Vertical Profile Of Reflectivity Research Articles

Empirical conversion of the vertical profile of reflectivity from Ku‐band to S‐band frequency

ABSTRACTThis paper presents an empirical method for converting reflectivity from Ku‐band (13.8 GHz) to S‐band (2.8 GHz) for several hydrometeor species, which facilitates the incorporation of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements into quantitative precipitation estimation (QPE) products from the U.S. Next‐Generation Radar (NEXRAD). The development of empirical dual‐frequency relations is based on theoretical simulations, which have assumed appropriate scattering and microphysical models for liquid and solid hydrometeors (raindrops, snow, and ice/hail). Particle phase, shape, orientation, and density (especially for snow particles) have been considered in applying the T‐matrix method to compute the scattering amplitudes. Gamma particle size distribution (PSD) is utilized to model the microphysical properties in the ice region, melting layer, and raining region of precipitating clouds. The variability of PSD parameters is considered to study the characteristics of dual‐frequency reflectivity, especially the variations in radar dual‐frequency ratio (DFR). The empirical relations between DFR and Ku‐band reflectivity have been derived for particles in different regions within the vertical structure of precipitating clouds. The reflectivity conversion using the proposed empirical relations has been tested using real data collected by TRMM‐PR and a prototype polarimetric WSR‐88D (Weather Surveillance Radar 88 Doppler) radar, KOUN. The processing and analysis of collocated data demonstrate the validity of the proposed empirical relations and substantiate their practical significance for reflectivity conversion, which is essential to the TRMM‐based vertical profile of reflectivity correction approach in improving NEXRAD‐based QPE.

Statistical and Physical Analysis of the Vertical Structure of Precipitation in the Mountainous West Region of the United States Using 11+ Years of Spaceborne Observations from TRMM Precipitation Radar

AbstractThis study presents a statistical analysis of the vertical structure of precipitation measured by NASA–Japan Aerospace Exploration Agency’s (JAXA) Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in the region of southern California, Arizona, and western New Mexico, where the ground-based Next-Generation Radar (NEXRAD) network finds difficulties in accurately measuring surface precipitation because of beam blockages by complex terrain. This study has applied TRMM PR version-7 products 2A23 and 2A25 from 1 January 2000 to 26 October 2011. The seasonal, spatial, intensity-related, and type-related variabilities are characterized for the PR vertical profile of reflectivity (VPR) as well as the heights of storm, freezing level, and bright band. The intensification and weakening of reflectivity at low levels in the VPR are studied through fitting physically based VPR slopes. Major findings include the following: precipitation type is the most significant factor determining the characteristics of VPRs, the shape of VPRs also influences the intensity of surface rainfall rates, the characteristics of VPRs have a seasonal dependence with strong similarities between the spring and autumn months, and the spatial variation of VPR characteristics suggests that the underlying terrain has an impact on the vertical structure. The comprehensive statistical and physical analysis strengthens the understanding of the vertical structure of precipitation and advocates for the approach of VPR correction to improve surface precipitation estimation in complex terrain.

Comparing the Convective Structure and Microphysics in Two Sahelian Mesoscale Convective Systems: Radar Observations and CRM Simulations

Abstract Two mesoscale convective systems (MCSs) observed during the African Monsoon Multidisciplinary Analyses (AMMA) experiment are simulated using the three-dimensional (3D) Goddard Cumulus Ensemble model. This study was undertaken to determine the performance of the cloud-resolving model in representing distinct convective and microphysical differences between the two MCSs over a tropical continental location. Simulations are performed using 1-km horizontal grid spacing, a lower limit on current embedded cloud-resolving models within a global multiscale modeling framework. Simulated system convective structure and microphysics are compared to radar observations using contoured frequency-by-altitude diagrams (CFADs), calculated ice and water mass, and identified hydrometeor variables. Vertical distributions of ice hydrometeors indicate underestimation at the mid- and upper levels, partially due to the inability of the model to produce adequate system heights. The abundance of high-reflectivity values below and near the melting level in the simulation led to a broadening of the CFAD distributions. Observed vertical reflectivity profiles show that high reflectivity is present at greater heights than the simulations produced, thought to be a result of using a single-moment microphysics scheme. Relative trends in the population of simulated hydrometeors are in agreement with observations, though a secondary convective burst is not well represented. Despite these biases, the radar-observed differences between the two cases are noticeable in the simulations as well, suggesting that the model has some skill in capturing observed differences between the two MCSs.

