Cloud Base Research Articles

Uncovering Below Cloud Rain‐Vapor Interactions During Tropical Rain Events Through Simultaneous and Continuous Real‐Time Monitoring of Rain and Vapor Isotopes

AbstractDue to limited water vapor measurements, vapor isotopes have been traditionally estimated under the assumption of isotopic equilibrium between rain and vapor below cloud base. However, recent advancements in analytical instruments allow more vapor isotopic measurements that have challenged this assumption. To enhance our understanding of rain‐vapor interactions below cloud base in tropical regions, we established an automated system to measure rain and vapor isotopes simultaneously and continuously in real time at minute intervals in Singapore. Among 324 rain events monitored from 2016 to 2019, 81% exhibited a substantial departure of rain and vapor isotopes from the expected equilibrium. This departure suggests that raindrop evaporation plays a larger role in determining their isotopes. The conclusion is supported by the generally lower slopes of the local meteoric water line. Seasonal variations in rain event characteristics indicate changing influences of rain‐vapor interactions: during monsoons, more frequent heavy rainfall maintains relatively high humidity below cloud base, favoring rain‐vapor isotopic equilibrium, whereas during inter‐monsoons, more light rain events lead to pronounced rain evaporation and larger isotopic differences. Furthermore, rain‐vapor interactions below cloud base significantly modulated their isotope evolution during individual events. As events progressed, reduced humidity favored evaporation, increasing rain isotope values and decreasing its d‐excess, whereas vapor isotope values decreased and its d‐excess increased. Our study introduces a new approach to capturing real‐time high‐resolution rain and vapor isotopes at minute intervals to understand the dynamics of rain‐vapor interactions below cloud base. Findings underscore the crucial role of these interactions in influencing rain and vapor isotopes during tropical rain events.

Airborne Observations of Highly Variable and Complex Freezing Drizzle and Mixed-Phase Environments

Abstract Airframe icing caused by interactions with supercooled cloud droplets and precipitation can pose a risk to aviation operations and life safety. The In-Cloud Icing and Large-drop Experiment (ICICLE) was conducted in January–March 2019 to capture measurements in freezing conditions in support of the Federal Aviation Administration (FAA) Terminal Area Icing Weather Information for NextGen (TAIWIN) program. The National Research Council of Canada’s Convair-580 research aircraft fulfilled the airborne data collection requirements for the ICICLE campaign and sampled icing clouds and atmospheric conditions over the midwestern United States. ICICLE flight 18, conducted on 17 February 2019, collected cloud and precipitation measurements during a widespread storm that generated supercooled small drops and freezing drizzle (FZDZ) within both liquid and mixed-phase regions. Supercooled liquid water content (LWC) typically ranged 0.30–0.45 g m−3 and exceeded 0.70 g m−3 in one instance. Maximum FZDZ diameters of 300–400 μm were commonly sampled near the base of clouds. Missed approaches performed at four Illinois airfields provided measurements of conditions from near ground level to above cloud top and supplied information regarding FZDZ formation and evolution. FZDZ was found to form at altitudes featuring relatively high LWC and sufficiently low droplet number concentrations. FZDZ formation zones were sometimes collocated with regions of atmospheric instability and/or wind shear. Flight through highly variable supercooled cloud droplet and FZDZ conditions resulted in significant Convair-580 airframe icing, highlighting the risk that icing conditions can pose to aircraft safety.

Analysis of Macro- and Microphysical Characteristics of Ice Clouds over the Tibetan Plateau Using CloudSat/CALIPSO Data

