Liquid Hydrometeors Research Articles

TheGSIcapability to assimilateTRMMandGPMhydrometeor retrievals inHWRF

Hurricane forecasting skills may be improved by utilizing increased precipitation observations available from the Global Precipitation Measurement mission (GPM). This study adds to the Gridpoint Statistical Interpolation (GSI)capability to assimilate satellite‐retrieved hydrometeor profile data in the operational Hurricane Weather Research and Forecasting (HWRF)system. The newly developed Hurricane Goddard Profiling (GPROF)algorithm produces Tropical Rainfall Measuring Mission (TRMM)/GPMhydrometeor retrievals specifically for hurricanes. Two new observation operators are developed and implemented inGSIto assimilate HurricaneGPROFretrieved hydrometeors inHWRF. They are based on the assumption that all water vapour in excess of saturation with respect to ice or liquid is immediately condensed out. Two sets of single observation experiments that include assimilation of solid or liquid hydrometeor from HurricaneGPROFare performed. Results suggest that assimilating single retrieved solid or liquid hydrometeor information impacts the current set of control variables ofGSIby adjusting the environment that includes temperature, pressure and moisture fields toward saturation with respect to ice or liquid. These results are explained in a physically consistent manner, implying satisfactory observation operators and meaningful structure of background error covariance employed byGSI. Applied to two real hurricane cases,Leslie(2012) andGonzalo(2014), the assimilation of the HurricaneGPROFdata in the innermost domain ofHWRFshows a physically reasonable adjustment and an improvement of the analysis compared to observations. However, the impact of assimilating the HurricaneGPROFretrieved hydrometeors on the subsequentHWRFforecasts, measured by hurricane tracks, intensities, sizes, satellite‐retrieved rain rates, and corresponding infrared images, is inconclusive. Possible causes are discussed.

Using dynamical downscaling to examine mechanisms contributing to the intensification of Central U.S. heavy rainfall events

AbstractThe frequency and intensity of heavy rainfall events have increased in the Central U.S. over the last several decades, and model projections from dynamical downscaling suggest a continuation with climate change. In this study, we examine how climate change might affect mechanisms related to the development of heavy rainfall events that occur on the scale of mesoscale convective systems over the Central U.S. To accomplish these goals, we incorporate dynamical downscaled simulations of two Coupled Model Intercomparison Project phase 5 models in the Weather Research and Forecasting model that accurately simulate heavy rainfall events. For each model, a set of heavy rainfall events that match the frequency, timing, and intensity of observed events are objectively identified in historical and future simulations. We then examine multimodel composites of select atmospheric fields during these events in simulations of historical and future scenarios, enabling an identification of possible physical mechanisms that could contribute to the intensification of heavy rainfall events with climate change. Simulations show that additional moisture is transported into convective updrafts during heavy rain events in future simulations, driving stronger evaporative cooling from the entrainment of drier midtropospheric air. This results in the formation of a stronger low‐level cold pool, which enhances moisture convergence above the cold pool and increases rainfall rates during future heavy precipitation events. In addition, a warmer profile in future simulations might allow for heavier rainfall rates as a deeper atmospheric column can support additional collision‐coalescence of liquid hydrometeors.

Microphysical Characteristics of Overshooting Convection from Polarimetric Radar Observations

Abstract The authors present observations of the microphysical characteristics of deep convection that overshoots the altitude of the extratropical tropopause from analysis of the polarimetric radar variables of radar reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP. Identified overshooting convective storms are separated by their organization and intensity into three classifications: organized convection, discrete ordinary convection, and discrete supercell convection. Composite analysis of identified storms for each classification reveals microphysical features similar to those found in previous studies of deep convection, with deep columns of highly positive ZDR and KDP representing lofting of liquid hydrometeors within the convective updraft and above the melting level. In addition, organized and discrete supercell classifications show distinct near-zero ZDR minima aligned horizontally with and at altitudes higher than the updraft column features, likely indicative of the frequent presence of large hail in each case. Composites for organized convective systems show a similar ZDR minimum throughout the portion of the convective core that is overshooting the tropopause, corresponding to ZH in the range of 15–30 dBZ and negative KDP observations, in agreement with the scattering properties of small hail and/or lump or conical graupel. Additional analyses of the evolution of overshooting storms reveals that the ZDR minima indicative of hail in the middle and upper troposphere and graupel in the overshooting top are associated with the mature and decaying stages of overshooting, respectively, supporting their inferred contributions to the observed polarimetric fields.

