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1

Protat, Alain, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby. "Three-way calibration checks using ground-based, ship-based, and spaceborne radars." Atmospheric Measurement Techniques 15, no. 4 (February 21, 2022): 915–26. http://dx.doi.org/10.5194/amt-15-915-2022.

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Abstract. This study uses ship-based weather radar observations collected from research vessel Investigator to evaluate the Australian weather radar network calibration monitoring technique that uses spaceborne radar observations from the NASA Global Precipitation Mission (GPM). Quantitative operational applications such as rainfall and hail nowcasting require a calibration accuracy of ±1 dB for radars of the Australian network covering capital cities. Seven ground-based radars along the western coast of Australia and the ship-based OceanPOL radar are first calibrated independently using GPM radar overpasses over a 3-month period. The calibration difference between the OceanPOL radar (used as a moving reference for the second step of the study) and each of the seven operational radars is then estimated using collocated, gridded, radar observations to quantify the accuracy of the GPM technique. For all seven radars the calibration difference with the ship radar lies within ±0.5 dB, therefore fulfilling the 1 dB requirement. This result validates the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks (provided that the spaceborne radar maintains a high calibration accuracy). The analysis of the day-to-day and hourly variability of calibration differences between the OceanPOL and Darwin (Berrimah) radars also demonstrates that quantitative comparisons of gridded radar observations can accurately track daily and hourly calibration differences between pairs of operational radars with overlapping coverage (daily and hourly standard deviations of ∼ 0.3 and ∼ 1 dB, respectively).
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2

Lombardo, F., F. Napolitano, F. Russo, G. Scialanga, L. Baldini, and E. Gorgucci. "Rainfall estimation and ground clutter rejection with dual polarization weather radar." Advances in Geosciences 7 (February 16, 2006): 127–30. http://dx.doi.org/10.5194/adgeo-7-127-2006.

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Abstract. Conventional radars, used for atmospheric remote sensing, usually operate at a single polarization and frequency to estimate storm parameters such as rainfallrate and water content. Because of the high variability of the drop size distribution conventional radars do not succeed in obtaining detailed information because they just use horizontal reflectivity. The potentiality of the dual-polarized weather radar is investigated, in order to reject the ground-clutter, using differential reflectivity. In this light, a radar meteorology campaign was conducted over the city of Rome (Italy), collecting measurements by the polarimetric Doppler radar Polar 55C and by a raingauge network. The goodness of the results is tested by comparison of radar rainfall estimates with raingauges rainfall measurements.
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3

Min, Chao, Sheng Chen, Jonathan J. Gourley, Haonan Chen, Asi Zhang, Yong Huang, and Chaoying Huang. "Coverage of China New Generation Weather Radar Network." Advances in Meteorology 2019 (June 16, 2019): 1–10. http://dx.doi.org/10.1155/2019/5789358.

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The China Meteorological Administration has deployed the China New Generation Weather Radar (CINRAD) network for severe weather detection and to improve initial conditions for numerical weather prediction models. The CINRAD network consists of 217 radars comprising 123 S-band and 94 C-band radars over mainland China. In this paper, a high-resolution digital elevation model (DEM) and beam propagation simulations are used to compute radar beam blockage and evaluate the effective radar coverage over China. Results show that the radar coverage at a height of 1 km above ground level (AGL) is restricted in complex terrain regions. The effective coverage maps at heights of 2 km and 3 km AGL indicate that the Yangtze River Delta, the Pearl River Delta, and North China Plain have more overlapping radar coverage than other regions in China. Over eastern China, almost all areas can be sampled by more than 2 radars within 5 km above mean sea level (MSL), but the radars operating in Qinghai-Tibet Plateau still suffer from serious beam blockage caused by intervening terrain. Overall, the radars installed in western China suffer from much more severe beam blockage than those deployed in eastern China. Maps generated in this study will inform users of the CINRAD data of their limitations for use in precipitation estimation, as inputs to other weather and hydrological models, and for satellite validation studies.
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4

Bestugin, A. R., M. B. Ryzhikov, and Iu A. Novikova. "The frequency range selection for airborne weather radar with the search for areas with the visibility of landmarks for flight and landing." Radio industry 28, no. 3 (August 29, 2018): 8–17. http://dx.doi.org/10.21778/2413-9599-2018-28-3-8-17.

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A radar dome of a small aircraft can accommodate an antenna with a small aperture only. The energy potential and radiation parameters required for detection of hazardous weather events are thereby impaired. Mathematical modeling of the effect of wavelength change on the quality of radar meteorological forecast has been performed. Performance parameters of small-sized weather radars have been evaluated for enhancing the safety of the flights of small aircraft. Mathematics have been presented for comparing the efficiency of detecting dangerous thunderstorm areas with allowance for the signal reflection from the ground surface. The formula take into account the wavelength, the directional function of the antenna system, the radar reflectivity of the ground surface, the speed and altitude of flight. The efficiency of the weather radar with a small-sized antenna aperture operating in3 cmand8 mmwave lengths has been reviewed. The detection range of small aircraft radars with different wavelengths in different weather conditions has been determined. A flight envelope search mode is proposed with a possibility of visual orientation and landing in bad weather conditions. The mode is based on measuring the radar reflectivity of moisture targets.
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5

Qi, Youcun, and Jian Zhang. "Correction of Radar QPE Errors Associated with Low and Partially Observed Brightband Layers." Journal of Hydrometeorology 14, no. 6 (November 22, 2013): 1933–43. http://dx.doi.org/10.1175/jhm-d-13-040.1.

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Abstract The melting of aggregated snow/crystals often results in an enhancement of the reflectivity observed by weather radars, and this is commonly referenced as the bright band (BB). The locally high reflectivity often causes overestimation in radar quantitative precipitation estimates (QPE) if no appropriate correction is applied. When the melting layer is high, a complete BB layer profile (including top, peak, and bottom) can be observed by the ground radar, and a vertical profile of reflectivity (VPR) correction can be made to reduce the BB impact. When a melting layer is near the ground and the bottom part of the bright band cannot be observed by the ground radar, a VPR correction cannot be made directly from the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar observations. This paper presents a new VPR correction method under this situation. From high-resolution precipitation profiler data, an empirical relationship between BB peak and BB bottom is developed. The empirical relationship is combined with the apparent BB peak observed by volume scan radars and the BB bottom is found. Radar QPEs are then corrected based on the estimated BB bottom. The new method was tested on 13 radars during seven low brightband events over different areas in the United States. It is shown to be effective in reducing the radar QPE overestimation under low brightband situations.
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6

Marzano, Frank S., Errico Picciotti, Mario Montopoli, and Gianfranco Vulpiani. "Inside Volcanic Clouds: Remote Sensing of Ash Plumes Using Microwave Weather Radars." Bulletin of the American Meteorological Society 94, no. 10 (October 1, 2013): 1567–86. http://dx.doi.org/10.1175/bams-d-11-00160.1.

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Microphysical and dynamical features of volcanic tephra due to Plinian and sub-Plinian eruptions can be quantitatively monitored by using ground-based microwave weather radars. The methodological rationale and unique potential of this remote-sensing technique are illustrated and discussed. Volume data, acquired by ground-based weather radars, are processed to automatically classify and estimate ash particle concentration and fallout. The physical– statistical retrieval algorithm is based on a backscattering microphysical model of fine, coarse, and lapilli ash particles, used within a Bayesian classification and optimal estimation methodology. The experimental evidence of the usefulness and limitations of radar acquisitions for volcanic ash monitoring is supported by describing several case studies of volcanic eruptions all over the world. The radar sensitivity due to the distance and the system noise, as well as the various radar bands and configurations (i.e., Doppler and dual polarized), are taken into account. The discussed examples of radar-derived ash concentrations refer to the case studies of the Augustine volcano eruption in 2002, observed in Alaska by an S-band radar; the Grímsvötn volcano eruptions in 2004 and 2011, observed in Iceland by C- and X-band weather radars and compared with in situ samples; and the Mount Etna volcano eruption in 2011, observed by an X-band polarimetric radar. These applications demonstrate the variety of radar-based products that can be derived and exploited for the study of explosive volcanism.
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7

Leinonen, Jussi, Dmitri Moisseev, Matti Leskinen, and Walter A. Petersen. "A Climatology of Disdrometer Measurements of Rainfall in Finland over Five Years with Implications for Global Radar Observations." Journal of Applied Meteorology and Climatology 51, no. 2 (February 2012): 392–404. http://dx.doi.org/10.1175/jamc-d-11-056.1.