Utilizing CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2007 to 2016, this study analyzed the distributions of optical and physical characteristics and change characteristics of ice clouds over the Tibetan Plateau (TP). The results show that the frequency of ice clouds in the cold season (November to March) on the plateau is over 80%, while in the warm season (May to September) it is around 60%. The average cloud base height of ice clouds in the warm season is 3–5 km, and mostly around 2 km in the cold season. The average cloud top height in the warm season is around 5–8 km, while in the cold season it is mainly around 4.5 km. The average thickness of ice clouds in both seasons is around 2 km. The statistical results of microphysical characteristics show that the ice water content is around 10−1 to 103 mg/m3, and the effective radius of ice clouds is mainly in the range of 10–90 μm. Both have their highest frequency in the west of the TP and lowest in the northeast. A comprehensive analysis of the change in temperature, water vapor, and ice cloud occurrence frequency shows that the rate of increase in water vapor in the warm season is greater than that in the cold season, while the rates of increase in both surface temperature and ice cloud occurrence are smaller than in the cold season. The rate of increase in temperature in the warm season is around 0.038 °C/yr, and that in the cold season is around 0.095 °C/yr. The growth rate of thin ice clouds in the warm season is around 0.15% per year, while that in the cold season is as high as 1% per year. The results suggest that the surface temperature change may be related to the occurrence frequency of thin ice clouds, with the notable increase in temperature during the cold season possibly being associated with a significant increase in the occurrence frequency of thin ice clouds.

Cloud classification through machine learning and global horizontal irradiance data analysis

AbstractCloud observations and characterization are crucial owing to their influence on energy balance, climate, and weather. Their particular effects on radiation vary depending on different cloud parameters, such as cloud base or top height, water content, and cloud optical thickness, all of them closely related to the specific cloud type. Cloud classification therefore becomes a crucial task in meteorology, although it remains challenging for weather services worldwide owing to the intensive associated labor and cost. In this study we introduce a new low‐cost method for automating cloud classification based on a combination of ground‐based global horizontal irradiance (GHI) measurements, a clear‐sky model, and machine learning. Based on the hypothesis that different cloud types have their own GHI signatures, we trained different supervised learning algorithms using GHI data manually labeled by meteorological observers from time‐synchronized all‐sky images. Multiple time windows were extracted from each GHI series, with eight features defined in each case to characterize the sequence. The best outcome was achieved using an XGBoost model on features extracted on time windows of 33 min, obtaining an accuracy of 0.88 and a Cohen's kappa of 0.84 in a held‐out test set. The development presented in this study has the ability to provide low‐cost cloud classification from ground‐based observations, which is a challenge for weather services worldwide owing to intensive labor and cost.

Initiation of Downward Positive Leader Beneath the Negative Leader Channel

AbstractDue to the weak radiation generated by positive leaders, our understanding of how positive leaders are initiated and reach the ground remains limited. This study investigated positive cloud‐to‐ground (CG) lightning induced after the long intracloud lightning based on high‐speed video and fast antenna mapping results. Below the cloud base in the field of view, re‐breakdowns of decayed negative branches occurred consecutively beneath the horizontal negative channel in the form of bidirectional leaders. These bidirectional leaders advanced along the same channel, and eventually, the third reached the ground, generating a positive return stroke (RS) with a peak current of 157 kA. Following the RS, new negative discharges emerge adjacent to the vertical return stroke channel, persisting and propagating to form a continuing current (CC) lasting over 200 milliseconds.

The Non-Monotonic Response of Cumulus Congestus to the Concentration of Cloud Condensation Nuclei

This study uses idealized simulations to investigate the impact of cloud condensation nuclei (CCN) on a cumulus congestus. Thirteen cases with the initial CCN_C, which is the CCN concentration at 1% supersaturation with respect to water, from 10 to 10,000 cm−3 are simulated. The analysis focuses on the liquid phase due to the negligible ice phase in this study. A non-monotonic response of cloud properties and precipitation to CCN concentration is observed. When CCN_C is increased from 10 to 50 cm−3, the enhanced condensation due to the more numerous droplets invigorates the cumulus congestus. The delayed precipitation formation due to the smaller droplets also facilitates the cloud development. The two processes together lead to a higher liquid water path (LWP), higher cloud top, and heavier precipitation. The cumulus congestus has the highest cloud top, the strongest updraft, and the most accumulated precipitation and at CCN_C = 50 cm−3. When CCN_C is increased from 50 to 500 cm−3, the condensation near the cloud base is further enhanced and the precipitation is further delayed, both of which lead to more liquid water remaining in the cloud, and thus an even higher LWP and heavier precipitation rate in the later stage. However, the significantly enhanced evaporation near the cloud top limits the vertical development of the cumulus congestus, leading to a lower cloud top. When CCN_C is further increased to be higher than 1000 cm−3, the cumulus congestus is strongly suppressed, and no precipitation forms. The ratio of the precipitation production rate to vertical cloud water flux in the updraft is not a constant, as is generally assumed in cumulus parameterization schemes, but decreases significantly with increasing CCN concentration. It is also found that the CCN effect on the cumulus congestus relies on which parameters are used to describe the cloud strength. In this study, as CCN_C increases, the LWP and the maximum precipitation rate peak at CCN_C = 500 cm−3, while the cloud top height, maximum updraft, and accumulated precipitation amount peak at CCN_C = 50 cm−3.

