Cloud-Resolving Model Intercomparison of an MC3E Squall Line Case: Part II. Stratiform Precipitation Properties
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54 ENVIRONMENTAL SCIENCES↗
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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.↗
Convective-Stratiform Precipitation Variability at Seasonal Scale from Eight Years of TRMM Observations: Implications for Multiple Modes of Diurnal Variability
This study investigated the variability of convective and stratiform rainfall from eight years (1998-2005) of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and TRMM Microwave Imager (TMI) measurements--focusing on seasonal diurnal variability. The main scientific goals are: (1) to understand the climatological variability of these two dominant forms of precipitation across the four cardinal seasons and over continents and oceans separately, and (2) to understand how differences in convective and stratiform rainfall variations ultimately determine how diurnal variability of total rainfall is modulated into multiple modes. There are distinct day-night differences for both convective and stratiform rainfall. Oceanic (continental) convective rainfall is up to 25% (50%) greater during nighttime (daytime) than daytime (nighttime). Seasonal variability of convective rainfall's day-night difference is relatively small, while stratiform rainfall exhibits very apparent day-night variations with a seasonal variability of these variations. There are consistent late evening diurnal peaks without obvious seasonal variations over ocean for convective, stratiform, and total rainfall. Over continents, convective and total rainfall exhibit a consistent dominant afternoon peak with little seasonal variability--with a late evening secondary peal exhibiting seasonal variation. Stratiform rainfall over continents shows a consistent strong late evening peak with a weak afternoon peak--with the afternoon mode undergoing seasonal variability. Therefore, the diurnal characteristics of stratiform rainfall control the afternoon secondary maximum of oceanic rainfall and the late evening secondary peak of continental rainfall. Even at seasonal-regional scale spatially or an interannual global scale temporally, the secondary mode can become very pronounced, but on an intermittent basis. Overall, the results demonstrate the importance of partitioning total rainfall into convective and stratiform components and that diurnal modes largely arise from distinct diurnal stratiform variations modulating convective variations.
Yang, Song↗
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↗
Improved Algorithm to Estimate Convective and Stratiform Rain from TRMM Microwave Radiometer Data
The rain rates associated with Mesoscale Convective Systems (MCSS) deduced from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) follow the well known log-normal type frequency distribution characteristic of conventional radars and rain gauges. On the other hand, the current microwave radiometer rain retrieval algorithms cannot give good representations of convective and stratiform precipitation. Thus they capture poorly this log-normal character. In particular, this is noticed clearly over land areas. The objective of the present study is to improve TRMM Microwave Imager (TMI) retrievals of convective and stratiform rain to a level comparable to the PR. For this purpose, we have developed a TMI rain retrieval algorithm that depends primarily on the 85 GHz brightness temperatures (Tbs) and their spatial distribution. We emphasize the 85 GHz channel because of its fine footprint size (about 5.5 km) and strong extinction property. The other spectral channels, because they are poorer in these respects, are given less importance. The brightness temperatures and spatial distribution information in the 85 GHz allows us to detect thunderstorms, or cumulonimbus clouds (Cbs), that are in different stages of development, as well as stratiform rain outside of these Cbs. Utilizing our retrieval technique, we have produced maps of convective and stratiform rain for several MCS events over land and ocean that agree well with those given by the PR. On average, the convective and stratiform rain rates given by our technique have an accuracy of about 15 % with respect to those given by the PR.
Prabhakara, C.↗
TRMM Precipitation Radar and Microwave Imager Observations of Convective and Stratiform Rain and Their Theoretical Implications
Theoretical models of radiative transfer are developed to simulate the 85 GHz brightness temperature, T85, observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer as a function of rain rate. These simulations are performed separately over regions of convective and stratiform rain. For the purpose of constructing vertical profiles of hydrometeors in these regions, guidance is taken from TRMM Precipitation Radar (PR) observations, and from recent investigations of LDR and Z(sub DR) measurements made by land-based polarimetric radars. We find that for a given rain rate, the extinction in 85 GHz due to hydrometeors above the freezing level is relatively weak in convective regions compared to that in stratiform regions. The hydrometeor profile above the freezing level responsible for this weak extinction in convective regions is inferred, from LDR and Z(sub DR) observations and theoretical considerations, to contain two layers: 1) a layer of two km thickness with mixed phase particles, liquid drops and graupel, directly above the freezing level, and 2) a layer of graupel extending from the top of the mixed-phase layer to the cloud top. Strong extinction in the stratiform regions is inferred to result from slowly-falling, low-density ice aggregates (snow) above the freezing level. These theoretical results are consistent with T85 measured by TMI and the rain rate deduced from PR for convective and stratiform rain regions. On the basis of this study we infer that the accuracy of the rain rate sensed by TMI depends critically on the specification of the convective or stratiform nature of the rain.
