Stratiform Case Research Articles

Assimilation of 3D polarimetric microphysical retrievals in a convective-scale NWP system

Abstract. This study assimilates for the first time polarimetric C-band radar observations from the German meteorological service (DWD) into DWD's convective-scale model ICON-D2 using DWD's ensemble-based KENDA assimilation framework. We compare the assimilation of conventional observations (CNV) with the additional assimilation of radar reflectivity Z (CNV + Z), with the additional assimilation of liquid or ice water content (LWC or IWC) estimates below or above the melting layer instead of Z where available (CNV + LWC/Z or CNV + IWC/Z respectively). Hourly quantitative precipitation forecasts (QPF) are evaluated for two stratiform and one convective rainfall events in the summers of 2017 and 2021. With optimized data assimilation settings (e.g., observation errors), the assimilation of LWC mostly improves first-guess QPF compared with the assimilation of Z alone (CNV + Z), whereas the assimilation of IWC does not, especially for convective cases, probably because of the lower quality of the IWC retrieval in these situations. Improvements are, however, notable for stratiform rainfall in 2021, for which the IWC estimator profits from better specific differential phase estimates owing to a higher radial radar resolution than the other cases. The assimilation of all radar data sets together (CNV + LWC + IWC + Z) yields the best first guesses. All assimilation configurations with radar information consistently improve deterministic 9 h QPF compared with the assimilation of only conventional data (CNV). Forecasts based on the assimilation of LWC and IWC retrievals on average slightly improve Fraction Skill Score (FSS) and Frequency Bias (FBI) compared with the assimilation of Z alone (CNV + Z), especially when LWC is assimilated for the 2017 convective case and when IWC is assimilated for the high-resolution 2021 stratiform case. However, IWC assimilation again degrades forecast FSS for the convective cases. Forecasts initiated using all radar data sets together (CNV + LWC + IWC + Z) yield the best FSS. The development of IWC retrievals that are more adequate for convection constitutes one next step to further improving the exploitation of ice microphysical retrievals for radar data assimilation.

Microphysical Characteristics of Precipitating Stratiform Clouds in North China Revealed by Joint Observations of an Aircraft and a Polarimetric Radar

Abstract Microphysical structures and processes in a case of precipitating stratiform clouds in North China on 21 May 2018 are investigated using joint observations from an aircraft and an X-band polarimetric radar. The results show that there are enhancements in differential reflectivity (ZDR) and specific differential phase (KDP) above the 7-km altitude, consistent with the existence of dendrites and platelike ice crystals. The horizontal reflectivity factor (ZH) increases and ZDR decreases downward above the melting layer (ML), due to the prevalent aggregation process, which is confirmed by the downward increasing volume-weighted mean diameter (Dm) and decreasing total number concentration (Nt) observed by the aircraft. Within the ML, the concentration of median-sized particles (2–5 mm) decreases rapidly downward due to the melting process. Within approximately the top 2/3 of the ML, the melting particles’ mean and maximum sizes increase, demonstrating the dominance of the aggregation process. This causes the enhancements of ZH and ZDR within the radar bright band together with the increase in the dielectric constant. Within the bottom 1/3 of the ML, the breakup process is responsible for the decreasing Dm and increasing Nt observed by the aircraft. Below the ML, the measurements by the polarimetric radar and the aircraft only show slight variance with altitude, indicating the near balance between microphysical processes favored by the nearly saturated air. The results of the microphysics in the stratiform case would help improve the microphysical parameterization of numerical modeling in the future.

