ALBERT

Description: The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment, including radiosondes optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height, and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE dataset, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

Description: Evidence of multiple-scattering-induced pulse stretching for the signal of both frequencies of the Dual-Frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) mission Core Observatory satellite is presented on the basis of collocated ground-based WSR-88D S-band observations of an extreme case: a tornadic supercell. The ground-based observations clearly show a tilted convective core with a so-called bounded weak-echo region—that is, locations where precipitation is absent or extremely light at the ground while large amounts of liquid or frozen precipitation are present aloft. The satellite observations in this region show reflectivity profiles that extend all the way to the surface despite the absence of near-surface precipitation: these are here referred to as “ghost echoes.” Furthermore, the Ku- and Ka-band profiles exhibit similar slopes, which is a typical sign that the observed power is almost entirely due to multiple scattering. A novel microphysical retrieval that is based on triple-frequency (S–Ku–Ka) observations shows that a dense ice core located between 4 and 14 km with particle sizes exceeding 2.5 cm and integrated ice contents exceeding 7.0 kg m−2 is the source of the ghost echoes of the signal in the lower layers. The level of confidence of this assessment is strengthened by the availability of the S-band data, which provide the necessary additional constraints to the radar retrieval that is based on DPR data. This study shows not only that multiple-scattering contributions may become predominant at Ka already very high up in the atmosphere but also that they play a key role at Ku band within the layers close to the surface. As a result, extreme caution must be paid even in the interpretation of Ku-based retrievals (e.g., the TRMM PR dataset or any DPR retrievals that are based on the assumption that Ku band is not affected by multiple scattering) when examining extreme surface rain rates that occur in the presence of deep dense ice layers.

Description: By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission Core Observatory satellite’s suite of sensors and by the ground-based S-band Next Generation Weather Radar (NEXRAD) network over the continental United States, proxies for the identification of hail are developed from the GPM Core Observatory satellite observables. The full capabilities of the GPM Core Observatory are tested by analyzing more than 20 observables and adopting the hydrometeor classification on the basis of ground-based polarimetric measurements being truth. The proxies have been tested using the critical success index (CSI) as a verification measure. The hail-detection algorithm that is based on the mean Ku-band reflectivity in the mixed-phase layer performs the best of all considered proxies (CSI of 45%). Outside the dual-frequency precipitation radar swath, the polarization-corrected temperature at 18.7 GHz shows the greatest potential for hail detection among all GPM Microwave Imager channels (CSI of 26% at a threshold value of 261 K). When dual-variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka bands outperforms all of the other proxies, with a CSI of 49%. The best-performing radar–radiometer algorithm is based on the mixed-phase reflectivity at Ku band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm that is based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

Description: A statistical analysis of simultaneous observations of more than 800 hailstorms over the continental United States performed by the Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) and the ground-based Next Generation Weather Radar (NEXRAD) network has been carried out. Several distinctive features of DPR measurements of hail-bearing columns, potentially exploitable by hydrometeor classification algorithms, are identified. In particular, the height and the strength of the Ka-band reflectivity peak show a strong relationship with the hail shaft area within the instrument field of view (FOV). Signatures of multiple scattering (MS) at the Ka band are observed for a range of rimed particles, including but not exclusively for hail. MS amplifies uncertainty in the effective Ka reflectivity estimate and has a negative impact on the accuracy of dual-frequency rainfall retrievals at the ground. The hydrometeor composition of convective cells presents a large inhomogeneity within the DPR FOV. Strong nonuniform beamfilling (NUBF) introduces large ambiguities in the attenuation correction at Ku and Ka bands, which additionally hamper quantitative retrievals. The effective detection of profiles affected by MS is a very challenging task, since the inhomogeneity within the DPR FOV may result in measurements that look remarkably like MS signatures. The shape of the DPR reflectivity profiles is the result of the complex interplay between the scattering properties of the different hydrometeors, NUBF, and MS effects, which significantly reduces the ability of the DPR system to detect hail at the ground.

