Hydrometeor Mixing Ratios Research Articles

Comparison of the Vertical Distributions of Cloud Properties from Idealized Extratropical Deep Convection Simulations Using Various Horizontal Resolutions

ABSTRACT The authors coarse-grained and analyzed the output from a large-eddy simulation (LES) of an idealized extratropical supercell storm using the Weather Research and Forecasting (WRF) Model with various horizontal resolutions (200 m, 400 m, 1 km, and 3 km). The coarse-grained physical properties of the simulated convection were compared with explicit WRF simulations of the same storm at the same resolution of coarse-graining. The differences between the explicit simulations and the coarse-grained LES output increased as the horizontal grid spacing in the explicit simulation coarsened. The vertical transport of the moist static energy and total hydrometeor mixing ratio in the explicit simulations converged to the LES solution at the 200-m grid spacing. Based on the analysis of the coarse-grained subgrid vertical flux of the moist static energy, the authors confirmed that the nondimensional subgrid vertical flux of the moist static energy varied with the subgrid fractional cloudiness according to a function of fractional cloudiness, regardless of the box size. The subgrid mass flux could not account for most of the total subgrid vertical flux of the moist static energy because the eddy-transport component associated with the internal structural inhomogeneity of convective clouds was of a comparable magnitude. This study highlights the ongoing challenge in developing scale-aware parameterizations of subgrid convection.

Convective-Scale Data Assimilation for the Weather Research and Forecasting Model Using the Local Particle Filter

Abstract Particle filters (PFs) are Monte Carlo data assimilation techniques that operate with no parametric assumptions for prior and posterior errors. A data assimilation method introduced recently, called the local PF, approximates the PF solution within neighborhoods of observations, thus allowing for its use in high-dimensional systems. The current study explores the potential of the local PF for atmospheric data assimilation through cloud-permitting numerical experiments performed for an idealized squall line. Using only 100 ensemble members, experiments using the local PF to assimilate simulated radar measurements demonstrate that the method provides accurate analyses at a cost comparable to ensemble filters currently used in weather models. Comparisons between the local PF and an ensemble Kalman filter demonstrate benefits of the local PF for producing probabilistic analyses of non-Gaussian variables, such as hydrometeor mixing ratios. The local PF also provides more accurate forecasts than the ensemble Kalman filter, despite yielding higher posterior root-mean-square errors. A major advantage of the local PF comes from its ability to produce more physically consistent posterior members than the ensemble Kalman filter, which leads to fewer spurious model adjustments during forecasts. This manuscript presents the first successful application of the local PF in a weather prediction model and discusses implications for real applications where nonlinear measurement operators and nonlinear model processes limit the effectiveness of current Gaussian data assimilation techniques.

A PDF-Based Parameterization of Subgrid-Scale Hydrometeor Transport in Deep Convection

Abstract A parameterization scheme is proposed for the subgrid-scale transport of hydrometeors in an assumed probability density function (PDF) scheme. Joint distributions of vertical velocity and hydrometeor mixing ratios are typically unknown, but marginal (1D) PDFs of these variables are available. The parameterization is developed using high-resolution simulations of continental and tropical deep convection. A 3D cloud-resolving model (CRM) providing benchmark solutions has a horizontal grid spacing of 250 m and employs the Morrison microphysics scheme, which treats prognostically mass and number mixing ratios for four types of precipitating hydrometeors (rain, graupel, snow, and ice) as well as cloud droplet number mixing ratio. The subgrid-scale hydrometeor transport scheme assumes input given in the form of marginal PDFs of vertical velocity and hydrometeor mixing ratios; in this study, these marginal distributions are provided by the cloud-resolving model. Conditional sampling and scaling are then applied to the marginal distributions to account for subplume correlations. The parameterized fluxes tested for four episodes of deep convection show good agreement with benchmark fluxes computed directly from the CRM output. The results demonstrate the potential use of the subgrid-scale hydrometeor transport scheme in an assumed PDF scheme to parameterize the covariances of vertical velocity and hydrometeor mixing ratios.

