Radar Reflectivity Factor Research Articles

Sampling Errors in the Measurement of Rainfall Parameters Using the Precipitation Occurrence Sensor System (POSS)

Abstract The Precipitation Occurrence Sensor System (POSS) is a small Doppler radar originally designed by the Meteorological Service of Canada (MSC) to report the occurrence, type, and intensity of precipitation in automated observing stations. It is also used for real-time estimation of raindrop size distributions (DSDs). From the DSD, various rainfall parameters can be calculated and relationships established, such as between the radar reflectivity factor (Z) and the rainfall rate (R). Earlier work presented first-order estimates of the sampling errors for some POSS rainfall parameter estimates. This work combines a Monte Carlo simulation and “inverse problem” analysis to better estimate errors due to the specific sampling problems of this disdrometer type. The uncertainties are necessary to determine the statistical significance of differences between DSD estimates by the POSS and other collocated disdrometers, or between POSS measurements in different climatologies. Additionally, confidence limits can be assigned to regression coefficients for rainfall parameter relationships determined from POSS estimates. An example is given of the uncertainties in the coefficients of measured Z–R relationships.

Monte Carlo simulation of backscattering by a melting layer of precipitation

The melting snow particles on top of clouds form the melting layer of precipitation. The melting process starts with the snow particles falling, so the microphysical characteristics of the melting layer vary continuously in vertical direction. In this paper, a Monte Carlo simulation model for the melting layer is developed, and the melting snow particles are modeled by more practical three-layered spherical particles. The size distribution of the melting snow particles is derived from the raindrops size distribution. Vertical profiles of radar reflectivity and specific attenuation factor are computed at 5, 10, 35 and 94 GHz using the Mie theory at rain rates below 12.5 mm/h. It is shown that the radar bright band can be absent in the melting layer at frequencies above 20 GHz. This agrees with radar observations at 35 and 94 GHz. Base on the radiative transfer theory, the Monte Carlo method is used to compute the reflectivity of the melting layer whose microphysical characteristics are continuous in vertical direction. We compared the reflectivity of the melting layers with two different size-distributions (Gamma size distribution and Marshall-Palmer size distribution). These provided theoretical and numerical basis for radar remote sensing of the melting layer with high frequencies electromagnetic waves.

Characterization of Ze and LDR of nonspherical and inhomogeneous ice particles for 95‐GHz cloud radar: Its implication to microphysical retrievals

Effect of density, shape, and orientation on radar reflectivity factor (Ze) and linear depolarization ratio (LDR) at 95 GHz are investigated by using the discrete dipole approximation (DDA) for ice cloud studies. We consider hexagonal plate, hollow hexagonal column, and hollow bullet rosette in horizontal (2‐D) or three‐dimensional (3‐D) random orientation. We first validate a widely used method to take into account the density and shape effects by the combinational use of Mie theory with the Maxwell‐Garnett mixing rule (the MG‐Mie method). It is found that the MG‐Mie method underestimates Ze and its applicability is limited to sizes smaller than 40 μm. On the basis of the DDA, it is possible to separately treat density, aspect ratio, orientation, and shape. Effect of density turns out to be minor. Orientation and shape are the major controlling factors for Ze especially at effective radius reff > 100 μm and LDR except for very large sizes where the effect of orientation in LDR diminishes. Comparison between the DDA results and the analytical solution for 3‐D Rayleigh spheroids show that LDR in the small size range is characterized by the target boundary and aspect ratio. In the large size range, LDR reveals features of a single target element; for example, LDR of bullet rosette is similar to that of a single branch of the particle. Combinational use of Ze and LDR is effective in microphysics retrieval for LDR < −23 dB. For LDR > −23 dB, additional information such as Doppler velocity is required.

