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Lu, Chunsong

Publications and source records attributed to Lu, Chunsong.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Convergence of Cloud Droplet Spectral Relative Dispersion During Entrainment‐Mixing Based on Particle‐Resolved Direct Numerical Simulations

Entrainment-mixing processes critically impact cloud microphysical properties, but their effects on the relative dispersion (d) of cloud droplet size distributions (CDSDs) remain elusive. A direct numerical simulation model is initialized with different CDSDs to fill the gap. These results show that d decreases for broad CDSDs and increases for narrow ones, ultimately converging to approximately 0.5 regardless of initial CDSDs during the evaporation-dominated mixing stage. The supersaturation fluctuation and the shape of CDSDs jointly influence the convergence behavior of d. Further sensitivity tests show that the initial microphysical/dynamical/thermodynamical conditions exert negligible effects on the final converged value of d but affect the convergence rate (k). The k generally increases with increasing droplet number concentration and dissipation rate, and increases with decreasing liquid water content, relative humidity of entrained air, and mixing fraction of cloudy air. A conceptual model with two timescales is proposed; k and the timescales are negatively correlated, meaning that slow mixing and/or evaporation process results in slow convergence of d. In conclusion, this finding provides an important reference for improving understanding and parameterization of d during the entrainment-mixing processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of a New Approach for Entrainment and Detrainment Rate Estimation

Entrainment and detrainment rates (ε and δ) constitute the most critical free parameters in mass flux schemes commonly employed for cumulus parameterizations. Recently, Zhu et al. (2021) introduced a new approach that utilizes aircraft observations to simultaneously estimate ε and δ for cumulus clouds, overcoming the limitation of other observation-based approaches that solely yield ε without offering insights into δ. This study aims to comprehensively evaluate the reliability of this new approach. First, evaluation using an Explicit Mixing Parcel Model demonstrates the capability of the new approach to back-calculate predetermined ε and δ based on the physical properties before and after the entrainment mixing. Second, evaluation using large-eddy simulations illustrates that the new approach yields consistent ε and δ profiles compared to the traditional approach. Sensitivity tests indicate a weak sensitivity of the estimated δ with the new approach to the entrained air source. A decrease in the proportion of cloudy air in the assumed detrained air leads to a reduction in the estimated δ, while ε remains unaffected. Finally, the most appropriate assumptions for entrained and detrained air are discussed. Estimating ε for cumulus parameterizations involves acquiring ambient air more than 500 m away from the cloud edge as entrained air. Due to implicit mean field approximations in the traditional approach, determining the optimal assumption for detrained air properties proves challenging. Finally, this study confirms the reliability of the new approach in estimating ε and δ, providing confidence in its application to extensive observational data and advancement in parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Effects of Shallow Cumulus Cloud Shape on Interactions Among Clouds and Mixing With Near-Cloud Environments

Cloud lifecycles are influenced by interactions among clouds and mixing with cloud-free environments. Cloud shapes dictate the length of cloud boundaries, which affects these interactions. This study uses a large eddy simulation to examine the relationships between the shallow cumulus cloud shapes, processes at their boundaries, and lifecycles. To characterize the shape of clouds, two metrics are newly defined: one reflects the overall horizontal cloud shape, and the other defines the cloud edge irregularity. Simulated clouds experience increased irregularity, but little changes in aspect ratio. Irregularity-driven cloud perimeter growth strongly indicates cloud splitting, with a more pronounced effect than aspect ratio-driven perimeter growth. Smaller cloud-shell gradients of properties across cloud boundaries are associated with more irregular clouds, suggesting enhanced mixing of clouds with the cloud-free environment. These findings indicate that the shallow cumulus evolution is partly driven by the irregularity of the cloud edge through lateral mixing and cloud splitting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Observational study of relationships between entrainment rate, homogeneity of mixing, and cloud droplet relative dispersion