Description: Instantaneous surface rain rate estimates from the Global Precipitation Measurement (GPM) mission’s Dual-Frequency Precipitation Radar (DPR) and combined DPR and multifrequency microwave imager (CMB) version-5 products are compared to those from the Met Office Radarnet 4 system’s Great Britain and Ireland (GBI) radar composite product. The spaceborne and ground-based rainfall products are collocated spatially and temporally and compared at 5- and 25-km resolutions over GBI during a 3-yr period (from May 2014 to April 2017). The comparison results are evaluated as a function of both the intensity and variability of precipitation within the DPR field of view and are stratified spatially and seasonally. CMB and DPR products underestimate rain rates with respect to the Radarnet product by 21% and 31%, respectively, when considering 25-km resolution data taken within 75 km of a ground-based radar. Large variability in the discrepancies between spaceborne and ground-based rain rate estimates is the result of limitations of both systems and random errors in the collocation of their measurements. The Radarnet retrieval is affected by issues with measuring the vertical extent of precipitation at far ranges, while the GPM system struggles in properly quantifying orographic precipitation. Part of the underestimation by the GPM products appears to be a consequence of an erroneous DPR clutter identification in the presence of low freezing levels. Both products are susceptible to seasonal variations in performance and decreases in precision with increased levels of heterogeneity within the instruments’ field of view.

Description: This study investigates how multifrequency cloud radar observations can be used to evaluate the representation of rain microphysics in the WRF Model using two bulk microphysics schemes. A squall line observed over Oklahoma on 12 June 2011 is used as a case study. A recently developed retrieval technique combining observations of two vertically pointing cloud radars provides quantitative description of the drop size distribution (DSD) properties of the transition and stratiform regions of the squall-line system. For the first time, the results of this multifrequency cloud radar retrieval are compared to more conventional retrievals from a nearby polarimetric radar, and a supplementary result of this work is that this new methodology provides a much more detailed description of the DSD vertical and temporal variations. While the extent and evolution of the squall line is well reproduced by the model, the 1-h low-reflectivity transition region is not. In the stratiform region, simulations with both schemes are able to reproduce the observed downdraft and the associated significative subsaturation below the melting level, but with a slight overestimation of the relative humidity. Under this subsaturated air, the simulated rain mixing ratio continuously decreases toward the ground, in agreement with the observations. Conversely, the profiles of the mean volume diameter and the concentration parameter of the DSDs are not well reproduced. These discrepancies pinpoint at an issue in the representation of rain microphysics. The companion paper, investigates the sources of the biases in the microphysics processes in the rain layer by performing numerical sensitivity studies.

Description: A comparison between retrieved properties of the rain drop size distributions (DSDs) from multifrequency cloud radar observations and WRF Model results using either the Morrison or the Thompson bulk microphysics scheme is performed in order to evaluate the model’s ability to predict the rain microphysics. This comparison reveals discrepancies in the vertical profile of the rain DSDs for the stratiform region of the squall-line system observed on 12 June 2011 over Oklahoma. Based on numerical sensitivity analyses, this study addresses the bias at the top of the rain layer and the vertical evolution of the DSD properties (i.e., of Dm and N0*). In this way, the Thompson scheme is used to explore the sensitivity to the melting process. Moreover, using the Thompson and Morrison schemes, the sensitivity of the DSD vertical evolution to different breakup and self-collection parameterizations is studied. Results show that the DSDs are strongly dependent on the representation of the melting process in the Thompson scheme. In the Morrison scheme, the simulations with more efficient breakup reproduce the DSD properties with better fidelity. This study highlights how the inaccuracies in simulated Dm and N0* for both microphysics schemes can impact the evaporation rate, which is systematically underestimated in the model.

Description: The joint European Space Agency–Japan Aerospace Exploration Agency (ESA–JAXA) Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is scheduled for launch in 2016 and features the first atmospheric Cloud Profiling Radar (CPR) with Doppler capability in space. Here, the uncertainty of the CPR Doppler velocity measurements in cirrus clouds and large-scale precipitation areas is discussed. These regimes are characterized by weak vertical motion and relatively horizontally homogeneous conditions and thus represent optimum conditions for acquiring high-quality CPR Doppler measurements. A large dataset of radar reflectivity observations from ground-based radars is used to examine the homogeneity of the cloud fields at the horizontal scales of interest. In addition, a CPR instrument model that uses as input ground-based radar observations and outputs simulations of CPR Doppler measurements is described. The simulator accurately accounts for the beam geometry, nonuniform beam-filling, and signal integration effects, and it is applied to representative cases of cirrus cloud and stratiform precipitation. The simulated CPR Doppler velocities are compared against those derived from the ground-based radars. The unfolding of the CPR Doppler velocity is achieved using simple conditional rules and a smoothness requirement for the CPR Doppler measurements. The application of nonuniform beam-filling Doppler velocity bias-correction algorithms is found necessary even under these optimum conditions to reduce the CPR Doppler biases. Finally, the analysis indicates that a minimum along-track integration of 5000 m is needed to reduce the uncertainty in the CPR Doppler measurements to below 0.5 m s−1 and thus enable the detection of the melting layer and the characterization of the rain- and ice-layer Doppler velocities.