Parametrization of drop size distribution with rain rate

Because the rain rate R is easier to observe than the drop size distribution (DSD), it is useful to express the DSD as a function of R only, i.e. N( D,R). Disdrometer data from four sites in West Africa are used to compare observed DSDs with fitting to a lognormal function in which the three parameters X i , with i = 1, 2, 3, are expressed as functions of R only. Observed DSDs are found well represented by such N( D,R) function. Writing the N( D,R) moments for a calculation of useful physical quantities, such as water content M, rain rate, or radar reflectivity factor Z, raises constraints of self consistency of the various equations. Modifying the analytical form of DSD in order to take into account the constraint of self-consistency is not found to increase significantly the quality of the DSD fitting with respect to the direct use of X i ( R) in the distribution, ignoring the lack of self-consistency. Then Z– R relations obtained by direct regression of observed data are compared with the relations derived analytically from N( D,R) and the expressions X i ( R) observed in each site. The two groups of relations compare very well.

Volcanic Ash Cloud Retrieval by Ground-Based Microwave Weather Radar

The potential of ground-based microwave weather radar systems for volcanic ash cloud detection and quantitative retrieval is evaluated. The relationship between radar reflectivity factor, ash concentration, and fall rate is statistically derived for various eruption regimes and ash sizes by applying a radar-reflectivity microphysical model. To quantitatively evaluate the ash detectability by weather radars, a sensitivity analysis is carried out by simulating synthetic ash clouds and varying ash concentration and size as a function of the range. Radar specifications are taken from typical radar systems at S-, C-, and X-band. A prototype algorithm for volcanic ash radar retrieval (VARR) is discussed. Starting from measured single-polarization reflectivity, the statistical inversion technique to retrieve ash concentration and fall rate is based on two cascade steps, namely: 1) classification of eruption regime and volcanic ash category and 2) estimation of ash concentration and fall rate. Expected accuracy of the VARR algorithm estimates is evaluated using a synthetic data set. An application of the VARR technique is finally shown, taking into consideration the eruption of the Grinodotacutemsvoumltn volcano in Iceland on November 2004. Volume scan data from a Doppler C-band radar, which is located at 260 km from the volcano vent, are processed by means of the VARR algorithm. Examples of the achievable VARR products are presented and discussed

A Quality Control Concept for Radar Reflectivity, Polarimetric Parameters, and Doppler Velocity

Abstract Over the last few years the use of weather radar data has become a fundamental part of various applications like rain-rate estimation, nowcasting of severe weather events, and assimilation into numerical weather prediction models. The increasing demand for radar data necessitates an automated, flexible, and modular quality control. In this paper a quality control procedure is developed for radar reflectivity factors, polarimetric parameters, and Doppler velocity. It consists of several modules that can be extended, modified, and omitted depending on the user requirement, weather situation, and radar characteristics. Data quality is quantified on a pixel-by-pixel basis and encoded into a quality-index field that can be easily interpreted by a nontrained end user or an automated scheme that generates radar products. The quality-index algorithms detect and quantify the influence of beam broadening, the height of the first radar echo, ground clutter contamination, return from non-weather-related objects, and attenuation of electromagnetic energy by hydrometeors on the quality of the radar measurement. The quality-index field is transferred together with the radar data to the end user who chooses the amount of data and the level of quality used for further processing. The calculation of quality-index fields is based on data measured by the polarimetric C-band Doppler radar (POLDIRAD) located in the Alpine foreland in southern Germany.

Ice water content and precipitation rate as a function of equivalent radar reflectivity and temperature based on in situ observations