The entrainment–mixing process is key to the cloud’s dynamical and microphysical processes. However, to the best of our knowledge, no study has quantitatively linked entrainment rate and homogeneity of mixing. Additionally, their combined effects on cloud droplet relative dispersion and physical mechanisms are even more unclear. This study analyzed the aircraft measurements of cumulus clouds collected in the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign to identify these relationships. The relationship between the entrainment rate and homogeneous mixing degree was found to be moderately positive, and the underlying mechanisms related to mixing and evaporation time scales and environmental relative humidity were explored. The relationship between relative dispersion and entrainment rate changes from positive to negative with increasing entrainment rate, depending on the dominance of evaporation of large or small droplets. The relative dispersion first increases and then decreases with increasing homogeneous mixing degree, validating the results of previous model simulations. Further, the results shed new light on understanding the interactions between cloud microphysics and cloud dynamics through turbulent entrainment and mixing processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions

Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models (GCMs) but also in various higher-resolution limited-area models such as cloud-resolving models (CRMs) and large-eddy simulation (LES) models. Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years, this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations: multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions; discrete vs “continuous” representation of hydrometeor types; turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation; theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology; and approaches for developing bulk microphysics parameterizations. Also presented are the spectral bin scheme and particle-based scheme (especially, super-droplet method) for representing explicit microphysics. Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations. Particle-resolved direct numerical simulation (DNS) models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds. Outstanding challenges and future research directions are explored as well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development of a triple-moment ice-phase cloud microphysics scheme and its application to the Single Column Atmosphere Model

Parameterization of cloud microphysics is critical for accurate simulation of weather and climate, in which the characteristics of cloud particle spectrum inevitably further affect climate simulation by changing the cloud evolution and cloud radiation effects. The popular currently used double-moment cloud microphysics schemes in numerical models can predict the intercept (N 0 ) and slope (λ) parameters of cloud particle spectrum but cannot predict the spectral shape parameter (μ), which hinders accurate description of cloud physical processes in climate models. Therefore, in the present study, we built upon the ideas of previously developed triple-moment cloud microphysics scheme, considered radar reflectivity factor as the third predictor in addition to number and mass concentration, and introduced its related prediction equation to the Single Column Atmosphere Model Version 5.3 (SCAM5.3). Moreover, the relevant microphysical process formulas in the model were revised, and a triple-moment ice-cloud microphysics scheme was constructed to predict the μ of ice particle spectrum. Based on this model, a 29-day case of the Atmospheric Radiation Measurement Program in the summer of 1997 (ARM97) was simulated, and the differences in cloud fraction and radiation simulations between the double- and triple-moment schemes were analysed. The μ of ice particle spectrum predicted by the triple-moment scheme mainly ranged from 0 to 4; the peak value was around 2, and at least 85% of the μ values were greater than the default 0. Therefore, the μ=0 setting in the double-moment scheme is unreasonable. Moreover, the developed triple-moment ice-cloud microphysics scheme yielded a narrower ice particle spectrum, which was closer to the observation results of previous studies, than the double-moment cloud microphysics scheme (e.g., height=233 hPa). Furthermore, compared with the double-moment scheme, the triple-moment scheme achieved closer simulations of the cloud fraction observations, particularly for ice clouds in the upper levels. Considering the close association between cloud fraction and radiation, the error with the triple-moment scheme was smaller than that with the double-moment scheme regardless of the shortwave (surface downward shortwave radiation, net downward shortwave radiation at the top of the atmosphere, and net shortwave radiation at the surface) or longwave (surface downward longwave radiation and net longwave radiation at the surface) flux density. Finally, the improvement mechanism of the triple-moment scheme on cloud fraction and radiation simulations was explored. The major reason is that the triple-moment scheme weakens the autoconversion of ice crystal to form snow and enhances the growth process of ice crystal deposition, thereby increasing the mass concentration of ice crystals and ice cloud fraction. Overall, the developed triple-moment ice-cloud microphysics scheme can help improve the simulation ability of models for cloud-climate feedback and other processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors

Cloud microphysical properties are significantly affected by entrainment and mixing processes. However, it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution. Previously, the relationship between relative dispersion and entrainment rate was found to be positive or negative. To reconcile the contrasting relationships, the Explicit Mixing Parcel Model is used to determine the underlying mechanisms. When evaporation is dominated by small droplets, and the entrained environmental air is further saturated during mixing, the relationship is negative. However, when the evaporation of big droplets is dominant, the relationship is positive. Whether or not the cloud condensation nuclei are considered in the entrained environmental air is a key factor as condensation on the entrained condensation nuclei is the main source of small droplets. However, if cloud condensation nuclei are not entrained, the relationship is positive. If cloud condensation nuclei are entrained, the relationship is dependent on many other factors. High vertical velocity, relative humidity of environmental air, liquid water content, and low droplet number concentration are more likely to cause the negative relationship since new saturation is easier to achieve by evaporation of small droplets. Further, the signs of the relationship are not strongly affected by the turbulence dissipation rate, but the higher dissipation rate causes the positive relationship more significant for a larger entrainment rate. A conceptual model is proposed to reconcile the contrasting relationships. This work enhances the understanding of relative dispersion and lays a foundation for the quantification of entrainment-mixing mechanisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds

Abstract. Different entrainment–mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment–mixing parameterization that uses the grid mean relative humidity without requiring the relative humidity of the entrained air. Then, the parameterization is implemented in a microphysics scheme in a large eddy simulation model, and sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment–mixing parameterization. The results indicate that the new entrainment–mixing parameterization has a larger impact on the number concentration, volume mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment–mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment–mixing parameterization by decreasing the cloud droplet size and evaporation timescale. The results of this new entrainment–mixing parameterization with grid mean relative humidity are validated by the use of a different entrainment–mixing parameterization that uses parameterized entrained air properties. This study sheds new light on the improvement of entrainment–mixing parameterizations in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in-situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from June 21 to July 20, 2017 and January 15 to February 18, 2018 in the Azores. The flights were designed to maximize the synergy between in-situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Lastly, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vertical Variations of Cloud Microphysical Relationships in Marine Stratocumulus Clouds Observed During the ACE‐ENA Campaign

Abstract This study examines the vertical variations of cloud microphysical relationships and their implications to cloud microphysical processes in marine stratocumulus clouds using in‐situ aircraft observations during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE‐ENA) field campaign. A new diagram with a coordinate system based on cloud droplet liquid water content (L c ) and phase relaxation time scale is proposed to investigate mixing mechanisms. This new diagram analysis shows that the inhomogeneous mixing trait is dominant near the cloud top, but homogeneous mixing trait is stronger at lower altitudes. The relevant scale parameters (i.e., transition length scale and transition scale number) also indicate a high likelihood of inhomogeneous mixing. The relationship between L c and standard deviation of droplet radius (σ R ) clearly shows the vertical transition: the correlation between L c and σ R is positive at lower cloud altitudes, but it becomes negative as altitude increases. Such a vertical transition is consistent with the vertical circulation mixing, modulating the cloud microphysical relationships to suggest homogeneous mixing at a significant depth from the cloud top.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A New Approach for Simultaneous Estimation of Entrainment and Detrainment Rates in Non- Precipitating Shallow Cumulus

A new approach is developed for estimating entrainment and detrainment rates in cumulus clouds based on aircraft observations. Equations relating entrainment and detrainment rates to gross entrainment and detrainment are derived. This approach is applied to the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign, supported by the U.S. Department of Energy's Atmospheric Radiation Measurement program. The results show that both entrainment and detrainment rates decrease with increasing height. Sensitivity tests with different detrained air assumptions yield similar results. The entrainment and detrainment rates can reproduce the cloud thermodynamic variables. Partial correlation analysis indicates that entrainment rate is positively correlated with environmental relative humidity (RH), and detrainment rate is negatively correlated with environmental RH and positively correlated with entrainment rate. This new approach can be applied to other cloud observations to obtain a data set of entrainment and detrainment rates in cumulus clouds.

Zhu, Lei↗