A real‐time automated convective and stratiform precipitation segregation algorithm in native radar coordinates

AbstractA new convective/stratiform (C/S) precipitation segregation algorithm was developed for applications with single radar volume scan data and in its native (spherical) coordinates. The new algorithm consists of two parts: the first is to find convective rainfall cores based on physical characteristics of different rainfall types, and the second is to delineate the full convective area through seeded region growing. The new scheme takes into account radar sampling characteristics and a variety of precipitation scenarios where the C/S delineation was relatively challenging. The new C/S delineation scheme has two impacts on radar quantitative precipitation estimation (QPE): (i) correctly separate convective and stratiform regions such that appropriate Ze–R relationships can be applied; (ii) correctly define the stratiform area such that a vertical profile of reflectivity (VPR) correction can be applied. The VPR correction is very important to reduce overestimation errors in radar QPEs associated with bright band. The new algorithm was tested on many events and showed improved performance over previous schemes, especially when handling strong bright band and melting graupels in stratiform precipitation. The new scheme was also tested in radar quantitative precipitation estimation (QPE) and it consistently reduced the root mean square error and mean absolute bias in the radar QPE when compared with gauges.

Intercomparison of Vertical Structure of Storms Revealed by Ground‐Based (NMQ) and Spaceborne Radars (CloudSat‐CPR and TRMM‐PR)

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.

Microwave remote sensing of the 2011 Plinian eruption of the Grímsvötn Icelandic volcano

The sub-glacial Plinian explosive eruption of the Grímsvötn volcano, which occurred on May 2011, is for the first time analyzed and quantitatively interpreted by using ground-based weather radar data and the Volcanic Ash Radar Retrieval (VARR) physically-based technique. The prevailing southerly winds stretched the erupted plume toward the Artic pole, thus preventing the ash cloud to move toward continental Europe and threatening the airline traffic (different from the less explosive Eyjafjöll eruption on April and May 2010). The 2011 Grímsvötn eruption has been continuously monitored by the Keflavík C-band weather radar, located at a distance of about 260km from the volcano vent. The VARR methodology is summarized and applied to available radar time series to estimate the coarse ash particle category, volume, fallout, concentration and the plume maximum height, every 5min within the volcano vent surroundings (i.e. an area of about 100×100km2 around the volcano). Due to the large distance from the volcano, fine-grained ash cannot be detected and estimated by the Keflavík C-band weather radar. Estimates of the eruption discharge rate, based on the retrieved ash plume top height, are provided together with an evaluation of the total erupted mass and volume. Deposited ash at ground is also retrieved from radar data by empirically reconstructing the vertical profile of radar reflectivity and estimating the near-surface ash fallout. Radar-based ash retrieval results can be compared with available satellite microwave radiometric imagery in order to show the potential contribution and limitations of these microwave remote sensing products to the understanding and modeling of explosive volcanic ash eruptions. Spaceborne microwave brightness temperatures show a correlation with ash columnar content, derived from VARR, depending on the millimeter-wave frequency and on the spatial averaging. Microphysical sensitivity of satellite microwave brightness temperatures to plume fine and coarse ash suggests their exploitation in synergy with satellite thermal infrared radiometer and ground-based microwave radar observations.

Radar-Based Quantitative Precipitation Estimation for the Cool Season in Complex Terrain: Case Studies from the NOAA Hydrometeorology Testbed

Abstract This study explores error sources of the National Weather Service operational radar-based quantitative precipitation estimation (QPE) during the cool season over the complex terrain of the western United States. A new, operationally geared radar QPE was developed and tested using data from the National Oceanic and Atmospheric Administration Hydrometeorology Testbed executed during the 2005/06 cool season in Northern California. The new radar QPE scheme includes multiple steps for removing nonprecipitation echoes, constructing a seamless hybrid scan reflectivity field, applying vertical profile of reflectivity (VPR) corrections to the reflectivity, and converting the reflectivity into precipitation rates using adaptive Z–R relationships. Specific issues in radar rainfall accumulations were addressed, which include wind farm contaminations, blockage artifacts, and discontinuities due to radar overshooting. The new radar QPE was tested in a 6-month period of the 2005/06 cool season and showed significant improvements over the current operational radar QPE (43% reduction in bias and 30% reduction in root-mean-square error) when compared with gauges. In addition, the new technique minimizes various radar artifacts and produces a spatially continuous rainfall product. Such continuity is important for accurate hydrological model predictions. The new technique is computationally efficient and can be easily transitioned into operations. One of the largest remaining challenges is obtaining accurate radar QPE over the windward slopes of significant mountain ranges, where low-level orographic enhancement of precipitation is not resolved by the operational radars leading to underestimation. Additional high-resolution and near-surface radar observations are necessary for more accurate radar QPE over these regions.

