Cloud-Resolving Model Intercomparison of an MC3E Squall Line Case: Part II. Stratiform Precipitation Properties
Not Available
54 ENVIRONMENTAL SCIENCES↗
SEARCH · Search NASA
Results for “stratiform”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Hydrometeor Transport and the Stratiform Water Budget in Amazonian Mesoscale Convective Systems
A significant portion of precipitation falls within the stratiform regions of mesoscale convective systems (MCSs). These regions are formed from convective clouds that have either weakened and formed a horizontally stratified structure or have advected hydrometeors to form a trailing-stratiform region, with further precipitation growth promoted by in situ dynamical and microphysical processes. Green Ocean Amazon 2014/5 (GoAmazon2014/5) field campaign observations are used to quantify the stratiform water budget of six MCSs (three each from the wet and dry seasons) utilizing the framework from Leary and Houze, with an emphasis on the transfer of hydrometeors (C A ) from the convective to the stratiform regions. The storms were predominantly leading-line/trailing-stratiform MCSs, but two had embedded convection in the stratiform region, which can complicate water budget calculations. A pulse-like pattern with a mean interval of 21 min occurs in C A during each storm resulting from a lag between the initial convective updrafts and the subsequent hydrometeor transport and sedimentation in the stratiform region. Here, the peaks in C A were followed by peaks in hydrometeor growth associated with the mesoscale updraft (C mu ) in the stratiform region. Averaged over the six storms, the positive contributions of C A and C mu to the stratiform water budget were roughly equal, although storm-to-storm variations existed. Negative contributions from evaporation below cloud base in the mesoscale downdraft and detrainment from the stratiform region into the nonprecipitating anvil cloud and environment accounted for 53% and 21% of the sum of C A and C mu , respectively, resulting in a mean stratiform region precipitation efficiency of 26%.
54 ENVIRONMENTAL SCIENCES↗
Subtropical marine low stratiform cloud deck spatial errors in the E3SMv1 Atmosphere Model
Marine low-level clouds continue to be poorly simulated in models despite many studies and field experiments devoted to their improvement. Here we focus on the spatial errors in the cloud decks in the Department of Energy Earth system model (E3SM) relative to the satellite climatology by calculating centroid distances, area ratios, and overlap ratios. Since model dynamics is better simulated than clouds, these errors are attributed primarily to the model physics. To gain additional insight, we performed a sensitivity run in which model winds were nudged to those of reanalysis. This results in a large change (but not necessarily an improvement) in the simulated cloud decks. These differences between simulations are mainly due to the interactions between model dynamics and physics. These results suggest that both model physics (widely recognized) and its interaction with dynamics (less recognized) are important to model improvement in simulating these low-level clouds.
Brunke, Michael A.↗
Three-Dimensional Convective–Stratiform Echo-Type Classification and Convectivity Retrieval from Radar Reflectivity
The Echo Classification from COnvectivity (ECCO) algorithm identifies convective and stratiform types of radar echo in three dimensions. It is based on the calculation of reflectivity texture—a combination of the intensity and the heterogeneity of the radar echoes on each horizontal plane in a 3D Cartesian volume. Reflectivity texture is translated into convectivity, which is designed to be a quantitative measure of the convective nature of each 3D radar grid point. It ranges from 0 (100% stratiform) to 1 (100% convective). By thresholding convectivity, a more traditional qualitative categorization is obtained, which classifies radar echoes as convective, mixed, or stratiform. In contrast to previous algorithms, these echo-type classifications are provided on the full 3D grid of the reflectivity field. The vertically resolved classifications, in combination with temperature data, allow for subclassifications into shallow, mid-, deep, and elevated convective features, and low, mid-, and high stratiform regions—again in three dimensions. The algorithm was validated using datasets collected over the U.S. Great Plains during the PECAN field campaign. An analysis of lightning counts shows ~90% of lightning occurring in regions classified as convective by ECCO. A statistical comparison of ECCO echo types with the well-established GPM radar precipitation-type categories show 84% (88%) of GPM stratiform (convective) echo being classified as stratiform (convective) or mixed by ECCO. ECCO was applied to radar grids for the continental United States, the United Arab Emirates, Australia, and Europe, illustrating its robustness and adaptability to different radar grid characteristics and climatic regions.