Using ice particle spectra measured in stratiform ice clouds in midlatitude and Arctic regions, ice water content (IWC) and precipitation rate (Fm) retrieval algorithms as a function of temperature and radar reflectivity factor (Z) have been developed. These parameterizations were compared with (1) direct measurements of IWC using a Nevzorov probe, (2) precipitation retrieved using an X‐band Doppler scanning radar and a Precipitation Occurrence Sensor System (POSS), (3) the Canadian Global Environmental Multiscale (GEM) and High‐Resolution Model Application Project (HIMAP) models, and (4) derived IWC and precipitation from measured ice spectra during four field projects. The derived IWC and Fm from measured spectra have a correlation coefficient (r) better than 0.8. The IWC retrieved using the X‐band scanning radar during the First Alliance Icing Research Studies (AIRS I) agreed with IWC measured using the Nevzorov Probe much better than conventional IWC retrieval schemes. The retrieved precipitation rate based on the new algorithm using the POSS reflectivity measurements during the Second Alliance Icing Research Study (AIRS II) project agreed reasonably well with the precipitation rates predicted by the GEM and HIMAP models. This study clearly demonstrated that conventional IWC‐Ze relationships fail to replicate the IWC measured with Nevzorov probe. Furthermore, the Fm –Z relationship currently in use in the Canadian operational radar network appears to underestimate the ice precipitation rate. However, since there are some uncertainties in the direct measurements of IWC and no reliable direct measurements of precipitation, further studies are required to validate these parameterizations.

Cloud optical thickness and effective particle radius derived from transmitted solar radiation measurements: Comparison with cloud radar observations

A method is presented for determining the optical thickness and effective particle radius of stratiform clouds containing liquid water drops in the absence of drizzle from transmitted solar radiation measurements. The procedure compares measurements of the cloud transmittance from the ground at water‐absorbing and nonabsorbing wavelengths with lookup tables of the transmittance precomputed for plane‐parallel, vertically homogeneous clouds. The optical thickness derived from the cloud transmittance may be used to retrieve vertical profiles of cloud microphysics in combination with the radar reflectivity factor. To do this, we also present an algorithm for solving the radar equation with a constraint of the optical thickness at the visible wavelength. Observations of clouds were made in August and September 2003 at Koganei, Tokyo, Japan, using a PREDE i‐skyradiometer and a 95‐GHz cloud radar Super Polarimetric Ice Crystal Detection and Explication Radar (SPIDER). The optical thickness and effective radius of water clouds were derived from the i‐skyradiometer. Then, the vertical profile of the effective radius was retrieved from SPIDER, using the optical thickness determined from the i‐skyradiometer. We found that the effective radii derived by using these two instruments were in good agreement.

The Retrieval of Ice Water Content from Radar Reflectivity Factor and Temperature and Its Use in Evaluating a Mesoscale Model

Abstract Ice clouds are an important yet largely unvalidated component of weather forecasting and climate models, but radar offers the potential to provide the necessary data to evaluate them. First in this paper, coordinated aircraft in situ measurements and scans by a 3-GHz radar are presented, demonstrating that, for stratiform midlatitude ice clouds, radar reflectivity in the Rayleigh-scattering regime may be reliably calculated from aircraft size spectra if the “Brown and Francis” mass–size relationship is used. The comparisons spanned radar reflectivity values from −15 to +20 dBZ, ice water contents (IWCs) from 0.01 to 0.4 g m−3, and median volumetric diameters between 0.2 and 3 mm. In mixed-phase conditions the agreement is much poorer because of the higher-density ice particles present. A large midlatitude aircraft dataset is then used to derive expressions that relate radar reflectivity and temperature to ice water content and visible extinction coefficient. The analysis is an advance over previous work in several ways: the retrievals vary smoothly with both input parameters, different relationships are derived for the common radar frequencies of 3, 35, and 94 GHz, and the problem of retrieving the long-term mean and the horizontal variance of ice cloud parameters is considered separately. It is shown that the dependence on temperature arises because of the temperature dependence of the number concentration “intercept parameter” rather than mean particle size. A comparison is presented of ice water content derived from scanning 3-GHz radar with the values held in the Met Office mesoscale forecast model, for eight precipitating cases spanning 39 h over southern England. It is found that the model predicted mean IWC to within 10% of the observations at temperatures between −30° and −10°C but tended to underestimate it by around a factor of 2 at colder temperatures.