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AbstractTo improve the understanding of high-latitude rain microphysics and its implications for the remote sensing of rainfall by ground-based and spaceborne radars, raindrop size measurements have been analyzed that were collected over five years with a Joss–Waldvogel disdrometer located in Järvenpää, Finland. The analysis shows that the regional climate is characterized by light rain and small drop size with narrow size distributions and that the mutual relations of drop size distribution parameters differ from those reported at lower latitudes. Radar parameters computed from the distributions demonstrate that the high latitudes are a challenging target for weather radar observations, particularly those employing polarimetric and dual-frequency techniques. Nevertheless, the findings imply that polarimetric ground radars can produce reliable “ground truth” estimates for space observations and identify dual-frequency radars utilizing a W-band channel as promising tools for observing rainfall in the high-latitude climate.
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8

Louf, Valentin, Alain Protat, Robert A. Warren, Scott M. Collis, David B. Wolff, Surendra Raunyiar, Christian Jakob, and Walter A. Petersen. "An Integrated Approach to Weather Radar Calibration and Monitoring Using Ground Clutter and Satellite Comparisons." Journal of Atmospheric and Oceanic Technology 36, no. 1 (January 2019): 17–39. http://dx.doi.org/10.1175/jtech-d-18-0007.1.

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AbstractThe stability and accuracy of weather radar reflectivity calibration are imperative for quantitative applications, such as rainfall estimation, severe weather monitoring and nowcasting, and assimilation in numerical weather prediction models. Various radar calibration and monitoring techniques have been developed, but only recently have integrated approaches been proposed, that is, using different calibration techniques in combination. In this paper the following three techniques are used: 1) ground clutter monitoring, 2) comparisons with spaceborne radars, and 3) the self-consistency of polarimetric variables. These techniques are applied to a C-band polarimetric radar (CPOL) located in the Australian tropics since 1998. The ground clutter monitoring technique is applied to each radar volumetric scan and provides a means to reliably detect changes in calibration, relative to a baseline. It is remarkably stable to within a standard deviation of 0.1 dB. To obtain an absolute calibration value, CPOL observations are compared to spaceborne radars on board TRMM and GPM using a volume-matching technique. Using an iterative procedure and stable calibration periods identified by the ground echoes technique, we improve the accuracy of this technique to about 1 dB. Finally, we review the self-consistency technique and constrain its assumptions using results from the hybrid TRMM–GPM and ground echo technique. Small changes in the self-consistency parameterization can lead to 5 dB of variation in the reflectivity calibration. We find that the drop-shape model of Brandes et al. with a standard deviation of the canting angle of 12° best matches our dataset.
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9

Li, Yinguang, Guifu Zhang, Richard Doviak, and Darcy Saxion. "Scan-to-Scan Correlation of Weather Radar Signals to Identify Ground Clutter." Geoscience and Remote Sensing Letters, IEEE 10, no. 4 (February 2013): 855–59. http://dx.doi.org/10.1109/lgrs.2012.2226233.

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The scan-to-scan correlation method to discriminate weather signals from ground clutter, described in this letter, takes advantage of the fact that the correlation time of radar echoes from hydrometeors is typically much shorter than that from ground objects. In this letter, the scan-to-scan correlation method is applied to data from the WSR-88D, and its results are compared with those produced by the WSR-88D's ground clutter detector. A subjective comparison with an operational clutter detection algorithm used on the network of weather radars shows that the scan-to-scan correlation method produces a similar clutter field but presents clutter locations with higher spatial resolution.
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10

Hunzinger, Alexis, Joseph C. Hardin, Nitin Bharadwaj, Adam Varble, and Alyssa Matthews. "An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans." Atmospheric Measurement Techniques 13, no. 6 (June 15, 2020): 3147–66. http://dx.doi.org/10.5194/amt-13-3147-2020.

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Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher-frequency radars as well as range–height indicator (RHI) scans. The calibration of weather radars represents one of the most dominant sources of error for their use in a variety of fields including quantitative precipitation estimation and model comparisons. While most weather radars are routinely calibrated, the frequency of calibration is often less than required, resulting in miscalibrated time periods. While full absolute calibration techniques often require the radar to be taken offline for a period of time, there have been online calibration techniques discussed in the literature. The relative calibration adjustment (RCA) technique uses the statistics of the ground clutter surrounding the radar as a monitoring source for the stability of calibration but has only been demonstrated to work at S- and C-band for plan-position indicator (PPI) scans at a constant elevation. In this work the RCA technique is modified to work with higher-frequency radars, including Ka-band cloud radars. At higher frequencies the properties of clutter can be much more variable. This work introduces an extended clutter selection procedure that incorporates the temporal stability of clutter and helps to improve the operational stability of RCA for relatively higher-frequency radars. The technique is also extended to utilize range–height scans from radars where the elevation is varied rather than the azimuth. These types of scans are often utilized with research radars to examine the vertical structure of clouds. The newly extended technique (eRCA) is applied to four Department of Energy Atmospheric Radiation Measurement (DOE ARM) weather radars ranging in frequency from C- to Ka-band. Cross comparisons of three co-located radars with frequencies C, X, and Ka at the ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) site show that the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic (ENA) site, we show how the technique can be modified to be more resilient to clutter fields that show increased variability, in this case due to sea clutter. The results show that this technique is promising for a posteriori data calibration and monitoring.
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11

Fall, Veronica M., Qing Cao, and Yang Hong. "Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/270726.

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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.
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12

Rennie, S. J., A. J. Illingworth, and S. L. Dance. "On differentiating ground clutter and insect echoes from Doppler weather radars using archived data." Atmospheric Measurement Techniques Discussions 3, no. 2 (April 16, 2010): 1843–60. http://dx.doi.org/10.5194/amtd-3-1843-2010.

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Abstract. Normally wind measurements from Doppler radars rely on the presence of rain. During fine weather, insects become a potential radar target for wind measurement. However, it is difficult to separate ground clutter and insect echoes when spectral or polarimetric methods are not available. Archived reflectivity and velocity data from repeated scans provide alternative methods. The probability of detection (POD) method, which maps areas with a persistent signal as ground clutter, is ineffective when most scans also contain persistent insect echoes. We developed a clutter detection method which maps the standard deviation of velocity (SDV) over a large number of scans, and can differentiate insects and ground clutter close to the radar. Beyond the range of persistent insect echoes, the POD method more thoroughly removes ground clutter. A new, pseudo-probability clutter map was created by combining the POD and SDV maps. The new map optimised ground clutter detection without removing insect echoes.
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13

Snyder, Jeffrey C., and Alexander V. Ryzhkov. "Automated Detection of Polarimetric Tornadic Debris Signatures Using a Hydrometeor Classification Algorithm." Journal of Applied Meteorology and Climatology 54, no. 9 (September 2015): 1861–70. http://dx.doi.org/10.1175/jamc-d-15-0138.1.

