Cloud Liquid Water Path Research Articles

Analysis of the Meteorological Conditions and Atmospheric Numerical Simulation of an Aircraft Icing Accident

With the rapid development of the general aviation industry in China, the influence of high-impact aeronautical weather events, such as aircraft icing, on flight safety has become more and more prominent. On 1 March 2021, an aircraft conducting weather modification operations crashed over Ji’an City, due to severe icing. Using multi-source meteorological observations and atmospheric numerical simulations, we analyzed the meteorological causes of this icing accident. The results indicate that a cold front formed in northwestern China and then moved southward, which is the main weather system in the icing area. Based on the icing index, we conducted an analysis of the temperature, relative humidity, cloud liquid water path, effective particle radius, and vertical flow field, it was found that aircraft icing occurred behind the ground front, where warm-moist airflows rose along the front to result in a rapid increase of water vapor in 600–500 hPa. The increase of water vapor, in conjunction with low temperature, led to the formation of a cold stratiform cloud system. In this cloud system, there were a large number of large cloud droplets. In addition, the frontal inversion increased the atmospheric stability, allowing cloud droplets to accumulate in the low-temperature region and forming meteorological conditions conducive to icing. The Weather Research and Forecasting model was employed to provide a detailed description of the formation process of the atmospheric conditions conducive to icing, such as the uplifting motion along the front and supercooled water. Based on a real case, we investigated the formation process of icing-inducing meteorological conditions under the influence of a front in detail in this study and verified the capability of a numerical model to simulate the meteorological environment of frontal icing, in order to provide a valuable reference for meteorological early warnings and forecasts for general aviation.

Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli

Abstract. Marine low-level clouds are key to the Earth's energy budget due to their expansive coverage over global oceans and their high reflectance of incoming solar radiation. Their responses to anthropogenic aerosol perturbations remain the largest source of uncertainty in estimating the anthropogenic radiative forcing of climate. A major challenge is the quantification of the cloud water response to aerosol perturbations. In particular, the presence of feedbacks through microphysical, dynamical, and thermodynamical pathways at various spatial and temporal scales could augment or weaken the response. Central to this problem is the temporal evolution in cloud adjustment, governed by entangled feedback mechanisms. We apply an innovative conditional Monte Carlo subsampling approach to a large ensemble of diurnal large-eddy simulation of non-precipitating marine stratocumulus to study the role of solar heating in governing the evolution in the relationship between droplet number and cloud water. We find a persistent negative trend in this relationship at night, confirming that the role of microphysically enhanced cloud-top entrainment. After sunrise, the evolution in this relationship appears buffered and converges to ∼-0.2 in the late afternoon. This buffering effect is attributed to a strong dependence of cloud-layer shortwave absorption on cloud liquid water path. These diurnal cycle characteristics further demonstrate a tight connection between cloud brightening potential and the relationship between cloud water and droplet number at sunrise, which has implications for the impact of the timing of advertent aerosol perturbations.

How Cloud Droplet Number Concentration Impacts Liquid Water Path and Precipitation in Marine Stratocumulus Clouds—A Satellite-Based Analysis Using Explainable Machine Learning

Aerosol–cloud–precipitation interactions (ACI) are a known major cause of uncertainties in simulations of the future climate. An improved understanding of the in-cloud processes accompanying ACI could help in advancing their implementation in global climate models. This is especially the case for marine stratocumulus clouds, which constitute the most common cloud type globally. In this work, a dataset composed of satellite observations and reanalysis data is used in explainable machine learning models to analyze the relationship between the cloud droplet number concentration (Nd), cloud liquid water path (LWP), and the fraction of precipitating clouds (PF) in five distinct marine stratocumulus regions. This framework makes use of Shapley additive explanation (SHAP) values, allowing to isolate the impact of Nd from other confounding factors, which proved to be very difficult in previous satellite-based studies. All regions display a decrease of PF and an increase in LWP with increasing Nd, despite marked inter-regional differences in the distribution of Nd. Polluted (high Nd) conditions are characterized by an increase of 12 gm−2 in LWP and a decrease of 0.13 in PF on average when compared to pristine (low Nd) conditions. The negative Nd–PF relationship is stronger in high LWP conditions, while the positive Nd–LWP relationship is amplified in precipitating clouds. These findings indicate that precipitation suppression plays an important role in MSC adjusting to aerosol-driven perturbations in Nd.