Drought response strategies of vascular epiphytes in isolated pasture trees in a Costa Rican tropical montane landscape.

Vascular epiphytes of tropical montane cloud forests are vulnerable to climate change, particularly as cloud bases elevate and reduce atmospheric inputs to the system. However, studies have generally focused on epiphytes in contiguous forests, with little research being done on epiphytes on isolated pasture trees. We investigated water relations of pasture-tree epiphytes at three sites located below and above the elevation of the average cloud base in Monteverde, Costa Rica. We measured sap velocity and four microclimate variables in both the dry and wet season of 2018. We also measured functional traits, including pressure volume (PV) curves, predawn/midday water potential, and various lab-based water relations traits. We used linear mixed models to assess the correlation between microclimate and sap velocity in both seasons and ANOVA to assess the variation in PV curve and water potential variables. The turgor loss point generally increased from the wettest to driest site. However, this trend was driven primarily by the increasing prevalence of leaf succulence at drier sites. Microclimatic variables correlated strongly with sap velocity in the wet season, but low soil moisture availability caused this correlation to break down during the dry season. Our results emphasize the vulnerability of cloud forest epiphytes to rising cloud bases. This vulnerability may be more severe in pasture trees that lack the potential buffer of surrounding forest, but additional research that directly compares the canopy microclimate conditions between forest and pasture trees is needed to confirm this possibility.

Cloud base height variability observed using a Laser-Based Ceilometer over a tropical station Pune, India

ABSTRACT Clouds play a pivotal role in determining Earth’s climate, impacting several atmospheric processes influencing the weather. The study explores the temporal variations in cloud base height (CBH) over Pune, a tropical station, from 2017 to 2023 using a Laser-Based Ceilometer with a range of 0–7500 m. Our analysis shows seasonal trends in CBH, with the monsoon season exhibiting unique characteristics showing the lowest average CBH and minimal diurnal changes during the study period. Conversely, the pre-monsoon, post-monsoon, and winter season show a gradual rise of CBH in the morning, maintaining higher levels until late afternoon, followed by a decline in the evening. Analysis of the diurnal frequency of cloud occurrence at 500 m intervals reveals the monsoon season’s dominance in the 500 m to 1000 m layer. Throughout the year, low cloud bases (CBH <2000 m) are most frequent, outpacing the frequency of mid and high cloud bases. High cloud base (7500 < CBH > 6000 m) is the least common, showing a semi-diurnal pattern in winter with peaks around noon and midnight. These findings not only enhance our understanding of Pune’s atmospheric behaviour but also offer valuable information for weather prediction, climate modelling, and environmental monitoring.

Measurement report: In situ vertical profiles of below-cloud aerosol over the central Greenland Ice Sheet

Abstract. Surface radiative cooling in polar regions can generate persistent stability in the atmospheric boundary layer. Stable layers below clouds can decouple the cloud layer from the near-surface environment. Under these conditions, surface aerosol measurements are not necessarily representative of the near-cloud or intra-cloud aerosol populations. To better understand the variability in the vertical structure of aerosol properties over the central Greenland Ice Sheet, in situ measurements of aerosol particle size distributions up to cloud base were made at Summit Station in July and August 2023. These measurements identified distinct vertical aerosol layers between the surface- and cloud-base-associated thermodynamic decoupling layers. Such decoupling layers occur 49 % of the time during the summer in central Greenland, suggesting that surface aerosol measurements are insufficient for describing the cloud-relevant aerosol population half of the time. Experience during this first measurement season demonstrated the ability of a tethered-balloon platform to operate effectively under icing conditions and at low surface pressure (&lt; 680 hPa). The results presented here illustrate the value of vertically resolved in situ measurements of aerosol properties in developing a nuanced understanding of the aerosol effects on cloud properties in polar regions.