Assessing the benefits of specific attenuation for quantitative precipitation estimation with a C-band radar network

AbstractRecent advances demonstrate the benefits of radar-derived specific attenuation at horizontal polarization (AH) for quantitative precipitation estimation (QPE) at S and X band. To date the methodology has, however, not been adapted for the widespread European C-band radars such as installed in the network of the German Meteorological Service (DWD, Deutscher Wetterdienst). Simulations based on a large dataset of drop size distributions (DSDs) measured over Germany are performed to investigate the DSD dependencies of the attenuation parameter αH for the AH estimates. The normalized raindrop concentration (Nw) and the change of differential reflectivity (ZDR) with reflectivity at horizontal polarization (ZH) are used to categorize radar observations into regimes for which scan-wise optimized αH values are derived. For heavier continental rain with ZH > 40 dBZ, the AH-based rainfall retrieval R(AH) is combined with a rainfall estimator using a substitute of specific differential phase (). We also assess the performance of retrievals based on specific attenuation at vertical polarization (AV). Finally, the regime-adapted hybrid QPE algorithms are applied to four convective cases and one stratiform case from 2017 to 2019, and compared to DWD’s operational RAdar-OnLine-ANeichung (RADOLAN) RW rainfall product, which is based on Zh only but adjusted to rain gauge measurements. For the convective cases, our hybrid retrievals outperform the traditional R(Zh) and pure R(AH/V) retrievals with fixed αH/V values when evaluated with gauge measurements and outperform RW when evaluated by disdrometer measurements. Potential improvements using ray-wise αH/V and segment-wise applications of the ZPHI method along the radials are discussed.

Preliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment

Abstract. The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Météo-France on top of the Moucherotte mountain (1901 m above sea level; hereinafter MOUC radar). In the Grenoble valley (220 m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Φdp) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Ψdp) from which the profiles of the specific differential phase shift on propagation (Kdp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k–Kdp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i) nine convective cases with high rain rates which allow us to study the ϕdp–PIA relationship in rain, and (ii) a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500 m a.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the ϕdp–PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k–Kdp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k–Kdp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding ϕdp value and their ratio are evidenced within the ML. In particular, the averaged PIA∕ϕdp ratio, a proxy for the slope of a linear k–Kdp relationship in the ML, peaks at the level of the copolar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.42 dB per degree. Its value in rain below the ML is 0.33 dB per degree, which is in rather good agreement with the slope of the linear k–Kdp relationship derived from DSD measurements at ground level. The PIA∕ϕdp ratio remains quite high in the upper part of the ML, between 0.32 and 0.38 dB per degree, before tending towards 0 above the ML.

STUDY ON SUMMER RAINDROP SIZE DISTRIBUTION AND RETRIEVED POLARIMETRIC RADAR PARAMETER OVER LEIZHOU PENINSULA

Abstract. Leizhou peninsula is located in the south of Guangdong Province, near South China Sea, and has a tropical and subtropical monsoon climate. Based on observed drop size distribution (DSD) data from July 2007 to August 2007 with PARSIVEL disdrometers deployed at Zhanjiang and Suixi, the characterists of DSDs are studied. Non-linear least squares method is used to fit Gamma distribution. Convective and stratiform averaged DSDs are in good agreement with Gamma distribution, especially in stratiform case. Convective average DSDs have a wider spectrum and higher peak. Microphysical parameter differences between convective and stratiform are discussed, convective precipitation has a higher mass-weighted mean diameter (Dm) and generalized intercepts (Nw) in both areas. The constrained relations between Gamma distribution parameter (μ, Λ, N0) is derived. The retrieved polarimetric radar parameter (KDP, ZDR, Zh) have a good self-consistency, which can be used to improve the accuracy of KDP calculation. R-KDP-ZDR is superior to the R-KDP, R-ZDR-Zh in quantitative precipitation estimation (QPE), with a correlation coefficient higher than 0.98.

Understanding Ice Cloud‐Precipitation Properties of Three Modes of Mesoscale Convective Systems During PECAN