Factors Affecting the Evolution of Hurricane Erin (2001) and the Distributions of Hydrometeors: Role of Microphysical Processes

Abstract Fine-resolution simulations of Hurricane Erin are conducted using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to investigate roles of thermodynamic, boundary layer, and microphysical processes on Erin’s structure and evolution. Choice of boundary layer scheme has the biggest impact on simulations, with the minimum surface pressure (Pmin) averaged over the last 18 h (when Erin is relatively mature) varying by over 20 hPa. Over the same period, coefficients used to describe graupel fall speeds (Vg) affect Pmin by up to 7 hPa, almost equivalent to the maximum 9-hPa difference between microphysical parameterization schemes; faster Vg and schemes with more hydrometeor categories generally give lower Pmin. Compared to radar reflectivity factor (Z) observed by the NOAA P-3 lower fuselage radar and the NASA ER-2 Doppler radar (EDOP) in Erin, all simulations overpredict the normalized frequency of occurrence of Z larger than 40 dBZ and underpredict that between 20 and 40 dBZ near the surface; simulations overpredict Z larger than 25 to 30 dBZ and underpredict that between 15 and 25 or 30 dBZ near the melting layer, the upper limit depending on altitude. Brightness temperatures (Tb) computed from modeled fields at 37.1- and 85.5-GHz channels that respond to scattering by graupel-size ice show enhanced scattering, mainly due to graupel, compared to observations. Simulated graupel mixing ratios are about 10 times larger than values observed in other hurricanes. For the control run at 6.5 km averaged over the last 18 simulated hours, Doppler velocities computed from modeled fields (Vdop) greater than 5 m s−1 make up 12% of Erin’s simulated area for the base simulation but less than 2% of the observed area. In the eyewall, 5% of model updrafts above 9 km are stronger than 10 m s−1, whereas statistics from other hurricanes show that 5% of updrafts are stronger than only 5 m s−1. Variations in distributions of Z, vertical motion, and graupel mixing ratios between schemes are not sufficient to explain systematic offsets between observations and models. A new iterative condensation scheme, used with the Reisner mixed-phase microphysics scheme, limits unphysical increases of equivalent potential temperature associated with many condensation schemes and reduces the frequency of Z larger than 50 dBZ, but has minimal effect on Z below 50 dBZ, which represent 95% of the modeled hurricane rain area. However, the new scheme changes the Erin simulations in that 95% of the updrafts are weaker than 5 m s−1 and Pmin is up to 12 hPa higher over the last 18 simulated hours.

Retrieving optically thick ice cloud microphysical properties by using airborne dual‐wavelength radar measurements

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER‐2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high‐altitude ER‐2 aircraft. In situ size distribution and total water content data from the CRYSTAL‐FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass‐length relationships and to deal with the density and nonspherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as deep convective and anvil clouds, which are very challenging for single‐wavelength radar and lidar. Examples of retrieved microphysical properties for deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter‐wave radiometer, CoSSIR, and dual‐wavelength radar measurements indicates accuracy of the IWC retrieved from the dual‐wavelength radar algorithm.

A 3D stochastic cloud model for investigating the radiative properties of inhomogeneous cirrus clouds