A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

Abstract. A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.

Regional Comparison of GOES Cloud-Top Properties and Radar Characteristics in Advance of First-Flash Lightning Initiation

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.

Можливість використання поляриметричного радіолокатора для оцінки атмосферної турбулентності

Викладено підхід, що дозволяє оцінити інтенсивність турбулентності за спектральними оцінками поляризаційного сигналу як випадкового процесу та зменшити час обробки сигналу. Турбулентність розглянуто як випадковий процес, рідкі гідрометеори, що викликають появу спектра поляризації – як фільтр, з якого знімається сигнал для подальшої обробки та передачі. Обґрунтовано вимоги до тракту передачі спектра поляризаційного сигналу. Показано, що тракт має бути спроможним передавати діапазон частот від значень, що є близькими до нуля, до частот, що визначаються частотою дискретизації, що є достатньою для визначення з заданою точністю параметрів поляризаційного спектра як випадкового процесу.

A possible new mechanism for northward propagation of boreal summer intraseasonal oscillations based on TRMM and MERRA reanalysis

Boreal summer intraseasonal oscillations (BSISOs) manifest in the active and break spells and act as the primary building block of the Indian summer monsoon. Although recent research has evolved a basic framework for understanding the scale selection and northward propagation of the BSISO, the role of different hydrometeors in modulating these processes remains poorly explored. In this study, TRMM-2A12 retrievals and Modern Era Retrospective-analysis for Research and Applications reanalysis data are examined to establish relationship between cloud hydrometeors and other atmospheric dynamical parameters with the northward propagation of the BSISOs. The study reveals that the cloud liquid water leads the deep convection during the northward propagation of BSISOs in the lower troposphere, while the cloud ice slightly lags the convection. This distribution indicates the occurrence of a possible mechanism of the lower level moistening through the large scale moisture advection in lower atmosphere and boundary layer (PBL) convergence, followed by triggering of the deep convection. The analyses of moisture advection and the dynamical fields with respect to the convection center show that low level moistening is a manifestation of the barotropic vorticity and PBL convergence of moisture anomaly north of the convection center. A new internal dynamical-thermodynamical mechanism is unraveled to understand the reason behind the middle tropospheric heating maximum and its role on the northward propagation. It is shown that the enhanced moisture perturbation in lower levels together with the heat transport by the sub-grid scale eddies within the PBL induces lower level instability required to precondition the lower atmosphere for triggering the deep convection. Vigorous upward motion inside the deep convection uplifts the liquid hydrometeors to upper levels and the formation of precipitable ice leads to the heating maxima in the middle troposphere. To check the robustness of the proposed hypothesis, similar analysis is performed for the weak northward propagating BSISO cases.

An evaluation and improvement of microphysical parameterization from a two-moment cloud microphysics scheme and the Southwest Monsoon Experiment (SoWMEX)/Terrain-influenced Monsoon Rainfall Experiment (TiMREX) observations

