Non-uniform Beam Filling Research Articles

Using a Continental-Scale Data Quality Monitoring Framework to Evaluate a New Nonweather Filter for Radar Observations

Abstract Removing nonweather echoes is a critical component of the quality control (QC) chain used in the context of radar data assimilation for numerical weather prediction, quantitative precipitation estimation, and nowcasting applications. Recent studies show that using a simple QC method based on the depolarization ratio (DR) performs remarkably well in many situations. Nonetheless, this method may misclassify echoes in regions affected by nonuniform beamfilling or melting particles. This study presents an updated version of this QC used to remove nonweather echoes that uses the DR-based classification together with a set of physically based rules for correcting misclassifications of hail, nonuniform beamfilling, and melting particles. The potential of the new QC is evaluated using a continental-scale monitoring framework that compares the radar observations after QC with the precipitation occurrence derived from aviation routine weather reports (METARs). For this evaluation, the study uses the radar data and the METARs available over North America during the summer of 2019 and winter of 2020. In addition, the study demonstrates the usefulness of the monitoring framework to determine the optimal QC configuration. Some practical limitations of using the METAR-derived precipitation to assess radar data quality are also discussed.

How Accurately Can Warm Rain Realistically Be Retrieved with Satellite Sensors? Part II: Horizontal and Vertical Heterogeneities

Abstract There are many sources of uncertainty in satellite precipitation retrievals of warm rain. In this paper, the second of a two-part study, we focus on uncertainties related to spatial heterogeneity and surface clutter. A cloud-resolving model simulation of warm, shallow clouds is used to simulate satellite observations from three theoretical satellite architectures—one similar to the Global Precipitation Measurement Core Observatory, one similar to CloudSat, and one similar to the planned Atmosphere Observing System (AOS). Rain rates are then retrieved using a common optimal estimation framework. For this case, retrieval biases due to nonuniform beamfilling are very large, with retrieved rain rates negatively (low) biased by as much as 40%–50% (depending on satellite architecture) at 5 km horizontal resolution. Surface clutter also acts to negatively bias retrieved rain rates. Combining all sources of uncertainty, the theoretical AOS satellite is found to outperform CloudSat in terms of retrieved surface rain rate, with a bias of −19% as compared with −28%, a reduced spread of retrieval errors, and an additional 17.5% of cases falling within desired uncertainty limits. The results speak to the need for additional high-resolution modeling simulations of warm rain so as to better characterize the uncertainties in satellite precipitation retrievals.

Impacts of Vertical Nonuniform Beam Filling on the Observability of Secondary Ice Production due to Sublimation

Abstract Quasi-vertical profiles (QVPs) of polarimetric radar data have emerged as a powerful tool for studying precipitation microphysics. Various studies have found enhancements in specific differential phase Kdp in regions of suspected secondary ice production (SIP) due to rime splintering. Similar Kdp enhancements have also been found in regions of sublimating snow, another proposed SIP process. This work explores these Kdp signatures for two cases of sublimating snow using nearly collocated S- and Ka-band radars. The presence of the signature was inconsistent between the radars, prompting exploration of alternative causes. Idealized simulations are performed using a radar beam-broadening model to explore the impact of nonuniform beam filling (NBF) on the observed reflectivity Z and Kdp within the sublimation layer. Rather than an intrinsic increase in ice concentration, the observed Kdp enhancements can instead be explained by NBF in the presence of sharp vertical gradients of Z and Kdp within the sublimation zone, which results in a Kdp bias dipole. The severity of the bias is sensitive to the Z gradient and radar beamwidth and elevation angle, which explains its appearance at only one radar. In addition, differences in scanning strategies and range thresholds during QVP processing can constructively enhance these positive Kdp biases by excluding the negative portion of the dipole. These results highlight the need to consider NBF effects in regions not traditionally considered (e.g., in pure snow) due to the increased Kdp fidelity afforded by QVPs and the subsequent ramifications this has on the observability of sublimational SIP. Significance Statement Many different processes can cause snowflakes to break apart into numerous tiny pieces, including when they evaporate into dry air. Purported evidence of this phenomenon has been seen in data from some weather radars, but we noticed it was not seen in data from others. In this work we use case studies and models to show that this signature may actually be an artifact from the radar beam becoming too big and there being too much variability of the precipitation within it. While this breakup process may actually be occurring in reality, these results suggest we may have trouble observing it with typical weather radars.

