Academic literature on the topic 'Contoured Frequency by Altitude Diagram (CFAD)'

Radar data with high spatiotemporal resolution and automatic weather station (AWS) data are used in the data assimilation experiment to improve the precipitation forecast of a numerical model. The numerical model considered in this study is the Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated the radar equivalent reflectivity factor using high resolution WRF and compared it with radar observations in South Korea. To compare the precipitation forecast characteristics of the three-dimensional variational (3D-Var) assimilation of radar data, four experiments were performed based on the scales of precipitation systems. Comparison of the 24 h accumulated rainfall with surface observation data, contoured frequency by altitude diagram (CFAD), time–height cross sections (THCS), and vertical hydrometeor profiles was used to evaluate the accuracy of the simulation of precipitation. The model simulations were performed with and without 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The combined effect of the radar and AWS data assimilation experiment improved the location of the precipitation area and rainfall intensity compared to the control run. There is a noticeable scale dependence in the improvement of precipitation systems. Improvements in simulating mesoscale convective systems were larger compared to synoptically driven precipitation systems.

Abstract The Korea Meteorological Administration (KMA) implemented a 10-yr project to develop its own global model (GM) by 2020. To reflect the complex topography and unique weather characteristics of the Korean Peninsula, a high-resolution model with accurate physics and input data is required. The WRF single-moment 6-class microphysics scheme (WSM6) and WRF double-moment 6-class microphysics scheme (WDM6) that will be implemented in the Korea GM (KGM) are evaluated. Comparisons of the contoured frequency by altitude diagram (CFAD), time–height cross sections, and vertical profiles of hydrometeors are utilized to assess the two schemes in simulating summer monsoon and convective precipitation cases over the Korean Peninsula during 2011. The results show that WSM6 and WDM6 overestimate the height of the melting level and bright band as compared to radar observations. However, the accuracy of WDM6 is in better agreement with radar observations. This is attributed to the difference in the sedimentation process simulated by the additional second-moment total number concentrations of liquid-phase particles in WDM6. WDM6 creates larger raindrops and higher relative humidity beneath the melting layer, allowing the scheme to simulate a more realistic reflectivity profile than WSM6 for the summer monsoon case. However, for the convective case, both schemes underestimate the precipitation and there is resolution dependence in the WRF Model’s ability to simulate convective precipitation.

Abstract Two mesoscale convective systems (MCSs) observed during the African Monsoon Multidisciplinary Analyses (AMMA) experiment are simulated using the three-dimensional (3D) Goddard Cumulus Ensemble model. This study was undertaken to determine the performance of the cloud-resolving model in representing distinct convective and microphysical differences between the two MCSs over a tropical continental location. Simulations are performed using 1-km horizontal grid spacing, a lower limit on current embedded cloud-resolving models within a global multiscale modeling framework. Simulated system convective structure and microphysics are compared to radar observations using contoured frequency-by-altitude diagrams (CFADs), calculated ice and water mass, and identified hydrometeor variables. Vertical distributions of ice hydrometeors indicate underestimation at the mid- and upper levels, partially due to the inability of the model to produce adequate system heights. The abundance of high-reflectivity values below and near the melting level in the simulation led to a broadening of the CFAD distributions. Observed vertical reflectivity profiles show that high reflectivity is present at greater heights than the simulations produced, thought to be a result of using a single-moment microphysics scheme. Relative trends in the population of simulated hydrometeors are in agreement with observations, though a secondary convective burst is not well represented. Despite these biases, the radar-observed differences between the two cases are noticeable in the simulations as well, suggesting that the model has some skill in capturing observed differences between the two MCSs.

This study investigates the ability of the high-resolution Weather Research and Forecasting (WRF) model to simulate summer precipitation with assimilation of X-band radar network data (X-Net) over the Seoul metropolitan area. Numerical data assimilation (DA) experiments with X-Net (S- and X-band Doppler radar) radial velocity and reflectivity data for three events of convective systems along the Changma front are conducted. In addition to the conventional assimilation of radar data, which focuses on assimilating the radial velocity and reflectivity of precipitation echoes, this study assimilates null-echoes and analyzes the effect of null-echo data assimilation on short-term quantitative precipitation forecasting (QPF). A null-echo is defined as a region with non-precipitation echoes within the radar observation range. The model removes excessive humidity and four types of hydrometeors (wet and dry snow, graupel, and rain) based on the radar reflectivity by using a three-dimensional variational (3D-Var) data assimilation technique within the WRFDA system. Some procedures for preprocessing radar reflectivity data and using null-echoes in this assimilation are discussed. Numerical experiments with conventional radar DA over-predicted the precipitation. However, experiments with additional null-echo information removed excessive water vapor and hydrometeors and suppressed erroneous model precipitation. The results of statistical model verification showed improvements in the analysis and objective forecast scores, reducing the amount of over-predicted precipitation. An analysis of a contoured frequency by altitude diagram (CFAD) and time–height cross-sections showed that increased hydrometeors throughout the data assimilation period enhanced precipitation formation, and reflectivity under the melting layer was simulated similarly to the observations during the peak precipitation times. In addition, overestimated hydrometeors were reduced through null-echo data assimilation.