Direct Assimilation of Radar Reflectivity without Tangent Linear and Adjoint of the Nonlinear Observation Operator in the GSI-Based EnVar System: Methodology and Experiment with the 8 May 2003 Oklahoma City Tornadic Supercell

Abstract A GSI-based EnVar data assimilation system is extended to directly assimilate radar reflectivity to initialize convective-scale forecasts. When hydrometeor mixing ratios are used as state variables (method mixing ratio), large differences of the cost function gradients with respect to the small hydrometeor mixing ratios and wind prevent efficient convergence. Using logarithmic mixing ratios as state variables (method logarithm) fixes this problem, but generates spuriously large hydrometeor increments partly due to the transform to and from the logarithmic space. The tangent linear of the reflectivity operators further contributes to spuriously small and large hydrometeor increments in method mixing ratio and method logarithm, respectively. A new method is proposed by directly adding the reflectivity as a state variable (method dBZ). Without the tangent linear and adjoint of the nonlinear operator, the new method therefore avoids the aforementioned problems. The newly proposed method is examined on the analysis and prediction of the 8 May 2003 Oklahoma City tornadic supercell storm. Both the probabilistic forecast of strong low-level vorticity and maintenance of strong updraft and vorticity in method dBZ are more consistent with reality than in method logarithm and method mixing ratio. Detailed diagnostics suggest that a more realistic cold pool due to the better analyzed hydrometeors in method dBZ than in other methods leads to constructive interaction between the surface gust front and the updraft aloft associated with the midlevel mesocyclone. Similar low-level vorticity forecast and maintenance of the storm are produced by the WSM6 and Thompson microphysics schemes in method dBZ. The Thompson scheme matches the reflectivity distribution with the observations better for all lead times, but shows more southeastward track bias compared to the WSM6 scheme.

Hydrometeor Mixing Ratio Retrievals for Storm-Scale Radar Data Assimilation: Utility of Current Relations and Potential Benefits of Polarimetry

Abstract The assimilation of radar data into storm-scale numerical weather prediction models has been shown to be beneficial for successfully modeling convective storms. Because of the difficulty of directly assimilating reflectivity (Z), hydrometeor mixing ratios, and sometimes rainfall rate, are often retrieved from Z observations using retrieval relations, and are assimilated as state variables. The most limiting (although widely employed) cases of these relations are derived, and their assumptions and limitations are discussed. To investigate the utility of these retrieval relations for liquid water content (LWC) and ice water content (IWC) in rain and hail as well as the potential for improvement using polarimetric variables, two models with spectral bin microphysics coupled with a polarimetric radar operator are used: a one-dimensional melting hail model and the two-dimensional Hebrew University Cloud Model. The relationship between LWC and Z in pure rain varies spatially and temporally, with biases clearly seen using the normalized number concentration. Retrievals using Z perform the poorest while specific attenuation and specific differential phase shift (KDP) perform much better. Within rain–hail mixtures, separate estimation of LWC and IWC is necessary. Prohibitively large errors in the retrieved LWC may result when using Z. The quantity KDP can be used to effectively retrieve the LWC and to isolate the contribution of IWC to Z. It is found that the relationship between Z and IWC is a function of radar wavelength, maximum hail diameter, and principally the height below the melting layer, which must be accounted for in order to achieve accurate retrievals.

Assimilating Cloud Water Path as a Function of Model Cloud Microphysics in an Idealized Simulation

Abstract The sensitivity of assimilating satellite retrievals of cloud water path (CWP) to the microphysics scheme used by a convection-allowing numerical model is explored. All experiments use the Advanced Research core of the Weather Research and Forecasting Model (WRF-ARW), with observations assimilated using the Data Assimilation Research Testbed ensemble adjustment Kalman filter and a 40-member ensemble. Three-dimensional idealized supercell simulations are generated from a deterministic WRF nature run started from a homogeneous set of initial conditions. Four cloud microphysics schemes are tested: Lin–Farley–Orville (LFO), Thompson (THOMP), Morrison double-moment (MOR), and Milbrandt–Yau (MY). For the idealized experiments, assimilating CWP generates a mature supercell after approximately 1 h for all microphysics schemes. Vertical profiles of ensemble covariances show large differences in the relationship between CWP and various hydrometeor mixing ratios. While the differences in overall CWP are small, the experiments generate very different reflectivity analyses of the simulated storm, with MOR and MY underestimating reflectivity by a large margin. Vertical profiles of hydrometeor mixing ratios from each experiment are generally consistent with scheme design, such that the Thompson scheme characterizes the storm top as mostly snow whereas the Milbrandt–Yau scheme characterizes the storm top as mostly ice. The impacts of these differences on 30-min forecasts show that MOR and MY are unable to maintain convection within the model while THOMP and LFO perform somewhat better, though all fail to capture the divergent movement of the storm split in the nature run.