AbstractThis study analyzes the precipitation and ice cloud microphysical features of three common modes of linear mesoscale convective systems during the Plains Elevated Convection at Night (PECAN) campaign. Three cases, one for each linear mesoscale convective system archetype (trailing stratiform, leading stratiform, and parallel stratiform precipitation), are selected. We focus primarily on analyzing ice cloud microphysical properties and precipitation rates (PRs) over the classified convective core (CC) and stratiform rain (SR) regions, as well as the two stratiform regions that developed behind (SR1) and ahead (SR2) of the convective line relative to the storm motion. In the three selected cases, the ice water path (IWP) and PR have strong correlations in the CC, but not in the SR. In terms of the temporal evolution of the mean IWPs and PRs, both CC and SR IWPs, as well as CC PRs, reach peaks quickly but take a longer time to dissipate than the increase period. For all the three cases, both SR1 and SR2 IWPs are 20–70% of their corresponding CC values in both the leading stratiform and parallel stratiform cases and up to 95% for the trailing stratiform case, while all of their PRs are only 7–25% of their CC values. These values suggest not only that the SR PRs may depend on IWPs but also that the microphysical properties of ice particles such as habit and size distribution may play an important role. Utilizing cloud‐resolving simulations of these systems may provide better understanding of the physical meanings behind the results in the future.

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds

Abstract. State-of-the-art aerosol-dependent parameterisations describing each heterogeneous ice nucleation mode (contact, immersion, and deposition ice nucleation), as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamic conditions between the cases, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays only a small role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurring simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration do affect the dominant ice nucleation mode; however, they have only a minor influence on the precipitation amount.

Estimation of Raindrop Size Distribution Parameters Using Rain Attenuation Data from a Ku-Band Communications Satellite

The rain attenuation of down-link radio wave signals from the Superbird-C satellite and surface rainfall data have been used to estimate the parameters of exponential raindrop size distribution (DSD) at Koto Tabang (100.32 ° E, 0.20 ° S), West Sumatra, Indonesia. Prior to analyzing the measured data, the ability of the method to recover the parameters of known DSDs from which the samples were taken was examined. It was found that the method can accurately retrieve the input parameter of the sample. Only six case studies are presented here, so the results are representative rather than definitive. The method successfully estimated the DSD parameters of a stratiform case with steady intensity and deep convective rains of a short duration. This can be inferred from the small difference between the parameters derived from rain attenuation data and those derived from a 2D video disdrometer. The poor performance of the method was observed for a stratiform case with strong rain intensity fluctuation and shallow convective rains with very low rain top height. This phenomenon is probably due to the bias that may be inherent in the estimation of specific rain attenuation, such as the assumption of a constant path length throughout the rain.

Convective transport of water vapor into the lower stratosphere observed during double-tropopause events

We present in situ observations of convectively injected water vapor in the lower stratosphere from instruments aboard two aircraft operated during the Deep Convective Clouds and Chemistry experiment. Water vapor mixing ratios in the injected air are observed to be 60–225 ppmv at altitudes 1–2 km above the tropopause (350–370 K potential temperature), well above observed background mixing ratios of 5–10 ppmv in the lower stratosphere. Radar observations of the responsible convective systems show deep overshooting at altitudes up to 4 km above the lapse rate tropopause and above the flight ceilings of the aircraft. Backward trajectories from the in situ observations show that convectively injected water vapor is observed from three distinct types of systems: isolated convection, a convective line, and a leading line-trailing stratiform mesoscale convective system. Significant transport of additional tropospheric or boundary layer trace gases is observed only for the leading line-trailing stratiform case. In addition, all observations of convective injection are found to occur within large-scale double-tropopause events from poleward Rossby wave breaking. Based on this relationship, we present a hypothesis on the role of the large-scale lower stratosphere during convective overshooting. In particular, the reduced lower stratosphere stability associated with double-tropopause environments may facilitate deeper levels of overshooting and convective injection.

Stochastic Space–Time Disaggregation of Rainfall into DSD fields

Abstract A stochastic method to disaggregate rain rate fields into drop size distribution (DSD) fields is proposed. It is based on a previously presented DSD simulator that has been modified to take into account prescribed block-averaged rain rate values at a coarser scale. The integral quantity used to drive the disaggregation process can be the rain rate, the radar reflectivity, or any variable directly related to the DSD. The proposed method is illustrated and qualitatively evaluated using radar rain rate data provided by MeteoSwiss for two rain events of very contrasted type (stratiform versus convective). The evaluation shows that both types of rainfall are correctly disaggregated, although the general agreement in terms of rain rate distributions, intermittency, and space–time structures is much better for the stratiform case. Possible extensions and generalizations of the technique (e.g., using radar reflectivities at two different frequencies or polarizations to drive the disaggregation process) are discussed at the end of the paper.