Opposite effects of aerosols and meteorological parameters on warm clouds in two contrasting regions over eastern China

Abstract. The sensitivity (S) of cloud parameters to the influence of different aerosol and meteorological parameters has in most previous aerosol–cloud interaction (aci) studies been addressed using traditional statistical methods. In the current study, relationships between cloud droplet effective radius (CER) and aerosol optical depth (AOD, used as a proxy for cloud condensation nuclei, CCN), i.e., the sensitivity (S) of CER to AOD, are investigated with different constraints of AOD and cloud liquid water path (LWP). In addition to traditional statistical methods, the geographical detector method (GDM) is applied in this study to quantify the relative importance of the effects of aerosol and meteorological parameters, as well as their interaction, on S. Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3 data and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-5 reanalysis data, for the period from 2008 to 2022, were used to investigate aci over eastern China. Two contrasting areas were selected: the heavily polluted Yangtze River Delta (YRD) and a relatively clean area over the East China Sea (ECS). Linear regression analysis shows that CER decreases with the increase in AOD (negative S) in the moderately polluted atmosphere (0.1<AOD<0.3) over the ECS, whereas, in contrast, CER increases with increasing AOD (positive S) in the polluted atmosphere (AOD>0.3) over the YRD. Evaluation of S as function of the LWP shows that in the moderately polluted atmosphere over the ECS, S is negative in the LWP interval [40 g m−2, 200 g m−2], and the sensitivity of CER to AOD is substantially stronger as LWP is larger. In contrast, in the polluted atmosphere over the YRD, S is positive in the LWP interval [0 g m−2, 120 g m−2] and does not change notably as function of LWP in this interval. The study further shows that over the ECS, the CER is larger for higher low tropospheric stability (LTS) and relative humidity (RH) but lower for higher pressure vertical velocity (PVV). Over the YRD, there is no significant influence of LTS on the relationship between CER and AOD. The GDM has been used as an independent method to analyze the sensitivity of cloud parameters to AOD and meteorological parameters (RH, LTS and PVV). The GDM has also been used to analyze the effects of interactions between two parameters and thus obtain information on confounding meteorological effects on the aci. Over the ECS, cloud parameters are sensitive to almost all parameters considered except for cloud top pressure (CTP), and the sensitivity to AOD is larger than that to any of the meteorological factors. Among the meteorological factors, the cloud parameters are most sensitive to PVV and least sensitive to RH. Over the YRD, the explanatory power of the sensitivity of cloud parameters to AOD and meteorological parameters is much smaller than over the ECS, except for RH, which has a statistically significant influence on CTP and can explain 74 % of the variation of CTP. The results from the GDM analysis show that cloud parameters are more sensitive to the combination of aerosol and a meteorological parameter than to each parameter alone, but confounding effects due to co-variation of both parameters cannot be excluded.

Relationship between aerosol and cloud characteristics over Delhi in North India during the dry and wet season

The study investigates the spatio-temporal variations of aerosol and cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite at an urban megacity Delhi in the northern part of India during the dry and wet season for 15 years period from November 2004 to October 2019. This research comprises the study of crucial aerosol optical properties such as aerosol optical depth (AOD), Angstrom exponent (AE) along with the cloud properties such as water vapor (WV), cloud liquid water path (CLWP), cloud effective radius liquid (CERL), cloud fraction (CF), cloud optical depth (COD), cloud top pressure (CTP), and cloud top temperature (CTT). High AOD was observed across the Indo-Gangetic Plain (IGP), including Delhi and exhibited a range of 0.49–0.89 during the dry season and 0.73 to 0.98 during the wet season with a mean value of 0.73 ± 0.05 during the entire study period. High AE value (mean 1.40 ± 0.05) indicates dominance of fine-mode aerosols over the station, associated with high anthropogenic activities. A significantly large increasing trend in AOD was observed over the station during the wet season as compared to the dry season. The seasonal studies represent the maximum value of WV and CTP in the wet season. In addition, CF, CERL, COD and CLWP values were also high during the wet season. Furthermore, a correlation analyses between the aerosol and cloud parameters were carried out during both the seasons. From the analysis, AOD shows a positive correlation with WV, CF, COD and CLWP in both the seasons whereas a negative correlation was observed with CTP in wet season, while positive in dry season. On the other hand, a poor correlation was observed between AOD verses AE and CTT in both the seasons. These findings can contribute to advancing our understanding of aerosol-cloud interactions and inflate air quality assessments at an urban megacity like Delhi.

Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic

Abstract. Warm boundary layer clouds in the eastern North Atlantic region exhibit significant diurnal variations in cloud properties. However, the diurnal cycle of the aerosol indirect effect (AIE) for these clouds remains poorly understood. This study takes advantage of recent advancements in the spatial resolution of geostationary satellites to explore the daytime variation in the AIE by estimating the cloud susceptibilities to changes in cloud droplet number concentration (Nd). Cloud retrievals for the month of July over 4 years (2018–2021) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat-11 over this region are analyzed. Our results reveal a significant “U-shaped” daytime cycle in susceptibilities of the cloud liquid water path (LWP), cloud albedo, and cloud fraction. Clouds are found to be more susceptible to Nd perturbations at noon and less susceptible in the morning and evening. The magnitude and sign of cloud susceptibilities depend heavily on the cloud state defined by cloud LWP and precipitation conditions. Non-precipitating thin clouds account for 44 % of all warm boundary layer clouds in July, and they contribute the most to the observed daytime variation. Non-precipitating thick clouds are the least frequent cloud state (10 %), and they exhibit more negative LWP and albedo susceptibilities compared to thin clouds. Precipitating clouds are the dominant cloud state (46 %), but their cloud susceptibilities show minimal variation throughout the day. We find evidence that the daytime variation in LWP and albedo susceptibilities for non-precipitating clouds is influenced by a combination of the diurnal transition between non-precipitating thick and thin clouds and the “lagged” cloud responses to Nd perturbations. The daytime variation in cloud fraction susceptibility for non-precipitating thick clouds can be attributed to the daytime variation in cloud morphology (e.g., overcast or broken). The dissipation and development of clouds do not adequately explain the observed variation in cloud susceptibilities. Additionally, daytime variation in cloud susceptibility is primarily driven by variation in the intensity of cloud response rather than the frequency of occurrence of cloud states. Our results imply that polar-orbiting satellites with an overpass time at 13:30 LT underestimate daytime mean values of cloud susceptibility, as they observe susceptibility daily minima in the study region.

Evaluation of Stratocumulus Evolution Under Contrasting Temperature Advections in CESM2 Through a Lagrangian Framework

AbstractThis study leveraged a Lagrangian framework to examine the evolution of stratocumulus clouds under cold and warm advections (CADV and WADV) in the Community Earth System Model 2 (CESM2) against observations. We found that CESM2 simulates a too rapid decline in low‐cloud fraction (LCF) and cloud liquid water path (CLWP) under CADV conditions, while it better aligns closely with observed LCF under WADV conditions but overestimates the increase in CLWP. Employing an explainable machine learning approach, we found that too rapid decreases in LCF and CLWP under CADV conditions are related to overestimated drying effects induced by sea surface temperature, whereas the substantial increase in CLWP under WADV conditions is associated with the overestimated moistening effects due to free‐tropospheric moisture and surface winds. Our findings suggest that overestimated drying effects of sea surface temperature on cloud properties might be one of crucial causes for the high equilibrium climate sensitivity in CESM2.