A limited area model (LAM) intercomparison study of a TWP‐ICE active monsoon mesoscale convective event

A limited area model (LAM) intercomparison study is conducted based on a tropical monsoonal deep convection case observed during the Tropical Warm Pool ‐ International Cloud Experiment (TWP‐ICE). The LAM simulations are compared with the variational analyses (VA) based on the Atmospheric Radiation Measurement (ARM) observations and the cloud resolving model (CRM) simulations forced by the VA. Driven by the ECMWF analyses or global model forecasts, LAMs are able to produce the large‐scale thermodynamic field reasonably well compared with the VA. However, the LAM simulated dynamic fields, such as the large‐scale horizontal divergence, vertical velocity, and cyclogenesis in the monsoonal trough, have a large inter‐model spread and deviate substantially from observations. Despite the differences in large‐scale forcing, there is certain consistency between the CRM and LAM simulations: stratiform (w ≤ 1 m s−1) ice clouds dominate the cloud fraction and convective (w > 3 m s−1) clouds occupy less than 3 percent of the total cloudy area. But the hydrometeor content of stratiform ice clouds is only one tenth of that of convective and transitional (1 m s−1 < w ≤ 3 m s−1) ice clouds. However, there is a large inter‐LAM spread in the simulated cloud fraction and hydrometeor mixing ratios. The inter‐LAM difference in solid phase hydrometeors (cloud ice, snow, and graupel) can be up to nearly a factor of 10. Among all the hydrometeor types, the stratiform ice clouds are simulated least consistently by the LAMs. The large inter‐LAM spread suggests that obtaining consistent and reliable dynamic and cloud fields remains a challenge for the LAM approach.

Characteristics of Mesoscale Organization in WRF Simulations of Convection during TWP-ICE

Abstract Compared to satellite-derived heating profiles, the Goddard Institute for Space Studies general circulation model (GCM) convective heating is too deep and its stratiform upper-level heating is too weak. This deficiency highlights the need for GCMs to parameterize the mesoscale organization of convection. Cloud-resolving model simulations of convection near Darwin, Australia, in weak wind shear environments of different humidities are used to characterize mesoscale organization processes and to provide parameterization guidance. Downdraft cold pools appear to stimulate further deep convection both through their effect on eddy size and vertical velocity. Anomalously humid air surrounds updrafts, reducing the efficacy of entrainment. Recovery of cold pool properties to ambient conditions over 5–6 h proceeds differently over land and ocean. Over ocean increased surface fluxes restore the cold pool to prestorm conditions. Over land surface fluxes are suppressed in the cold pool region; temperature decreases and humidity increases, and both then remain nearly constant, while the undisturbed environment cools diurnally. The upper-troposphere stratiform rain region area lags convection by 5–6 h under humid active monsoon conditions but by only 1–2 h during drier break periods, suggesting that mesoscale organization is more readily sustained in a humid environment. Stratiform region hydrometeor mixing ratio lags convection by 0–2 h, suggesting that it is strongly influenced by detrainment from convective updrafts. Small stratiform region temperature anomalies suggest that a mesoscale updraft parameterization initialized with properties of buoyant detrained air and evolving to a balance between diabatic heating and adiabatic cooling might be a plausible approach for GCMs.