AbstractThe three‐dimensional structure of clouds is known to be important for determining their radiative effects, but it is difficult to obtain this structure directly from observations. In this paper a stochastic model is described that is capable of simulating the structural properties unique to cirrus: fallstreak geometry and shear‐induced mixing. We first present an analysis of time–height cloud radar sections from southern England to extract the cirrus parameters of interest. It is found that horizontal power spectra of the logarithm of ice‐water content (estimated from radar reflectivity factor and temperature) typically exhibit a spectral slope of around −5/3 near cloud top that decreases with depth into the cloud, to values as low as −3.5 in some cases. This decrease can be explained by wind shear coupled with a spread of particle fall speeds leading to a homogenization that acts preferentially at smaller scales. The power spectra exhibit a distinct scale break, becoming flat at scales larger than around 50 km (the ‘outer scale’). The orientation of the fallstreaks may be predicted from the profile of mean wind and mean ice fall speed. We then describe the stochastic model, which takes as input profiles of the mean and fractional standard deviation of ice‐water content, spectral slope, outer scale and wind speed. It first generates an isotropic 3‐D fractal field by performing an inverse 3‐D Fourier transform on a matrix of simulated Fourier coefficients with amplitudes consistent with the observed 1‐D spectra. Random phases for the coefficients allow multiple realizations of a cloud with the same statistical properties to be generated. Then horizontal slices from the domain are manipulated in turn to simulate horizontal displacement and changes to the spectra with height. Finally the field is scaled to produce the observed mean and fractional standard deviation of ice‐water content. Vertical 2‐D slices extracted from the domain are very similar in appearance to cloud radar observations. Radiative‐transfer calculations using the independent column approximation are used to show that the different fallstreak orientation resulting from different wind shears can change mean top‐of‐atmosphere radiative fluxes by in excess of 45 W m−2 in the short‐wave and 15 W m−2 in the long‐wave. The effect of wind shear to induce horizontal mixing causes an additional but smaller radiative effect. We also investigate the biases that would be expected from the assumptions made in the radiation schemes of general‐circulation models (GCMs). It is found that there is some compensation between the errors arising from the assumptions of horizontal homogeneity and maximum‐random overlap; if a GCM were to improve the overlap assumption but still assume clouds to be horizontally homogeneous then the total error in cloud radiative effect would be likely to increase. Copyright © 2005 Royal Meteorological Society.

The Influence of the Acoustic-electric Coalescence on Phase and Mass Transfer of Supercooled Drops

The objective of this work is to study the influence of electrical discharge on the evolution of the cloud droplet spectra using a 1-D cloud model. It is shown that droplet motion and the electrical effects produced by lightning may cause a rapid and effective droplet coalescence process, with noticeably more phase transfer from liquid toward frozen water. As a measure of the drop spectra changes, we investigated variations of the radar reflectivity factor and the mass-weighted mean diameters at five temperature levels (0, −5, −10, −15, and −20C) with 15 combinations of the initial conditions. The model simulations suggest that about where the lightning occurred, after a few seconds, the initial unimodal spectra of supercooled water drops can be transferred to the bimodal spectra of unfrozen and frozen water drops. The number of newly created frozen drops is a few orders less than unfrozen water drops, but can still be very important for further transformations due to gravitational coagulation and other microphysical processes, e.g. glaciation. The results indicate that the procedure established to describe processes related to the electrical discharge and droplet spectra transformations can be used within a 3-D mesoscale model. It is concluded that the outcome can be also used to explain some of the physical characteristics inferred from polarimetric radar observations.

Calibration of Dual-Polarization Radar in the Presence of Partial Beam Blockage

Abstract In the presence of partial beam blockage (PBB), weather radar measurements can experience significant bias that directly compromises the accuracy of the hydrologic applications. Techniques for the calibration of the radar reflectivity factor Z and differential reflectivity ZDR, measured with dual-polarization weather radars in the presence of partial beam obstruction, are examined in this paper. The proposed ZDR calibration technique utilizes radar measurements of ZDR in light rain and dry aggregated snow at unblocked and blocked elevations. This calibration technique was tested for the National Severe Storms Laboratory’s (NSSL’s) Cimarron radar that suffers from PBB, and a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) that does not experience PBB. Results indicate that the ZDR bias that is associated with PBB can be calibrated with an accuracy of 0.2–0.3 dB, provided that the dataset is sufficiently large. Calibration of Z in the presence of PBB is based on the idea of self-consistency among Z, ZDR, and the specific differential phase KDP in rain. The self-consistency calibration of Z from the Cimarron radar is performed following an area–time integral method. Integration is partitioned into small azimuthal sectors to assess the azimuthal modulation of the Z bias. The suggested technique is validated by direct comparisons of reflectivity factors that are measured by the Cimarron radar and the unobstructed operational WSR-88D radar. It is shown that the azimuthal modulation of Z that is caused by PBB is well captured, and the accuracy of the Z calibration is within 2–3 dB.