Diurnal Patterns in the Observed Cloud Liquid Water Path Response to Droplet Number Perturbations

AbstractA key uncertainty in Aerosol‐cloud interactions is the cloud liquid water path (LWP) response to increased aerosols (λ). LWP can either increase due to precipitation suppression or decrease due to entrainment‐drying. Previous research suggests that precipitation suppression dominates in thick clouds, while entrainment‐drying prevails in thin clouds. The time scales of the two competing effects are vastly different, requiring temporally resolved observations. We analyze 3‐day Lagrangian trajectories of stratocumulus clouds over the southeast Pacific using 2019–2021 geostationary data. We find that clouds with a LWP exceeding 200 g m−2 exhibit a positive response, while clouds with lower LWP show a negative response. We observe a significant diurnal cycle in λ, indicating a more strongly negative daytime adjustment driven by entrainment‐drying. In contrast, at night, precipitation suppression can occasionally fully counteract the entrainment‐drying mechanism. Overall, λ appears weaker than previously suggested in studies that do not account for the diurnal cycle.

Impact of HY‐2B SMR radiance assimilation on CMA global medium‐range weather forecasts

AbstractThe Chinese second ocean dynamic environment satellite Haiyang‐2B (HY‐2B) was successfully launched on October 25, 2018, carrying a scanning microwave radiometer (SMR) to provide information about the ocean and atmosphere. For the first time, this study investigated the impact of radiance data from the HY‐2B SMR in the four‐dimensional variational (4DVar) data assimilation system of the Global Forecast System developed by the China Meteorology Administration (CMA‐GFS). Prior to the radiance assimilation, we evaluated the data quality and developed suitable quality control (QC) procedures for the HY‐2B SMR observations. In addition, the cloud liquid water path (CLWP) and ocean wind speed (OWS) were introduced as new bias correction (BC) predictors to remove the systematic bias originating from the forward operator in the CMA‐GFS 4DVar system. The assimilation effects of SMR observations were evaluated through one‐month cycling experiments. Verification with independent observations and reanalysis data has demonstrated that assimilating SMR clear‐sky radiance can greatly reduce the analysis errors for temperature and humidity, while indirectly improving the quality of wind analysis. Furthermore, significant improvements in geopotential height forecasts were found for days 1–5 in the lower troposphere of the tropical region.

A Novel Method for Diagnosing Land–Atmosphere Coupling Sensitivity in a Single-Column Model

Abstract The response of boundary layer properties and cloudiness to changes in surface evaporative fraction (EF) is investigated in a single-column model to quantify the locally coupled impact of subgrid surface variations on the atmosphere during summer. Sensitive coupling days are defined when the model atmosphere exhibits large variations across a range of EFs centered on the analyzed value. Coupling sensitivity exists as both positive feedback (cloudiness increases with EF) and negative feedback (clouds increase with decreasing EF) regimes. The positive regime manifests in shallow convection situations, which are capped by a strengthened inversion and subsidence, restricting the vertical extent of convection to just above the boundary layer. Surfaces with larger EF (greater surface latent heat flux) can inject more moisture into the vertically confined system, lowering the cloud base and an increasing cloud liquid water path (LWP). Negative feedback regimes tend to manifest when large-scale deep convection, such as from mesoscale convective systems and fronts, is advected through the domain, where convection strengthens over surfaces with a lower EF (greater surface sensible heat flux). The invigoration of these systems by the land surface leads to an increase in LWP through strengthened updrafts and stronger coupling between the boundary layer and the free atmosphere. These results apply in the absence of heterogeneity-induced mesoscale circulations, providing a one-dimensional dynamical perspective on the effect of surface heterogeneity. This study provides a framework of intermediate complexity, lying between parcel theory and high-resolution coupled land–atmosphere modeling, and therefore isolates the relevant first-order processes in land–atmosphere interactions. Significance Statement Cloud formation, distribution, and other properties may be sensitive to heterogeneous surfaces depending on the strength and location of such heterogeneities and the background atmospheric state. This may drive differences in the cloud population depending on which part of the domain one is located. This may also lead to mesoscale circulations, which may strengthen or weaken this effect. Currently, climate models act on scales (∼100 km) that are too large to explicitly represent these processes, which are strongest at smaller scales (around 5–40 km). Therefore, subgrid-scale heterogeneity is neglected, and any predictability and model fidelity it may provide is lost. We use a simple model to diagnose sensitivity of the local atmosphere to surface variations meant to represent possible subgrid heterogeneity, providing a first-order estimate of its effect. We conclude that preferentially sensitive atmospheric states exist that lead to positive and/or negative feedback between land and atmosphere. This information is valuable to future climate model parameterizations aimed at improving the representation of these feedbacks.