Comparison of precipitation observations from a prototype space-based cloud radar and ground-based radars

A prototype space-based cloud radar has been developed and was installed on an airplane to observe a precipitation system over Tianjin, China in July 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured reflectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar (SA radar), and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.

CAPPI 반사도의 오차구조 및 지구곡률효과로 인한 거리오차 보정

It is important to characterize and quantify the inherent error in the radar rainfall to make full use of the radar rainfall. This study verified the error structure of the reflectivity and corrected the range dependent error in the CAPPI using a VPR (vertical profile of reflectivity) model. The error of the CAPPI to display the reflectivity data becomes bigger for the range longer than 100 km. This range dependent error, however, is significantly improved by corrected the CAPPI data using the VPR model.

On the Effect of Non-Raining Parameters in Retrieval of Surface Rain Rate Using TRMM PR and TMI Measurements

Microwave radiation with the inherent advantage of its ability to partially penetrate clouds is ideally suited for remote measurements of precipitation, especially over the oceanic regions. The retrieval problem is of great practical interest, as precipitation over the oceans has to be necessarily remotely sensed. More importantly, precipitation is also a crucial input in many weather and climate models. A downward looking space borne radiometer such as the TRMM's Microwave Imager (TMI), however, does not sense the surface rain fall directly. Rather, it measures the upwelling radiation coming from the top-of-atmosphere which depends on the total quantities of the parameters that can affect the radiation in the chosen frequency range. In addition to precipitation, the attenuation and augmentation of total cloud content and integrated precipitable water content by absorption and emission, respectively, affect the microwave brightness temperatures in various frequencies. In the present work, a systematic study has been conducted to investigate the effect of total cloud and precipitable water contents on surface rainrate retrievals from the TMI measured brightness temperatures (BT). While a Bayesian framework is used to assimilate radar reflectivities into hydrometeor structures, a neural network is used to correlate rain and cloud parameters with brightness temperatures. The correlation between the TMI brightness temperatures and the TRMM's Precipitation Radar (TRMM-PR) is used as the benchmark for comparison. A community developed software meso-scale Weather Research and Forecast (WRF) is used to simulate the cloud and precipitable water content, along with the surface rainfall rate for several rain events in the past. Four cases are considered: (a) TRMM PR's near surface rain rate is correlated with TMI brightness temperatures directly; (b) the total cloud and precipitable water contents along with surface rainfall simulated using WRF are correlated with TMI BTs; (c) similar to case (b) with near surface rainfall taken from TRMM PR measurements; (d) total cloud and precipitable water contents and the surface rain rate are corrected with PR vertical reflectivity profile in a Bayesian framework. The freely available QuickBeam software has been used for simulation of reflectivities at the TRMM PR frequency. The corrected data are then correlated with TMI BTs. Results show that surface rain fall retrievals can be radically improved by using TRMM PR vertical rain corrected total cloud and precipitable water content.

Comparison of polarimetric signatures of hail at S and C bands for different hail sizes

In this study, severe hail cases in Oklahoma/USA are investigated by analyzing the data simultaneously collected by two closely located polarimetric weather radars operating at S and C bands. Polarimetric radar variables measured in the presence of hail at C band are quite different from the ones at S band due to more pronounced effects of resonance scattering and much stronger impact of attenuation. The differences are particularly strong in melting hail below the freezing level, but they can be substantial even at higher altitudes where hail is dry or grows in wet regime. As a consequence, the algorithms for hail detection and determination of its size developed at S band can't be directly applied to C band. Differences between vertical profiles of radar reflectivity Z, differential reflectivity ZDR, and cross-correlation coefficient ρhv in hail-bearing parts of the storms have been examined for large and giant hail. It is shown that in the presence of hail, ZDR(C) is usually higher than ZDR(S) and ρhv(C)<ρhv(S). The height of radar resolution volume with respect to the freezing level has to be taken into account in polarimetric hail detection/sizing. It is also demonstrated that giant hail is commonly associated with pronounced depression of ρhv in the areas of hail generation above the freezing level and the corresponding drop in ρhv at C band is much stronger than at S band. These results are compared to C-band polarimetric data collected in hail-bearing thunderstorms in Austria, where additional small hail size reports are available.