Connections Between Sub‐Cloud Coherent Updrafts and the Life Cycle of Maritime Shallow Cumulus Clouds in Large Eddy Simulation

AbstractWe develop a novel approach to detect cloud‐subcloud coupling during the cloud life cycle and analyze a large eddy simulation of marine shallow cumulus based on the Barbados oceanographic and meteorological experiment campaign. Our results demonstrate how the activity of sub‐cloud coherent updrafts (SCUs) affect the evolution of shallow cloud properties during their life cycles, from triggering to development, and through to dissipation. Most clouds are related to SCUs during their lifetime but not every SCU ( for short‐lived ones) leads to cloud formation. The fastest growing SCUs in a relatively moist region are most likely to initiate clouds. The evolution of cloud base mass‐flux depends on cloud lifetime. Compared with short‐lived clouds, longer lived clouds have longer periods of development, even normalized by the full lifetime, and tend to increase their cloud base mass‐flux to a stronger maximum. This is consistent with the evolution of mass flux near the top of SCU, indicating that the development of clouds is closely related to the sub‐cloud activity. When the SCUs decay and detach from the lifting condensation level, the corresponding cloud base starts to rise, signifying the start of cloud dissipation, during which the cloud top lowers to approach the rising cloud base. Previous studies have described similar conceptual pieces of this relationship but here we provide a continuous framework to cover all the stages of cloud‐subcloud coupling. Our findings provide quantitative evidence to supplement the conceptual model of shallow cloud life cycle and is critical to improve the steady‐state assumption in parameterization.

Microphysical Prescriptions for Parameterized Water Cloud Formation on Ultra-cool Substellar Objects

Water must condense into ice clouds in the coldest brown dwarfs and exoplanets. When they form, these icy clouds change the emergent spectra, temperature structure, and albedo of the substellar atmosphere. The properties of clouds are governed by complex microphysics but these complexities are often not captured by the simpler parameterized cloud models used in climate models or retrieval models. Here, we combine microphysical cloud modeling and 1D climate modeling to incorporate insights from microphysical models into a self-consistent, parameterized cloud model. Using the 1D Community Aerosol and Radiation Model for Atmospheres (CARMA), we generate microphysical water clouds and compare their properties with those from the widely used EddySed cloud model for a grid of Y dwarfs. We find that the mass of water condensate in our CARMA water clouds is significantly limited by available condensation nuclei; in models without additional seed particles for clouds added, the atmosphere becomes supersaturated. We incorporate water latent heat release in the convective and radiative parts of the atmosphere and find no significant impact on water-ice cloud formation for typical gas giant compositions. Our analysis reveals the CARMA cloud profiles have a gradual decrease in opacity of approximately 4% per bar below the cloud base. Incorporating this gradual cloud base falloff and a variable f sed parameter allows spectra generated from the parameterized Eddysed model to better match those of the microphysical CARMA model. This work provides recommendations for efficiently generating microphysically informed water clouds for future models of cold substellar objects with H/He atmospheres.

Cirrus cloud occurrence and its geometrical and optical properties during the transient monsoon conditions

Knowledge of variation in the percentage occurrence of the cirrus clouds (POC) during transient monsoon conditions is essential for understanding the role of the monsoon in transporting the water vapor into the lower stratosphere which is vital in quantifying the radiation budget of the earth–atmosphere system. In this paper, we present the spatial structure of the POC, the geometrical properties such as cloud top and base height (CTH & CBH), cloud thickness (CTH-CBH), optical properties such as optically thick, thin, and subvisible cirrus clouds during the active and break phases of the Asian summer monsoon using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during July–August 2006–2018. The active and break phases are identified based on the central India rainfall from the India Meteorological Department dataset. The POC is found to be higher by 10–30 % over central India and some parts of the eastern Arabian Sea (AS) and Bay of Bengal (BoB) during the active phase compared to the break phase which shows enhancement in POC over the foothill of Himalaya and southern part of BoB and AS. The higher POC is attributed to the increase in the convective activities associated with the increase in tropical easterly jet during the active phase. The CTH and CBH range ~14–18 km and 12–16 km, respectively during the active phase compared to the break phase. The contributions of optically thick and thin clouds are higher in POC during both phases compared to subvisible clouds. Both convectively generated and in situ-formed cirrus clouds dominate during the active phase compared to the break phase indicating the dominance of the freeze-drying processes during the active phase.