[1] This study evaluates the simulated cloud properties, especially the simulated raindrop size distribution, by the Chinese Academy of Meteorological Sciences bulk microphysics scheme (CAMS BMS) and two other two-moment microphysics schemes (Morrison and WDM6) in the Weather Research and Forecasting model (WRF v3.1). Measurements from a mesoscale convective system that occurred on 14 June 2008 during the Southwest Monsoon Experiment (SoWMEX) and Terrain-influenced Monsoon Rainfall Experiment (TiMREX) are used. The model reflectivity (ZH), differential reflectivity (ZDR), and microwave brightness temperature (TB) are compared with the corresponding observations by the S band dual-polarization Doppler radar (S-Pol) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Results show that the simulated ZDR, which is sensitive to the drop size distribution (DSD) of raindrops, from the original CAMS BMS and Morrison schemes are larger than those from the S-Pol observations. On the other hand, the simulated ZDR values from the WDM6 scheme are smaller than the radar observations. To improve the model results, modifications are made by controlling the intercept parameter of raindrop DSD and by increasing the raindrop breakup rates in the original CAMS BMS scheme. The modifications reduce the raindrop size and consequently increase the rain evaporation rate. The improved simulations of ZH and ZDR indicate that the modified CAMS BMS scheme adequately simulates the amount and size of liquid hydrometeors. Moreover, the simulated brightness temperatures at liquid water absorption frequency and the simulated surface precipitation rates are also significantly improved by using the modified CAMS BMS scheme.

CloudSat Studies of Stratiform Precipitation Systems Observed in the Vicinity of the Southern Great Plains Atmospheric Radiation Measurement Site

Abstract The spaceborne W-band (94 GHz) radar on board the CloudSat polar-orbiting satellite offers new opportunities for retrieving parameters of precipitating cloud systems. CloudSat measurements can resolve the vertical cross sections of such systems. The radar brightband features, which are commonly present when observing stratiform precipitating systems, allow the vertical separation of the ice, mixed, and liquid precipitating hydrometeor layers. In this study, the CloudSat data are used to simultaneously retrieve ice water path (IWP) values for ice layers of precipitating systems using absolute radar reflectivity measurements and mean rainfall rates Rm in the liquid hydrometeor layers using the attenuation-based reflectivity gradient method. The retrievals were performed for precipitating events observed in the vicinity of the Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Climate Research Facility. The retrieval results indicated that IWP values in stratiform precipitating systems vary from a few hundreds up to about 10 thousands of grams per meter squared, and the mean rain rates were in a general range between 0.5 and about 12 mm h−1. On average, mean rainfall increases with an increase in ice mass observed above the melting layer; the corresponding mean correlation coefficient is about 0.35, although events with higher correlation as well as those with no appreciable correlation were observed. Horizontal advection, wind shear, and vertical air motions might be some of the reasons for decorrelation between IWP and Rm retrieved for the same vertical atmospheric column. A mean statistical relation between IWP and Rm derived from CloudSat retrievals is in good agreement with the data obtained from multiwavelength ground-based cloud radar measurements at the SGP site.

The influence of aerosol particle number and hygroscopicity on the evolution of convective cloud systems and their precipitation: A numerical study based on the COPS observations on 12 August 2007

The 3D cloud model DESCAM-3D with bin resolved microphysics for ice, water and aerosol particles is used to study the role of particles on the evolution of summertime mid-level convective clouds and the subsequent precipitation during the COPS field campaign which occurred at mid-latitude near the French/German border in summer 2007. Using a 3D grid resolution of 250 m, DESCAM-3D, is able to simulate well the dynamical, cloud and precipitation features of the convective cloud system observed during the afternoon of the 12th August. This mid-level convective system was dominated by warm-phase microphysics. The simulated convective system led to a 1.5 h long lasting precipitation event in agreement with the radar observations. The results of the fine numerical scale compare well with the high resolved radar reflectivities of the LaMP X-band radar and the DLR-Poldirad radar. The prediction of the liquid hydrometeor spectra allows a detailed calculation of the cloud radar reflectivity. In order to better understand the role of aerosol particles on cloud evolution and precipitation formation, several sensitivity studies were performed by modifying aerosol number concentration as well as their physico-chemical properties. Drastic changes in the aerosol solubility lead to a variation in precipitation on the order of 10% for the same convective case. In contrast, changes in the aerosol number concentrations can lead to a variation in total precipitation of up to 30%. Hence, the role of changes in aerosol number concentrations is more important than changes in particle solubility for this case of continental mid-level convection at mid-latitude. A subsequent analysis of the in-cloud microphysics revealed that in-cloud properties are modified significantly in all scenarios. Key parameter is the supersaturation whose magnitude influences both cloud microphysics (cloud droplet and rain drop formation) as well as cloud thermodynamics and cloud dynamics. Furthermore, supersaturation can remain quite low in polluted clouds reducing strongly the release of latent heat and, thus, the intensity of the convective dynamics. As much as a quarter of the polluted cloud volume was found to be subsaturated in this case whereas it was smaller in the continental or clean environments.