Potential Impacts of the Introduction of Low-Sulfur Fuel on Concentrations at Breathing Level in a Subarctic City

The effects of using low-sulfur fuel for oil-heating and oil-burning facilities on the concentrations at breathing level in an Alaska city surrounded by vast areas were examined with the Weather Research and Forecasting model coupled with chemistry packages that was modified for the subarctic. Simulations were performed in forecast mode for a cold season using the National Emission Inventory 2008 and alternatively emissions that represent the use of low-sulfur fuel for oil-heating and oil-burning facilities while keeping the emissions of other sources the same as in the reference simulation. The simulations suggest that introducing low-sulfur fuel would decrease the monthly mean 24 h-averaged concentrations over the city’s nonattainment area by 4%, 9%, 8%, 6%, 5%, and 7% in October, November, December, January, February, and March, respectively. The quarterly mean relative response factors for of 0.96 indicate that with a design value of 44.7 μg/m3introducing low-sulfur fuel would lead to a new design value of 42.9 μg/m3that still exceeds the US National Ambient Air Quality Standard of 35 μg/m3. The magnitude of the relation between the relative response of sulfate and nitrate changes differs with temperature. The simulations suggest that, in the city, concentrations would decrease stronger on days with low atmospheric boundary layer heights, low hydrometeor mixing ratio, low downward shortwave radiation, and low temperatures.

Kinematics and microphysics of MAP-IOP3 event from radar observations and Meso-NH simulations

This paper presents a kinematic and microphysical study of the MAP-IOP3 orographic precipitation event performed with radar observations and Meso-NH numerical simulations. Studies relying on both observations and mesoscale model simulations are of great interest for achieving a better understanding of intense precipitation events. Despite some slight discrepancies between radar observations and numerical outputs in the present work, both emphasize the same phenomena. The merging of two convective cells, which is an important mechanism to locally enhance precipitation is shown. Beyond Meso-NH outputs and radar observations similarities, the Meso-NH model completes and precises qualitative conclusions inferred from radar observations. In particular, it permits to identify and quantify the microphysical processes involved in the triggering and development of the orographic precipitation. The computation of hydrometeor mixing ratio and microphysical budgets highlights the convective nature of the IOP3 precipitation, which is characterized by efficient microphysical mechanisms such as heavy riming, warm coalescence, and melting of heavy particles (graupel and hail). More precisely, the initiation of the system is associated with warm microphysics whereas the development of the system and enhancement of rain involve graupel and hail.

A 3.5‐Dimensional Variational Method for Doppler Radar Data Assimilation and Its Application to Phased‐Array Radar Observations

A 3.5‐dimensional variational method is developed for Doppler radar data assimilation. In this method, incremental analyses are performed in three steps to update the model state upon the background state provided by the model prediction. First, radar radial‐velocity observations from three consecutive volume scans are analyzed on the model grid. The analyzed radial‐velocity fields are then used in step 2 to produce incremental analyses for the vector velocity fields at two time levels between the three volume scans. The analyzed vector velocity fields are used in step 3 to produce incremental analyses for the thermodynamic fields at the central time level accompanied by the adjustments in water vapor and hydrometeor mixing ratios based on radar reflectivity observations. The finite element B‐spline representations and recursive filter are used to reduce the dimension of the analysis space and enhance the computational efficiency. The method is applied to a squall line case observed by the phased‐array radar with rapid volume scans at the National Weather Radar Testbed and is shown to be effective in assimilating the phased‐array radar observations and improve the prediction of the subsequent evolution of the squall line.

Responses of vertical structures in convective and stratiform regions to large-scale forcing during the landfall of severe tropical storm Bilis (2006)

The responses of vertical structures, in convective and stratiform regions, to the large-scale forcing during the landfall of tropical storm Bilis (2006) are investigated using the data from a two-dimensional cloud-resolving model simulation. An imposed large-scale forcing with upward motion in the mid and upper troposphere and downward motion in the lower troposphere on 15 July suppresses convective clouds, which leads to ∼100% coverage of raining stratiform clouds over the entire model domain. The imposed forcing extends upward motion to the lower troposphere during 16–17 July, which leads to an enhancement of convective clouds and suppression of raining stratiform clouds. The switch of large-scale lower-tropospheric vertical velocity from weak downward motion on 15 July to moderate upward motion during 16–17 July produces a much broader distribution of the vertical velocity, water vapor and hydrometeor fluxes, perturbation specific humidity, and total hydrometeor mixing ratio during 16–17 July than those on 15 July in the analysis of contoured frequency-altitude diagrams. Further analysis of the water vapor budget reveals that local atmospheric moistening is mainly caused by the enhancement of evaporation of rain associated with downward motion on 15 July, whereas local atmospheric drying is mainly determined by the advective drying associated with downward motion over raining stratiform regions and by the net condensation associated with upward motion over convective regions during 16–17 July.

