latitudes. MODIS satellite imagery and AIRS surface temperature data are used as inputs into a radiative transfer model in order to constrain the IWC and ice water path of the cirrus. The derived cloud IWC is consistent with in situ observations made at other locations but at similarly cold temperatures. The optical depths derived from the model agree with those calculated directly from the lidar data. This study demonstrates the value of a combination of ground-based lidar observations and a radiative transfer model in constraining microphysical cloud parameters that could be utilized at locations where other lidar measurements are made.

Improving the Retrieval of Cloudy Atmospheric Profiles from Brightness Temperatures Observed with a Ground-Based Microwave Radiometer

Atmospheric temperature and humidity retrievals from ground-based microwave remote sensing are useful in a variety of meteorological and environmental applications. Though the influence of clouds is usually considered in current retrieval algorithms, the resulting temperature and humidity estimates are still biased high in overcast conditions compared to radiosonde observations. Therefore, there is a need to improve the quality of retrievals in cloudy conditions. This paper presents an approach to make brightness temperature (TB) correction for cloud influence before the data can be used in the inversion of vertical profiles of atmospheric temperature and humidity. A three-channel method is proposed to make cloud parameter estimation, i.e., of the total 22 channels of the ground-based radiometer, three are adopted to set up a relationship between cloud parameters and brightness temperatures, so that the observations from the three channels can be used to estimate cloud thickness and water content and complete the cloud correction for the rest of the channels used in the retrieval. Based on two years of data from the atmosphere in Beijing, a comparison of the retrievals with radiosonde observations (RAOB) shows: (1) the temperature retrievals from this study have a higher correlation with RAOB and are notably better than in the vendor-provided LV2. The bias of the temperature retrievals from this study is close to zero at all heights, and the RMSE is greatly reduced from >5 °C to <2 °C in the layer, from about 1.5 km up to 5 km. The temperature retrievals from this study have higher correlation with RAOB data compared to the vendor-provided LV2, especially at and above a 2 km height. (2) The bias of the water vapor density profile from this study is near to zero, while the LV2 has a positive bias as large as 4 g/m3. The RMSE of the water vapor density profile from this study is <2 g/m3, while the RMSE for LV2 is as large as 10 g/m3. That is, both the bias and RMSE from this study are evidently less than the LV2, with a greater improvement in the lower troposphere below 5 km. Correlation with RAOB is improved even more for the water vapor density. The correlation of the retrievals from this study increases to one within the boundary layer, but the correlation of LV2 with RAOB is only 0.8 at 0.5 km height, 0.7 at 1 km, and even less than 0.5 at 2 km. (3) A parameter named the Cloud Impact index, determined by cloud water concentration and cloud thickness, together with the cloud base height, has been defined to show that both BIAS and RMSE of “high-CI subsample” are larger than those of the “low-CI subsample”, indicating that high-CI cloud has a higher impact on the retrievals and the correction for cloud influence is more necessary.

Chemical Characteristics of Cloud Water and Sulfate Production Under Excess Hydrogen Peroxide in a High Mountainous Region of Central Japan

Over the last two decades, atmospheric sulfur dioxide (SO2) concentrations have decreased in air-polluted regions. However, this decrease was accompanied by a rise in cloud water acidity (pH), which remains below 5. With this change, gas-phase hydrogen peroxide (H2O2) exceeded SO2 in most of these regions. These conditions where SO2 10) in our observation site, which was due to power plant restrictions in Japan since the 1970s. The ion species concentrations in cloud water indicated that cloud acidification resulted from dissolution of gaseous HNO3 and SO2, whereas gaseous hydrochloric acid and organic acid had a minor contribution to the acidification. Significant losses of Cl− and Mg2+ were observed in some of the cloud water. The excess value of non-sea-salt sulfate (nss-SO42−) over NH4+ in cloud water implies the in-cloud oxidation of gaseous SO2 to aqueous SO42−. A Se tracer technique was used to conduct in-situ measurements of in-cloud SO42− production. The results showed that the in-cloud production varied in a range between 7 ± 2 and 41 ± 14%. This temporal variation might be due to ambient SO2 concentrations based on Henry’s law.

Aircraft Observations of Characteristics and Growth of Ice Particles of Two Different Snowfall Clouds in Shanxi Province, China

The ice crystal habits, distributions and growth processes in two snowfall cloud cases on 29 November 2009 and 3 March 2012 in northern China were compared and analyzed with aircraft data. The results showed that ice crystal habits were affected by the height of ice clouds. Ice crystals in clouds with cloud top temperatures of −12.6 °C were predominantly needle, plate, dendrite and irregular. When the cloud top temperature was lower than −19.5 °C, plates, dendrites and irregular ice crystals were observed in addition to needles, capped-column crystals were observed in the lower and middle layers of clouds, and column crystals were observed in the upper layer of clouds. The liquid water content of the two snowfall processes was lower than 0.1 g·m−3. Ice particles grew mainly via deposition, riming and aggregation processes. On 29 November, the liquid water content of the stratospheric mixed snowfall cloud was distributed in the lower part of the cloud. The maximum values of particle concentration and ice water content detected by a cloud imaging probe were 187 L−1 and 1.05 g·m−3, which were at −8.7 °C, and the ice water content was higher. On 3 March, the liquid water content of snowfall in stratiform clouds was located in the middle layer, and the maximum ice water was low, which was only 0.052 g m−3. The ice water value on 29 November was higher, which was mainly due to the convective zone embedded in the cumulus mixed cloud containing a large number of riming and aggregated snow crystals. Using an exponential function to fit the crystal spectrum of the two snowfall processes, N0 and λ were 109−1011 m−4 and 108−1010 m−4 and 103−104 m−1 and 104 m−1, respectively. Compared with 3 March, N0 on 29 November was larger and the variation range of λ was one more order of magnitude. N0 and λ conformed to a power function distribution. By analyzing the scatter plot of the correlation coefficient and slope, it was found that the exponential function can accurately express the crystal spectrum of snow clouds.

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

AbstractA wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: 1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? 2) What is the sensitivity to the cloud fraction parameterization complexity? 3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a 6-week observation campaign in the U.S. southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals, and surface observations. It is shown that not using a cloud fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud-base height, optical thickness, and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

A Bimodal Diagnostic Cloud Fraction Parameterization. Part I: Motivating Analysis and Scheme Description

AbstractCloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional midlatitude forecasts, the Met Office uses a diagnostic cloud fraction scheme that relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. For model grid boxes located in this entrainment zone, collocated moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given gridbox mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the southern Great Plains in the United States, it is shown that the new scheme improves the relation between cloud fraction, relative humidity, and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in Part II.