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AbstractAlthough radial velocity data from Doppler radars can partially resolve some tornadoes, particularly large tornadoes near the radar, most tornadoes are not explicitly resolved by radar owing to inadequate spatiotemporal resolution. In addition, it can be difficult to determine which mesocyclones typically observed on radar are associated with tornadoes. Since debris lofted by tornadoes has scattering characteristics that are distinct from those of hydrometeors, the additional information provided by polarimetric weather radars can aid in identifying debris from tornadoes; the polarimetric tornadic debris signature (TDS) provides what is nearly “ground truth” that a tornado is ongoing (or has recently occurred). This paper outlines a modification to the hydrometeor classification algorithm used with the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) network in the United States to include a TDS category. Examples of automated TDS classification are provided for several recent cases that were observed in the United States.
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14

Doviak, R., and D. Zrnic. "Siting of Doppler weather radars to shield ground targets." IEEE Transactions on Antennas and Propagation 33, no. 7 (July 1985): 685–89. http://dx.doi.org/10.1109/tap.1985.1143652.

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15

Norin, Lars. "Observations of anomalous propagation over waters near Sweden." Atmospheric Measurement Techniques 16, no. 7 (April 4, 2023): 1789–801. http://dx.doi.org/10.5194/amt-16-1789-2023.

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Abstract. Radio waves propagating in the atmosphere are affected by the prevailing atmospheric state. The state of the atmosphere can cause radio waves to refract more or less towards the ground. When the refractive index of the atmosphere differs from standard atmospheric conditions, the propagation is considered to be anomalous. Radars which are affected by anomalous propagation can observe ground clutter far beyond the radar horizon. In this work, 4.5 years' worth of data from five operational Swedish C-band dual-polarization weather radars are presented. Analyses of the data reveal a strong seasonal cycle and a weaker diurnal cycle in ground clutter from coastal regions across nearby waters. A comparison was drawn between the impacts of anomalous propagation on ground clutter measured with horizontal polarization and vertical polarization, respectively; however, no clear difference was found.
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16

Vivekanandan, J., W. C. Lee, E. Loew, J. L. Salazar, V. Grubišić, J. Moore, and P. Tsai. "The next generation airborne polarimetric Doppler weather radar." Geoscientific Instrumentation, Methods and Data Systems Discussions 4, no. 1 (January 20, 2014): 1–42. http://dx.doi.org/10.5194/gid-4-1-2014.

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Abstract. Results from airborne field deployments emphasized the need to obtain concurrently high temporal and spatial resolution measurements of 3-D winds and microphysics. A phased array radar on an airborne platform using dual-polarization antenna has the potential for retrieving high resolution, collocated 3-D winds and microphysical measurements. Recently, ground-based phased array radar (PAR) demonstrated the high time resolution estimation of accurate Doppler velocity and reflectivity of precipitation and clouds when compared to mechanically scanning radar. PAR uses the electronic scanning (e-scan) to rapidly collect radar measurements. Since an airborne radar has a limited amount of time to collect measurements over a specified sample volume, the e-scan will significantly enhance temporal and spatial resolution of airborne radar observations. At present, airborne weather radars use mechanical scan, and they are not designed for collecting dual-polarization measurements to remotely estimate microphysics. This paper presents a possible configuration of a novel Airborne Phased Array Radar (APAR) to be installed on an aircraft for retrieving improved dynamical and microphysical scientific products. The proposed APAR would replace the aging, X-band Electra Doppler radar (ELDORA). The ELDORA X-band radar's penetration into precipitation is limited by attenuation. Since attenuation at C-band is lower than at X-band, the design specification of a C-band airborne phased array radar (APAR) and its measurement accuracies are presented.
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17

Başpınar, Ömer Oğuzhan, Berk Omuz, and Ahmet Öncü. "Detection of the Altitude and On-the-Ground Objects Using 77-GHz FMCW Radar Onboard Small Drones." Drones 7, no. 2 (January 27, 2023): 86. http://dx.doi.org/10.3390/drones7020086.

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Small drones are being utilized by researchers for applications such as object tracking, imaging and remote sensing as they have become more available, inexpensive and mobile with the advancements in sensor and UAV technologies. They can be equipped with sensors such as cameras and radars. Radars can be used onboard for navigation aid by detecting range and velocity, as well as for radar imaging applications. Although they are used in the latter commonly, radars can be used in navigation aid as well since they are barely affected by weather conditions or smoke. FMCW radars are suitable for drones since they can be lightweight and can detect range and velocity. Therefore, an FMCW radar-equipped drone system is designed and implemented for UAV positioning applications. A postprocessing algorithm is developed for detecting the altitude above ground level as well as the amount of reflection coming from the material on the ground surface, and a range compensation method is proposed to improve the performance of the algorithm. The results of a field experiment showed that the radar system and the postprocessing algorithm can be used for drone-based airborne positioning applications. Altitude values obtained with the radar postprocessing are in agreement with the altitude of the drone. Reflections coming from the metal objects are distinguished from those coming from the ground. With the range compensation method, minimum detectable altitude value is improved and the magnitude of ground reflections obtained from different altitudes became similar. The proposed system and algorithm can be utilized in navigation and in landing aid applications.
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18

Uijlenhoet, R., S. H. van der Wielen, and A. Berne. "Uncertainties in rainfall retrievals from ground-based weather radar: overview, case study, and simulation experiment." Hydrology and Earth System Sciences Discussions 3, no. 4 (August 28, 2006): 2385–436. http://dx.doi.org/10.5194/hessd-3-2385-2006.

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Abstract. Because rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We investigate the potential of ground-based weather radar to provide such measurements through a detailed analysis of the associated observation uncertainties. First, a historical perspective on measuring the space-time distribution of rainfall, from the rain gauge to the radar era, is presented. Subsequently, we provide an overview of the various errors and uncertainties affecting radar rainfall retrievals. As an example, we present a case study of the relation between measurements from an operational C-band weather radar and a network of tipping bucket rain gauges as a function of range. Finally, a recently developed stochastic model of range profiles of rainfall microstructure is employed in a simulation experiment designed to investigate the rainfall retrieval uncertainties associated with weather radars operating in different widely used frequency bands.
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19

Torres, Sebastián M., and David A. Warde. "Ground Clutter Mitigation for Weather Radars Using the Autocorrelation Spectral Density." Journal of Atmospheric and Oceanic Technology 31, no. 10 (October 1, 2014): 2049–66. http://dx.doi.org/10.1175/jtech-d-13-00117.1.

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Abstract Radar returns from the ground, known as ground clutter, can contaminate weather signals, often resulting in severely biased meteorological estimates. If not removed, these contaminants may artificially inflate quantitative precipitation estimates and obscure polarimetric and Doppler signatures of weather. A ground-clutter filter is typically employed to mitigate this contamination and provide less biased meteorological-variable estimates. This paper introduces a novel adaptive filter based on the autocorrelation spectral density, which is capable of mitigating the adverse effects of ground clutter without unnecessarily degrading the quality of the meteorological data. The so-called Clutter Environment Analysis using Adaptive Processing (CLEAN-AP) filter adjusts its suppression characteristics in real time to match dynamic atmospheric environments and meets Next Generation Weather Radar (NEXRAD) clutter-suppression requirements.
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20

Narula, Lakshay, Peter Iannucci, and Todd Humphreys. "All-Weather, sub-50-cm, Radar-Inertial Positioning." Field Robotics 2, no. 1 (March 10, 2022): 525–56. http://dx.doi.org/10.55417/fr.2022019.

