Stratiform Area Research Articles

Review of the History of Mesoscale Convective System Forecasts on Aviation

Airports are important national resources, and Aviation Weather Services are critical to the aviation industry's success. According to the National Transportation Safety Board's (NTSB) analysis of weather-related circumstances that influence near- surface aircraft operations, wind and turbulence caused 1381 accidents, visibility, ceiling height (hc), and precipitation-related accidents occurred 485 times, and aircraft icing caused 150 accidents between 2003 and 2007. Mesoscale convective systems (MCSs) arise when cumulonimbus clouds merge into a single entity that can span hundreds of miles and continue for hours, posing a higher threat to aviation due to its size and duration. The mesoscale downdraft of a squall-line MCS's stratiform area sometimes merges with the convective downdrafts in the leading line of convection, and these mergers can produce strong effects, with the gust front surging forward and triggering new convection in the form of a “bow echo," according to Doppler radar. Bow echo events are of particular concern to forecasters because they are typically associated with strong, damaging surface winds. Because MCSs are still a major socioeconomic issue, it's critical to construct climate models that incorporate them, whether through cloud-resolving modeling or parameterization. MCS characteristics are influenced by the increasingly contaminated aerosol environment in most parts of the world, and as the Earth warms, MCS patterns will certainly change.

Impact of Assimilating Radar Data with 3D Thermodynamic Fields in an Ensemble Kalman Filter: Proof of Concept and Feasibility

Abstract This study examined the impact of assimilating 3D temperature and water vapor information in addition to radar observations in a multiscale weather system. A frontal system with extremely heavy rainfall over northern Taiwan was selected. Using the WRF–LETKF Radar Assimilation System, we performed three sets of observing system simulation experiments to assimilate radar observations with or without thermodynamic variables obtained using different methods. First, assimilating the radar data for 2 h showed better structure and short-term forecast than 1 h. Second, we assimilated radar data and thermodynamic variables from a perfect model simulation. The results of the analysis revealed that when a precipitation position error occurred in the background field, assimilating thermodynamic information with the radar data could correct the dynamic structure and shorten the spinup assimilation period, resulting in substantial improvements to the quantitative precipitation forecast. Third, we applied a thermodynamics retrieval algorithm for a feasibility study. With a warm and wet bias of the retrieved fields, assimilating the temperature data had significant impact on the midlevel of stratiform areas and the forecast of the heavy rainfall was consequently improved. Assimilating the water vapor information helped reconstruct the range and intensity of the cold pool, but the improvement of rainfall forecast was limited. The optimal results of analysis and short-term forecast were achieved when both retrieved temperature and water vapor fields were assimilated. In conclusion, assimilating thermodynamic variables in the precipitation system is feasible for shortening the spinup period of data assimilation and improving the analysis and short-term forecast.

Evaluating the Performance of a Convection-Permitting Model by Using Dual-Polarimetric Radar Parameters: Case Study of SoWMEX IOP8

In this study, a dual-polarimetric radar observation operator is established and modified for the Taiwan area for the purpose of model verification. A severe squall line case during the Southwest Monsoon Experiment Intensive Observing Period 8 (SoWMEX IOP#8) on 14 June 2008, is selected and examined. Because the operator is adopted from the use of the midlatitude region, sensitivity tests are performed to obtain the optimal setting of the operator in the subtropical region. To accurately capture the dynamic structure of the squall lines, the ensemble-based data assimilation system, which assimilates both radial wind and reflectivity data, is used to obtain the optimal analysis field on the mesoscale for evaluating the performance of model simulation. The characteristics of two microphysics schemes are investigated, and the results obtained using the schemes are compared with the S-band dual-polarimetric radar observations. The horizontal and vertical cross-sections show that the analyses resemble the observations. Both schemes can replicate the polarimetric parameter signature such as ZDR and KDP columns. When comparing model simulation with polarimetric parameters through the drawing of contour frequency by altitude diagrams (CFADs), the results reveal that the single moment microphysics scheme performs better than the double moment scheme in this case. However, the reflectivity field in the stratiform area is more accurately captured when using the double moment scheme. Furthermore, validation with polarimetric variables (ZH, ZDR and KDP) histograms shows underestimation of the KDP field in both schemes. Overall, this study indicates the benefit of assimilating radial wind and reflectivity data for the analyses of severe precipitation systems and the necessity of assimilating polarimetric parameters for the accuracy of microphysical processes, especially complex microphysics schemes in subtropical region.