This study examined the performance of Artificial Neural Network (ANN)-backpropagation to classify rain types from observations of Micro Rain Radar (MRR) in Serpong (6.359oSL; 106.673oEL). The inputs of ANN are radar reflectivity, Doppler velocity, and Liquid Water Content (LWC). Rain events on January 5, 2017; at 16.28 – 21.21 local time were used as training data. The ANN results were validated with rain classified by the Bright Band (BB) and Countour Frequency by Altitude Diagram (CFAD) methods. The most appropriate ANN-backpropagation architecture is the 3-6-1 architecture (input layer-hidden layer-output layer), with an activation-transfer function being competitive and a learning rate of 0.9. The Mean Square Error (MSE) of the training step was 0.0098735, and the average percentage of accuracy for the test step was 94%. A rain event with a single type of rain can be classified accurately by ANN and gives the same results as the CFAD method. Thus, the ANN can be a solution to the shortcomings of the BB method, which sometimes classification results of a single type of rain events is interspersed with another type, which is physically impossible.

Abstract Radar-observed vertical structure of precipitation as defined by contoured frequency by altitude diagrams (CFADs) is related to dynamic and thermodynamic environmental parameters. CFADs from 559 storms occurring over the years 2004–11 in the vicinity of Locarno, Switzerland, combined with Interim ECMWF Re-Analysis (ERA-Interim) data show that the radar-observed vertical structure of precipitation correlates with synoptic pattern (as defined by 1000- and 500-hPa geopotential heights), integrated water vapor flux, atmospheric stability, and vertical profiles of temperature, moisture, and wind. Following the analysis of vertical structure and environmental parameters, a generalized linear model (GLM) is developed for radar-observed vertical structure as a function of data from ERA-Interim. The GLM provides expected values for the vertical extent and magnitude of radar reflectivity and predicts storm vertical structure type with 79% overall accuracy. The relationships found between environmental parameters and storm vertical structure underscore the importance of including both dynamic and thermodynamic variables when evaluating climate change effects on precipitation. In addition, the ability of the GLM to reproduce storm types shows the potential for using GLMs as a link between lower-resolution global model data and high-resolution precipitation observations.

Abstract Cloud and precipitation properties of the midlatitude storm-track regions over the Southern Ocean (SO) and North Atlantic (NA) are explored using reanalysis datasets and A-Train observations from 2007 to 2011. In addition to the high-level retrieval products, lower-level observed variables—CloudSat radar reflectivity and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar attenuated backscatter—are directly examined using both contoured frequency by altitude diagrams (CFADs) and contoured frequency by temperature diagrams (CFTDs) to provide direct insight into thermodynamic phase properties. While the wintertime temperature profiles are similar over the two regions, the summertime environment is warmer over the NA. The NA atmosphere is generally moister than the SO, while the SO boundary layer is moister during winter. The results herein suggest that although the two regions exhibit many similarities in the prevalence of boundary layer clouds (BLCs) and frontal systems, notable differences exist. The NA environment exhibits stronger seasonality in thermodynamic structure, cloud, and precipitation properties than the SO. The regional differences of cloud properties are dominated by microphysics in winter and thermodynamics in summer. Glaciated clouds with higher reflectivities are found at warmer temperatures over the NA. BLCs (primarily below 1.5 km) are a predominant component over the SO. The wintertime boundary layer is shallower over the SO. Midlevel clouds consisting of smaller hydrometeors in higher concentration (potentially supercooled liquid water) are more frequently observed over the SO. Cirrus clouds are more prevalent over the NA. Notable differences exist in both the frequencies of thermodynamic phases of precipitation and intensity of warm rain over the two regions.