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Deploying automated ground vehicles beyond the confines of sunny and dry climes will require sub-lane-level positioning techniques that use radio waves, rather than near-visible light radiation. Like human sight, LiDAR and optical cameras perform poorly in low-visibility conditions. We present and demonstrate a novel technique for robust, sub-50-cm, urban ground vehicle positioning based on all-weather sensors. The technique incorporates a computationally-efficient, globally-optimal radar scan registration algorithm within a larger estimation pipeline that fuses data from commercially-available, low-cost, automotive radars, low-cost inertial sensors, vehicle motion constraints, and, when available, precise GNSS measurements. We evaluate the performance of the presented technique on an extensive and realistic urban dataset derived from all-weather sensors. Comparison against ground truth shows that during 60 min of GNSS-denied driving in the urban center of Austin, TX, the technique maintains 95th-percentile errors below 50 cm in horizontal position and 0.5 in heading.
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Nguyen, Cuong M., and V. Chandrasekar. "Gaussian Model Adaptive Processing in Time Domain (GMAP-TD) for Weather Radars." Journal of Atmospheric and Oceanic Technology 30, no. 11 (November 1, 2013): 2571–84. http://dx.doi.org/10.1175/jtech-d-12-00215.1.

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Abstract The Gaussian model adaptive processing in the time domain (GMAP-TD) method for ground clutter suppression and signal spectral moment estimation for weather radars is presented. The technique transforms the clutter component of a weather radar return signal to noise. Additionally, an interpolation procedure has been developed to recover the portion of weather echoes that overlap clutter. It is shown that GMAP-TD improves the performance over the GMAP algorithm that operates in the frequency domain using both signal simulations and experimental observations. Furthermore, GMAP-TD can be directly extended for use with a staggered pulse repetition time (PRT) waveform. A detailed evaluation of GMAP-TD performance and comparison against the GMAP are done using simulated radar data and observations from the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar using uniform and staggered PRT waveform schemes.
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22

Christodoulou, C. I., and S. C. Michaelides. "Statistical and neural classifiers in estimating rain rate from weather radar measurements." Advances in Geosciences 10 (April 26, 2007): 111–15. http://dx.doi.org/10.5194/adgeo-10-111-2007.

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Abstract. Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. Clouds that backscatter more electromagnetic radiation consist of larger droplets of rain and therefore they produce more rain. The idea is to estimate rain rate by using weather radar as an alternative to rain-gauges measuring rainfall on the ground. In an experiment during two days in June and August 1997 over the Italian-Swiss Alps, data from weather radar and surrounding rain-gauges were collected at the same time. The statistical KNN and the neural SOM classifiers were implemented for the classification task using the radar data as input and the rain-gauge measurements as output. The proposed system managed to identify matching pattern waveforms and the rainfall rate on the ground was estimated based on the radar reflectivities with a satisfactory error rate, outperforming the traditional Z/R relationship. It is anticipated that more data, representing a variety of possible meteorological conditions, will lead to improved results. The results in this work show that an estimation of rain rate based on weather radar measurements treated with statistical and neural classifiers is possible.
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Muth, X., M. Schneebeli, and A. Berne. "A sun-tracking method to improve the pointing accuracy of weather radar." Atmospheric Measurement Techniques Discussions 4, no. 4 (August 29, 2011): 5569–95. http://dx.doi.org/10.5194/amtd-4-5569-2011.

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Abstract. Accurate positioning of data collected by a weather radar is of primary importance for their appropriate georeferencing, which in turn makes it possible to combine those with additional sources of information (topography, land cover maps, meteorological simulations from numerical weather models to list a few). This issue is especially acute for mobile radar systems, for which accurate and stable levelling might be difficult to ensure. The sun is a source of microwave radiation, which can be detected by weather radars and used for the accurate positioning of the radar data. This paper presents a technique based on the sun echoes to quantify and hence correct for the instrumental errors which can affect the pointing accuracy of radar antenna. The proposed method is applied to data collected in the Swiss Alps using a mobile X-band radar system. The obtained instrumental bias values are evaluated by comparing the locations of the ground echoes predicted using these bias estimates with the observed ground echo locations. The very good agreement between the two confirms the good accuracy of the proposed method.
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Koistinen, Jarmo, and Heikki Pohjola. "Estimation of Ground-Level Reflectivity Factor in Operational Weather Radar Networks Using VPR-Based Correction Ensembles." Journal of Applied Meteorology and Climatology 53, no. 10 (October 2014): 2394–411. http://dx.doi.org/10.1175/jamc-d-13-0343.1.

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AbstractAn operational method is presented that corrects the bias of radar-based quantitative precipitation estimations (QPE) in radar networks that is due to the vertical profile of reflectivity (VPR) factor. It is used in both rain and snowfall. Measured average VPRs are obtained from the volume scans of each radar at ranges of 2–40 km. At each radar, two time ensembles of the bias estimates are made use of: the first ensemble contains 0–24 members at each range gate, calculated by beam convolution from the measured VPRs at 15-min intervals during the most recent 6 h. The second ensemble similarly contains 24 members calculated from parameterized climatological VPRs. In each scan the precipitation type classification and the climatological VPR are matched with the freezing level obtained from a numerical weather prediction model. The members of the two ensembles are weighted for both time lapse and quality and are then combined. At each composite grid point, the value of the networked VPR correction is then determined as a distance-weighted mean of the time ensembles of biases from all radars located closer than 300 km. In the absence of calibration errors, the resulting estimate of the reflectivity factor at ground level Ze is a seamless continuous field. As verified by radar–radar and radar–gauge comparisons in the Finnish network of eight C-band Doppler radars, the method efficiently reduces the range-dependent bias in QPE. For example, at radar ranges of 141–219 km, the average bias in the ground level Ze was −8.7 and 1.2 dB before and after the VPR correction, respectively.
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25

Meneghini, Robert, and Liang Liao. "On the Equivalence of Dual-Wavelength and Dual-Polarization Equations for Estimation of the Raindrop Size Distribution." Journal of Atmospheric and Oceanic Technology 24, no. 5 (May 1, 2007): 806–20. http://dx.doi.org/10.1175/jtech2005.1.

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Abstract For air- and spaceborne weather radars, which typically operate at frequencies of 10 GHz and above, attenuation correction is usually an essential part of any rain estimation procedure. For ground-based radars, where the maximum range within the precipitation is usually much greater than that from air- or spaceborne radars, attenuation correction becomes increasingly important at frequencies above about 5 GHz. Although dual-polarization radar algorithms rely on the correlation between raindrop shape and size, while dual-wavelength weather radar algorithms rely primarily on non-Rayleigh scattering at the shorter wavelength, the equations for estimating parameters of the drop size distribution (DSD) are nearly identical in the presence of attenuation. Many of the attenuation correction methods that have been proposed can be classified as one of two types: those that employ a kZ (specific attenuation–radar reflectivity factor) relation, and those that use an integral equation formalism where the attenuation is obtained from the DSD parameters at prior gates, either stepping outward from the radar or inward toward the radar from some final range gate. The similarity is shown between the dual-polarization and dual-wavelength equations when either the kZ or the integral equation formulation is used. Differences between the two attenuation correction procedures are illustrated for simulated measurements from an X-band dual-polarization radar.
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26

Billault-Roux, Anne-Claire, Jacopo Grazioli, Julien Delanoë, Susana Jorquera, Nicolas Pauwels, Nicolas Viltard, Audrey Martini, et al. "ICE GENESIS: Synergetic Aircraft and Ground-Based Remote Sensing and In Situ Measurements of Snowfall Microphysical Properties." Bulletin of the American Meteorological Society 104, no. 2 (February 2023): E367—E388. http://dx.doi.org/10.1175/bams-d-21-0184.1.

