Beyond Cloud Microphysics: Representing Subgrid-Scale Processes in Lagrangian Cloud Models

2020 ◽  
Author(s):  
Fabian Hoffmann
Keyword(s):  
Three Dimensional ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Droplet Growth ◽  
Subgrid Scale ◽  
Modeling Framework ◽  
Mixing Processes ◽  
New Approach ◽  
Cloud Models ◽  
Mixed Phase Clouds

<p>While the use of Lagrangian cloud microphysical models dates back as far as the 1950s, the integration of this framework into fully-coupled, three-dimensional dynamical models is only possible for about 10 years. In addition to the highly accurate and detailed representation of cloud microphysical processes, these so-called Lagrangian Cloud Models (LCMs) also allow for new ways of representing subgrid-scale dynamical processes and their effects on the microphysical development of clouds, typically neglected or only crudely parameterized due to computational constraints.</p><p>In this talk, I will present a new approach in which supersaturation fluctuations on the subgrid-scale of a large-eddy simulation (LES) model are represented by an economical, one-dimensional model that represents turbulent compression and folding. With a resolution comparable to direct numerical simulation (DNS), inhomogeneous and finite rate mixing processes are explicitly resolved. Applications of this modeling approach for warm-phase shallow cumuli and stratocumuli, and first applications for mixed-phase clouds will be discussed. Generally, clouds susceptible to inhomogeneous mixing show a reduction in the droplet number concentration and stronger droplet growth, in agreement with theory. Stratocumulus entrainment rates tend to be lower using the new approach compared to simulations without it, indicating a more appropriate representation of the entrainment-mixing process. Finally, the Wegner-Bergeron-Findeisen-Process, leading to a rapid ice formation in mixed-phase clouds, is decelerated.</p><p>All in all, this new modeling framework is capable of bridging the gap between LES and DNS, i.e., it enables representing all scales relevant to cloud physics, from entire cloud fields to the smallest turbulent fluctuations, in a single model, allowing to study their interactions explicitly and granting new insights.</p>

scholarly journals Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

2020 ◽  
Vol 13 (9) ◽  
pp. 4107-4157 ◽  
Author(s):  
Shin-ichiro Shima ◽  
Yousuke Sato ◽  
Akihiro Hashimoto ◽  
Ryohei Misumi
Keyword(s):  
Method Development ◽  
Cloud Condensation Nuclei ◽  
Deep Convection ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Computational Time ◽  
Ice Particles ◽  
Mass Dimension ◽  
Mixed Phase Clouds ◽  
Droplet Method

Abstract. The super-droplet method (SDM) is a particle-based numerical scheme that enables accurate cloud microphysics simulation with lower computational demand than multi-dimensional bin schemes. Using SDM, a detailed numerical model of mixed-phase clouds is developed in which ice morphologies are explicitly predicted without assuming ice categories or mass–dimension relationships. Ice particles are approximated using porous spheroids. The elementary cloud microphysics processes considered are advection and sedimentation; immersion/condensation and homogeneous freezing; melting; condensation and evaporation including cloud condensation nuclei activation and deactivation; deposition and sublimation; and coalescence, riming, and aggregation. To evaluate the model's performance, a 2-D large-eddy simulation of a cumulonimbus was conducted, and the life cycle of a cumulonimbus typically observed in nature was successfully reproduced. The mass–dimension and velocity–dimension relationships the model predicted show a reasonable agreement with existing formulas. Numerical convergence is achieved at a super-particle number concentration as low as 128 per cell, which consumes 30 times more computational time than a two-moment bulk model. Although the model still has room for improvement, these results strongly support the efficacy of the particle-based modeling methodology to simulate mixed-phase clouds.

scholarly journals Hemispheric contrasts in ice formation in stratiform mixed-phase clouds: disentangling the role of aerosol and dynamics with ground-based remote sensing

2021 ◽  
Vol 21 (23) ◽  
pp. 17969-17994
Author(s):  
Martin Radenz ◽  
Johannes Bühl ◽  
Patric Seifert ◽  
Holger Baars ◽  
Ronny Engelmann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Gravity Wave ◽  
Detection Threshold ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Ice Formation ◽  
Absolute Difference ◽  
Optical Parameters ◽  
Mixed Phase Clouds