Retrieval of Cloud Liquid Water Path from MSU-GS Data Onboard Arktika-M 1

Retrieval of Cloud Liquid Water Path from MSU-GS Data Onboard Arktika-M 1

Specific Features of the Land-Sea Contrast of Cloud Liquid Water Path in Northern Europe as Obtained from the Observations by the SEVIRI Instrument: Artefacts or Reality?

Liquid water path (LWP) is one of the most important cloud parameters and is crucial for global and regional climate modelling, weather forecasting, and modelling of the hydrological cycle and interactions between different components of the climate system: the atmosphere, the hydrosphere, and the land surface. Space-borne observations by the SEVIRI instrument have already provided evidence of the systematic difference between the cloud LWP values derived over the land surface in Northern Europe and those derived over the Baltic Sea and major lakes during both cold and warm seasons. In the present study, the analysis of this LWP land-sea contrast for the period 2011–2017 reveals specific temporal and spatial variations, which, in some cases, seem to be artefacts rather than of natural origin. The geographical objects of investigation are water bodies and water areas located in Northern Europe that differ in size and other geophysical characteristics: the Gulf of Finland and the Gulf of Riga in the Baltic Sea and large and small lakes in the neighbouring region. The analysis of intra-seasonal features has detected anomalous conditions in the Gulf of Riga and the Gulf of Finland, which show up as very low values of the LWP land-sea contrast in August with respect to the values in June and July every year within the considered time period. This anomaly is likely an artefact caused by the LWP retrieval algorithm since the transition from large LWP contrast to very low contrast occurs sharply, synchronically, and at a certain date every year at different places in the Baltic Sea.

Observational evidence of strong forcing from aerosol effect on low cloud coverage.

Aerosols cool Earth's climate indirectly by increasing low cloud brightness and their coverage (Cf), constituting the aerosol indirect forcing (AIF). The forcing partially offsets the greenhouse warming and positively correlates with the climate sensitivity. However, it remains highly uncertain. Here, we show direct observational evidence for strong forcing from Cf adjustment to increased aerosols and weak forcing from cloud liquid water path adjustment. We estimate that the Cf adjustment drives between 52% and 300% of additional forcing to the Twomey effect over the ocean and a total AIF of -1.1 ± 0.8 W m-2. The Cf adjustment follows a power law as a function of background cloud droplet number concentration, Nd. It thus depends on time and location and is stronger when Nd is low. Cf only increases substantially when background clouds start to drizzle, suggesting a role for aerosol-precipitation interactions. Our findings highlight the Cf adjustment as the key process for reducing the uncertainty of AIF and thus future climate projections.

Warm Clouds Biases in CMIP6 Models Linked to Indirect Effects of Falling Ice‐Radiation Interactions Over the Tropical and Subtropical Pacific

AbstractWe examine the spatial distributions of CMIP6‐simulated cloud liquid water path (CLWP) and content (CLWC) against MODIS and CloudSat synthesized data over the tropical and subtropical Pacific. Three subsets of models are categorized based on their treatments of frozen ice‐radiative interactions. CLWP/CLWC are generally well simulated in subset with separately‐calculated radiative effects of cloud ice and falling ice (SON2). Too much warm clouds above 750 hPa are produced in either subset with total frozen ice radiative effects (SON1) or subset without radiative effects of falling ice (NOS) and thus CLWP/CLWC are overestimated over the open ocean including the trade‐wind regions. Stratocumulus clouds off the coasts of North and South America are severely underestimated in NOS models. We attribute the overestimates of clouds above the trade‐wind boundary layers to anomalous ascending motion associated with warmer sea surface temperature and weaker surface wind stress linked to indirect effects of falling ice‐radiation interactions.