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Abstract An international field experiment took place in the Swiss Jura in January 2021 as a milestone of the European ICE GENESIS project (www.ice-genesis.eu/), which aims to better measure, understand, and model the ice/snow particle properties and mechanisms responsible for icing of rotor-craft and aircraft. The field campaign was designed to collect observations of clouds and snowfall at a prescribed range of temperatures (−10° to +2°C). The suite of in situ and remote sensing instruments included airborne probes and imagers on board a SAFIRE ATR-42 aircraft, able to sample liquid and ice particles from the micron to the millimeter size range, as well as icing sensors and cameras. Two 95 GHz Doppler cloud radars were installed on the SAFIRE ATR-42, while six Doppler weather radars operating at frequencies ranging from 10 to 95 GHz (and one lidar) were ground based. An operational polarimetric weather radar in nearby France (Montancy) complements the coverage. Finally, observations of standard meteorological variables as well as high-resolution pictures of falling snowflakes from a multiangle snowflake camera were collected at the ground level. The campaign showed its full potential during five (multihourly) flights where precipitation was monitored from cloud to ground. The originality of this campaign resides in the targeted specific temperature range for snowfall and in the synchronization between the ground-based remote sensing and the aircraft trajectories designed to maximize the collection of in situ observations within the column above the radar systems.
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27

Lee, Jeong-Eun, Soohyun Kwon, and Sung-Hwa Jung. "Real-Time Calibration and Monitoring of Radar Reflectivity on Nationwide Dual-Polarization Weather Radar Network." Remote Sensing 13, no. 15 (July 26, 2021): 2936. http://dx.doi.org/10.3390/rs13152936.

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Monitoring calibration bias in reflectivity (ZH) in an operational S-band dual-polarization weather radar is the primary requisite for monitoring and prediction (nowcasting) of severe weather and routine weather forecasting using a weather radar network. For this purpose, we combined methods based on self-consistency (SC), ground clutter (GC) monitoring, and intercomparison to monitor the ZH in real time by complementing the limitations of each method. The absolute calibration bias can be calculated based on the SC between dual-polarimetric observations. Unfortunately, because SC is valid for rain echoes, it is impossible to monitor reflectivity during the non-precipitation period. GC monitoring is an alternative method for monitoring changes in calibration bias regardless of weather conditions. The statistics of GC ZH near radar depend on the changes in radar system status, such as antenna pointing and calibration bias. The change in GC ZH relative to the baseline was defined as the relative calibration adjustment (RCA). The calibration bias was estimated from the change in RCA, which was similar to that estimated from the SC. The ZH in the overlapping volume of adjacent radars was compared to verify the homogeneity of ZH over the radar network after applying the calibration bias estimated from the SC. The mean bias between two radars was approximately 0.0 dB after correcting calibration bias. We can conclude that the combined method makes it possible to use radar measurements, which are immune to calibration bias, and to diagnose malfunctioning radar systems as soon as possible.
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28

Vivekanandan, J., W. C. Lee, E. Loew, J. L. Salazar, V. Grubišić, J. Moore, and P. Tsai. "The next generation airborne polarimetric Doppler weather radar." Geoscientific Instrumentation, Methods and Data Systems 3, no. 2 (July 21, 2014): 111–26. http://dx.doi.org/10.5194/gi-3-111-2014.

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Abstract. Results from airborne field deployments emphasized the need to obtain concurrently high temporal and spatial resolution measurements of 3-D winds and microphysics. A phased array radar on an airborne platform using dual-polarization antenna has the potential for retrieving high-resolution, collocated 3-D winds and microphysical measurements. Recently, ground-based phased array radar (PAR) has demonstrated the high time-resolution estimation of accurate Doppler velocity and reflectivity of precipitation and clouds when compared to mechanically scanning radar. PAR uses the electronic scanning (e-scan) to rapidly collect radar measurements. Since an airborne radar has a limited amount of time to collect measurements over a specified sample volume, the e-scan will significantly enhance temporal and spatial resolution of airborne radar observations. At present, airborne weather radars use mechanical scans, and they are not designed for collecting dual-polarization measurements to remotely estimate microphysics. This paper presents a possible configuration of a novel airborne phased array radar (APAR) to be installed on an aircraft for retrieving improved dynamical and microphysical scientific products. The proposed APAR would replace the aging, X-band Electra Doppler radar (ELDORA). The ELDORA X-band radar's penetration into precipitation is limited by attenuation. Since attenuation at C-band is lower than at X-band, the design specification of a C-band airborne phased array radar (APAR) and its measurement accuracies are presented. Preliminary design specifications suggest the proposed APAR will meet or exceed ELDORA's current sensitivity, spatial resolution and Doppler measurement accuracies of ELDORA and it will also acquire dual-polarization measurements.
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29

Marzano, F. S., M. Lamantea, M. Montopoli, S. Di Fabio, and E. Picciotti. "The Eyjafjöll explosive volcanic eruption from a microwave weather radar perspective." Atmospheric Chemistry and Physics Discussions 11, no. 4 (April 20, 2011): 12367–409. http://dx.doi.org/10.5194/acpd-11-12367-2011.

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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 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 far 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.
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30

Marzano, F. S., M. Lamantea, M. Montopoli, S. Di Fabio, and E. Picciotti. "The Eyjafjöll explosive volcanic eruption from a microwave weather radar perspective." Atmospheric Chemistry and Physics 11, no. 18 (September 16, 2011): 9503–18. http://dx.doi.org/10.5194/acp-11-9503-2011.

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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.
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31

Muth, X., M. Schneebeli, and A. Berne. "A sun-tracking method to improve the pointing accuracy of weather radar." Atmospheric Measurement Techniques 5, no. 3 (March 9, 2012): 547–55. http://dx.doi.org/10.5194/amt-5-547-2012.

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Abstract. Accurate positioning of data collected by a weather radar is of primary importance for their appropriate georeferencing, which in turn makes it possible to combine those with additional sources of information (topography, land cover maps, meteorological simulations from numerical weather models to list a few). This issue is especially acute for mobile radar systems, for which accurate and stable leveling might be difficult to ensure. The sun is a source of microwave radiation, which can be detected by weather radars and used for accurate positioning of radar data. This paper presents a technique based on the similarity between theodolites and radar systems as well as on the sun echoes to quantify and hence correct the instrumental errors which can affect the pointing accuracy of radar antenna. The proposed method is applied to data collected in the Swiss Alps using a mobile X-band radar system. The obtained instrumental bias values are evaluated by comparing the locations of the ground echoes predicted using these bias estimates with the observed ground echo locations. The very good agreement between the two confirms the accuracy of the proposed method.
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32

Ritvanen, Jenna, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois. "Complementarity of wind measurements from co-located X-band weather radar and Doppler lidar." Atmospheric Measurement Techniques 15, no. 21 (November 11, 2022): 6507–19. http://dx.doi.org/10.5194/amt-15-6507-2022.

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Abstract. Accurate wind profile measurements are important for applications ranging from aviation to numerical weather prediction. The spatial pattern of winds can be obtained with ground-based remote sensing instruments, such as weather radars and Doppler lidars. As the return signal in weather radars is mostly due to hydrometeors or insects, and in Doppler lidars due to aerosols, the instruments provide wind measurements in different weather conditions. However, the effect of various weather conditions on the measurement capabilities of these instruments has not been previously extensively quantified. Here we present results from a 7-month measurement campaign that took place in Vantaa, Finland, where a co-located Vaisala WRS400 X-band weather radar and WindCube 400S Doppler lidar were employed continuously to perform wind measurements. Both instruments measured plan position indicator (PPI) scans at 2.0∘ elevation from the horizontal. Direct comparison of radial Doppler velocities from both instruments showed good agreement with R2=0.96. We then examined the effect of horizontal visibility, cloud base height, and precipitation intensity on the measurement availability of each instrument. The Doppler lidar displayed good availability in clear air situations and the X-band radar in precipitation. Both instruments exhibited high availability in clear air conditions in summer when insects were present. The complementary performance in the measurement availability of the two instruments means that their combination substantially increases the spatial coverage of wind observations across a wide range of weather conditions.
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33

Bharadwaj, Nitin, V. Chandrasekar, and Francesc Junyent. "Signal Processing System for the CASA Integrated Project I Radars." Journal of Atmospheric and Oceanic Technology 27, no. 9 (September 1, 2010): 1440–60. http://dx.doi.org/10.1175/2010jtecha1415.1.