Abstract. Multi-year ground-based remote-sensing datasets were acquired with the Leipzig Aerosol and Cloud Remote Observations System (LACROS) at three sites. A highly polluted central European site (Leipzig, Germany), a polluted and strongly dust-influenced eastern Mediterranean site (Limassol, Cyprus), and a clean marine site in the southern midlatitudes (Punta Arenas, Chile) are used to contrast ice formation in shallow stratiform liquid clouds. These unique, long-term datasets in key regions of aerosol–cloud interaction provide a deeper insight into cloud microphysics. The influence of temperature, aerosol load, boundary layer coupling, and gravity wave motion on ice formation is investigated. With respect to previous studies of regional contrasts in the properties of mixed-phase clouds, our study contributes the following new aspects: (1) sampling aerosol optical parameters as a function of temperature, the average backscatter coefficient at supercooled conditions is within a factor of 3 at all three sites. (2) Ice formation was found to be more frequent for cloud layers with cloud top temperatures above -15∘C than indicated by prior lidar-only studies at all sites. A virtual lidar detection threshold of ice water content (IWC) needs to be considered in order to bring radar–lidar-based studies in agreement with lidar-only studies. (3) At similar temperatures, cloud layers which are coupled to the aerosol-laden boundary layer show more intense ice formation than decoupled clouds. (4) Liquid layers formed by gravity waves were found to bias the phase occurrence statistics below -15∘C. By applying a novel gravity wave detection approach using vertical velocity observations within the liquid-dominated cloud top, wave clouds can be classified and excluded from the statistics. After considering boundary layer and gravity wave influences, Punta Arenas shows lower fractions of ice-containing clouds by 0.1 to 0.4 absolute difference at temperatures between −24 and -8∘C. These differences are potentially caused by the contrast in the ice-nucleating particle (INP) reservoir between the different sites.

scholarly journals Sensitivity of cirrus and mixed-phase clouds to the ice nuclei spectra in McRAS-AC: single column model simulations

2012 ◽  
Vol 12 (6) ◽  
pp. 14927-14957
Author(s):  
R. Morales Betancourt ◽  
D. Lee ◽  
L. Oreopoulos ◽  
Y. C. Sud ◽  
D. Barahona ◽  
...  
Keyword(s):  
Cloud Microphysics ◽  
Ice Nucleation ◽  
Mixed Phase ◽  
Cloud Particle ◽  
Water Path ◽  
Ice Water Path ◽  
Single Column ◽  
Mixed Phase Clouds ◽  
Ice Water ◽  
The Impact

Abstract. The salient features of mixed-phase and ice clouds in a GCM cloud scheme are examined using the ice formation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of LP and BN ice nucleation parameterizations were assessed in the GEOS-5 AGCM using the McRAS-AC cloud microphysics framework in single column mode. Four dimensional assimilated data from the intensive observation period of ARM TWP-ICE campaign was used to drive the fluxes and lateral forcing. Simulation experiments where established to test the impact of each parameterization in the resulting cloud fields. Three commonly used IN spectra were utilized in the BN parameterization to described the availability of IN for heterogeneous ice nucleation. The results show large similarities in the cirrus cloud regime between all the schemes tested, in which ice crystal concentrations were within a factor of 10 regardless of the parameterization used. In mixed-phase clouds there are some persistent differences in cloud particle number concentration and size, as well as in cloud fraction, ice water mixing ratio, and ice water path. Contact freezing in the simulated mixed-phase clouds contributed to transfer liquid to ice efficiently, so that on average, the clouds were fully glaciated at T~260 K, irrespective of the ice nucleation parameterization used. Comparison of simulated ice water path to available satellite derived observations were also performed, finding that all the schemes tested with the BN parameterization predicted average values of IWP within ±15% of the observations.

scholarly journals Studying Scale Dependency of Aerosol–Cloud Interactions Using Multiscale Cloud Formulations

2020 ◽  
Vol 77 (11) ◽  
pp. 3847-3868
Author(s):  
Timothy Glotfelty ◽  
Kiran Alapaty ◽  
Jian He ◽  
Patrick Hawbecker ◽  
Xiaoliang Song ◽  
...  
Keyword(s):  
United States ◽  
Cloud Microphysics ◽  
Western United States ◽  
Scale Dependency ◽  
Subgrid Scale ◽  
Grid Spacing ◽  
Modeling Framework ◽  
Aerosol Cloud ◽  
Spatial Coverage ◽  
Aerosol Cloud Interactions