An Improved Representation of Rimed Snow and Conversion to Graupel in a Multicomponent Bin Microphysics Scheme

Abstract This paper describes the development of a new multicomponent detailed bin ice microphysics scheme that predicts the number concentration of ice as well as the rime mass mixing ratio in each mass bin. This allows for local prediction of the rime mass fraction. In this approach, the ice particle mass size, projected area size, and terminal velocity–size relationships vary as a function of particle mass and rimed mass fraction, based on a simple conceptual model of rime accumulation in the crystal interstices that leads to an increase in particle mass, but not in its maximum size, until a complete “filling in” with rime and conversion to graupel occurs. This approach allows a natural representation of the gradual transition from unrimed crystals to rimed crystals and graupel during riming. The new ice scheme is coupled with a detailed bin representation of the liquid hydrometeors and applied in an idealized 2D kinematic flow model representing the evolution of a mixed-phase precipitating cumulus. Results using the bin scheme are compared with simulations using a two-moment bulk scheme employing the same approach (i.e., separate prediction of bulk ice mixing ratio from vapor deposition and riming, allowing for local prediction of bulk rime mass fraction). The bin and bulk schemes produce similar results in terms of ice and liquid water paths and optical depths, as well as the timing of the onset and peak surface precipitation rate. However, the peak domain-average surface precipitation rate produced by the bulk scheme is about 4 times that in the bin simulation. The bin scheme is also compared with simulations that assume the ice particles consist entirely of either unrimed snow or graupel. While overall results are fairly similar, the onset and timing of the peak domain-average surface precipitation rate are substantially delayed in the simulations that treat the ice particles as either unrimed snow or graupel. These results suggest the importance of representing different ice types, including partially rimed crystals, for this case.

Synergetic use of millimeter- and centimeter-wavelength radars for retrievals of cloud and rainfall parameters

Abstract. A remote sensing approach for simultaneous retrievals of cloud and rainfall parameters in the vertical column above the US Department of Energy's (DOE) Climate Research Facility at the Tropical Western Pacific (TWP) Darwin site in Australia is described. This approach uses vertically pointing measurements from a DOE Ka-band radar and scanning measurements from a nearby C-band radar pointing toward the TWP Darwin site. Rainfall retrieval constraints are provided by data from a surface impact disdrometer. The approach is applicable to stratiform precipitating cloud systems when a separation between the liquid hydrometeor layer, which contains rainfall and liquid water clouds, and the ice hydrometeor layer is provided by the radar bright band. Absolute C-band reflectivities and Ka-band vertical reflectivity gradients in the liquid layer are used for retrievals of the mean layer rain rate and cloud liquid water path (CLWP). C-band radar reflectivities are also used to estimate ice water path (IWP) in regions above the melting layer. The retrieval uncertainties of CLWP and IWP for typical stratiform precipitation systems are about 500–800 g m−2 (for CLWP) and a factor of 2 (for IWP). The CLWP retrieval uncertainties increase with rain rate, so retrievals for higher rain rates may be impractical. The expected uncertainties of layer mean rain rate retrievals are around 20%, which, in part, is due to constraints available from the disdrometer data. The applicability of the suggested approach is illustrated for two characteristic events observed at the TWP Darwin site during the wet season of 2007. A future deployment of W-band radars at the DOE tropical Climate Research Facilities can improve CLWP estimation accuracies and provide retrievals for a wider range of stratiform precipitating cloud events.