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Abstract This paper describes the waveform design space and signal processing system for dual-polarization Doppler weather radar operating at X band. The performance of the waveforms is presented with ground clutter suppression capability and mitigation of range–velocity ambiguity. The operational waveform is designed based on operational requirements and system/hardware requirements. A dual–Pulse Repetition Frequency (PRF) waveform was developed and implemented for the first generation X-band radars deployed by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This paper presents an evaluation of the performance of the waveforms based on simulations and data collected by the first-generation CASA radars during operations.
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34

Matrosov, Sergey Y. "Comparative Evaluation of Snowfall Retrievals from the CloudSat W-band Radar Using Ground-Based Weather Radars." Journal of Atmospheric and Oceanic Technology 36, no. 1 (January 2019): 101–11. http://dx.doi.org/10.1175/jtech-d-18-0069.1.

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AbstractInstantaneous liquid-equivalent snowfall rates S retrieved from CloudSat W-band cloud radar reflectivity Ze measurements are compared to estimates of S from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems when the CloudSat satellite overflew the ground-based radar sites during spatially extensive nimbostratus snowfall events. For these comparisons, the ground-based radar measurements are interpolated to closely match in space and time spaceborne radar resolution volumes above ground clutter, thus avoiding uncertainties in deriving near-surface snowfall rates from measurements aloft by both radar types. Although typical uncertainties of both ground-based and spaceborne snowfall-rate retrieval approaches are quite high, the results from the standard optimal estimation CloudSat 2C-SNOW-PROFILE algorithm are on average in good agreement with the WSR-88D default snowfall algorithm results with correlation coefficients being around 0.8–0.85. The CloudSat standard optimal estimation snowfall-rate products are also shown to be in satisfactory agreement with retrievals from several simple W-band Ze–S relations suggested earlier. The snowfall rate and snow/ice water content (IWC) parameters from the CloudSat 2C-SNOW-PROFILE algorithm are highly interdependent. A tight relation between S and IWC is apparently introduced through the ice particle fall velocity assumption that is made in the reflectivity-based snowfall retrieval algorithm. This suggests that ice sedimentation rate estimates can also be deduced from applications of numerous empirical IWC–reflectivity relations derived previously for different cloud conditions when appropriate assumptions about fall velocities are made. Intercomparisons between different CloudSat snow/ice water content products indicated significant discrepancies in IWC values from different standard CloudSat retrieval algorithms.
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35

Williams, Christopher R., Kenneth S. Gage, Wallace Clark, and Paul Kucera. "Monitoring the Reflectivity Calibration of a Scanning Radar Using a Profiling Radar and a Disdrometer." Journal of Atmospheric and Oceanic Technology 22, no. 7 (July 1, 2005): 1004–18. http://dx.doi.org/10.1175/jtech1759.1.

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Abstract This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998. The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.
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36

Sachidananda, M., and Dusan S. Zrnic. "Ground Clutter Filtering Dual-Polarized, Staggered PRT Sequences." Journal of Atmospheric and Oceanic Technology 23, no. 8 (August 1, 2006): 1114–30. http://dx.doi.org/10.1175/jtech1904.1.

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Abstract A procedure to filter the ground clutter from a dual-polarized, staggered pulse repetition time (PRT) sequence and recover the complex spectral coefficients of the weather signal is presented. While magnitude spectra are sufficient for estimation of the spectral moments from staggered PRT sequences, computation of differential phase in dual-polarized radars requires recovery of the complex spectra. Herein a method is given to recover the complex spectral coefficients after the ground clutter is filtered. Under the condition of “narrow” spectra, it is possible to recover the differential phase, ΦDP, and the copolar correlation coefficient, ρhv, accurately, in addition to the differential reflectivity, ZDR. The technique is tested on simulated time series and on actual radar data. The efficacy of the method is demonstrated on plan position indicator (PPI) plots of polarimetric variables.
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37

Lopez, Philippe. "A 5-yr 40-km-Resolution Global Climatology of Superrefraction for Ground-Based Weather Radars." Journal of Applied Meteorology and Climatology 48, no. 1 (January 1, 2009): 89–110. http://dx.doi.org/10.1175/2008jamc1961.1.

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Abstract The propagation of electromagnetic waves emitted from ground-based meteorological radars is determined by the stratification of the atmosphere. In extreme superrefractive situations characterized by strong temperature inversions or strong vertical gradients of moisture, the radar beam can be deflected toward the ground (ducting or trapping). This phenomenon often results in spurious returned echoes and misinterpretation of radar images such as erroneous precipitation detection. In this work, a 5-yr global climatology of the frequency of superrefractive and ducting conditions and of trapping-layer base height has been produced using refractivity computations from ECMWF temperature, moisture, and pressure analyses at a 40-km horizontal resolution. The aim of this climatology is to better document how frequent such events are, which is a prerequisite for fully benefiting from radar data information for the multiple purposes of model validation, precipitation analysis, and data assimilation. First, the main climatological features are summarized for the whole globe: high- and midlatitude oceans seldom experience superrefraction or ducting whereas tropical oceans are strongly affected, especially in regions where the trade wind inversion is intense and lying near the surface. Over land, seasonal averages of superrefraction (ducting) frequencies reach 80% (40%) over tropical moist areas year-round but remain below 40% (15%) in most other regions. A particular focus is then laid on Europe and the United States, where extensive precipitation radar networks already exist. Seasonal statistics exhibit a pronounced diurnal cycle of ducting occurrences, with averaged frequencies peaking at 60% in summer late afternoon over the eastern half of the United States, the Balkans, and the Po Valley but no ducts by midday. Similarly high ducting frequencies are found over the southwestern coast of the United States at night. A potentially strong reduction of ducting occurrences with increased radar height (especially in midlatitude summer late afternoon) is evidenced by initiating refractivity vertical gradient computations from either the lowest or the second lowest model level. However, installing radar on tall towers also brings other problems, such as a possible amplification of sidelobe clutter echoes.
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38

Snyder, Jeffrey C., Howard B. Bluestein, Zachary B. Wienhoff, Charles M. Kuster, and Dylan W. Reif. "An Analysis of an Ostensible Anticyclonic Tornado from 9 May 2016 Using High-Resolution, Rapid-Scan Radar Data." Weather and Forecasting 35, no. 5 (October 1, 2020): 1685–712. http://dx.doi.org/10.1175/waf-d-20-0055.1.

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AbstractTornadic supercells moved across parts of Oklahoma on the afternoon and evening of 9 May 2016. One such supercell, while producing a long-lived tornado, was observed by nearby WSR-88D radars to contain a strong anticyclonic velocity couplet on the lowest elevation angle. This couplet was located in a very atypical position relative to the ongoing cyclonic tornado and to the supercell’s updraft. A storm survey team identified damage near where this couplet occurred, and, in the absence of evidence refuting otherwise, the damage was thought to have been produced by an anticyclonic tornado. However, such a tornado was not seen in near-ground, high-resolution radar data from a much closer, rapid-scan, mobile radar. Rather, an elongated velocity couplet was observed only at higher elevation angles at altitudes similar to those at which the WSR-88D radars observed the strong couplet. This paper examines observations from two WSR-88D radars and a mobile radar from which it is argued that the anticyclonic couplet (and a similar one ~10 min later) were actually quasi-horizontal vortices centered ~1–1.5 km AGL. The benefits of having data from a radar much closer to the convective storm being sampled (e.g., better spatial resolution and near-ground data coverage) and providing more rapid volume updates are readily apparent. An analysis of these additional radar data provides strong, but not irrefutable, evidence that the anticyclonic tornado that may be inferred from WSR-88D data did not exist; consequently, upon discussions with the National Weather Service, it was not included in Storm Data.
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39

Kim, Ji-Hye, Mi-Lim Ou, Jun-Dong Park, Kenneth R. Morris, Mathew R. Schwaller, and David B. Wolff. "Global Precipitation Measurement (GPM) Ground Validation (GV) Prototype in the Korean Peninsula." Journal of Atmospheric and Oceanic Technology 31, no. 9 (September 1, 2014): 1902–21. http://dx.doi.org/10.1175/jtech-d-13-00193.1.