Moving Cellular Structure of Fog Echoes Obtained with a Millimeter-Wave Scanning Doppler Radar at Kushiro, Japan

Abstract Observations of fogs with a millimeter-wave scanning Doppler radar were conducted at Kushiro in Hokkaido, Japan, in the summer seasons of 1999 and 2000. Three typical types of plan position indicator (PPI) displays were observed: cellular echoes with high radar reflectivity factors (∼−10 dBZ), uniformly distributed echoes with high reflectivities (∼−10 dBZ), and uniformly distributed echoes with low reflectivities (∼−30 dBZ). The authors focused on advection fog with cellular echoes observed on 5 August 1999 and 31 July 2000. Echoes showed structures of cells with a reflectivity of −10 dBZ and with intervals of about 1 km. This echo pattern moved northward (i.e., from the sea to the land). There was a vertical shear of the horizontal wind at a height around 200 m in both cases, and structures of each cell were upright above the shear line and were leaning below it. The direction and the speed of the echo pattern in both PPI and range–height indicator (RHI) displays agreed well with that of the horizontal wind at heights above the shear (200 m). In the echo cells, existence of drizzle drops is implied.

Retrieval of Arbitrarily Shaped Raindrop Size Distributions from Wind Profiler Measurements

Abstract An efficient iterative retrieval method for arbitrarily shaped raindrop size distributions (ITRAN) is developed for Doppler spectra measured with a wind profiler. A measured Doppler spectrum is a convolution of the precipitation spectrum and the turbulent spectrum. Deconvolution of the Doppler spectra is achieved through repeated convolutions. The developed method assumes no prior shape of drop size distributions and automatically obtains raindrop size distributions; additionally, it can be applied to large data volumes. Furthermore, it is insensitive to initial values. The method was applied to both simulated and observed spectra. Derived drop size distributions agree with simulated values. Narrower turbulent spectral widths yield better results. Integral values of median volume diameter (D0), liquid water content (LWC), and radar reflectivity factor are estimated with errors of less than 10%. Accurate vertical profiles of raindrop size distributions result when this method is applied to wind profiler data. The technique performed very well with most observed spectra. Some recovered spectra departed from the corresponding measured spectra, for cases in which a clear-air peak could not be accurately reproduced because of uncertainties in the location of the minimum position between the clear-air echo and the precipitation echo. Statistical relationships between LWC and integral rainfall parameters yield interesting features. The median volume diameter is statistically independent of the LWC and is associated with the large variability of the total number of drops, NT, between events. Vertical profiles from one event show a clear inverse relationship between NT and D0

On optimum rain rate estimation from a pulsed Doppler Weather Radar at Chennai

A 10 cm S-band Doppler Weather Radar (DWR) has been installed as a replacement of an outlived analogue S-band radar at Cyclone Detection Radar (CDR) station, Chennai during September-October, 2001. Technical specifications and capabilities of this DWR have been briefly mentioned in this paper. The digital data obtained from this DWR have been used for the period November-December, 2001 to estimate the rain rate based on the Marshall-Palmer relationship between the radar reflectivity factor (z) and the rain rate (R). The relation z = 267R1.345 estimates well the rain rate as measured by the self recording rain gauges located within 100 km radius from the DWR. This relationship has been tested for its operational applicability during March 2002 - December, 2003 and found that the accumulated precipitation from the radar estimation was within an error of 15% from the rain gauge measured values. Information on the twenty four hours accumulated areal distribution of precipitation can be used by the water managers and operational hydrologists for the effective water management over the catchments since the error in rain rate estimation over a wider area is relatively small in comparison to point rainfall estimation. 
 