A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds

AbstractTraditional 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.

Simulating a Mesoscale Convective System Using WRF With a New Spectral Bin Microphysics: 1: Hail vs Graupel

AbstractA modified Fast Spectral Bin Microphysics scheme (FSBM‐2) embedded into the Weather Research and Forecasting (WRF) model is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM‐2 uses modified source codes as compared to the current FSBM (FSBM‐1). In contrast to FSBM‐1, FSBM‐2 can simulate hail of several centimeters in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall‐line structures in both the convective and stratiform regions. In contrast, if graupel particles are used to represent high‐density hydrometeors in convective areas, the ratio of convective‐to‐stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM‐2 show a good agreement with observations. The regeneration of cloud condensational nuclei (CCN) by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8‐ to 9‐km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification.

The isotopic signature of monsoon conditions, cloud modes, and rainfall type

AbstractThis work provides a comprehensive physically based framework for the interpretation of the north Australian rainfall stable isotope record (δ18O and δ2H). Until now, interpretations mainly relied on statistical relationships between rainfall amount and isotopic values on monthly timescales. Here, we use multiseason daily rainfall stable isotope and high resolution (10 min) ground‐based C‐band polarimetric radar data and show that the five weather types (monsoon regimes) that constitute the Australian wet season each have a characteristic isotope ratio. The data suggest that this is not only due to changes in regional rainfall amount during these regimes but, more importantly, is due to different rain and cloud types that are associated with the large scale circulation regimes. Negative (positive) isotope anomalies occurred when stratiform rainfall fractions were large (small) and the horizontal extent of raining areas were largest (smallest). Intense, yet isolated, convective conditions were associated with enriched isotope values whereas more depleted isotope values were observed when convection was widespread but less intense. This means that isotopic proxy records may record the frequency of which these typical wet season regimes occur. Positive anomalies in paleoclimatic records are most likely associated with periods where continental convection dominates and convection is sea‐breeze forced. Negative anomalies may be interpreted as periods when the monsoon trough is active, convection is of the oceanic type, less electric, and stratiform areas are wide spread. This connection between variability of rainfall isotope anomalies and the intrinsic properties of convection and its large‐scale environment has important implications for all fields of research that use rainfall stable isotopes.

Cloud‐resolving model intercomparison of an MC3E squall line case: Part I—Convective updrafts

AbstractAn intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Ze > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Ze in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low‐level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low‐level vertical wind shear, and rear‐inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice‐related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no‐ice simulations mainly because of scheme differences in collision‐coalescence parameterizations.

A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

AbstractRadar-based latent heating retrievals typically apply a lookup table (LUT) derived from model output to surface rain amounts and rain type to determine the vertical structure of heating. In this study, a method has been developed that uses the size characteristics of precipitating systems (i.e., area and mean echo-top height) instead of rain amount to estimate latent heating profiles from radar observations. This technique [named the convective–stratiform area (CSA) algorithm] leverages the relationship between the organization of convective systems and the structure of latent heating profiles and avoids pitfalls associated with retrieving accurate rainfall information from radars and models. The CSA LUTs are based on a high-resolution regional model simulation over the equatorial Indian Ocean. The CSA LUTs show that convective latent heating increases in magnitude and height as area and echo-top heights grow, with a congestus signature of midlevel cooling for less vertically extensive convective systems. Stratiform latent heating varies weakly in vertical structure, but its magnitude is strongly linked to area and mean echo-top heights. The CSA LUT was applied to radar observations collected during the DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/ARM MJO Investigation Experiment (AMIE) field campaign, and the CSA heating retrieval was generally consistent with other measures of heating profiles. The impact of resolution and spatial mismatch between the model and radar grids is addressed, and unrealistic latent heating profiles in the stratiform LUT, namely, a low-level heating peak, an elevated melting layer, and net column cooling, were identified. These issues highlight the need for accurate convective–stratiform separations and improvement in PBL and microphysical parameterizations.