Recovering the Elusive Spectral Width From Spaceborne Doppler Profiling Radar Measurements: The “ExpliSyT” Approach

This article presents a novel method to retrieve spectral widths from measurements of spaceborne Doppler profiling radars operating in low-Earth orbit. The proposed “ExpliSyT” approach, is based on a formulation of the Doppler broadening in terms of the distributions of reflectivity and velocity in the footprint. This formulation makes it possible to estimate the broadening and remove it from the spectral-width measurement. Two implementations of the ExpliSyT correction are described: 1) a numerical implementation that uses Wiener’s deconvolution, and 2) an analytical implementation based on Taylor expansions of the radar observations. The ExpliSyT corrections enable retrievals of higher-order Doppler information such as posterior power spectra. Results are shown for simulations of the radar of EarthCARE (Earth Cloud Aerosol Radiation Explorer developed by the European and Japanese space agencies) and a Displaced Phase Center Antenna (DPCA) configuration, for which the ExpliSyT corrections perform significantly better. A novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">canonical Doppler resampling diagram</i> is introduced to explain the correlation between non-uniform beamfilling (NUBF) and spectral broadening. This tool shows that 1) the NUBF of reflectivity modulates the spacecraft-induced spectral broadening, and 2) the NUBF of velocity can either broaden or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">shrink</i> the Doppler spectrum. This spectral shrinkage, although important, is not typically thought of when dealing with spaceborne Doppler radars. The ability to estimate spectral widths accurately from space paves the way for future microphysical and dynamical characterizations of hydrometeors in shear or turbulence.

Understanding Errors in Cloud Liquid Water Path Retrievals Derived from CloudSat Path-Integrated Attenuation

Abstract An algorithm that derives the nonprecipitating cloud liquid water path Wcld from CloudSat using a surface reference technique (SRT) is presented. The uncertainty characteristics of the SRT are evaluated. It is demonstrated that an accurate analytical formulation for the pixel-scale precision can be derived. The average precision of the SRT is estimated to be 34 g m−2 at the individual pixel scale; however, precision systematically decreases from around 30 to 40 g m−2 as cloud fraction varies from 0% to 100%. The retrievals of clear-sky Wcld have a mean bias of 0.9 g m−2. Output from a large-eddy simulation coupled to a radar simulator shows that an additional bias of −8% may result from nonuniformity within the footprint of cloudy pixels. The retrieval yield for the SRT, measured relative to all warm clouds over ocean between 60°N and 60°S latitude is 43%. The SRT Wcld is compared with one estimate of Wcld from the Moderate Resolution Imaging Spectroradiometer (MODIS) using an adiabatic cloud profile and an effective radius derived from 3.7-μm reflectance. A strong correlation between the mean MODIS Wcld and SRT Wcld is found across diverse cloud regimes, but with biases in the mean Wcld that are cloud-regime dependent. Overall, the mean bias of the SRT relative to MODIS is −13.1 g m−2. Systematic underestimates of Wcld by the SRT resulting from nonuniform beamfilling cannot be ruled out as an explanation for the retrieval bias.

Application of Nonuniform Beam Filling (NUBF) Doppler Velocity Error Correction on Airborne Radar Measurements

Non-uniform beam filling (NUBF) within an atmospheric radar sampling volume can cause significant Doppler velocity errors when the radar is located on a fast-moving platform. A case of strong NUBF errors was identified in ER-2 X-band Radar (EXRAD) data from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) 2020 field campaign. A basic NUBF correction was employed using an estimate of the along-track radar reflectivity gradient. The relationship is verified empirically using co-located Doppler velocity measurements from the higher-resolution Cloud Radar System (CRS).