Clear air echoes from the atmospheric boundary layer over Chennai – A study using S-band Doppler Weather Radar

During December 2002 – early April 2003, between 2345 and 0215 UTC and between 1230 and 1400 UTC covering the twilight period, radar reflectivities as high as 28-38 dBZ were measured in the atmospheric boundary layer by the Doppler Weather Radar (DWR) installed at Cyclone Detection Radar station, Chennai regularly. On analysis, it was found that these radar returns were not from precipitating clouds but from some other invisible source(s). The contributory mechanisms for this high order of reflectivity have been analysed from meteorological and non-meteorological angles. Thermodynamical parameters and potential radio refractive index have been computed and analysed. The refractive index structure constant (Cn2) has been computed from the 0000 and 1200 UTC RS/RW data as well as from the radar reflectivity data. The prevalence of convectively unstable atmosphere in the first layer adjacent to the surface (upto 350 m a.g.l) at 1200 UTC and nocturnal surface inversion at 0000 UTC contribute to the enhanced Cn2 in the range of 3.58 ´ 10-12 to 10-15 m-2/3 in the layers upto 900 m a.g.l. This sort of Bragg scattering with high Cn2 could have contributed to radar reflectivity factor as high as +0.8 dBZ only. During the last three decades, there is an alarming increase in nocturnal surface inversion frequencies over Chennai presumably due to high concentration of suspended particulate matters and respirable dust particles. The contribution by these pollutants to the radar reflectivity factor is restricted to a maximum of about – 0.9 dBZ only. Migratory birds of about eight to twelve thousand in number with 10 – 50 cm2 radar cross section and possibly innumerable insects appear as sources of the enhanced reflectivity.

Scale Dependence of Radar-Rainfall Rates—An Assessment Based on Raindrop Spectra

Abstract Scale differences may introduce a bias when comparing, merging, or assimilating rainfall measurements because the dynamic range of values representing the underlying physical process strongly depends on the resolution of the data. The present study addresses this issue from the perspective of how well coarser-resolution radar-rainfall observations may be used for evaluation of hydrologic point processes occurring at the land surface, such as rainfall erosion, infiltration, ponding, and runoff. Conceptual and quantitative analyses reveal that scale differences may yield substantial biases. Even for perfect measurements, the overall bias is composed of two contributing factors: one related to a reduction of dynamic range of rain rates and the other related to a dependence of the relationship between observed radar reflectivity factor and retrieved rainfall rate on the scale of observation. The effects of scale differences are evaluated empirically from a perspective of averaging in time based on raindrop spectra observations. Averaging drop spectra over 5 min, on average over a large dataset, resulted in an underestimation of median and maximum rainfall rates of approximately 50% compared to the corresponding 1-min values. Overall, standard deviations of rain rates retrieved from 5-min-averaged radar reflectivity factors may easily be off a corresponding high-resolution (1 min) rainfall rate by a factor 2 or more. This magnitude is larger than the uncertainty resulting from limitations of the radar measurement precision. Scale-difference effects are thus important and should be considered when comparing, merging, or assimilating data from very different spatial and temporal scales. A similar challenge arises for downscaling schemes attempting to recover subgrid-scale features from coarse-resolution information.

Mathematical–Physical Framework for Retrieval of Rain DSD Properties from Dual-Frequency Ku–Ka-Band Satellite Radar

In developing the upcoming Global Precipitation Measurement (GPM) mission, a dual-frequency Ku–Ka-band radar system will be used to measure rainfall in such a fashion that the reflectivity ratio intrinsic to the measurement will be sensitive to underlying variations in the drop size distribution (DSD) of rain. This will enable improved techniques for retrieving rain rates, which are dependent upon several key properties of the DSD. This study examines this problem by considering a three-parameter set defined by liquid water content (W), DSD effective radius (re), and DSD effective variance (υe). Using radiative transfer simulations, this parameter set is shown to be related to a radar reflectivity factor and specific attenuation in such a fashion that details of the DSDs are immaterial under constant W, and thus effectively represent important variations in DSD that affect rain rate but with a minimal number of parameters. The analysis also examines the effectiveness of including some measure of mean Doppler fall velocity of raindrops (υ), given that the fundamental properties of a given precipitation situation are uniquely defined by a combination of a drop mass spectrum and drop vertical velocity spectrum. The results of this study have bearing on how future dual-frequency precipitation retrieval algorithms could be formulated to optimize the sensitivity to underlying DSD variability, a problem that has greatly upheld past progress in radar rain retrieval.