Radars/Radar observations↗
Comparison of Antarctic and Arctic Single-Layer Stratiform Mixed-Phase Cloud Properties Using Ground-Based Remote Sensing Measurements
Ground-based remote sensing measurements from the Atmospheric Radiation Measurement Program (ARM) West Antarctic Radiation Experiment (AWARE) campaign at the McMurdo station and the ARM North Slope of Alaska (NSA) $Utqia\dot{g}vik$ site are used to retrieve and analyze single-layer stratiform mixed-phase cloud macro- and microphysical properties for these different polar environments. Single-layer stratiform mixed-phase clouds have annual frequencies of occurrence of ~14.7% at $Utqia\dot{g}vik$ and ~7.3% at McMurdo, with the highest occurrences in early autumn. Compared to $Utqia\dot{g}vik$, stratiform mixed-phase clouds at McMurdo have overall higher and colder cloud-tops, thicker ice layer depth, thinner liquid- dominated layer depth, and smaller liquid water path. These properties reflect clear seasonal variations. Supercooled liquid fraction at McMurdo is greater than at $Utqia\dot{g}vik$ because, at a given temperature, McMurdo clouds have comparable liquid water paths but smaller ice water paths. Assessment of retrieved cloud microphysical properties show that, compared to $Utqia\dot{g}vik$, stratiform mixed-phase clouds at McMurdo have greater liquid droplet number concentration, smaller layer-mean effective radius, and smaller ice water content and ice number concentration at a given cloud-top temperature. These relationships may be related to different aerosol loading and chemical composition, and environment dynamics. Findings introduced in this report can be used as observational constraints for model representations of stratiform mixed-phase clouds.
54 ENVIRONMENTAL SCIENCES↗
Vertically Resolved Convective–Stratiform Echo-Type Identification and Convectivity Retrieval for Vertically Pointing Radars
Using data from the airborne HIAPER Cloud Radar (HCR), a partitioning algorithm (ECCO-V) that provides vertically resolved convectivity and convective versus stratiform radar-echo classification is developed for vertically pointing radars. The algorithm is based on the calculation of reflectivity and radial velocity texture fields that measure the horizontal homogeneity of cloud and precipitation features. The texture fields are translated into convectivity, a numerical measure of the convective or stratiform nature of each data point. The convective–stratiform classification is obtained by thresholding the convectivity field. Subcategories of low, mid-, and high stratiform, shallow, mid-, deep, and elevated convective, and mixed echoes are introduced, which are based on the melting-layer and divergence-level altitudes. As the algorithm provides vertically resolved classifications, it is capable of identifying different types of vertically layered echoes, and convective features that are embedded in stratiform cloud layers. Its robustness was tested on data from four HCR field campaigns that took place in different meteorological and climatological regimes. The algorithm was adapted for use in spaceborne and ground-based radars, proving its versatility, as it is adaptable not only to different radar types and wavelengths, but also different research applications.
54 ENVIRONMENTAL SCIENCES↗
A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds
Abstract Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale environment is in statistical equilibrium with a large number of small and short‐lived convective clouds. They fail to capture nonequilibrium transitions such as the diurnal cycle and the formation of mesoscale convective systems as well as observed precipitation statistics and extremes. Informed by analysis of radar observations, cloud‐permitting model simulation, theory, and machine learning, this work presents a new stochastic cloud population dynamics model for characterizing the interactions between convective and stratiform clouds, with the goal of informing the representation of these interactions in global climate models. Fifteen wet seasons of precipitating cloud observations by a C‐band radar at Darwin, Australia are fed into a machine learning algorithm to obtain transition functions that close a set of coupled equations relating large‐scale forcing, mass flux, the convective cell size distribution, and the stratiform area. Under realistic large‐scale forcing, the derived transition functions show that, on the one hand, interactions with stratiform clouds act to dampen the variability in the size and number of convective cells and therefore in the convective mass flux. On the other, for a given convective area fraction, a larger number of smaller cells is more favorable for the growth of stratiform area than a smaller number of larger cells. The combination of these two factors gives rise to solutions with a few convective cells embedded in a large stratiform area, reminiscent of mesoscale convective systems.