A regional ensemble forecast system for stratiform precipitation events in northern China. Part I: A case study

A single-model, short-range, ensemble forecasting system (Institute of Atmospheric Physics, Regional Ensemble Forecast System, IAP REFS) with 15-km grid spacing, configured with multiple initial conditions, multiple lateral boundary conditions, and multiple physics parameterizations with 11 ensemble members, was developed using the Weather and Research Forecasting Model Advanced Research modeling system for prediction of stratiform precipitation events in northern China. This is the first part of a broader research project to develop a novel cloud-seeding operational system in a probabilistic framework. The ensemble perturbations were extracted from selected members of the National Center for Environmental Prediction Global Ensemble Forecasting System (NCEP GEFS) forecasts, and an inflation factor of two was applied to compensate for the lack of spread in the GEFS forecasts over the research region. Experiments on an actual stratiform precipitation case that occurred on 5–7 June 2009 in northern China were conducted to validate the ensemble system. The IAP REFS system had reasonably good performance in predicting the observed stratiform precipitation system. The perturbation inflation enlarged the ensemble spread and alleviated the underdispersion caused by parent forecasts. Centering the extracted perturbations on higher-resolution NCEP Global Forecast System forecasts resulted in less ensemble mean root-mean-square error and better accuracy in probabilistic quantitative precipitation forecasts (PQPF). However, the perturbation inflation and recentering had less effect on near-surface-level variables compared to the mid-level variables, and its influence on PQPF resolution was limited as well.

Evaluation of microphysical assumptions of the COSMO model using radar and rain gauge observations

The exact forecast of precipitation is a challenge. New microphysics formulations were introduced recently into the COSMO model in order to improve the precipitation forecast. An important modification was the change from the autoconversion and accretion scheme following the Kessler (1969) formulation to the Seifert and Beheng (2001) scheme. The other main modification was implemented in the snow parameterisation by replacing the constant intercept parameter to a temperature dependent intercept parameter. These micro-physics modifications are evaluated in detail in three case studies (one stratiform and two convective cases) by comparing the modelled and observed reflectivity and precipitation data. Comparisons to weather radar reflectivity data show that especially light to moderate precipitation forecast (< 20 dB) is improved. For the evaluation of the modelled precipitation, weather radar and rain gauge data are combined in order to get spatially high resolution data of high accuracy. For the quality analysis, the new error measure SAL (analysis of structure, amplitude and location) is used. The results show that the new microphysics formulations improve the precipitation amplitude forecast of up to 50% for the convective cases while the forecast for the stratiform case is not improved.

Evaluation of moist processes during intense precipitation in km-scale NWP models using remote sensing and in-situ data: Impact of microphysics size distribution assumptions

This study investigates the sensitivity of moist processes and surface precipitation during three extreme precipitation events over Belgium to the representation of rain, snow and hail size distributions in a bulk one-moment microphysics parameterisation scheme. Sensitivities included the use of empirically derived relations to calculate the slope parameter and diagnose the intercept parameter of the exponential snow and rain size distributions and sensitivities to the treatment of hail/graupel. A detailed evaluation of the experiments against various high temporal resolution and spatially distributed observational data was performed to understand how moist processes responded to the implemented size distribution modifications. Net vapour consumption by microphysical processes was found to be unaffected by snow or rain size distribution modifications, while it was reduced replacing formulations for hail by those typical for graupel, mainly due to intense sublimation of graupel. Cloud optical thickness was overestimated in all experiments and all cases, likely due to overestimated snow amounts. The overestimation slightly deteriorated by modifying the rain and snow size distributions due to increased snow depositional growth, while it was reduced by including graupel. The latter was mainly due to enhanced cloud water collection by graupel and reduced snow depositional growth. Radar reflectivity and cloud optical thickness could only be realistically represented by inclusion of graupel during a stratiform case, while hail was found indispensable to simulate the vertical reflectivity profile and the surface precipitation structure. Precipitation amount was not much altered by any of the modifications made and the general overestimation was only decreased slightly during a supercell convective case.