The Role of In‐Cloud Wet Removal in Simulating Aerosol Vertical Profiles and Cloud Radiative Forcing

AbstractAmong the physical processes controlling aerosol vertical profiles, in‐cloud wet removal is of utmost importance while its representation in global climate models (GCMs) is crude. In this study, we implement into the Community Atmosphere Model version 6 (CAM6) a physically‐based aerosol wet removal parameterization scheme that explicitly treats aerosol activation, removal and resuspension. Evaluation against in‐situ observations shows that the default scheme substantially overestimates the upper tropospheric black carbon (BC) and sea salt mass. Our physically‐based scheme reduces BC and sea salt mass by a factor of 10 and 1,000, respectively, in better agreement with observations. Also, the new scheme slightly increases number of aerosol particles between 12 nm and 4.8 μm in diameter, thereby mitigating the aerosol number underestimation in the default scheme. Our new scheme reduces the overestimation of coarse‐mode aerosol (0.5–4.8 μm) number. Overall, the aerosol property changes (mass decrease and number increase) reduce the cloud condensation nuclei (CCN) concentration at low supersaturation (i.e., 0.02% and 0.1%), and increase CCN at high supersaturations (i.e., 0.5% and 1%). Consequently, the global annual mean cloud liquid water path increases by 1.89 g m−2 and the ice water path increases by 0.51 g m−2. The global annual mean shortwave, longwave, and net cloud radiative forcing change by −1.06, 0.57, and −0.48 W m−2, respectively. Further improvement is needed to reflect the real physics that the removal efficiencies for aerosol mass and number are disproportionate and to advect cloud‐borne (activated) aerosols for a complete aerosol lifecycle.

Corrections for Geostationary Cloud Liquid Water Path Using Microwave Imagery

Abstract Geostationary observations provide measurements of the cloud liquid water path (LWP), permitting continuous observation of cloud evolution throughout the daylit portion of the diurnal cycle. Relative to LWP derived from microwave imagery, these observations have biases related to scattering geometry, which systematically varies throughout the day. Therefore, we have developed a set of bias corrections using microwave LWP for the Geostationary Operational Environmental Satellite-16 and -17 (GOES-16 and GOES-17) observations of LWP derived from retrieved cloud-optical properties. The bias corrections are defined based on scattering geometry (solar zenith, sensor zenith, and relative azimuth) and low cloud fraction. We demonstrate that over the low-cloud regions of the northeast and southeast Pacific, these bias corrections drastically improve the characteristics of the retrieved LWP, including its regional distribution, diurnal variation, and evolution along short-time-scale Lagrangian trajectories. Significance Statement Large uncertainty exists in cloud liquid water path derived from geostationary observations, which is caused by changes in the scattering geometry of sunlight throughout the day. This complicates the usefulness of geostationary satellites to analyze the time evolution of clouds using geostationary data. Therefore, microwave imagery observations of liquid water path, which do not depend on scattering geometry, are used to create a set of corrections for geostationary data that can be used in future studies to analyze the time evolution of clouds from space.

What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations

Abstract. Single-layer nonprecipitating warm clouds are integral to Earth's climate, and accurate estimates of cloud liquid water content for these clouds are critical for constraining cloud models and understanding climate feedbacks. As the only cloud-sensitive radar currently in space, CloudSat provides very important cloud-profiling capabilities. However, a significant fraction of clouds is missed by CloudSat because they are either too thin or too close to the Earth's surface. We find that the CloudSat Radar-Visible Optical Depth Cloud Water Content Product, 2B-CWC-RVOD, misses about 73 % of nonprecipitating liquid cloudy pixels and about 63 % of total nonprecipitating liquid cloud water content compared to coincident Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Those percentages increase to 84 % and 69 %, respectively, if MODIS “partly cloudy” pixels are included. We develop a method, based on adiabatic parcel theory but modified to account for the fact that observed clouds are often subadiabatic, to estimate profiles of cloud liquid water content based on MODIS observations of cloud-top effective radius and cloud optical depth combined with lidar observations of cloud-top height. We find that, for cloudy pixels that are detected by CloudSat, the resulting subadiabatic profiles of cloud water are similar to what is retrieved from CloudSat. For cloudy pixels that are not detected by CloudSat, the subadiabatic profiles can be used to supplement the CloudSat profiles, recovering much of the missing cloud water and generating realistic-looking merged profiles of cloud water. Adding this missing cloud water to the CWC-RVOD product increases the mean cloud liquid water path by 228 % for single-layer nonprecipitating warm clouds. This method will be included in a subsequent reprocessing of the 2B-CWC-RVOD algorithm.