Simple Derivation of the Nonuniform Beam Filling (NUBF) Bias Formula in Spaceborne Doppler Radar Measurements

The nonuniform beam filling (NUBF) bias in Doppler velocity measurements from a spaceborne precipitation radar is investigated. A simple derivation of the already-known formula that relates the bias to the along-track gradient of measured radar reflectivity in dBZ is shown. From the formula, the uncertainty of bias correction due to discretization is discussed. The error is shown to be proportional to the square of the spacing for discretization, and is related to the third moment of the distribution of the radar reflectivity convolved with the antenna pattern. The effectiveness of averaging is also shown from a simulation.

McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

Abstract. The aim of this paper is to present the Monte Carlo code McRALI that provides simulations under multiple-scattering regimes of polarized high-spectral-resolution (HSR) lidar and Doppler radar observations for a three-dimensional (3D) cloudy atmosphere. The effects of nonuniform beam filling (NUBF) on HSR lidar and Doppler radar signals related to the EarthCARE mission are investigated with the help of an academic 3D box cloud characterized by a single isolated jump in cloud optical depth, assuming vertically constant wind velocity. Regarding Doppler radar signals, it is confirmed that NUBF induces a severe bias in velocity estimates. The correlation of the NUBF bias of Doppler velocity with the horizontal gradient of reflectivity shows a correlation coefficient value around 0.15 m s−1 (dBZ km-1)-1, close to that given in the scientific literature. Regarding HSR lidar signals, we confirm that multiple-scattering processes are not negligible. We show that NUBF effects on molecular, particulate, and total attenuated backscatter are mainly due to unresolved variability of cloud inside the receiver field of view and, to a lesser extent, to the horizontal photon transport. This finding gives some insight into the reliability of lidar signal modeling using independent column approximation (ICA).

Global Precipitation Measuring Dual-Frequency Precipitation Radar Observations of Hailstorm Vertical Structure: Current Capabilities and Drawbacks

AbstractA 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.

Relationships between Extreme Rain Rates and Convective Intensities from the Perspectives of TRMM and WSR-88D Radars

AbstractTRMM PR 2A25, version 7 (V7), retrievals of reflectivity Z and rainfall rate R are compared with WSR-88D dual-polarimetric S-band radar data for 28 radars over the southeastern United States after matching their horizontal resolution and sampling. TRMM Ku-band measurements are converted to S-band approximations to more directly compare reflectivity estimates. Rain rates are approximated from WSR-88D data using the CSU–hydrometeor identification rainfall optimization (HIDRO) algorithm. Tropics-wide TRMM retrievals confirm previous findings of a low overlap fraction between extreme convective intensity, as approximated by the maximum 40-dBZ height, and extreme near-surface rain rates. WSR-88D data also confirm this low overlap but show that it is likely higher than TRMM PR retrievals indicate. For maximum 40-dBZ echo heights that extend above the freezing level, mean WSR-88D reflectivities at low levels are approximately 2 dB higher than TRMM PR reflectivities. Higher WSR-88D-retrieved rain rates for a given low-level reflectivity combine with these higher low-level reflectivities for a given maximum 40-dBZ height to produce rain rates that are approximately double those retrieved by the TRMM PR for maximum 40-dBZ heights that extend above the freezing level. TRMM PR path-integrated attenuation, and WSR-88D specific differential phase, differential reflectivity, and hail fraction indicate that the TRMM PR 2A25 V7 algorithm is possibly misidentifying low–midlevel hail and/or graupel as greater attenuating liquid, or vice versa. This misidentification, coupled with underestimation of path-integrated attenuation caused by nonuniform beamfilling and higher rain rates produced by specific differential phase (KDP)–R than Z–R relationships, results in low-biased 2A25 V7 rain rates in intense convection.