Regional Variability within Global-Scale Relations between Passive Microwave Signatures and Raining Clouds over the Tropical Oceans

AbstractEmpirical orthogonal function (EOF) analysis of radiance vectors associated with emission and scattering indices for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) has been performed to examine the regional variability in relations between brightness temperature and rain rate over portions of the tropical oceans known to exhibit regional differences due to different thermodynamic environments and different large-scale forcing. The TMI indices and rain rates used in this study are the products of the Goddard profiling algorithm (GPROF), version 6. The EOF framework reduces the nine-dimensional space of the brightness temperatures and their polarizations to just two dimensions associated with the EOF coefficients. Vertical profiles of reflectivity from the TRMM precipitation radar (PR) are used to show that the statistically obtained EOFs represent bulk physical characteristics of raining clouds. Hence, EOF analysis provides an efficient framework for diagnosing regional differences in cloud structures that affect brightness temperature–rain-rate relations. The EOF framework revealed fundamental differences in the behavior of TMI surface rain-rate retrievals versus retrievals that are based on the PR aboard the TRMM satellite. In EOF space, TMI rain rates were bimodally distributed, with one mode indicating higher rain rates with greater high-density ice and rainwater content in the cloud and the other mode being consistent with moderately heavy warm rain from shallow convection. In contrast, the PR rain-rate distribution showed high rain rates being assigned over a much greater diversity of cloud structures. The manifold of EOF space constructively shows that, of the regions examined here, the tropical northwestern Pacific Ocean region produces the greatest occurrence of particularly strong cumulonimbus clouds.

Relationships between lightning flash rates and radar reflectivity vertical structures in thunderstorms over the tropics and subtropics

Relationships between the vertical profile of radar reflectivity and lightning flash rates are investigated using 13 years of Tropical Rainfall Measuring Mission (TRMM) observations during 1998–2010. First the Radar Precipitation Features (RPFs) are defined by grouping raining areas detected by the TRMM Precipitation Radar (PR). Then the characteristics of radar reflectivity and lightning flash rate are calculated in each RPF using PR and Lightning Imaging Sensor (LIS) observations. Using these RPFs, temperatures at 20, 30, and 40 dBZ radar echo tops, used as proxies of the maximum convective intensity of precipitation systems, are examined as indicators of the probability of lightning. Although 30 and 40 dBZ echo top temperatures are better indicators of the probability of lightning than the 20 dBZ echo top temperature, there is a large regional variation in the temperature thresholds, especially between land and ocean. In general, oceanic thunderstorms have higher 20 dBZ echo top and larger horizontal extent than those over land. However, radar reflectivity is more likely to exceed 30 and 40 dBZ at cold temperatures over land than over ocean. The correlations between flash rates and radar echo top temperatures, areas and volumes of radar reflectivity, and ice water contents in the mixed phase region are analyzed using RPFs with at least one flash. In agreement with previous studies, the correlations with the echo top temperatures are low, but the correlations between flash rates and areas and volumes of high radar reflectivity in the mixed phase region are much higher. There is a high correlation between the flash rates and the volumes with radar reflectivity greater than 30, 35, or 40 dBZ in the mixed phase region, but the correlation coefficient varies significantly between thunderstorms over different regions, especially between land and ocean. These results are confirmed by repeating the analysis for regions of the storms defined as convective, thus eliminating the contribution from large areas of stratiform radar echo that have much less lightning.

Diagnosis of the Warm Rain Process in Cloud-Resolving Models Using Joint CloudSat and MODIS Observations

Abstract This study examines the warm rain formation process in global and regional cloud-resolving models. Methodologies developed to analyze CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations are employed to investigate the cloud-to-precipitation processes and are applied to model results for comparisons with corresponding statistics from the observations. Three precipitation categories of no precipitation, drizzle, and rain are defined according to nonattenuated near-surface radar reflectivity, and their fractional occurrences and the probability of precipitation are investigated as a function of cloud properties such as droplet size, optical thickness, droplet number concentration, and liquid water path. The comparisons reveal how the models are qualitatively similar to, but quantitatively different from, observations in terms of cloud-to-rainwater conversion processes. Statistics from one model reveal a much faster formation of rain than observed, with drizzle occurrence being much less frequent, whereas statistics from the other model illustrate rain formation closer to satellite observations but still faster formation of drizzle water. Vertical profiles of radar reflectivity that are rescaled as a function of in-cloud optical depth and classified according to particle size are also compared. The results show that each model indicates systematically faster formation of rain and drizzle, respectively, than observed in vertical profiles although they indicate that the cloud-to-rain transitions are qualitatively similar to observations. These results characterize the model behavior in terms of warm cloud microphysics and then point to a possible area of model improvement for more realistic representation of warm rain formation processes.