AbstractThe Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) configuration is used to investigate the scale dependency of aerosol–cloud interactions (ACI) across the “gray zone” scales for grid-scale and subgrid-scale clouds. The impacts of ACI on weather are examined across regions in the eastern and western United States at 36, 12, 4, and 1 km grid spacing for short-term periods during the summer of 2006. ACI impacts are determined by comparing simulations with current climatological aerosol levels to simulations with aerosol levels reduced by 90%. The aerosol–cloud lifetime effect is found to be the dominant process leading to suppressed precipitation in regions of the eastern United States, while regions in the western United States experience offsetting impacts on precipitation from the cloud lifetime effect and other effects that enhance precipitation. Generally, the cloud lifetime effect weakens with decreasing grid spacing due to a decrease in relative importance of autoconversion compared to accretion. Subgrid-scale ACI are dominant at 36 km, while grid-scale ACI are dominant at 4 and 1 km. At 12 km grid spacing, grid-scale and subgrid-scale ACI processes are comparable in magnitude and spatial coverage, but random perturbations in grid-scale ACI impacts make the overall grid-scale ACI impact appear muted. This competing behavior of grid- and subgrid-scale clouds complicate the understanding of ACI at 12 km within the current WRF modeling framework. The work implies including subgrid-scale cloud microphysics and ice/mixed-phase-cloud ACI processes may be necessary in weather and climate models to study ACI effectively.

scholarly journals The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application

2019 ◽  
Vol 147 (5) ◽  
pp. 1491-1511 ◽  
Author(s):  
Timothy Glotfelty ◽  
Kiran Alapaty ◽  
Jian He ◽  
Patrick Hawbecker ◽  
Xiaoliang Song ◽  
...  
Keyword(s):  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Subgrid Scale ◽  
Liquid Water Path ◽  
Modeling Framework ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
The Impact ◽  
Weather Research

Abstract The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) is developed for studying aerosol effects on gridscale and subgrid-scale clouds using common aerosol activation and ice nucleation formulations and double-moment cloud microphysics in a scale-aware subgrid-scale parameterization scheme. Comparisons of both the standard WRF and WRF-ACI models’ results for a summer season against satellite and reanalysis estimates show that the WRF-ACI system improves the simulation of cloud liquid and ice water paths. Correlation coefficients for nearly all evaluated parameters are improved, while other variables show slight degradation. Results indicate a strong cloud lifetime effect from current climatological aerosols increasing domain average cloud liquid water path and reducing domain average precipitation as compared to a simulation with aerosols reduced by 90%. Increased cloud-top heights indicate a thermodynamic invigoration effect, but the impact of thermodynamic invigoration on precipitation is overwhelmed by the cloud lifetime effect. A combination of cloud lifetime and cloud albedo effects increases domain average shortwave cloud forcing by ~3.0 W m−2. Subgrid-scale clouds experience a stronger response to aerosol levels, while gridscale clouds are subject to thermodynamic feedbacks because of the design of the WRF modeling framework. The magnitude of aerosol indirect effects is shown to be sensitive to the choice of autoconversion parameterization used in both the gridscale and subgrid-scale cloud microphysics, but spatial patterns remain qualitatively similar. These results indicate that the WRF-ACI model provides the community with a computationally efficient tool for exploring aerosol–cloud interactions.

Application of COSMO-SPECS for remote sensing observations of mixed-phase clouds during CyCare and DACAPO-PESO

2021 ◽  
Author(s):  
Roland Schrödner ◽  
Johannes Bühl ◽  
Fabian Senf ◽  
Oswald Knoth ◽  
Jens Stoll ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Conditions ◽  
Case Studies ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
Horizontal Resolution ◽  
Model System ◽  
Mixed Phase ◽  
Real Case ◽  
Mixed Phase Clouds

<p>During the campaigns CyCyare (Limassol, Cyprus) and DACAPO-PESO (Punta Arenas, Chile), remote sensing methods were applied to study mixed-phase clouds. The two sites show contrasting aerosol loads with very clean, marine atmosphere over southern Chile and higher aerosol mass and number concentrations over Cyprus, which frequently are dust-laden. The observations suggest differing cloud properties. To further study the properties and evolution of the observed clouds as well as their relation to the ambient aerosol, the detailed coupled cloud microphysical model COSMO-SPECS is applied for selected real case studies.</p><p>The SPECtral bin cloud microphysicS model SPECS was developed to simulate cloud processes using fixed-bin size distributions of aerosol particles and of liquid and frozen hydrometeors. It was implemented in the numerical weather prediction model COSMO. COSMO-SPECS has been used for idealized case studies with horizontally periodic boundary conditions. Recently, the model system has been enhanced by considering lateral boundary conditions for the hydrometeor spectra allowing for high-resolution real case studies on nested domains. The simulations are carried out by first applying the meteorological driver COSMO using its standard two-moment microphysics scheme on multiple nests with increasing horizontal resolution. Finally, the COSMO-SPECS model system is applied on the innermost domain with a horizontal resolution of a few hundred meters using boundary data derived from the finest driving COSMO domain. For this purpose, the bulk hydrometeor fields of the driving model need to be translated into the corresponding hydrometeor mass and number distributions of SPECS’ hydrometeor spectra.</p><p>In this work, we present first results for selected case-studies of mixed-phase clouds observed during CyCyare and DACAPO-PESO. The results of the model simulations are compared against the LIDAR and cloud radar observations at the two sites.</p>