The Role of Vertically Propagating Gravity Waves Forced by Melting-Induced Cooling in the Formation and Evolution of Wide Cold-Frontal Rainbands

Abstract Realistic mesoscale model simulations using the Weather Research and Forecasting (WRF) Model and idealized dry simulations were used to study the mechanisms responsible for the formation and evolution of wide cold-frontal rainbands (WCFRs) associated with a wintertime cyclone that moved onto the Washington coast. The WRF simulation reproduced observed characteristics of three successively formed WCFRs, including their spacing and movement as well as the timing of the formation of two WCFRs behind the first. Sensitivity experiments showed that melting-induced cooling in the stratiform precipitation area behind the surface cold front was essential for the formation of the first and second WCFRs, whereas the third WCFR was formed by the release of potential instability within an ascent forced by upper-level frontogenesis. Enhanced frontal updrafts responsible for the first and second WCFRs were created by a superposition of a broad updraft caused by frontal dynamics and upward-propagating gravity waves generated by the melting-induced cooling. The dry simulations forced by specified cooling revealed specific mechanisms for the wave generation and the evolution of the first and second WCFRs. The gravity waves were generated at the intersection of the low-level frontal zone and the melting layer, where strong vertical shear of the cross-front wind and upshear-sloped cooling by melting cooperatively enhanced the wave generation. The formation of the second WCFR behind the first and subsequent dissipation of these WCFRs was attributed to the evolution of a wave pattern associated with the evolution of cross-front flow above the frontal zone.

Ice microphysics retrieval in the convective systems of the Indian Ocean during the CINDY–DYNAMO campaign

The last decades have shown the relevance of polarimetric radar measurements in various domains of Earth science to characterize different types of particles in natural media such as snow covers, vegetation canopy and clouds. In atmospheric physics, the need to accurately define the frozen hydrometeor properties (type, size, density) in precipitating systems is directly related to our understanding of the convective processes. These microphysical properties are also particularly critical in setting ice parameterization in models.Ground-based polarimetric radars can provide information on the most likely type of ice particles present in a sampled volume. These classifications can be used to build ice particle habit statistics once they are validated.The SPolKa classification scheme (PID, Particle IDentificator) for various types of frozen hydrometeors is compared to in-situ measurements collected during the CINDY–DYNAMO campaign in the Indian Ocean. The French Falcon-20 flew inside the polarimetric radar area measuring the particle habits with several in-situ microphysical probes (FSSP, 2DS, CPI, PIP, 2DP, Nevzorov). These in-situ data are organized as catalog of images and matched to the classifications proposed by Magono and Lee (1966) and Kikuchi et al. (2013). The PID classification and the Precipitation Imaging Probe (PIP) data images are compared over two sequences representing two different atmospheric situations: a large stratiform area sampled on November 27th, 2011 and some convective activity embedded in stratiform precipitation on December 8th, 2011.The general agreement is very good for most species. Since the PIP only provides us with a 2D image of the particles' shadow, some species are difficult to identify unambiguously and could be matched with more than one PID. This is particularly critical for species with complex history.

