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>

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.

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

2012 ◽  
Vol 12 (22) ◽  
pp. 10679-10692 ◽  
Author(s):  
R. Morales Betancourt ◽  
D. Lee ◽  
L. Oreopoulos ◽  
Y. C. Sud ◽  
D. Barahona ◽  
...  
Keyword(s):  
Cloud Microphysics ◽  
Ice Nucleation ◽  
Mixed Phase ◽  
Water Path ◽  
Ice Water Path ◽  
Single Column ◽  
Effective Transfer ◽  
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 nucleation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of both parameterizations was 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 were 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 describe the availability of IN for heterogeneous ice nucleation. The results showed 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 were 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 the effective transfer of liquid to ice, 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 Detailed dual-Doppler structure of Kelvin-Helmholtz waves from an airborne profiling radar over complex terrain. Part II: Evidence for precipitation enhancement from observations and modeling

2021 ◽  
Author(s):  
Coltin Grasmick ◽  
Bart Geerts ◽  
Xia Chu ◽  
Jeffrey R. French ◽  
Robert M. Rauber
Keyword(s):  
Cloud Microphysics ◽  
Mixed Phase ◽  
Small Scale ◽  
Eddy Simulation ◽  
Stratiform Clouds ◽  
Ice Water Content ◽  
Microphysical Processes ◽  
Scale Turbulence ◽  
Ice Water ◽  
Quantitative Impact

AbstractKelvin-Helmholtz (KH) waves are a frequent source of turbulence in stratiform precipitation systems over mountainous terrain. KH waves introduce large eddies into otherwise laminar flow, with updrafts and downdrafts generating small-scale turbulence. When they occur in-cloud, such dynamics influence microphysical processes that impact precipitation growth and fallout. Part I of this paper used dual-Doppler, 2D wind and reflectivity measurements from an airborne cloud radar to demonstrate the occurrence of KH waves in stratiform orographic precipitation systems and identified four mechanisms for triggering KH waves. In Part II, we use similar observations to explore the effects of KH wave updrafts and turbulence on cloud microphysics. Measurements within KH wave updrafts reveal the production of liquid water in otherwise ice-dominated clouds, which can contribute to snow generation or enhancement via depositional and accretional growth. Fallstreaks beneath KH waves contain higher ice water content, composed of larger and more numerous ice particles, suggesting that KH waves and associated turbulence may also increase ice nucleation.A Large-Eddy Simulation (LES), designed to model the microphysical response to the KH wave eddies in mixed phase cloud, shows that depositional and accretional growth can be enhanced in KH waves, resulting in more precipitation when compared to a baseline simulation. While sublimation and evaporation occur in KH downdrafts, persistent supersaturation with respect to ice allows for net increase in ice mass. These modeling results and observations suggest that KH waves embedded in mixed-phase stratiform clouds may increase precipitation, although the quantitative impact remains uncertain.

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 Numerical simulations of June 7, 2020 convective precipitation over Slovakia using deterministic, probabilistic, and convection-permitting approaches

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 571-607
Author(s):  
André Simon ◽  
Martin Belluš ◽  
Katarína Čatlošová ◽  
Mária Derková ◽  
Martin Dian ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Weather Prediction ◽  
Severe Weather ◽  
Precipitation Forecast ◽  
Convective Precipitation ◽  
Small Scale ◽  
Limited Area ◽  
Systematic Effect ◽  
The Impact