scholarly journals Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

2010 ◽  
Vol 10 (17) ◽  
pp. 8173-8196 ◽  
Author(s):  
A. Muhlbauer ◽  
T. Hashino ◽  
L. Xue ◽  
A. Teller ◽  
U. Lohmann ◽  
...  
Keyword(s):  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Small Scale ◽  
Orographic Precipitation ◽  
Model Intercomparison ◽  
Droplet Coalescence ◽  
Aerosol Cloud ◽  
Aerosol Effect ◽  
Mixed Phase Clouds

Abstract. Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from −19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result. Furthermore, it is found that neither a decrease in cloud droplet coalescence nor a decrease in riming necessarily implies a decrease in precipitation due to compensation effects by other microphysical pathways. The simulations suggest that mixed-phase conditions play an important role in buffering the effect of aerosol perturbations on cloud microphysics and reducing the overall susceptibility of clouds and precipitation to changes in the aerosol number concentrations. As a consequence the aerosol effect on precipitation is suggested to be less pronounced or even inverted in regions with high terrain (e.g., the Alps or Rocky Mountains) or in regions where mixed-phase microphysics is important for the climatology of orographic precipitation.

scholarly journals A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

2013 ◽  
Vol 6 (4) ◽  
pp. 1275-1298 ◽  
Author(s):  
M. Leriche ◽  
J.-P. Pinty ◽  
C. Mari ◽  
D. Gazen
Keyword(s):  
Wet Deposition ◽  
Mesoscale Model ◽  
Three Dimensional ◽  
Chemical Species ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Two Dimensional ◽  
Deposition Rates ◽  
Scavenging Efficiency ◽  
Ice Phase

Abstract. A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.

Assessment of the impact of INP and CCN perturbations on mixed-phase cloud microphysics using a spectral-bin model and reference observations

2020 ◽  
Author(s):  
Junghwa Lee ◽  
Patric Seifert ◽  
Tempei Hashino ◽  
Roland Schrödner ◽  
Michael Weger ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Doppler Spectrum ◽  
Small Scale ◽  
Prediction System ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Mixed Phase Clouds ◽  
The Impact

<p>Ice- and mixed-phase clouds largely contribute to global precipitation due to their high spatiotemporal coverage. It has been highlighted that aerosol-cloud interaction is a critical factor. However, our current understanding of the complexity of their microphysical properties is still rather limited.  </p><p>In this talk, we will discuss the impact of perturbations of the cloud condensation nuclei (CCN) and ice-nucleating particle (INP) on the structure and composition of mixed-phase clouds. The main methods are ground-based observations (i.e., Ka-band polarimetric cloud radar) as well as the spectral-bin microphysical methodology called AMPS (Advanced Microphysics Prediction System). Until now, significant efforts have been underway to improve microphysical processes in AMPS, such as the schemes for immersion freezing and habit prediction. Despite these endeavors, it is still challenging using modeling alone to resolve such complexity of microphysical processes due to many parameterizations and assumptions. In particular, the ice habit prediction system in AMPS is sensitive to the 3-D Eulerian advection scheme. Meanwhile, the Doppler-spectra derived from polarimetric cloud radar enables us to retrieve the hydrometeor habit of the significant signal peak in the Doppler spectrum of mixed-phase clouds. The synergy between the above mentioned advanced modeling approach and state-of-the-art observation techniques are in our study used to evaluate the effects of the CCN and INP perturbations on mixed-phase clouds. </p><p>The steps are as follows. First of all, we will present the evaluation of a case study of a mixed-phase cloud by observation data. In the course of the work, AMPS is coupled with the German weather prediction system COSMO (Consortium for Small-scale Modeling) model. We choose an observation dataset from the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign in Cabauw, Netherlands, which was conducted during fall 2014. Also, we use the radar forward operator CR-SIM (Cloud Resolving Model Radar Simulator) that translates the dataset of simulation output into radar variables. Therefore, we will present direct comparisons between ground-based observation and modeling datasets. In the next step, AMPS is coupled with a simple 1-D dynamic core KiD (Kinematic Driver for microphysics intercomparison), so-called KiD-AMPS. In doing so, we will discuss the comparison with other schemes (i.e., Morrison 2-moment). Finally, in the frame of KiD-AMPS, we will debate the impact of the CCN and INP perturbations on mixed-phase clouds. </p>

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