Climatology of Storm Characteristics in Costa Rica using the TRMM Precipitation Radar

Abstract Tropical Rainfall Measuring Mission Precipitation Radar precipitation features are analyzed to understand the role of storm characteristics on the seasonal and diurnal cycles of precipitation in four distinct regions in Costa Rica. The distribution of annual rainfall is highly dependent on the stratiform precipitation, driven largely by seasonal increases in stratiform area. The monthly distribution of stratiform rain is bimodal in most regions, but the timing varies regionally and is related to several important large-scale features: the Caribbean low-level jet, the ITCZ, and the Chorro del Occidente Colombiano (CHOCO) jet. The relative importance of convective precipitation increases on the Caribbean side during wintertime cold air surges. Except for the coastal Caribbean domain, most regions show a strong diurnal cycle with an afternoon peak in convection followed by an evening increase in stratiform rain. Along the Caribbean coast, the diurnal cycle is weaker, with evidence of convection associated with the sea breeze, as well as a nocturnal increase in storms. The behavior of extreme precipitation features with rain volume in the 99th percentile is also analyzed. They are most frequent from May to November, with notable differences between features at the beginning/end of the rainy season versus those in the middle, as well as between wet and dry seasons. Convective rain exceeds stratiform in winter and midsummer extreme features, while stratiform rain is larger at the beginning and end of the wet season. Given projected changes in precipitation and extreme events in Costa Rica for future climate change scenarios, the results indicate the importance of understanding both changes in total precipitation and in the storm characteristics.

Image Segmentation Method for Identifying Convective and Stratiform Rain using MSG SEVIRI Data

This paper provides a new method for the classification of rainfall areas in convective and stratiform rain using MSG/SEVIRI (Spinning Enhanced Visible and Infrared) data. The proposed approach is based on spectral and temporal properties of clouds. The spectral parameters used are: brightness temperature (BT) and brightness temperature differences (BTDs), and the temporal parameter (RCT10.8) is the rate of change of (BT) in the 10.8µm channel over two consecutive images. The developed rain area classification technique (RACT-DN) is based on two multilayer perceptron neural networks (MLP-D for daytime and MLP-N for nighttime) which relies on the correlation of satellite data with convective and stratiform rain. The two algorithms (MLP-D and MLP-N) are trained using as reference data from ground meteorological radar over northern Algeria. The results show that RACT-DN classifier gives accurate discrimination between convective and stratiform areas during daytime and nighttime. Index Terms—Classification, Artificial neural network, Radar, MSG image.

MSG SEVIRI Image Segmentation Using a Method Based on Spectral, Temporal and Textural Features

A new scheme for the classification of rainfall areas in convective and stratiform rain using MSG/SEVIRI (Spinning Enhanced Visible and Infrared) data is developed in this paper. The technique is based on spectral, temporal and textural properties of clouds. The introduced classification method uses as spectral parameters: brightness temperature BT(TIR10.8), brightness temperature differences BTDs (TIR10.8-TIR12.1, TIR8.7 -TIR10.8,TWV6.2-TIR10.8) during daytime and nighttime, temperature differences (TIR3.9 -TIR10.8 and TIR3.9-TWV7.3) during nighttime, and reflectances( RVIS0.6, RNIR1.6) during daytime. The textural information is based on the grey level rank approach where each pixel of the brightness temperature in the 10.8µm channel image is represented by a code which takes into account the relations between the spatial positions and the grey level ranks of the neighborhood pixels. The textural parameter of each pixel correspond to the occurrence frequency vector of a 24 pixel code possibilities computed within a window analysis of 31 x 31 pixels. The temporal parameter (RCT10.8) is the rate of change of brightness temperature over two consecutive images. The developed daytime and nighttime rain area classification technique (RACT-DN) is based on two multilayer perceptron neural networks (MLP-D for daytime and MLP-N for nighttime) which relies on the correlation of satellite data with convective and stratiform rain. The two algorithms (MLP-D and MLP-N) are trained using as reference convective and stratiform classification data from ground meteorological radar over northern Algeria. It was found that the introduction of temporal and textural parameters improved the results of discrimination between convective and stratiform areas

Water isotopic variability in response to mesoscale convective system over the tropical ocean