Impacts of Mesoscale Cloud Organization on Aerosol‐Induced Cloud Water Adjustment and Cloud Brightness

AbstractThe role of mesoscale cellular convection (MCC) in regulating aerosol‐induced cloud brightness remains unaddressed. Using 7 years of satellite‐based observations of cloud water adjustment to aerosol‐induced perturbations for closed MCCs across different sizes (8, 16, 32, and 64 km) over the North Atlantic Ocean, we show that MCC cell‐size plays a nontrivial role in regulating aerosol‐induced cloud brightness via cloud water adjustment. In cells that are primarily non‐precipitating, the adjustment in small‐scale MCCs can be 10 times more negative than in large‐scale MCCs, consistent with stronger evaporation via cloud top entrainment. Consequently, the response of cloud brightness is significantly stronger for large‐scale MCCs. We also find notable intra‐cell co‐variability between cloud liquid water path (LWP) and drop concentration (Nd) within MCCs that varies with cell size. Erroneously considering such co‐variability as a LWP response to Nd can lead to a significant positive bias, especially for small scale MCCs.

Analysis of Precipitation Process and Operational Precipitation Enhancement in Panxi Region Based on Cloud Parameters Retrievals from China’s Next−Generation Geostationary Meteorological Satellite FY−4A

Geostationary meteorological satellite data with high spatial and temporal resolution can be used to retrieve cloud physical parameters, which has significant advantages in tracking cloud evolution and development. Based on satellite multispectral RGB composite image and cloud physical analysis methods, we quantitatively analyze the evolution characteristics of cloud parameters in the pre-, mid- and post-artificially influenced weather process, explore the application potential benefits of satellite data in monitoring the operating conditions of the artificially influenced weather in the Panxi region, and verify the feasibility analysis of the evaluation of their effects. In this study, cloud parameters such as cloud particle effective radius (Re), cloud liquid water path (LWP), cloud ice water path (IWP), and cloud top height and temperature (CTH and CTT) are retrieved using FY−4A satellite data. For the Panxi region, the evolution characteristics of typical cloud parameters in the affected area before and after two aircraft artificial operational precipitation enhancements are analyzed. The results show that the satellite retrieval of cloud characteristic parameters in the Panxi region has good application value, which can be used to guide the artificial Operational Precipitation Enhancement. In this precipitation process, there are solid particles in the upper layer cloud and supercooled water in the lower layer cloud. After the cold cloud catalysis, the cloud top height, liquid water and ice water content, particle effective radius and ground precipitation in the operational area increased, and the cloud top temperature decreased. Thus, it effectively alleviated the drought in the Panxi region. The satellite retrieval of cloud characteristic parameters in the Panxi region has a good application value, which can provide a basis and guidance for future weather modification operations in the Panxi region.

Competition Between Radiative and Seeding Effects of Overlying Clouds on Underlying Marine Stratocumulus

AbstractOverlying cloud can affect the radiative and precipitation features of underlying cloud via its radiative and seeding effects. Using 4 years of CALIPSO and CloudSat observations, this study demonstrates that overlying clouds usually suppress the vertical development of underlying stratocumulus (Sc) by their radiative effect, thus reducing the precipitation, cloud liquid water path and thickness of Sc on a global scale. The radiative effect intensity increases with increasing optical depth (COD) of overlying cloud and decreasing cloud distance between cloud layers. By dividing the overlying clouds into seeder and non‐seeder groups, we find that seeding by overlying clouds can partly or even totally offset the precipitation suppression caused by their radiative effect. The net effect on precipitation of Sc switches from suppression to enhancement when COD of overlying cloud exceeds 0.16. This finding indicates that the competition between radiative and seeding effects of overlying cloud should be considered in cloud‐precipitation interaction.