Abstract. Ensemble simulations with the Terrestrial Systems Modelling Platform (TSMP) covering northwestern Germany are evaluated for three summertime convective storms using polarimetric X-band radar measurements. Using a forward operator, the simulated microphysical processes have been evaluated in radar observation space. Observed differential reflectivity (ZDR) columns, which are proxies for updrafts, and multi-variate fingerprints for size sorting and aggregation processes are captured by the model, but co-located specific differential phase (KDP) columns in observations are not reproduced in the simulations. Also, the simulated ZDR columns, generated by only small-sized supercooled drops, show smaller absolute ZDR values and a reduced width compared to their observational counterparts, which points to deficiencies in the cloud microphysics scheme as well as the forward operator, which does not have explicit information of water content of ice hydrometeors. Above the melting layer, the simulated polarimetric variables also show weak variability, which can be at least partly explained by the reduced particle diversity in the model and the inability of the T-matrix method to reproduce the polarimetric signatures of snow and graupel; i.e. current forward operators need to be further developed to fully exploit radar data for model evaluation and improvement. Below the melting level, the model captures the observed increase in reflectivity, ZDR and specific differential phase (KDP) towards the ground. The contoured frequency altitude diagrams (CFADs) of the synthetic and observed polarimetric variables were also used to evaluate the model microphysical processes statistically. In general, CFADs of the cross-correlation coefficient (ρhv) were poorly simulated. CFADs of ZDR and KDP were similar but the model exhibits a relatively narrow distribution above the melting layer for both, and a bimodal distribution for ZDR below the melting layer, indicating either differences in the mechanism of precipitation formation or errors in forward operator which uses a functional form of drop size distribution. In general, the model was found to underestimate the convective area fraction, high reflectivities, and the width/magnitude of ZDR columns, all leading to an underestimation of the frequency distribution for high precipitation values.

Abstract Lightning initiation (LI) events over Florida and Oklahoma are examined and statistically compared to understand the behavior of observed radar and infrared satellite interest fields (IFs) in the 75-min time frame surrounding LI. Lightning initiation is defined as the time of the first lightning, of any kind, generated in a cumulonimbus cloud. Geostationary Operational Environmental Satellite (GOES) infrared IFs, contoured frequency by altitude diagrams (CFADs) of radar reflectivity, and model sounding data, analyzed in concert, show the mean characteristics over time for 36 and 23 LI events over Florida and Oklahoma, respectively. CFADs indicate that radar echoes formed 60 min before Florida LI, yet Oklahoma storms exhibited a ~30-min delayed development. Large ice volumes in Florida developed from the freezing of lofted liquid hydrometeors formed by long-lived (~45 min) warm rain processes, which are mostly absent in Oklahoma. However, ice volumes developed abruptly in Oklahoma storms despite missing a significant warm rain component. GOES fields were significantly different before 30 min prior to LI between the two locations. Compared to Florida storms, lower precipitable water (PW), higher convective available potential energy, and higher 3.9-μm reflectance in Oklahoma, suggest stronger and drier updrafts producing a greater abundance of small ice particles. Somewhat larger 15-min 10.7-μm cooling rates in Oklahoma confirm stronger updrafts, while clouds in the 60–30-min pre-LI period show more IF variability (e.g., in the 6.5–10.7-μm difference). Florida storms (high PW, slower growth) offer more lead time for LI predictability, compared to Oklahoma storms (low PW, explosive growth), with defined anvils being obvious at the time of LI.

Abstract. This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 h prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217–0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude diagrams (CFADs) reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