Tropical Rainfall Associated with Convective and Stratiform Clouds: Intercomparison of Disdrometer and Profiler Measurements

The motivation for this research is to move in the direction of improved algorithms for the remote sensing of rainfall, which are crucial for meso- and large-scale circulation studies and climate applications through better determinations of precipitation type and latent heating profiles. Toward this end a comparison between two independent techniques, designed to classify precipitation type from 1) a disdrometer and 2) a 915-MHz wind profiler, is presented, based on simultaneous measurements collected at the same site during the Intensive Observing Period of the Tropical Ocean Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment. Disdrometer-derived quantities such as differences in drop size distribution parameters, particularly the intercept parameter N0 and rainfall rate, were used to classify rainfall as stratiform or convective. At the same time, profiler-derived quantities, namely, Doppler velocity, equivalent reflectivity, and spectral width, from Doppler spectra were used to classify precipitation type in four categories: shallow convective, deep convective, mixed convective‐stratiform, and stratiform. Overall agreement between the two algorithms is found to be reasonable. Given the disdrometer stratiform classification, the mean profile of reflectivity shows a distinct bright band and associated large vertical gradient in Doppler velocity, both indicators of stratiform rain. For the disdrometer convective classification the mean profile of reflectivity lacks a bright band, while the vertical gradient in Doppler velocity below the melting level is opposite to the stratiform case. Given the profiler classifications, in the order shallow‐deep‐mixed‐stratiform, the composite raindrop spectra for a rainfall rate of 5 mm h 21 show an increase in D0, the median volume diameter, consistent with the dominant microphysical processes responsible for drop formation. Nevertheless, the intercomparison does reveal some limitations in the classification methodology utilizing the disdrometer or profiler algorithms in isolation. In particular, 1) the disdrometer stratiform classification includes individual cases in which the vertical profiles appear convective, but these usually occur at times when the disdrometer classification is highly variable; 2) the profiler classification scheme also appears to classify precipitation too frequently as stratiform by including cases that have small vertical Doppler velocity gradients at the melting level but no bright band; and 3) the profiler classification scheme includes a category of mixed (stratiform‐convective) precipitation that has some features in common with deep convection (e.g., enhanced spectral width above the melting level) but other features in common with stratiform precipitation (e.g., well-developed melting layer signature). Comparison of the profiler-derived vertical structure with disdrometer-determined rain rates reveals that almost all cases of rain rates greater than 10 mm h 21 are convective. For rain rates less than 5 mm h21 all four profiler-determined precipitation classes are well represented.

Evaluation of radiative parameterizations using an explicit cloud microphysical model

Based on the simulations with a 3-D large-eddy simulation model of marine cloud-topped boundary layer that includes explicit cloud physics formulation, we have evaluated the effect of spatial inhomogeneities in cloud macro- and microstructure on the performance of parameterizations of optical depth commonly used in large-scale models. We have shown that an accurate parameterization of the grid average optical depth alone is not sufficient for correct determination of cloud transmittance to solar radiation due to the non-linear dependence between these two variables. The problem can be solved by introducing the “equivalent” value of optical depth that differs from the ordinarily defined mean optical depth by a factor α t, that depends on the degree of cloud inhomogeneity and ranges from about 2 in the cumulus case to about 1.3 in the stratiform case. The accuracy of cloud optical depth parameterizations commonly employed in largescale models has been evaluated using the data from the explicit microphysical model as a benchmark for comparison. It has been shown that in the cumulus cloud case the parameterized expressions can err by as much as 100%. The error is smaller for more uniform stratiform clouds, where the error for some parameterizations varied in the 10–40% range. The best results are given by parameterizations that account for vertical stratification of parameters on which they are based. However, the error given by a particular parameterization varies and is different at cloud and surface levels. The results show the limitations of the existing simplified parameterizations and illustrate the scope and complexity of the cloud radiation parameterization problem.