A study of microphysical properties within a precipitation system using wind profiler spectra

This study investigates microphysical properties from wind profiler Doppler spectra observed within a precipitation system that produced high rainfall rates up to 40 mm hr−1 near the southern coast of the Korean Peninsula on 25∼26 June 2010. A 1290-MHz wind profiler located in the National Center for Intensive Observation of Severe Weather at Boseong, Korea, observed a widespread stratiform region and short-lived convective cells from 1850 UTC 25 to 0200 UTC 26 June 2010. By using a spectral model applied to observed profiler spectra, rainfall parameters and raindrop size distributions were retrieved below a melting layer during this period. Three representative periods during precipitation were selected based on intensities of bright band and characteristics in vertical profiles of radar reflectivity and Doppler velocity. During a brief convective period (∼30 min), radar reflectivity tended to be proportional to vertical air motion (positive upward), suggesting that updrafts up to ∼3 m s−1 over a large vertical extent through the melting layer probably contributed to increasing rainfall rates at the surface. In reflectivityrainfall rate distributions, large drop spectra (high reflectivity) were analyzed within downdrafts and small drop spectra (low reflectivity) within updrafts, similar to the large and small drop spectra but found in stratiform and convective regions, respectively, in previous studies. This indicates that the degree of spread between reflectivity and rainfall rate may be strongly dependent on positive and negative magnitudes of vertical air motion. For three categories of vertical air motion (i.e., updrafts, neutral, and downdrafts), physical relations between the retrieved rainfall parameters were examined.

The Eyjafjöll explosive volcanic eruption from a microwave weather radar perspective

Abstract. The sub-glacial Eyjafjöll explosive volcanic eruptions of April and May 2010 are analyzed and quantitatively interpreted by using ground-based weather radar data and the Volcanic Ash Radar Retrieval (VARR) technique. The Eyjafjöll eruptions have been continuously monitored by the Keflavík C-band weather radar, located at a distance of about 155 km from the volcano vent. Considering that the Eyjafjöll volcano is approximately 20 km from the Atlantic Ocean and that the northerly winds stretched the plume toward the mainland Europe, weather radars are the only means to provide an estimate of the total ejected tephra. The VARR methodology is summarized and applied to available radar time series to estimate the plume maximum height, ash particle category, ash volume, ash fallout and ash concentration every 5 min near the vent. Estimates of the discharge rate of eruption, based on the retrieved ash plume top height, are provided together with an evaluation of the total erupted mass and volume. Deposited ash at ground is also retrieved from radar data by empirically reconstructing the vertical profile of radar reflectivity and estimating the near-surface ash fallout. Radar-based retrieval results cannot be compared with ground measurements, due to the lack of the latter, but further demonstrate the unique contribution of these remote sensing products to the understating and modelling of explosive volcanic ash eruptions.

Cross Validation of Spaceborne Radar and Ground Polarimetric Radar Aided by Polarimetric Echo Classification of Hydrometeor Types

AbstractGround-based polarimetric weather radar is arguably the most powerful validation tool that provides physical insight into the development and interpretation of spaceborne weather radar algorithms and observations. This study aims to compare and resolve discrepancies in hydrometeor retrievals and reflectivity observations between the NOAA/National Severe Storm Laboratory “proof of concept” KOUN polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) and the spaceborne precipitation radar (PR) on board NASA’s Tropical Rainfall Measuring Mission (TRMM) platform. An intercomparison of PR and KOUN melting-layer heights retrieved from 2 to 5 km MSL shows a high correlation coefficient of 0.88 with relative bias of 5.9%. A resolution volume–matching technique is used to compare simultaneous TRMM PR and KOUN reflectivity observations. The comparisons reveal an overall bias of &lt;0.2% between PR and KOUN. The bias is hypothesized to be from non-Rayleigh scattering effects and/or errors in attenuation correction procedures applied to Ku-band PR measurements. By comparing reflectivity with respect to different hydrometeor types (as determined by KOUN’s hydrometeor classification algorithm), it is found that the bias is from echoes that are classified as rain–hail mixture, wet snow, graupel, and heavy rain. These results agree with expectations from backscattering calculations at Ku and S bands, but with the notable exception of dry snow. Comparison of vertical reflectivity profiles shows that PR suffers significant attenuation at lower altitudes, especially in convective rain and in the melting layer. The attenuation correction performs very well for both stratiform and convective rain, however. In light of the imminent upgrade of the U.S. national weather radar network to include polarimetric capabilities, the findings in this study will potentially serve as the basis for nationwide validation of space-based precipitation products and also invite synergistic development of coordinated space–ground multisensor precipitation products.