Assessing Downburst Kinematics Using Video Footage Analysis

Measurements of downburst outflows using standard meteorological instruments (e.g., anemometers) are rare due to their transient and localized nature. However, video recordings of such events are becoming more frequent. This short communication (Technical Note) study presents a new approach to estimating the kinematics of a downburst event using video footage recordings of the event. The main geometric dimensions of the event, such as downdraft diameter, cloud base height, outflow depth, and the radius of the outflow at a given moment in time, are estimated by sizing them against reference structures of known dimensions that are present in the video footage. From this analysis, and knowing the frame rate of the video recording, one can estimate the characteristic velocities in the downburst event, such as the mean downdraft velocity and the mean velocity of the radial outflow propagation. The proposed method is tested on an August 2015 downburst event that hit Tucson, Arizona, United States. The diameter of the downburst outflow increased with the time from approximately 1.10 km to 3.35 km. This range of values indicates that the event was a microburst. The mean descending velocity of downburst downdraft was 8.9 m s−1 and the horizontal velocity of outflow propagation was 17.7 m s−1. The latter velocity is similar to the measured wind gust at the nearby weather station and Doppler radar. The outflow depth is estimated at 160 m, and the cloud base height was approximately 1.24 km. Estimating the kinematics of downbursts using video footage, while subject to certain limitations, does yield a useful estimation of the main downburst kinematics that contribute to a better quantification of these localized windstorms.

Distinct structure, radiative effects, and precipitation characteristics of deep convection systems in the Tibetan Plateau compared to the tropical Indian Ocean

Abstract. Using spaceborne lidar and radar observations, this study identifies deep convection systems (DCSs), including deep convection cores (DCCs) and anvils, over the Tibetan Plateau (TP) and tropical Indian Ocean (TO) and finds that DCSs over the TP are less frequent, exhibiting narrower and thinner DCCs and anvils compared to those over the TO. The thinner DCCs over the TP exert weaker radiative cooling effects at the top of atmosphere (TOA) compared to the TO. But, the shortwave TOA cloud radiative effect (CRE) of TP anvils is stronger than that of the TO possibly due to more densely packed cloud tops over the TP. It results in a stronger TOA CRE of DCSs over the TP than that of TO. In particular, the longwave CRE of DCSs over the TP is notably greater at surface and low-level atmosphere due to the distinct lower temperature and less water vapour. The width of DCSs shows a positive correlation with wind shear and atmospheric instability, and the underlying mechanisms are discussed. We also find that the impact of aerosols on cloud top heights and precipitation displays significant discrepancies between the two regions. It is because that the aerosol invigoration effect is less efficient on the TP DCSs, mainly attributed to the significantly colder cloud base. Due to competition between invigoration and direct/semi-direct radiative effects of aerosols, the correlation between precipitation and aerosols over the TP is not obvious. However, precipitation in the TO experiences invigoration followed by suppression with increasing aerosols, due to the dominance of aerosol radiative effects and enhancement entrainment under polluted conditions.

Ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data

Abstract. Ceilometers are used routinely at aerodromes worldwide to derive the height and sky coverage fraction of cloud layers. This information, possibly combined with direct observations by human observers, contributes to the production of meteorological aerodrome reports (METARs). Here, we present ampycloud, a new algorithm, and its associated Python package for automatic processing of ceilometer data with the aim of determining the sky coverage fraction and base height of cloud layers above aerodromes. The ampycloud algorithm was developed at the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss) as part of the AMAROC (AutoMETAR/AutoReport rOund the Clock) program to help in the fully automatic production of METARs at Swiss civil aerodromes. ampycloud is designed to work with no direct human supervision. The algorithm consists of three distinct, sequential steps that rely on agglomerative clustering methods and Gaussian mixture models to identify distinct cloud layers from individual cloud base hits reported by ceilometers. The robustness of the ampycloud algorithm stems from the first processing step, which is simple and reliable. It constrains the two subsequent processing steps that are more sensitive but also better suited to handling complex cloud distributions. The software implementation of the ampycloud algorithm takes the form of an eponymous, pip-installable Python package developed on GitHub and made publicly accessible.

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

A note of double-layer cloud detection method based on cloud base height and brightness

Double-layer cloud is a special cloud condition, and clouds in two layers have different effects on solar radiation reaching ground. Getting the shape of double-layer clouds is helpful to study the change of solar irradiance. The proposed double-layer clouds detection method is based on the cloud base height (CBH) and brightness of double-layer clouds. The CBH is calculated based on binocular parallax, which requires two images filmed synchronously by two cameras, and the brightness is offered by the brightness channel in HSV color space. The accuracy of this method is 98.5% for single-layer clouds and 89.4% for double-layer clouds. The reasons for misidentifications are (1) the brightness contrast decreases when the high-layer clouds are thick, (2) the distant low clouds have different brightness in top and bottom.

Deforestation amplifies climate change effects on warming and cloud level rise in African montane forests

Tropical montane forest ecosystems are pivotal for sustaining biodiversity and essential terrestrial ecosystem services, including the provision of high-quality fresh water. Nonetheless, the impact of montane deforestation and climate change on the capacity of forests to deliver ecosystem services is yet to be fully understood. In this study, we offer observational evidence demonstrating the response of air temperature and cloud base height to deforestation in African montane forests over the last two decades. Our findings reveal that approximately 18% (7.4 ± 0.5 million hectares) of Africa’s montane forests were lost between 2003 and 2022. This deforestation has led to a notable increase in maximum air temperature (1.37 ± 0.58 °C) and cloud base height (236 ± 87 metres), surpassing shifts attributed solely to climate change. Our results call for urgent attention to montane deforestation, as it poses serious threats to biodiversity, water supply, and ecosystem services in the tropics.

Evaluation and Improvement of a CALIPSO-Based Algorithm for Cloud Base Height in China

Clouds are crucial in regulating the Earth’s energy budget. Global cloud top heights have been easily retrieved from satellite measurements, but there are few methods for determining cloud base height (CBH) from satellite measurements. The Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm was proposed to derive the height of the lower-troposphere liquid cloud base by using the Cloud-Aerosol Lidar with Orthogonal polarization cloud aerosol LiDAR (CALIOP) profiles and weather observations at airports from aviation routine and special weather report (METARs and SPECIs, called METAR) observation data in the United States. A modification to the CBASE algorithm over China (CNMETAR-CBASE) is presented in this paper. In this paper, the ability of the CBASE algorithm to calculate CBH in China is evaluated, and METAR observations over China (CNMETAR) were then used to modify the CBASE algorithm. The results including CNMETAR observation data in China can better retrieve CBH over China compared with the results using the original CBASE algorithm, and the accuracy of the global CBH results has been improved. Overestimations of CBH with the original algorithm range from 500 to 800 m in China, which have been reduced to about 300 m with an improved algorithm. The deviations calculated by the algorithm also have a significant reduction, from 480 m (CBASE) to 420 m (CNMETAR-CBASE). In conclusion, the modified CBASE algorithm not only calculates the CBH more accurately in China but also improves the results of the global CBH retrieved from satellites.

Improving Aerosol Radiative Forcing and Climate in E3SM: Impacts of New Cloud Microphysics and Improved Wet Removal Treatments

AbstractNumerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m−2, while the ZM_plus increases it by 0.27 W m−2, resulting from excessive direct (0.31 W m−2) and indirect forcing (−1.79 W m−2). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m−2) and indirect aerosol forcing (−1.52 W m−2). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m−2 and −1.31 W m−2, respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.