54 ENVIRONMENTAL SCIENCES↗
Aerosol effects on the anvil characteristics, cold pool forcing and stratiform-convective precipitation partitioning and latent heating of mesoscale convective systems
The overarching science goal of this project has been to assess the impacts of aerosols on mesoscale convective systems (MCSs). More specifically we have investigated the impacts of (a) aerosol types, (b) aerosol concentrations, and (c) the vertical and horizontal location of aerosols on the (1) anvil cloud characteristics and feedbacks; (2) total precipitation and the partitioning between convective and stratiform precipitation; (3) the vertical heating structure; (4) hydrometeor size distributions; and (5) the strength and intensity of the cold pools and updrafts. These have been achieved both through observational analyses and high-resolution cloud-resolving model simulations of three MCSs that were observed during the MC3E field campaign (25 April, 20 May and 23 May 2011). The primary findings of these research are the following: Condensation and deposition are the primary contributors to MCS latent warming, when compared to riming and nucleation processes. In terms of MCS latent cooling, sublimation, melting, and evaporation all play significant roles. Throughout the MCS lifecycle, convective regions demonstrate an approximately linear decrease in the magnitudes of latent heating rates, while latent heating within stratiform regions is associated with transitions between MCS flow regimes including the rear inflow jet. Such information regarding the temporal evolution of latent heating within convective and stratiform MCS regions could be useful in developing parameterizations representing convective organization. Increasing aerosol concentration from a clean continental to a highly polluted state produces an increase in the riming rates of cloud water, which results in less lofted cloud water in polluted environments. Aerosol-induced trends in the cloud mixing ratio profiles are, however, nonmonotonic in the mixed phase region, such that a moderate increase in aerosol concentration produces the greatest reduction in cloud water. Less lofted cloud water due to enhanced riming rates leads to reduced anvil ice mixing ratios but to greater numbers of small ice crystals within the anvil. In spite of reduced anvil ice mixing ratio, the anvil clouds exhibit greater areal coverage, increased albedo, reduced cloud top cooling, and reduced net radiative flux, which produces an aerosol-induced warming (reduced cooling) effect in these MCSs. Lower-tropospheric aerosol particles largely influence the MCS precipitation response directly rearward of the leading cold pool boundary. However, further backward in the MCS, the relative impact of lower- versus mid-tropospheric aerosol particles is strongly dependent on the MCS structure and differences in the line-normal wind shear. Mid-tropospheric aerosol particles are able to activate new cloud droplets in the mid-tropospheric levels of convective updrafts and thereby enhance mixed-phase precipitation through increased cloud riming.
54 ENVIRONMENTAL SCIENCES↗
Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E
In this study, the liquid water path (LWP) below the melting layer in stratiform precipitation systems is retrieved, which is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP). The retrieval algorithm uses measurements from the vertically pointing radars (VPRs) at 35 and 3 GHz operated by the US Department of Energy Atmospheric Radiation Measurement (ARM) and National Oceanic and Atmospheric Administration (NOAA) during the field campaign Midlatitude Continental Convective Clouds Experiment (MC3E). The measured radar reflectivity and mean Doppler velocity from both VPRs and spectrum width from the 35 GHz radar are utilized. With the aid of the cloud base detected by a ceilometer, the LWP in the liquid layer is retrieved under two different situations: (I) no cloud exists below the melting base, and (II) cloud exists below the melting base. In (I), LWP is primarily contributed from raindrops only, i.e., RLWP, which is estimated by analyzing the Doppler velocity differences between two VPRs. In (II), cloud particles and raindrops coexist below the melting base. The CLWP is estimated using a modified attenuation-based algorithm. Two stratiform precipitation cases (20 and 11 May 2011) during MC3E are illustrated for two situations, respectively. With a total of 13 h of samples during MC3E, statistical results show that the occurrence of cloud particles below the melting base is low (9 %); however, the mean CLWP value can be up to 0.56 kg m -2 , which is much larger than the RLWP (0.10 kg m -2 ). When only raindrops exist below the melting base, the average RLWP value is larger (0.32 kg m -2 ) than the with-cloud situation. The overall mean LWP below the melting base is 0.34 kg m -2 for stratiform systems during MC3E.