Description: Spaceborne Doppler radars have the potential to provide key missing observations of convective vertical air motions especially over the tropical oceans. Such measurements can improve understanding of the role of tropical convection in vertical energy transport and its interaction with the environment. Several millimeter wavelength Doppler radar concepts have been proposed since the 1990s. The Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) Cloud Profiling Radar (CPR) will be the first Dopplerized atmospheric radar in space but has not been optimized for Doppler measurements in deep convective clouds. The key challenge that constrains the CPR performance in convective clouds is the range–Doppler dilemma. Polarization diversity (PD) offers a solution to this constraint by decoupling the coherency (Doppler) requirement from the unambiguous range requirement. Careful modeling of the radar signal depolarization and its impact on radar receiver channel cross talk is needed to accurately assess the performance of the PD approach. The end-to-end simulator presented in this work allows reproduction of the signal sensed by a Doppler radar equipped with polarization diversity when overpassing realistic three-dimensional convective cells, with all relevant cross-talk sources accounted for. The notional study highlights that multiple scattering is the primary source of cross talk, highly detrimental for millimeter Doppler velocity accuracy. The ambitious scientific requirement of 1 m s−1 accuracy at 500-m integration for reflectivities above −15 dBZ are within reach for a W-band radar with a 2.5-m antenna with optimal values of the pulse-pair interval between 20 and 30 μs but only once multiple scattering and ghost-contaminated regions are screened out. The identification of such areas is key for Doppler accuracies and can be achieved by employing an interlaced pulse-pair mode that measures the cross and the copolar reflectivities. To mitigate the impact of attenuation and multiple scattering, the Ka band has been considered as either alternative or additional to the W band. However, a Ka system produces worse Doppler performances than a W-band system with the same 2.5-m antenna size. Furthermore, in deep convection it results in similar levels of multiple scattering and therefore it does not increase significantly the depth of penetration. In addition, the larger footprint causes stronger nonuniform beam-filling effects. One advantage of the Ka-band option is the larger Nyquist velocity that tends to reduce the Doppler accuracies. More significant benefits are derived from the Ka band when observing precipitation not as intense as the deep convection is considered here. This study demonstrates that polarization diversity indeed represents a very promising methodology capable of significantly reducing aliasing and Doppler moment estimate errors, two main error sources for Doppler velocity estimates in deep convective systems and a key step to achieving typical mission requirements for convection-oriented millimeter radar-based spaceborne missions.

Description: The Department of Energy Atmospheric Radiation Measurement (ARM) Program has recently initiated a new research avenue toward a better characterization of the transition from cloud to precipitation. Dual-wavelength techniques applied to millimeter-wavelength radars and a Rayleigh reference have a great potential for rain-rate retrievals directly from dual-wavelength ratio measurements. In this context, the recent reconfiguration of the ARM 915-MHz wind profilers in a vertically pointing mode makes these instruments the ideal candidate for providing the Rayleigh reflectivity/Doppler velocity reference. Prior to any scientific study, the wind profiler data must be carefully quality checked. This work describes the signal postprocessing steps that are essential for the delivery of high-quality reflectivity and mean Doppler velocity products—that is, the estimation of the noise floor from clear-air echoes, the absolute calibration with a collocated disdrometer, the dealiasing of Doppler velocities, and the merging of the different modes of the wind profiler. The improvement added by the proposed postprocessing is confirmed by comparison with a high-quality S-band profiler deployed at the ARM Southern Great Plains site during the Midlatitude Continental Convective Clouds Experiment. With the addition of a vertically pointing mode and with the postprocessing described in this work in place, besides being a key asset for wind research wind profilers observations may therefore become a centerpiece for rain studies in the years to come.