Uncertainty Characteristics of Total Water Path Retrievals in Shallow Cumulus Derived from Spaceborne Radar/Radiometer Integral Constraints

AbstractA precipitating marine cumulus cloud simulation is coupled to radiation propagation models to simulate active and passive microwave observations at 94 GHz. The simulations are used to examine the error characteristics of the total water path retrieved from the integral constraints of the passive microwave brightness temperature or the path-integrated attenuation (PIA) using a spatial interpolation technique. Three sources of bias are considered: 1) the misdetection of cloudy pixels as clear, 2) the systematic differences in the column water vapor between cloudy and clear skies, and 3) the nonuniform beamfilling effects on the observables. The first two sources result in biases on the order of 5–10 g m−2 of opposite signs that tend to cancel. The third source results in a bias that increases monotonically with the water path that approaches 50%. Nonuniform beamfilling is sensitive to footprint size. Random error results from both instrument measurement precision and the natural variability in the relationship between the water path and the observables. Random errors for the retrievals using the CloudSat PIA are estimated to be the larger of either 20 g m−2 or 30%. A radar/radiometer system with a measurement precision of 0.3 K or 0.05 dB could reduce this error to the larger of either 10 g m−2 or 30%. All error mechanisms reported here result from variability in either the spatial structure of the atmosphere or the hydrometeor drop size distribution. The results presented here are specific to the cloud simulation and in general the magnitude will vary globally.

Reduction of Nonuniform Beamfilling Effects by Multiple Constraints: A Simulation Study

AbstractA spaceborne precipitation radar samples the vertical structure of precipitating hydrometeors from the top down. The viewing geometry and operating frequency result in certain limitations and opportunities. Among the limitations is attenuation of the radar signal that can cause the measured radar reflectivity factor to be substantially less than the desired quantity, the true radar reflectivity factor. Another error source is the spatial variability in precipitation rates that occurs at scales smaller than the sensor field of view (FOV), giving rise to the nonuniform beamfilling (NUBF) effect. The opportunities arise when the radar return from the surface can be used to obtain constraints on the path-integrated attenuation (PIA) for use in hybrid attenuation correction algorithms. The surface return can also provide some information on the degree of NUBF at off-nadir viewing angles. In this paper ground-based radar data are used to simulate spaceborne radar data at nadir and off-nadir viewing angles at Ku band and Ka band and to test attenuation correction algorithms in the presence of nonuniform beamfilling. The cross-FOV gradient in PIA is found to be an important characteristic for describing the performance of attenuation correction algorithms.

Error Analysis of a Conceptual Cloud Doppler Stereoradar with Polarization Diversity for Better Understanding Space Applications

AbstractAn error budget analysis is performed for retrieval of along-track winds based on the design of a spaceborne Doppler radar using polarization diversity. The analysis is conducted within the framework of a case study of an Atlantic hurricane. The proposed concept consists of either a Ka-band or W-band stereoradar mounted on an LEO satellite equipped with both nadir- and forward-viewing beams and with an optional cross-scanning capability. Such a radar design is intended for observing the microphysical and dynamical structures of cloud systems, including disturbed mesoscale convective systems. Because of the high winds involved in such weather phenomena and because of the Doppler fading introduced by platform motion, polarization diversity is adopted. The simulation framework enables a breakdown of the Doppler velocity measurement error budget into its most important components, that is, nonuniform beamfilling, multiple scattering, and inherent signal noise. The impact of each of these error terms on the total error depends on the adopted integration length, the number of scanned tracks, and the specifics of the radar. This allows for optimally selecting an integration length suitable for minimizing the total rms velocity error. The analysis shows that the use of a large antenna could achieve impressive measurement accuracy of the along-line-of-sight wind velocities. Notably, this would be the case for integration lengths longer than 3 km, even when carrying out cross-track scanning for up to 17 separate tracks. Examples of retrieved along-track wind fields also reveal that the large antenna configurations are capable of identifying and quantifying the foremost dynamic features (e.g., vertical wind shear and convergence/divergence regions).

Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014

Abstract. A diagnostic analysis of the space–time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar (PR) on the Tropical Rainfall Measurement Mission (TRMM) satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. IPHEx is the first NASA ground-validation field campaign after the launch of the Global Precipitation Measurement (GPM) satellite. In anticipation of GPM, a science-grade high-density raingauge network was deployed at mid to high elevations in the southern Appalachian Mountains, USA, since 2007. This network allows for direct comparison between ground-based measurements from raingauges and satellite-based QPE (specifically, PR 2A25 Version 7 using 5 years of data 2008–2013). Case studies were conducted to characterize the vertical profiles of reflectivity and rain rate retrievals associated with large discrepancies with respect to ground measurements. The spatial and temporal distribution of detection errors (false alarm, FA; missed detection, MD) and magnitude errors (underestimation, UND; overestimation, OVR) for stratiform and convective precipitation are examined in detail toward elucidating the physical basis of retrieval error. The diagnostic error analysis reveals that detection errors are linked to persistent stratiform light rainfall in the southern Appalachians, which explains the high occurrence of FAs throughout the year, as well as the diurnal MD maximum at midday in the cold season (fall and winter) and especially in the inner region. Although UND dominates the error budget, underestimation of heavy rainfall conditions accounts for less than 20% of the total, consistent with regional hydrometeorology. The 2A25 V7 product underestimates low-level orographic enhancement of rainfall associated with fog, cap clouds and cloud to cloud feeder–seeder interactions over ridges, and overestimates light rainfall in the valleys by large amounts, though this behavior is strongly conditioned by the coarse spatial resolution (5 km) of the topography mask used to remove ground-clutter effects. Precipitation associated with small-scale systems (&lt; 25 km2) and isolated deep convection tends to be underestimated, which we attribute to non-uniform beam-filling effects due to spatial averaging of reflectivity at the PR resolution. Mixed precipitation events (i.e., cold fronts and snow showers) fall into OVR or FA categories, but these are also the types of events for which observations from standard ground-based raingauge networks are more likely subject to measurement uncertainty, that is raingauge underestimation errors due to undercatch and precipitation phase. Overall, the space–time structure of the errors shows strong links among precipitation, envelope orography, landform (ridge–valley contrasts), and a local hydrometeorological regime that is strongly modulated by the diurnal cycle, pointing to three major error causes that are inter-related: (1) representation of concurrent vertically and horizontally varying microphysics; (2) non-uniform beam filling (NUBF) effects and ambiguity in the detection of bright band position; and (3) spatial resolution and ground-clutter correction.

GPMとTRMMのマッチアップ事例におけるKuPRアルゴリズムの評価

GPM Core Observatory satellite has been in operation since February, 2014. Before the GPM operation started, TRMM had observed the rain rate in tropical regions. GPM's KuPR is a successor of TRMM/PR, and both have the same design [1]. However, differences have been confirmed in their estimates for the same rainfall. Therefore, we focus on the retrieval method of rain rate, and compare the rain rate estimates by KuPR and PR. As a result of comparison, path-integrated attenuation (PIA), surface reference technique (SRT) and non-uniform beam filling (NUBF) are regarded as the factors of differences of the rain rate. Particularly, overestimation of PIA in KuPR is one of the most important factors of the differences of rain rate. On the other hand, rain rate is overestimated in KuPR when SRT is ignored. Therefore, the number of cases is needed to be increased, and it is necessary to improve the parameters of SRT and NUBF.

A Polarimetric and Microphysical Investigation of the Northeast Blizzard of 8–9 February 2013