Prabhakara, C.↗
Use of TRMM Data to Test an Improved Parameterization of Stratiform Precipitation
We successfully implemented our EAUcup parameterization of convection in our most recent geodesic-grid version of the Colorado State University General Circulation Model (CSU GCM). Tendencies due to convection and large-scale cloud microphysics are computed using the same time-step, allowing smoother interactions between convective and large-scale moist processes. Figures illustrate our most recent progress on the simulation of convective and stratiform precipitations for January. Comparisons against TRMM precipitation radar (PR) data would reveal a systematic overestimation of the simulated monthly-mean convective rainfall over well-known areas of deep convection. One major deficiency in the global distribution of stratiform precipitation simulated in the CSU GCM is the lack of stratiform precipitation over land in the tropics. This result strongly disagree with Fowler and Randall who show that convective and stratiform precipitations always coexist and that their ratio to the total precipitation is about 0.5. We believe that stratiform precipitation over land evaporates before reaching the ground because the lower troposphere remains too dry in response to the lack of convective detrainment occurring immediately above the Planetary Boundary Layer (PBL). This issue is further investigated at present. We made significant progress in the development of our parameterization of fractional cloudiness. As an example of our ongoing research effort, a figure shows the global distribution of the cloud ice mixing ratio and corresponding fractional area of ice clouds at 250 hPa. These results were obtained using our latitude-longitude grid version of the CSU GCM. There is a nice correspondence between areas of high (low) values of the cloud ice mixing ratio and the cloud fraction. A nice correspondence between the global distribution of the cloud water mixing ratio and fraction of water clouds in the lower troposphere can also be found. We are pursuing this effort, but in the geodesic version of the GCM. We hope to be able to make comparison of the simulated precipitation against TRMM precipitation data in the near future.
Randall, David A.↗
Relating Convective and Stratiform Rain to Latent Heating
The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate-high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.58 horizontal resolution, the occurrence of conditional rain rates over 100 mm/day is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations. An improved convective-stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.
Tao, Wei-Kuo↗
Drop Size Distribution - Based Separation of Stratiform and Convective Rain
For applications in hydrology and meteorology, it is often desirable to separate regions of stratiform and convective rain from meteorological radar observations, both from ground-based polarimetric radars and from space-based dual frequency radars. In a previous study by Bringi et al. (2009), dual frequency profiler and dual polarization radar (C-POL) observations in Darwin, Australia, had shown that stratiform and convective rain could be separated in the log10(Nw) versus Do domain, where Do is the mean volume diameter and Nw is the scaling parameter which is proportional to the ratio of water content to the mass weighted mean diameter. Note, Nw and Do are two of the main drop size distribution (DSD) parameters. In a later study, Thurai et al (2010) confirmed that both the dual-frequency profiler based stratiform-convective rain separation and the C-POL radar based separation were consistent with each other. In this paper, we test this separation method using DSD measurements from a ground based 2D video disdrometer (2DVD), along with simultaneous observations from a collocated, vertically-pointing, X-band profiling radar (XPR). The measurements were made in Huntsville, Alabama. One-minute DSDs from 2DVD are used as input to an appropriate gamma fitting procedure to determine Nw and Do. The fitted parameters - after averaging over 3-minutes - are plotted against each other and compared with a predefined separation line. An index is used to determine how far the points lie from the separation line (as described in Thurai et al. 2010). Negative index values indicate stratiform rain and positive index indicate convective rain, and, moreover, points which lie somewhat close to the separation line are considered 'mixed' or 'transition' type precipitation. The XPR observations are used to evaluate/test the 2DVD data-based classification. A 'bright-band' detection algorithm was used to classify each vertical reflectivity profile as either stratiform or convective, depending on whether or not a clearly-defined melting layer is present at an expected height, and if present, maximum reflectivity within the melting layer as well as the corresponding height are determined. We will present results of quantitative comparisons between the XPR observations-based classifications and the simultaneous 2DVD data-based classifications. Time series comparisons will be presented for thirteen events in Huntsville.
Thurai, Merhala↗
Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments
During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.
Lightning↗
Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments
During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.
Lightning↗
Convective and stratiform components of a Winter Monsoon Cloud Cluster determined from geosynchronous infrared satellite data
The horizontal precipitation structure of cloud clusters observed over the South China Sea during the Winter Monsoon Experiment (WMONEX) is analyzed using a convective-stratiform technique (CST) developed by Adler and Negri (1988). The technique was modified by altering the method for identifying convective cells in the satellite data, accounting for the extremely cold cloud tops characteristic of the WMONEX region, and modifying the threshold infrared temperature for the boundary of the stratiform rain area. The precipitation analysis was extended to the entire history of the cloud cluster by applying the modified CST to IR imagery from geosynchronous-satellite observations. The ship and aircraft data from the later period of the cluster's lifetime make it possible to check the locations of convective and stratiform precipitation identified by the CST using in situ observations. The extended CST is considered to be effective for determining the climatology of the convective-stratiform structure of tropical cloud clusters.
Goldenberg, Stanley B.↗
Vertical Structure of Stratiform Rain During TEFLUN-B and TRMM-LBA as Derived From an Airborne Radar Perspective
The NASA aircraft instrumented with airborne radars overflew a number of stratiform rain systems during the Texas and Florida Underflights Experiment-B TEFLUN-B) and TRMM-LBA (LBA). TEFLUN-B was conducted near Melbourne Florida during late Summer 1998 for validation of the TRMM satellite. LBA was conducted in Rondonia, Brazil in the Amazon region. Key in these campaigns were the ER-2 and DC-8 aircraft, as well as extensive ground-validation networks including the NCAR S-band (S-POL) polarization radar and University of North Dakota Citation II in situ microphysics measurements. This paper compares the vertical structure of precipitation and vertical motions for four cases: 5 September 1998 and 13 August 1998 during TEFLUN-B and 17 February 1999 and 21 February 1999 during LBA. Both these stratiform systems were within close range of the S-POL radar, and were sampled with downlooking radars and radiometers on the ER-2 (and DC-8 during LBA). Emphasis in the paper is on statistics of the vertical hydrometeor profiles, and their relation to the vertical velocity structure deduced from the ER-2 Doppler Radar (EDOP) measurements. These profiles are used to identify whether growth regions exist as would be expected with mesoscale updrafts often associated with stratiform regions. Finally, rain rates in the stratiform rain derived from EDOP and S-POL are compared.
Heymsfield, Gerald M.↗