Winter precipitation fields in the Southeastern Mediterranean area as seen by the Ku-band spaceborne weather radar and two C-band ground-based radars

The spaceborne weather radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite can be used to adjust Ground-based Radar (GR) echoes, as a function of the range from the GR site. The adjustment is based on the average linear radar reflectivity in circular rings around the GR site, for both the GR and attenuation-corrected NearSurfZ TRMM Precipitation Radar (TPR) images. In previous studies, it was found that in winter, for the lowest elevation of the Cyprus C-band radar, the GR/TPR equivalent rain rate ratio was decreasing, on average, of approximately 8dB per decade. In this paper, the same analysis has been applied to another C-band radar in the southeastern Mediterranean area. For the lowest elevation of the “Shacham” radar in Israel, the GR/TPR equivalent rain rate ratio is found to decrease of approximately 6dB per decade. The average departure at the “reference”, intermediate range is related to the calibration of the GR. The negative slope of the range dependence is considered to be mainly caused by an overshooting problem (increasing sampling volume of the GR with range combined with non-homogeneous beam filling and, on average, a decreasing vertical profile of radar reflectivity). To check this hypothesis, we have compared the same NearSurfZ TPR images versus GR data acquired using the second elevation. We expected these data to be affected more by overshooting, especially at distant ranges: the negative slope of the range dependence was in fact found to be more evident than in the case of the lowest GR elevation for both the Cypriot and Israeli radar.

Radar characteristics of continental, coastal, and maritime convection observed during AMMA/NAMMA

AbstractGround‐based radar observations at three distinct geographical locations in West Africa along a common latitudinal band (Niamey, Niger (continental), Kawsara, Senegal (coastal), and Praia, Republic of Cape Verde (maritime)) are analyzed to determine convective system characteristics in each domain during a 29‐day period in 2006. Ancillary datasets provided by the African Monsoon Multidisciplinary Analyses (AMMA) and NASA‐AMMA (NAMMA) field campaigns are also used to place the radar observations in context. Results show that the total precipitation is dominated by propagating mesoscale convective systems. Convective characteristics vary according to environmental properties, such as vertical shear, CAPE, and the degree of synoptic forcing. Data are bifurcated based on the presence or absence of African easterly waves. In general, African easterly waves appear to enhance mesoscale convective system strength characteristics (e.g. total precipitation and vertical reflectivity profiles) at the inland and maritime sites. The wave regime also resulted in an increased population of the largest observed mesoscale convective systems observed near the coast, which led to an increase in stratiform precipitation. Despite this increase, differentiation of convective strength characteristics was less obvious between wave and no‐wave regimes at the coast. Owing to the propagating nature of these advecting mesoscale convective systems, interaction with the regional thermodynamic and dynamic environment appears to result in more variability than enhancements due to the wave regime, independent of location. Copyright © 2011 Royal Meteorological Society

Statistical model of the range-dependent error in radar-rainfall estimates due to the vertical profile of reflectivity

Summary The authors developed an approach for deriving a statistical model of range-dependent error (RDE) in radar-rainfall estimates by parameterizing the structure of the non-uniform vertical profile of radar reflectivity (VPR). The proposed parameterization of the mean VPR and its expected variations are characterized by several climatological parameters that describe dominant atmospheric conditions related to vertical reflectivity variation. We have used four years of radar volume scan data from the Tulsa weather radar WSR-88D (Oklahoma) to illustrate this approach and have estimated the model parameters by minimizing the sum of the squared differences between the modeled and observed VPR influences that were computed using radar data. We evaluated the mean and standard deviation of the modeled RDE against rain gauge data from the Oklahoma Mesonet network. No rain gauge data were used in the model development. The authors used the three lowest antenna elevation angles to demonstrate the model performance for cold (November–April) and warm (May–October) seasons. The RDE derived from the parameterized models shows very good agreement with the observed differences between radar and rain gauge estimates of rainfall. For the third elevation angle and cold season, there are 82% and 42% improvements for the RDE and its standard deviation with respect to the no-VPR case. The results of this study indicate that VPR is a key factor in the characterization of the radar range-dependent bias, and the proposed models can be used to represent the radar RDE in the absence of rain gauge data.