In tropical regions, the empirical negative relationship between the isotopic content of precipitation and rainfall amount, known as the “amount effect”, has been used as a rationale for paleohydroclimate reconstruction from isotope records. However, there is still no comprehensive physical explanation for this empirical effect. Here we reconsider the well‐known amount effect using newly available isotope data for both surface water vapor and precipitation obtained from shipboard observations. In this study, we hypothesized that stratiform rainfall associated with mesoscale convective systems (MCSs) is a key process in reducing tropical water isotopic concentrations and tested this hypothesis with an idealized MCS model. Our conceptual model reasonably accounted for several observed features and indicated that isotopic reductions in tropical oceanic regions reflect a precipitating system's change. Relatively high isotope ratios corresponded to disorganized convection. On the other hand, MCSs were characterized by lower isotope ratios with increasing stratiform area. In addition, the amplitude of this isotopic depletion was related to the scale of the precipitation system. The lowest isotopic ratios were observed during the passage of large‐scale disturbances—corresponding to the Madden‐Julian oscillation convective envelope—in which MCSs are embedded. This means that the frequent appearance of MCSs results in further decreases in the isotopic ratio of surface vapor and precipitation. From this, we conclude that the amount effect can be interpreted as the development of a precipitation system from an isolated convection cell into a large‐scale system containing several MCSs and that past large‐scale convective activity can be reconstructed from isotope records.

A real‐time automated convective and stratiform precipitation segregation algorithm in native radar coordinates

AbstractA new convective/stratiform (C/S) precipitation segregation algorithm was developed for applications with single radar volume scan data and in its native (spherical) coordinates. The new algorithm consists of two parts: the first is to find convective rainfall cores based on physical characteristics of different rainfall types, and the second is to delineate the full convective area through seeded region growing. The new scheme takes into account radar sampling characteristics and a variety of precipitation scenarios where the C/S delineation was relatively challenging. The new C/S delineation scheme has two impacts on radar quantitative precipitation estimation (QPE): (i) correctly separate convective and stratiform regions such that appropriate Ze–R relationships can be applied; (ii) correctly define the stratiform area such that a vertical profile of reflectivity (VPR) correction can be applied. The VPR correction is very important to reduce overestimation errors in radar QPEs associated with bright band. The new algorithm was tested on many events and showed improved performance over previous schemes, especially when handling strong bright band and melting graupels in stratiform precipitation. The new scheme was also tested in radar quantitative precipitation estimation (QPE) and it consistently reduced the root mean square error and mean absolute bias in the radar QPE when compared with gauges.

The separation of convective and stratiform precipitation regions of simulated Typhoon Chanchu and its sensitivity to the number concentration of cloud droplets

Following a numerical simulation study, we analyze the effect of the parameter of the cloud condensation nuclei concentration (CNP) on Typhoon Chanchu in convective, stratiform, and mixed precipitation areas based on the following three experiments: (1) a control (CTL) experiment using a mesoscale model and the Reisner-2 cloud scheme with the CNP value specified as 100cm−3; (2) a very clean marine (VCM) CNP experiment (CNP=25cm−3); (3) and a severe contamination (SC) CNP experiment (CNP=1000cm−3). We compare and analyze the simulated cloud structure and microphysical processes of the three experiments within the convective, stratiform, and mixed areas. The three precipitating areas are classified based on the ratio of cloud ice content to cloud water content at all precipitating grids proposed by Sui et al. (2007). The results show that the intensities of most microphysical processes are the largest in the convective area and the smallest in the stratiform area. Ice is dominant in the stratiform region and the water hydrometeor is dominant in the convective region. Furthermore, cloud water develops more quickly than cloud ice do in the mixed area. The response of the convective area to a varying CNP is greater than that of the stratiform area, and the mixed area is only slightly sensitive to the CNP. The dominance of cloud microphysical processes related to the growth of water hydrometeors weakens as the CNP increases.