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Abstract Since 2009, the Korea Meteorological Administration (KMA) has participated in ground validation (GV) projects through international partnerships within the framework of the Global Precipitation Measurement (GPM) Mission. The goal of this work is to assess the reliability of ground-based measurements in the Korean Peninsula as a means for validating precipitation products retrieved from satellite microwave sensors, with an emphasis on East Asian precipitation. KMA has a well-developed operational weather service infrastructure composed of meteorological radars, a dense rain gauge network, and automated weather stations. Measurements from these systems, including data from four ground-based radars (GRs), were combined with satellite data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and used as a proxy for GPM GV over the Korean Peninsula. A time series of mean reflectivity differences (GR − PR) for stratiform-only and above-brightband-only data showed that the time-averaged difference fell between −2.0 and +1.0 dBZ for the four GRs used in this study. Site-specific adjustments for these relative mean biases were applied to GR reflectivities, and detailed statistical comparisons of reflectivity and rain rate between PR and bias-adjusted GR were carried out. In rain-rate comparisons, surface rain from the TRMM Microwave Imager (TMI) and the rain gauges were added and the results varied according to rain type. Bias correction has had a positive effect on GR rain rate comparing with PR and gauge rain rates. This study confirmed advance preparation for GPM GV system was optimized on the Korean Peninsula using the official framework.
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40

Ferretti, R., K. De Sanctis, L. Molini, A. Parodi, M. Montopoli, F. S. Marzano, and F. Siccardi. "Investigating the sensitivity of high-resolution mesoscale models to microphysical parameters by the use of polarimetric radar observations." Atmospheric Chemistry and Physics Discussions 10, no. 8 (August 27, 2010): 20461–514. http://dx.doi.org/10.5194/acpd-10-20461-2010.

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Abstract. An improved methodology for investigating mesoscale model microphysics is presented and discussed for a case study. Polarimetric radar data are used to assess numerical weather prediction (NWP) model's skill in reproducing the microphysical features of severe rainfall. To this aim, an event of deep convection, developed on 20 May 2003 in the Po Valley (Italy), is analyzed. During the selected case study, two weather radars, sited in Gattatico and San Pietro Capofiume (near Bologna, Italy), detected a deep-convective and hail cell with a large inner graupel core which reached the ground, as was reported by local weather authorities and citizens. A hydrometeor classification algorithm, based on a Bayesian approach and a radar simulator model, are used to retrieve the vertical structure of the storm and characterize its ground effects. These products are used for evaluating the sensitivity of NWP models with respect to the graupel density, described in terms of the intercept parameter of the graupel size distribution and its depositional velocity. To this purpose two mesoscale NWP models, specifically COSMO-LAMI and MM5-V3, are used at high spatial resolution. Their ability in reproducing the vertical and the horizontal structure and the microphysical distribution of the major convective cell is evaluated. Both models show large sensitivity to different microphysical settings and a capability to reproduce fairly well the observed hail cell. Ground-radar reflectivity fields and the hydrometeor vertical structure are correctly simulated by both NWP models as opposed to a failure in reproducing the graupel distribution near the ground.
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41

Vaccarono, Mattia, Renzo Bechini, Chandra V. Chandrasekar, Roberto Cremonini, and Claudio Cassardo. "An integrated approach to monitoring the calibration stability of operational dual-polarization radars." Atmospheric Measurement Techniques 9, no. 11 (November 8, 2016): 5367–83. http://dx.doi.org/10.5194/amt-9-5367-2016.

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Abstract. The stability of weather radar calibration is a mandatory aspect for quantitative applications, such as rainfall estimation, short-term weather prediction and initialization of numerical atmospheric and hydrological models. Over the years, calibration monitoring techniques based on external sources have been developed, specifically calibration using the Sun and calibration based on ground clutter returns. In this paper, these two techniques are integrated and complemented with a self-consistency procedure and an intercalibration technique. The aim of the integrated approach is to implement a robust method for online monitoring, able to detect significant changes in the radar calibration. The physical consistency of polarimetric radar observables is exploited using the self-consistency approach, based on the expected correspondence between dual-polarization power and phase measurements in rain. This technique allows a reference absolute value to be provided for the radar calibration, from which eventual deviations may be detected using the other procedures. In particular, the ground clutter calibration is implemented on both polarization channels (horizontal and vertical) for each radar scan, allowing the polarimetric variables to be monitored and hardware failures to promptly be recognized. The Sun calibration allows monitoring the calibration and sensitivity of the radar receiver, in addition to the antenna pointing accuracy. It is applied using observations collected during the standard operational scans but requires long integration times (several days) in order to accumulate a sufficient amount of useful data. Finally, an intercalibration technique is developed and performed to compare colocated measurements collected in rain by two radars in overlapping regions. The integrated approach is performed on the C-band weather radar network in northwestern Italy, during July–October 2014. The set of methods considered appears suitable to establish an online tool to monitor the stability of the radar calibration with an accuracy of about 2 dB. This is considered adequate to automatically detect any unexpected change in the radar system requiring further data analysis or on-site measurements.
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42

Qi, Youcun, Jian Zhang, Qing Cao, Yang Hong, and Xiao-Ming Hu. "Correction of Radar QPE Errors for Nonuniform VPRs in Mesoscale Convective Systems Using TRMM Observations." Journal of Hydrometeorology 14, no. 5 (October 1, 2013): 1672–82. http://dx.doi.org/10.1175/jhm-d-12-0165.1.

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Abstract Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.
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43

Petracca, M., L. P. D’Adderio, F. Porcù, G. Vulpiani, S. Sebastianelli, and S. Puca. "Validation of GPM Dual-Frequency Precipitation Radar (DPR) Rainfall Products over Italy." Journal of Hydrometeorology 19, no. 5 (May 1, 2018): 907–25. http://dx.doi.org/10.1175/jhm-d-17-0144.1.

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Abstract The Ka–Ku Dual-Frequency Precipitation Radar (DPR) and the Microwave Imager on board the Global Precipitation Measurement (GPM) mission core satellite have been collecting data for more than 3 years, providing precipitation products over the globe, including oceans and remote areas where ground-based precipitation measurements are not available. The main objective of this work is to validate the GPM-DPR products over a key climatic region with complex orography such as the Italian territory. The performances of the DPR precipitation rate products are evaluated over an 18-month period (July 2015–December 2016) using both radar and rain gauge data. The ground reference network is composed of 22 weather radars and more than 3000 rain gauges. DPR dual-frequency products generally show better performance with respect to the single-frequency (i.e., Ka- or Ku-band only) products, especially when ground radar data are taken as reference. A sensitivity analysis with respect to season and rainfall intensity is also carried out. It was found that the normal scan (NS) product outperforms the high-sensitivity scan (HS) and matched scan (MS) during the summer season. A deeper analysis is carried out to investigate the larger discrepancies between the DPR-NS product and ground reference data. The most relevant improvement of the DPR products’ performance was found by limiting the comparison to the upscaled radar data with a higher quality index. The resulting scores in comparison with ground radars are mean error (ME) = −0.44 mm h−1, RMSE = 3.57 mm h−1, and fractional standard error (FSE) = 142%, with the POD = 65% and FAR = 1% for rainfall above 0.5 mm h−1.
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44

Rahimi, A. R., A. R. Holt, G. J. G. Upton, S. Krämer, A. Redder, and H.-R. Verworn. "Attenuation Calibration of an X-Band Weather Radar Using a Microwave Link." Journal of Atmospheric and Oceanic Technology 23, no. 3 (March 1, 2006): 395–405. http://dx.doi.org/10.1175/jtech1855.1.