The paper presented is dedicated to the evaluation of the influence of various improvements to the numerical weather prediction (NWP) systems exploited at the Slovak Hydrometeorological Institute (SHMÚ). The impact was illustrated in a case study with multicell thunderstorms and the results were confronted with the reference analyses from the INCA nowcasting system, regional radar reflectivity data, and METEOSAT satellite imagery. The convective cells evolution was diagnosed in non-hydrostatic dynamics experiments to study weak mesoscale vortices and updrafts. The growth of simulated clouds and evolution of the temperature at their top were compared with the brightness temperature analyzed from satellite imagery. The results obtained indicated the potential for modeling and diagnostics of small-scale structures within the convective cloudiness, which could be related to severe weather. Furthermore, the non-hydrostatic dynamics experiments related to the stability and performance improvement of the time scheme led to the formulation of a new approach to linear operator definition for semi-implicit scheme (in text referred as NHHY). We demonstrate that the execution efficiency has improved by more than 20%. The exploitation of several high resolution measurement types in data assimilation contributed to more precise position of predicted patterns and precipitation representation in the case study. The non-hydrostatic dynamics provided more detailed structures. On the other hand, the potential of a single deterministic forecast of prefrontal heavy precipitation was not as high as provided by the ensemble system. The prediction of a regional ensemble system A-LAEF (ALARO Limited Area Ensemble Forecast) enhanced the localization of precipitation patterns. Though, this was rather due to the simulation of uncertainty in the initial conditions and also because of the stochastic perturbation of physics tendencies. The various physical parameterization setups of A-LAEF members did not exhibit a systematic effect on precipitation forecast in the evaluated case. Moreover, the ensemble system allowed an estimation of uncertainty in a rapidly developing severe weather case, which was high even at very short range.

scholarly journals Vehicle-to-Vehicle Radio Channel Characteristics for Congestion Scenario in Dense Urban Region at 5.9 GHz

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yishui Shui ◽  
Fang Li ◽  
Junyi Yu ◽  
Wei Chen ◽  
Changzhen Li ◽  
...  
Keyword(s):  
Communication Systems ◽  
Radio Channel ◽  
Average Power ◽  
Urban Region ◽  
Doppler Spectrum ◽  
Small Scale ◽  
Power Delay Profile ◽  
Car Following ◽  
Vehicle To Vehicle ◽  
The Impact

This paper reports the results of a car-following measurement of the wireless propagation channel at 5.9 GHz on a seriously congested urban road in Wuhan, China. The small-scale amplitude-fading distribution was determined to be a Ricean distribution using the Akaike information criterion. This result shows that this car-following scenario can be regarded as a line-of-sight radio channel. Moreover, the statistical K-factor features follow a Gaussian distribution. According to the power delay profile and average power delay profile, we found that street buildings in this dense urban environment contributed to very strong reflection phenomena. The impact of a powerful reflection is analyzed through path loss, delay, and Doppler spreads in the channel statistical properties. In the frequency domain, we observe a U-shape delay-Doppler spectrum that proved that the dense urban scenario consists of scattering channels. All these results are summarized in tabular form that will be useful in the modeling of vehicle-to-vehicle wireless communication systems.

Role of initial condition and parametric uncertainty in a severe hailstorm forecast

2021 ◽  
Author(s):  
Patrick Kuntze ◽  
Annette Miltenberger ◽  
Corinna Hoose ◽  
Michael Kunz
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Parametric Uncertainty ◽  
Radar Data ◽  
Cloud Microphysics ◽  
Initial Condition ◽  
Relative Contribution ◽  
Cloud Properties ◽  
Set Up ◽  
The Impact

<p>Forecasting high impact weather events is a major challenge for numerical weather prediction. Initial condition uncertainty plays a major role but so potentially do uncertainties arising from the representation of physical processes, e.g. cloud microphysics. In this project, we investigate the impact of these uncertainties for the forecast of cloud properties, precipitation and hail of a selected severe convective storm over South-Eastern Germany.<br>To investigate the joint impact of initial condition and parametric uncertainty a large ensemble including perturbed initial conditions and systematic variations in several cloud microphysical parameters is conducted with the ICON model (at 1 km grid-spacing). The comparison of the baseline, unperturbed simulation to satellite, radiosonde, and radar data shows that the model reproduces the key features of the storm and its evolution. In particular also substantial hail precipitation at the surface is predicted. Here, we will present first results including the simulation set-up, the evaluation of the baseline simulation, and the variability of hail forecasts from the ensemble simulation.<br>In a later stage of the project we aim to assess the relative contribution of the introduced model variations to changes in the microphysical evolution of the storm and to the fore- cast uncertainty in larger-scale meteorological conditions.</p>

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