State estimation of convective storms with a two‐moment microphysics scheme and an ensemble Kalman filter: Experiments with simulated radar data

AbstractThe ability of the ensemble Kalman filter method to estimate an increased number of state variables associated with a double‐moment (DM) microphysics scheme is examined for the first time through observing system simulation experiments, assuming either a perfect or imperfect prediction model and/or observation operators. With the DM scheme, mixing ratios and total number concentrations of hydrometeor species are predicted.It is found that the increased number of state variables can be reasonably well estimated when both radial velocity (Vr) and reflectivity (ZH) observations are used and when the prediction model is assumed to be perfect. However, the errors increase significantly when ZH is used alone. In this case, the filter has difficulty in estimating independently‐varying mixing ratios and number concentrations, which are both directly involved in the calculation of ZH. The addition of Vr data helps alleviate a problem associated with the solution not being sufficiently constrained by observations.With the DM scheme, the correlations between ZH and model state variables exhibit complex spatial structures that depend on the location of the ZH observation. Collocated ZH and vertical velocity show negative correlation when the observation is taken where ice phase hydrometeors are dominant, but positive correlation when it is taken where large quantities of liquid hydrometeors exist. Further study is needed to fully understand the complex correlation structures.Imperfect model experiments were performed, with two types of model errors: (1) microphysical parametrization error due to incorrectly assumed shape parameter of the gamma particle size distribution (PSD), and (2) different ways of calculating hydrometeor scattering. The results show that the model error degrades the state estimation in general. Nevertheless, the estimated states are still reasonably good when both Vr and ZH are assimilated. Perturbing the shape parameter of gamma PSDs within the forecast ensemble improves the overall state estimation. Copyright © 2010 Royal Meteorological Society

A Rain-Rate Retrieval Algorithm for Attenuated Radar Measurements

Abstract A dynamic regularization scheme for rain-rate retrievals from attenuated radar measurements is presented. Most regularization techniques, including the optimal estimation method, use the state-space parameters to regularize the problem, which will always lead to a bias in the solution. To avoid this problem the authors introduce an evolutionary regularization technique, which is based on the spatial derivative of the measured reflectivity profile and allows for a bias-free global solution. The regularization strength is determined by the quadratic eigenvalue solution using the regularized total least squares method. With the new method, the authors perform a retrieval of rain-rate profiles from simulated measurements of a nadir-pointing W-band (94 GHz) radar, in a configuration similar to the cloud radar employed on CloudSat. The simulations assume that multiple scattering is negligible and only liquid hydrometeors are taken into account. The authors compare the results of this method with the outcome of an optimal estimation method and demonstrate that their method is superior in terms of reliability, correlation coefficient, and dispersion to the optimal estimation method for layers experiencing high values of attenuation; therefore, the a priori bias typical for optimal estimation solutions is avoided.

Simultaneous estimates of cloud and rainfall parameters in the atmospheric vertical column above the Atmospheric Radiation Measurement Program southern Great Plains site

A novel remote sensing approach to simultaneously retrieve cloud liquid water paths (LWP) and ice water paths (IWP) and mean rainfall rate in a vertical atmospheric column was applied for stratiform‐like precipitation events observed during the warm period of 2007 at the southern Great Plains site of the Atmospheric Radiation Measurement (ARM) Program. The retrieval method is based on multifrequency radar measurements at W, Ka, and S bands and raindrop size distribution estimates from a ground‐based impact disdrometer. The radar measurements also provide a robust separation of the liquid, mixed, and ice hydrometeor layers. Characteristic values of LWP are about 300–400 g m−2, although values up to 1000 g m−2 and higher are not uncommon. There is on average insignificant correlation between cloud LWP and rainfall rates. IWP, which represents the precipitating cloud part of the atmospheric column that is observed above the freezing level, usually significantly exceeds cloud LWP in the liquid hydrometeor layer and can reach values of approximately 104 g m−2 and even higher. On average, mean rainfall in the liquid layer, Rm, increases with an increase in ice mass observed above the melting layer, although a corresponding mean correlation coefficient between Rm and IWP is only 0.32. There is noticeable variability in IWP‐Rm relations between individual events. Storm dynamics is likely to influence the correlation between cloud and rainfall parameters as inferred from simultaneous columnar retrievals. Initial estimates indicate that IWP and rainfall are stronger related for events which exhibit lower vertical variability of wind.