Spatial and Temporal Evolution of a Multi‐Cell Thunderstorm Charge Structure in Coastal Areas

AbstractThe spatial and temporal variations of charge structure and the relationship with intensity of radar echo of a thunderstorm over low elevation, Shandong of China, have been analyzed with the radiation sources of lightning discharge three‐dimensional mapping system. The results indicate the charge structure was typical dipolar in the convective areas. The intensity of the positive charge region increased and the height of location rose with the development of thunderstorm. The negative charge region was in the area where the intensity of radar echo was more than 40 dBz and the positive charge region was in the 40 dBz radar echo area approximately. The charge structure was also inferred to be dipolar with low charge height and weak charge intensity in stratiform areas. In the dissipation stage of thunderstorm, the charge structure was ruptured for the different dissipation levels of different parts in cloud. The positive and negative charge regions sank in front of the cloud, and the height of the positive and negative charge regions had a little change in the middle part of the cloud, whereas the negative charge region attenuated. So the charge region was four layers in convective areas during dissipation stage. The above results show that the advantage charge generation mechanism often generates dipole or tripole charge structure and does not generate multipole charge structure. This paper also analyzes a negative cloud‐ to‐ground flash discharge process. Its charge structure is the same as the thunderstorm charge structure. So the thunderstorm charge structure can be illustrated by the observations of the three‐dimensional lightning mapping system.

A comparison of TWP‐ICE observational data with cloud‐resolving model results

Observations made during the TWP‐ICE campaign are used to drive and evaluate thirteen cloud‐resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one‐ and two‐moment microphysics, several variations on large‐scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6‐day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of ∼2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large‐scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After ∼10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud‐modulated radiative flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation‐based evaluation of the underlying micro‐ and macrophysical properties of convective and stratiform structures.

Observations of Coastally Transitioning West African Mesoscale Convective Systems during NAMMA

Observations from the NASA 10 cm polarimetric Doppler weather radar (NPOL) were used to examine structure, development, and oceanic transition of West African Mesoscale Convective Systems (MCSs) during the NASA African Monsoon Multidisciplinary Analysis (NAMMA) to determine possible indicators leading to downstream tropical cyclogenesis. Characteristics examined from the NPOL data include echo-top heights, maximum radar reflectivity, height of maximum radar reflectivity, and convective and stratiform coverage areas. Atmospheric radiosondes launched during NAMMA were used to investigate environmental stability characteristics that the MCSs encountered while over land and ocean, respectively. Strengths of African Easterly Waves (AEWs) were examined along with the MCSs in order to improve the analysis of MCS characteristics. Mean structural and environmental characteristics were calculated for systems that produced TCs and for those that did not in order to determine differences between the two types. Echo-top heights were similar between the two types, but maximum reflectivity and height and coverage of intense convection (>50 dBZ) are all larger than for the TC producing cases. Striking differences in environmental conditions related to future TC formation include stronger African Easterly Jet, increased moisture especially at middle and upper levels, and increased stability as the MCSs coastally transition.

Evaluation of cloud-resolving model intercomparison simulations using TWP-ICE observations: Precipitation and cloud structure

The Tropical Warm Pool.International Cloud Experiment (TWP ]ICE) provided extensive observational data sets designed to initialize, force, and constrain atmospheric model simulations. In this first of a two ]part study, precipitation and cloud structures within nine cloud ]resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Seven of nine simulations overestimate convective area by 20% or more leading to general overestimation of convective rainfall. This is balanced by underestimation of stratiform rainfall by 5% to 50% despite overestimation of stratiform area by up to 65% because of a preponderance of very low stratiform rain rates in all simulations. All simulations fail to reproduce observed radar reflectivity distributions above the melting level in convective regions and throughout the troposphere in stratiform regions. Observed precipitation ]sized ice reaches higher altitudes than simulated precipitation ]sized ice despite some simulations that predict lower than observed top ]of ]atmosphere infrared brightness temperatures. For the simulations that overestimate radar reflectivity aloft, graupel is the cause with one ]moment microphysics schemes whereas snow is the cause with two ]moment microphysics schemes. Differences in simulated radar reflectivity are more highly correlated with differences in mass mean melted diameter (Dm) than differences in ice water content. Dm is largely dependent on the mass ]dimension relationship and gamma size distribution parameters such as size intercept (N0) and shape parameter (m). Having variable density, variable N0, or m greater than zero produces radar reflectivities closest to those observed.