54 ENVIRONMENTAL SCIENCES↗
EPCAPE Stratiform Cloud Analysis for Radiative Properties Experiment (SCARPE) Field Campaign Report
A unique attribute of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) is the availability of an elevated secondary measurement site just 5 km from the main U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on Scripps Pier. Mount Soledad, at 250 m elevation, offers the ability to frequently measure aerosol chemical and microphysical properties within the low-level Eastern Pacific coastal stratiform clouds that the AMF is observing from below. Based on the EPCAPE experiment design to deploy three major systems on Mount Soledad—the scanning radars, the Russell aerosol mobile laboratory, and an ARM microwave radiometer (MWR)—an additional plan was made to deploy a suite of Eppley Laboratory radiometers at this site to measure the radiative response to instantaneous changes in observed aerosol properties and MWR retrieved cloud liquid water path (LWP). This supplemental field campaign was proposed as the Stratiform Cloud Analysis for Radiative Properties Experiment (SCARPE).
54 ENVIRONMENTAL SCIENCES↗
Ice particle production in mid-level stratiform mixed-phase clouds observed with collocated A-Train measurements
Abstract. Collocated A-Train CloudSat radar and CALIPSO lidar measurements between 2006 and 2010 are analyzed to study primary ice particle production characteristics in mid-level stratiform mixed-phase clouds on a global scale. For similar clouds in terms of cloud top temperature and liquid water path, Northern Hemisphere latitude bands have layer-maximum radar reflectivity (ZL) that is ∼ 1 to 8 dBZ larger than their counterparts in the Southern Hemisphere. The systematically larger ZL under similar cloud conditions suggests larger ice number concentrations in mid-level stratiform mixed-phase clouds over the Northern Hemisphere, which is possibly related to higher background aerosol loadings. Furthermore, we show that springtime northern mid- and high latitudes have ZL that is larger by up to 6 dBZ (a factor of 4 higher ice number concentration) than other seasons, which might be related to more dust events that provide effective ice nucleating particles. Our study suggests that aerosol-dependent ice number concentration parameterizations are required in climate models to improve mixed-phase cloud simulations, especially over the Northern Hemisphere.
47 OTHER INSTRUMENTATION↗
Combined Effect of the Wegener–Bergeron–Findeisen Mechanism and Large Eddies on Microphysics of Mixed-Phase Stratiform Clouds
Abstract The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts and some parts of updrafts, depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about 10 L −1 , the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. At ice particle concentrations of a few tens per liter, the oscillatory regime took place due to the ice–liquid interaction. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.
54 ENVIRONMENTAL SCIENCES↗
The Microphysics of Stratiform Precipitation During OLYMPEX: Compatibility Between Triple‐Frequency Radar and Airborne In Situ Observations
Abstract The link between stratiform precipitation microphysics and multifrequency radar observables is thoroughly investigated by exploiting simultaneous airborne radar and in situ observations collected from two aircraft during the OLYMPEX/RADEX (Olympic Mountain Experiment/Radar Definition Experiment 2015) field campaign. Above the melting level, in situ images and triple‐frequency radar signatures both indicate the presence of moderately rimed aggregates. Various mass‐size relationships of ice particles and snow scattering databases are used to compute the radar reflectivity from the in situ particle size distribution. At Ku and Ka band, the best agreement with radar observations is found when using the self‐similar Rayleigh‐Gans approximation for moderately rimed aggregates. At W band, a direct comparison is challenging because of the non‐Rayleigh effects and of the probable attenuation due to ice aggregates and supercooled liquid water between the two aircraft. A variational method enables the retrieval of the full precipitation profile above and below the melting layer, by combining the observations from the three radars. Even with three radar frequencies, the retrieval of rain properties is challenging over land, where the integrated attenuation is not available. Otherwise, retrieved mean volume diameters and water contents of both solid and liquid precipitation are in agreement with in situ observations and indicate local changes of the degree of riming of ice aggregates, on the scale of 5 km. Finally, retrieval results are analyzed to explore the validity of using continuity constraints on the water mass flux and diameter within the melting layer in order to improve retrievals of ice properties.