Very small fractional area (0.1%) occupied by the cumulonimbus (Cb) clouds belies their importance in Earths hydrological cycle and climate. For example, Riehl and Malkus (1958) estimated that the vertical transport of energy needed for the global energy balance can be accomplished by 1500 to 5000 active, undiluted Cb clouds (i.e., hot towers). Cb clouds feed hydrometeors to the anvil cloud region in mesoscale convective system (MCS). Applications such as the estimation of the vertical profile of latent heating, cumulus parameterizations, satellite rainfall retrievals, inferring the probability of lightening, etc., require information on the vertical distribution of hydrometeors in convective clouds (e.g., Xu and Zipser, 2012). Knowledge of the vertical structure of Cb clouds near individual cloud scale becomes necessary for validating cloud resolving model results. However, information on the vertical structure of convective clouds at horizontal scales comparable to that of a deep convective cloud is not available over most regions in the tropics. The PR provides an unprecedented long time series of data on the 3D structure of precipitating clouds in the tropics. The TRMM PR equivalent radar reflectivity factor (Ze) data product 2A25 version 6 is the main data used in the study. The present thesis work primarily focuses on the properties of convective clouds at the PR pixel scale. TRMM, operational since December 1997, is a non-sunsynchronous satellite with 350 inclination and samples the tropics several times a day (e.g., Kummerow et al., 1998, 2000). The PR works in Ku band (13.8 GHz or 2.2 cm wavelength), and its scan, consisting of 49 beams, had a width of 215 km when launched and _250 km after August 2001. The beam width is 0.710; nearby beams are separated by 0.710, giving a maximum scan angle of 170 (Kummerow et al., 1998). There are 80 levels in the vertical, each having 250 m resolution with the lowest level being the Earths ellipsoid. The height corresponding to different vertical levels in the 2A25 data set is the distance measured along the PR beam. Hence, corrections to pixel heights along different beams have been applied. Present thesis presents the vertical structure of radar reflectivity factor in tall cumulonimbus towers (CbTs) and intense convective clouds (ICCs) embedded in the South Asian monsoon systems and other tropical deep cloud systems. CbT is defined referring to a reflectivity threshold of 20 dBZ at 12 km altitude and is at least 9 km thick. ICCs are constructed referring to reflectivity thresholds at 8 km and 3 km altitudes. Cloud properties reported here are based on 10 year climatology. It is observed that the frequency of occurrence of CbTs is highest over the foothills of Himalayas, plains of northern India and Bangladesh, and minimum over the Arabian Sea and equatorial Indian Ocean west of 900E. The regional differences depend on the reference height selected, namely, small in the case of CbTs and prominent in 6􀀀13 km height range for ICCs. Land cells are more intense than the oceanic ones for convective cells defined using the reflectivity threshold at 3 km, whereas land versus ocean contrasts are not observed in the case of CbTs. Compared to cumulonimbus clouds elsewhere in the tropics, the South Asian counterparts have higher reflectivity values above 11 km altitude. One of the main findings of the present thesis is the close similarity in the average vertical profiles of CbTs and ICCs in the mid and lower troposphere across the ocean basins, while differences over land areas are larger and depend on the reference height selected. Foothills of the Western Himalayas, southeast South America and Indo-Gangetic Plain contain the most intense CbTs, while equatorial Africa, foothills of the Western Himalayas and equatorial South America contain the most intense ICCs. Close similarity among the oceanic cells suggests that the development of vigorous convective cells over warm oceans is similar and understanding gained in one region is extendable to other areas. South Asia contains several areas where the seasonal summer monsoon rainfall is influenced by the orography. One of the fundamental questions concerning the orographic rainfall is the nature of the associated precipitating clouds in the absence of synoptic forcing. It is believed that these are shallow and mid-level clouds, however, there is not much information in the literature on their vertical structure. Chapter 4 explores the vertical structure of active shallow (SC) and mid-level clouds (MLC) in Southeast Asia which are associated with the orographic features. Shallow and mid-level clouds have been defined such that their tops lie below 4.5 km and between 4.5 and 8 km, respectively. Only those TRMM PR passes are considered for active shallow and mid level cloud, which consists less than 5% deep cloud (_ 8 Km), compared to shallow cloud (_ 4.5 km) and mid level cloud (4.5 and _ 8 km). The reflectivity and height thresholds with constraint on percentage of deep clouds, ensure that we only captures the intense and isolated shallow and mid level clouds, away from deep cloud. The Western Ghats contains the highest fraction of the shallow clouds followed by the adjacent eastern Arabian Sea, while the Khasi hills in Meghalaya and Cardamom Mountains in Cambodia contain the least fraction of them. Average vertical profiles of shallow clouds are similar in different mountainous areas while that of mid-level clouds show some differences. Below 3 km, cloud liquid water content of the mid-level clouds is the highest over the Western Ghats and the eastern Arabian Sea. The average cloud liquid water content increases by 0.19 gm m􀀀3 for SCs between 3 km and 1.5 km, while the corresponding increase for MLCs is around 0.08 gm m􀀀3. MCS has a life cycle consisting of formative, intensifying, mature and dissipating stages. From the maximum projection of reflectivity on longitude and latitude plane from the 3D reflectivity fields, CS is defined as the common area of connected pixels with Ze _ 17 dBZ and polarized corrected temperature (PCT) _ 250 K, with atleast 500 km2. A CS is considered in subsequent analysis if its area detected in the Ze projection is at least 50% of its area seen in the PCT imagery. An algorithm is applied to obtain the phase of evolution. The algorithm is based on the average vertical profile of CSs and the reflectivity peak altitude (Hmax). An index namely reflectivity difference (RD) and Hmax is used to identify the phases of evolution. A close similarity has been observed during different phases in average vertical profiles as well as in CFAD. Growing or intensifying stage consists the highest reflectivity below the 2 km altitude. Mature phase does not show the much variation in Ze below the freezing level, whereas in the decaying stage, shows the largest regional differences in this layer of the atmosphere. Melting band signature is most pronounced in the decaying stage. Fraction of convective area decreases as CSs go through its life cycle, except over Atlantic Ocean during winter.