Abstract On 8–9 February 2013, the northeastern United States experienced a historic winter weather event ranking among the top five worst blizzards in the region. Heavy snowfall and blizzard conditions occurred from northern New Jersey, inland to New York, and northward through Maine. Storm-total snow accumulations of 30–61 cm were common, with maximum accumulations up to 102 cm and snowfall rates exceeding 15 cm h−1. Dual-polarization radar measurements collected for this winter event provide valuable insights into storm microphysical processes. In this study, polarimetric data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Upton, New York (KOKX), are investigated alongside thermodynamic analyses from the 13-km Rapid Refresh model and surface precipitation type observations from both Meteorological Phenomena Identification Near the Ground (mPING) and the National Weather Service (NWS) Forecast Office in Upton, New York, for interpretation of polarimetric signatures. The storm exhibited unique polarimetric signatures, some of which have never before been documented for a winter system. Reflectivity values were unusually large, reaching magnitudes &amp;gt;50 dBZ in shallow regions of heavy wet snow near the surface. The 0°C transition line was exceptionally distinct in the polarimetric imagery, providing detail that was often unmatched by the numerical model output. Other features include differential attenuation of magnitudes typical of melting hail, depolarization streaks that provide evidence of electrification, nonuniform beamfilling, a “snow flare” signature, and localized downward excursions of the melting-layer bright band collocated with observed transitions in surface precipitation types. In agreement with previous studies, widespread elevated depositional growth layers, located at temperatures near the model-predicted −15°C isotherm, appear to be correlated with increased snowfall and large reflectivity factors ZH near the surface.

Simulation of EarthCARE Spaceborne Doppler Radar Products Using Ground-Based and Airborne Data: Effects of Aliasing and Nonuniform Beam-Filling

This paper describes the expected performance of the Doppler cloud profiling radar being built for the Earth Cloud Aerosols Radiation Explorer (EarthCARE) mission of the Japanese Aerospace Exploration Agency and the European Space Agency. Spaceborne Doppler radar data are simulated starting from high-resolution Doppler measurements provided by ground-based and airborne Doppler radars, ranging from nonconvective to moderately convective scenarios. The method hinges upon spatial and spectral resampling to consider the specificities of the spaceborne configuration. An error analysis of the resulting Doppler product is conducted to address aliasing and nonuniform beam-filling (NUBF) problems. A perturbation analysis is applied to explore the latter problem and allow for a self-standing systematic correction of NUBF using merely the received reflectivity factor and mean Doppler velocities as measured by the instrument. The results of our simulations show that, at a horizontal integration of 1 km, after proper de-aliasing and NUBF correction, the radar will typically yield a velocity accuracy in the order of 1.3 m·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> over intertropical regions where the pulse-repetition frequency (PRF)=6.1 kHz, of 0.8 m·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> where the cloud-profiling radar (CPR) operates at PRF=7 kHz, and, of 0.7 m·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> over high latitudes where the CPR of EarthCARE will operate at PRF=7.5 kHz.

Evaluation of EarthCARE Cloud Profiling Radar Doppler Velocity Measurements in Particle Sedimentation Regimes

Abstract 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.

Modified Hitschfeld–Bordan Equations for Attenuation-Corrected Radar Rain Reflectivity: Application to Nonuniform Beamfilling at Off-Nadir Incidence

Abstract As shown by Takahashi et al., multiple path attenuation estimates over the field of view of an airborne or spaceborne weather radar are feasible for off-nadir incidence angles. This follows from the fact that the surface reference technique, which provides path attenuation estimates, can be applied to each radar range gate that intersects the surface. This study builds on this result by showing that three of the modified Hitschfeld–Bordan estimates for the attenuation-corrected radar reflectivity factor can be generalized to the case where multiple path attenuation estimates are available, thereby providing a correction to the effects of nonuniform beamfilling. A simple simulation is presented showing some strengths and weaknesses of the approach.

Reduction of Nonuniform Beam Filling Effects by Vertical Decorrelation: Theory and Simulations

Algorithms for estimating precipitation rates from spaceborne radar observations of apparent radar reflectivity depend on attenuation correction procedures. The algorithm suite for the Ku-band precipitation radar aboard the Tropical Rainfall Measuring Mission satellite is one such example. The well-known problem of nonuniform beam filling is a source of error in the estimates, especially in regions where intense deep convection occurs. The error is caused by unresolved horizontal variability in precipitation characteristics such as specific attenuation, rain rate, and effective reflectivity factor. This paper proposes the use of vertical decorrelation for correcting the nonuniform beam filling error developed under the assumption of a perfect vertical correlation. Empirical tests conducted using ground-based radar observations in the current simulation study show that decorrelation effects are evident in tilted convective cells. However, the problem of obtaining reasonable estimates of a governing parameter from the satellite data remains unresolved.