47 OTHER INSTRUMENTATION↗
Observation and Reanalysis Derived Relationships Between Cloud and Land Surface Fluxes Across Cumulus and Stratiform Coupling Over the Southern Great Plains
Abstract Understanding interactions between low clouds and land surface fluxes is critical to comprehending Earth's energy balance, yet their relationships remain elusive, with discrepancies between observations and modeling. Leveraging long‐term field observations over the Southern Great Plains, this investigation revealed that cloud‐land interactions are closely connected to cloud‐land coupling regimes. Observational evidence supports a dual‐mode interaction: coupled stratiform clouds predominate in low sensible heat scenarios, while coupled cumulus clouds dominate in high sensible heat scenarios. Reanalysis data sets, MERRA‐2 and ERA‐5, obscure this dichotomy owing to a shortfall in representing boundary layer clouds, especially in capturing the initiation of coupled cumulus in high sensible heat scenarios. ERA‐5 demonstrates a relatively closer alignment with observational data, particularly in capturing relationships between cloud frequency and latent heat, markedly outperforming MERRA‐2. Our study underscores the necessity of distinguishing different cloud coupling regimes, essential to the understanding of their interactions for advancing land‐atmosphere interactions.
54 ENVIRONMENTAL SCIENCES↗
Final Report on “Influence of nucleation on ice microphysical properties of mixed-phase stratiform clouds”
This is a final report based on tasks supported by the Atmospheric System Research program (DOE Office of Biological and Environmental Research), DOE Award Number DE-SC0011690. This project has been focused on the following objectives: 1. Laboratory studies of immersion and contact nucleation of ice; 2. Investigation of the influence of time-dependence of ice nucleation on microphysical properties of Arctic and other thin, mixed-phase stratiform clouds; and 3. Theoretical and modeling studies of the conditions necessary for producing large droplets in clouds that can help initiate the collision—coalescence process.
54 ENVIRONMENTAL SCIENCES↗
Organisation of Diverse Mechanisms of Secondary Ice Production among Basic Convective and Stratiform Cloud-types
This 3-year DoE-funded joint project had the over-arching aim of understanding how ice is initiated in clouds of various types. Focus was given to processes of fragmentation of pre-existing ice, which can occur in positive feedback loops (‘ice multiplication’). A basic question to address was which fragmentation processes prevail in which basic cloud-types. The approach was to use cloud models and field observations, while pioneering our own lab observations of ice initiation to break the deadlock from the past lack of lab observations. Historically, the tendency of the cloud physics community to avoid doing lab observations has allowed a vast gap in knowledge about ice initiation to persist for decades. During the first part of the project, new formulations were created to treat two overlooked types of fragmentation of ice. First, sublimational breakup of ice was treated based on a theoretical formula that we fitted to a pooled dataset of lab observations published previously in the literature. Second, a new mode of fragmentation of freezing raindrops was treated, which involves a supercooled drop being hit by a more massive ice particle. Some of the secondary droplets from the impact freeze. This work was done at Manchester University by Co-I Connolly. Then during the second part, both formulations were implemented in our ‘aerosol-cloud model’ (AC). AC has a hybrid bin/bulk microphysics scheme, and now represents four processes of SIP. The accuracy of AC was evaluated for four cases typifying four basic cloud-types: slightly cold-based stratiform cloud and cold-, warm- and very warm-based convective clouds. We discovered that the warmth of cloud-base, especially in the tropics, promotes SIP processes of raindrop-freezing fragmentation and rime-splintering, and surprisingly, sublimational breakup too. It was found that breakup in ice-ice collisions is ubiquitous. Finally, a portable laboratory chamber was constructed at Lund and deployed in northern Sweden to observe breakup in graupel-snow collisions outdoors. This was seen to be even more prolific than treated in our 2018 formulation. Papers describing results are either published or soon to be published.
54 ENVIRONMENTAL SCIENCES↗
Combining Long‐Term Observations and Lagrangian Case Studies to Evaluate Stratiform Cloud Precipitation Processes in Climate Models
Final Technical Report for DE‐SC0021983 Combining Long‐Term Observations and Lagrangian Case Studies to Evaluate Stratiform Cloud Precipitation Processes in Climate Models
Russell, Lynn [Univ. of California, San Diego, CA ↗