Sensitivity of satellite observations for freshly produced lightning NO<sub>x</sub>

Abstract. In this study, we analyse the sensitivity of nadir viewing satellite observations in the visible range to freshly produced lightning NOx. This is a particular challenge due to the complex and highly variable conditions of meteorology, (photo-) chemistry, and radiative transfer in and around cumulonimbus clouds. For the first time, such a study is performed accounting for photo-chemistry, dynamics, and radiative transfer in a consistent way: A one week episode in the TOGA COARE/CEPEX region (Pacific) in December 1992 is simulated with a 3-D cloud resolving chemistry model. The simulated hydrometeor mixing ratios are fed into a Monte Carlo radiative transfer model to calculate box-Air Mass Factors (box-AMFs) for NO2. From these box-AMFs, together with model NOx profiles, slant columns of NO2 (SNO2), i.e. synthetic satellite measurements, are calculated and set in relation to the actual model NOx vertical column (VNOx), yielding the "sensitivity" SNO2/VNOx. From this study, we find a mean sensitivity of 0.46. NOx below the cloud bottom is mostly present as NO2, but shielded from the satellites' view, whereas NOx at the cloud top or above is shifted to NO due to high photolysis and low temperature, and hence not detectable from space. However, a significant fraction of the lightning produced NOx in the middle part of the cloud is present as NO2 and has a good visibility from space. Due to the resulting total sensitivity being quite high, nadir viewing satellites provide a valuable additional platform to quantify NOx production by lightning; strong lightning events over "clean" regions should be clearly detectable in satellite observations. Since the observed enhancement of NO2 column densities over mesoscale convective systems are lower than expected for current estimates of NOx production per flash, satellite measurements can in particular constrain the upper bound of lightning NOx production estimates.

Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part I: Observation Operators for Reflectivity and Polarimetric Variables

Abstract A radar simulator for polarimetric radar variables, including reflectivities at horizontal and vertical polarizations, the differential reflectivity, and the specific differential phase, has been developed. This simulator serves as a test bed for developing and testing forward observation operators of polarimetric radar variables that are needed when directly assimilating these variables into storm-scale numerical weather prediction (NWP) models, using either variational or ensemble-based assimilation methods. The simulator takes as input the results of high-resolution NWP model simulations with ice microphysics and produces simulated polarimetric radar data that may also contain simulated errors. It is developed based on calculations of electromagnetic wave propagation and scattering at the S band of wavelength 10.7 cm in a hydrometeor-containing atmosphere. The T-matrix method is used for the scattering calculation of raindrops and the Rayleigh scattering approximation is applied to snow and hail particles. The polarimetric variables are expressed as functions of the hydrometeor mixing ratios as well as their corresponding drop size distribution parameters and densities. The presence of wet snow and wet hail in the melting layer is accounted for by using a new, relatively simple melting model that defines the water fraction in the melting snow or hail. The effect of varying density due to the melting snow or hail is also included. Vertical cross sections and profiles of the polarimetric variables for a simulated mature multicellular squall-line system and a supercell storm show that polarimetric signatures of the bright band in the stratiform region and those associated with deep convection are well captured by the simulator.