A Method to Estimate Vertically Integrated Amounts of Cloud Ice and Liquid and Mean Rain Rate in Stratiform Precipitation from Radar and Auxiliary Data

Abstract A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.

A Method to Estimate Vertically Integrated Amounts of Cloud Ice and Liquid and Mean Rain Rate in Stratiform Precipitation from Radar and Auxiliary Data

A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.

Verification of Hydrometeor Properties Simulated by a Cloud-Resolving Model Using a Passive Microwave Satellite and Ground-Based Radar Observations for a Rainfall System Associated with the Baiu Front

This paper compares satellite microwave radiometer and ground-based radar observations with the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) simulations, using a bulk microphysical parameterization, for a typical rainfall system associated with the Baiu front around the Okinawa Islands, Japan, on 8 June 2004. The JMA-NHM correctly replicated the shape, location and intensity of the precipitation associated with the observed rainfall system. Radar reflectivities and microwave brightness temperatures (TBs) were simulated using output from the JMA-NHM simulations. They were then compared with concurrent corresponding observations by the National Institute of Information and Communications Technology (NICT), CRL Okinawa Bistatic Polarimetric Radar (COBRA), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E). Fairly good agreement was obtained between the simulated and observed reflectivities under the melting layer and TBs at low frequency (18.7 GHz), indicating that the JMA-NHM adequately simulated the amount of liquid hydrometeors. However, the intensity of scattering in the simulations was stronger than that in the COBRA observations above the melting layer and the AMSR-E observations at high frequencies (36.5 and 89.0 GHz). This was due to the fact that the JMA-NHM overestimated the amount and size of snow particles as a result of large depositional growth. The excessive snow contents were reduced by adjusting some of the microphysical processes in the JMANHM: the snowfall speeds were increased and a riming threshold for snow to graupel conversion was changed. These adjustments helped to reduce the amount and size of snow, resulting in further agreement with the COBRA observations. These adjustments also further improved the simulated TBs at high frequencies, especially at 36.5 GHz. However, differences still exist between the simulated and the observed TBs at high frequencies, suggesting that additional adjustment to and improvement of the snow microphysical processes are needed for the application of the model to microwave remote sensing of precipitation.

Cloud physical properties and empirical polarimetric measurements of rain signatures at C-Band

Abstract. Raindrops are one type of precipitation in stratiform and convective clouds. To get relationships for describing the raindrops two different methods were used. In the first way, the microphysical properties of the liquid hydrometeors were examined. For this the use of the Rayleigh approximation for small particles (raindrops at C-Band) and the drop size distribution by Ulbrich (Γ-DSD) lead to the calculation of the reflectivity at horizontal polarisation ZHH, the reflectivity at vertical polarisation ZVV and the differential reflectivity ZDR. In the second way, rain signatures were separated from polarimetric measurements. The database of these measurements consists of datasets measured by the dual polarimetric C-Band weather radar POLDIRAD (DLR, Oberpfaffenhofen). The aim of this study was then to combine and to compare the results from the real radar measurements against the theoretical calculations in the ZHH-ZDR plane. Based on these observations and calculations, scientific results for future practical use will be presented in form of empirical equations including ZHH-ZDR. Finally in form of scientific discussion, the ZHH-ZDR plane will be critically assessed for outstanding problems or issues.

A Bulk Microphysics Parameterization with Multiple Ice Precipitation Categories

Abstract A single-moment bulk microphysics scheme with multiple ice precipitation categories is described. It has 2 liquid hydrometeor categories (cloud droplets and rain) and 10 ice categories that are characterized by habit, size, and density—two ice crystal habits (column and plate), rimed cloud ice, snow (ice crystal aggregates), three categories of graupel with different densities and intercepts, frozen drops, small hail, and large hail. The concept of riming history is implemented for conversions among the graupel and frozen drops categories. The multiple precipitation ice categories allow a range of particle densities and fall velocities for simulating a variety of convective storms with minimal parameter tuning. The scheme is applied to two cases—an idealized continental multicell storm that demonstrates the ice precipitation process, and a small Florida maritime storm in which the warm rain process is important.