Kinematics, cloud microphysics and spatial structures of tropical cloud clusters: A two-dimensional cloud-resolving modeling study

Kinematics, cloud microphysics and spatial structures of tropical cloud clusters are investigated using hourly outputs from a two-dimensional cloud-resolving model simulation. The model is forced by the large-scale vertical velocity, zonal wind and horizontal advections obtained from Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). A period of 1600–2300 LST 21 December 1992 is selected for this study when the zonal-mean westerly winds in the lower troposphere intensify while the zonal-mean easterly winds above weaken. Under the vertical-shear environment, there are a westward-propagating cloud cluster, a newly-formed cloud cluster, and four eastward-moving cloud clusters. Two weak eastward-moving cloud clusters merge into strong westward-moving cloud clusters. Merged clouds display notable growth in the eastern edge, indicating that merging processes enhance convection. The development of the new cloud at the western edge of the existing cloud cluster before merging may account for the westward propagation of cloud cluster group, while the advection of the maximum total hydrometeor mixing ratio by the westerly winds after merging may cause the eastward propagation of individual cloud clusters.

A modeling study of moist and dynamic vorticity vectors associated with two‐dimensional tropical convection

Moist ( × ∇qv/ρ, MVV) and dynamic ( × /ρ, DVV) vorticity vectors are introduced to study 2‐D tropical convection with 2‐D cloud‐resolving simulation data. The cloud model is forced by vertical velocity, zonal wind, horizontal advection, and sea surface temperature data obtained from TOGA COARE and is integrated for a selected 10‐day period. The MVV and DVV have zonal and vertical components in the 2‐D x‐z frame. Analysis of zonally averaged and mass‐integrated quantities shows that the vertical (zonal) component of the MVV and the sum of the cloud hydrometeor mixing ratios are in phase with a correlation coefficient of 0.78 (0.32), and the vertical (zonal) component of the DVV and the sum of the mixing ratios are in (out of) phase with a correlation coefficient of 0.52 (−0.62), indicating that the vertical component of the MVV and both zonal and vertical component of the DVV are closely associated with tropical convection. The tendency equations for the MVV and DVV are derived, and the zonally averaged and mass‐integrated tendency budgets are analyzed. The tendency of the vertical component of the MVV is mainly determined by the interaction between the vorticity and the zonal gradient of condensational/depositional heating. The tendency of the zonal component of the DVV is controlled by the interaction between the vorticity, buoyancy, and vertical pressure gradient, whereas the tendency of the vertical component is determined by the interaction between the vorticity and zonal pressure gradient.

A convective vorticity vector associated with tropical convection: A two‐dimensional cloud‐resolving modeling study

Although dry/moist potential vorticity (( · ∇θe)/ρ) is a useful physical quantity for meteorological analysis, it cannot be applied to the analysis of two‐dimensional (2‐D) simulations. A new vorticity vector ( × ∇θe)/ρ (convective vorticity vector (CVV)) is introduced in this study to analyze 2‐D cloud‐resolving simulation data associated with 2‐D tropical convection. The cloud model is forced by the vertical velocity, zonal wind, horizontal advection, and sea surface temperature obtained from the Tropical Ocean‐Global Atmosphere (TOGA) Coupled Ocean‐Atmosphere Response Experiment (COARE) and is integrated for a selected 10‐day period. The CVV has zonal and vertical components in the 2‐D x‐z frame. Analysis of zonally averaged and mass‐integrated quantities shows that the correlation coefficient between the vertical component of the CVV and the sum of the cloud hydrometeor mixing ratios is 0.81, whereas the correlation coefficient between the zonal component and the sum of the mixing ratios is only 0.18. This indicates that the vertical component of the CVV is closely associated with tropical convection. The tendency equation for the vertical component of the CVV is derived and the zonally averaged and mass‐integrated tendency budgets are analyzed. The tendency of the vertical component of the CVV is determined by the interaction between the vorticity and the zonal gradient of cloud heating. The results demonstrate that the vertical component of the CVV is a cloud‐linked parameter and can be used to study tropical convection.

Diagnosis of hydrometeor profiles from area‐mean vertical‐velocity data

AbstractA simple one‐dimensional microphysical retrieval model is developed for estimating vertical profiles of liquid and frozen hydrometeor mixing ratios from observed vertical profiles of area‐mean vertical velocity in regions of convective and/or stratiform precipitation. The mean vertical‐velocity profiles can be obtained from Doppler radar (single and dual) or other means. The one‐dimensional results are shown to be in good agreement with two‐dimensional microphysical fields from a previous study. Sensitivity tests are performed.