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Abstract The attenuation of a radar signal is a serious problem facing meteorologists and hydrologists. In heavy rain, reflectivity information can be completely lost from large portions of a radar scan. The problem is particularly acute for X-band radars. Current methods of correcting for attenuation face many difficulties, mainly because the actual amount of attenuation at any given time is unknown. In this paper a backward-iterative attenuation-correction algorithm is presented that uses the attenuation measured by a microwave link with its receiver collocated with an X-band weather radar in Essen, Germany. Data are also available from a network of rain gauges located in the vicinity of the link path. This network provides a measure of “ground truth” rainfall against which radar estimates can be compared. The results show that the algorithm can recover much of the reflectivity information that is lost due to attenuation of the radar beam. The method is seen to be particularly effective in convective conditions where heavy rainfall can cause severe attenuation.
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45

Peters, Gerhard, Bernd Fischer, Hans Münster, Marco Clemens, and Andreas Wagner. "Profiles of Raindrop Size Distributions as Retrieved by Microrain Radars." Journal of Applied Meteorology 44, no. 12 (December 1, 2005): 1930–49. http://dx.doi.org/10.1175/jam2316.1.

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Abstract Data of vertically pointing microrain radars (MRRs), located at various sites around the Baltic Sea, were analyzed for a period of several years. From the Doppler spectra profiles of drop size distributions (DSDs) are obtained. A significant height dependence of the shape of the DSDs—and thus of the Z–R relations—is observed at high rain rates. This implies, for the considered sites, that ground-based Z–R relations lead to underestimation of high rain rates by weather radars.
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46

Ivić, Igor R., Christopher Curtis, and Sebastián M. Torres. "Radial-Based Noise Power Estimation for Weather Radars." Journal of Atmospheric and Oceanic Technology 30, no. 12 (December 1, 2013): 2737–53. http://dx.doi.org/10.1175/jtech-d-13-00008.1.

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Abstract A radar antenna intercepts thermal radiation from various sources including the ground, the sun, the sky, precipitation, and man-made radiators. In the radar receiver, this external radiation produces noise that constructively adds to the receiver internal noise and results in the overall system noise. Consequently, the system noise power is dependent on the antenna position and needs to be estimated accurately. Inaccurate noise power measurements may lead to reduction of coverage if the noise power is overestimated or to radar data images cluttered by noise speckles if the noise power is underestimated. Moreover, when an erroneous noise power is used at low-to-moderate signal-to-noise ratios, estimators can produce biased meteorological variables. Therefore, to obtain the best quality of radar products, it is desirable to compute meteorological variables using the noise power measured at each antenna position. In this paper, an effective method is proposed to estimate the noise power in real time from measured powers at each radial. The technique uses a set of criteria to detect radar range resolution volumes that do not contain weather signals and uses those to estimate the noise power. The algorithm is evaluated using both simulated and real time series data; results show that the proposed technique accurately produces estimates of the system noise power. An operational implementation of this technique is expected to significantly improve the quality of weather radar products with a relatively small computational burden.
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47

Matrosov, Sergey Y. "A Method to Estimate Vertically Integrated Amounts of Cloud Ice and Liquid and Mean Rain Rate in Stratiform Precipitation from Radar and Auxiliary Data." Journal of Applied Meteorology and Climatology 48, no. 7 (July 1, 2009): 1398–410. http://dx.doi.org/10.1175/2009jamc2106.1.

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Abstract A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.
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48

Uijlenhoet, R., and A. Berne. "Stochastic simulation experiment to assess radar rainfall retrieval uncertainties associated with attenuation and its correction." Hydrology and Earth System Sciences 12, no. 2 (March 19, 2008): 587–601. http://dx.doi.org/10.5194/hess-12-587-2008.

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Abstract. As rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We investigate the potential of ground-based weather radar to provide such measurements through a theoretical analysis of some of the associated observation uncertainties. A stochastic model of range profiles of raindrop size distributions is employed in a Monte Carlo simulation experiment to investigate the rainfall retrieval uncertainties associated with weather radars operating at X-, C-, and S-band. We focus in particular on the errors and uncertainties associated with rain-induced signal attenuation and its correction for incoherent, non-polarimetric, single-frequency, operational weather radars. The performance of two attenuation correction schemes, the (forward) Hitschfeld-Bordan algorithm and the (backward) Marzoug-Amayenc algorithm, is analyzed for both moderate (assuming a 50 km path length) and intense Mediterranean rainfall (for a 30 km path). A comparison shows that the backward correction algorithm is more stable and accurate than the forward algorithm (with a bias in the order of a few percent for the former, compared to tens of percent for the latter), provided reliable estimates of the total path-integrated attenuation are available. Moreover, the bias and root mean square error associated with each algorithm are quantified as a function of path-averaged rain rate and distance from the radar in order to provide a plausible order of magnitude for the uncertainty in radar-retrieved rain rates for hydrological applications.
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49

Reeves, Heather Dawn, and Jacqueline Waters. "Dual-Polarized Radar Coverage in Terminal Airspaces and Its Effect on Interpretation of Winter Weather Signatures: Current Capabilities and Future Recommendations." Journal of Applied Meteorology and Climatology 58, no. 1 (January 2019): 165–83. http://dx.doi.org/10.1175/jamc-d-18-0123.1.

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AbstractThis is a feasibility study on the use of dual-polarized radars to infer icing in terminal airspaces (TASs) of commercial airports. The amount and quality of radar coverage in each TAS is quantified as a function of its location, traffic, and vulnerability to icing. No airport has 100% of the TAS covered, but most high-traffic or high-icing airports have comparatively good coverage (between 70% and 90%). A common occurrence during icing is anomalous propagation as 79% of events had an inversion within the TAS. This leads to overestimates in the elevations of icing layers and can cause significant ground-clutter contamination, which can overwhelm the echo produced by precipitation. The effects of beam broadening were also considered. Typical dendrite growth and melting layers can only be resolved in part of the TAS part of the time, or not at all, as these layers are often shallower than the radar beam. Because most airports have coverage from multiple radars, use of a three-dimensional mosaic was investigated. This allows for an increase in the TAS coverage (generally between 5% and 15%) and partly mitigates some of the resolution issues, but the maxima within individual layers are somewhat reduced in the interpolation process. A series of recommendations is made to address the concerns raised by this investigation. These include using only icing tops (not bottoms) to identify areas of icing, use of data mining to retrieve precipitation echo in the presence of ground clutter, and including the beamwidth in radar mosaics.
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50

Lee, Yoonjin, Christian D. Kummerow, and Milija Zupanski. "Latent heating profiles from GOES-16 and its impacts on precipitation forecasts." Atmospheric Measurement Techniques 15, no. 23 (December 12, 2022): 7119–36. http://dx.doi.org/10.5194/amt-15-7119-2022.

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Abstract. Latent heating (LH) is an important factor in both weather forecasting and climate analysis, being the essential factor affecting both the intensity and structure of convective systems. Yet, inferring LH rates from our current observing systems is challenging at best. For climate studies, LH has been retrieved from the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM) using model simulations in a lookup table (LUT) that relates instantaneous radar data to corresponding heating profiles. These radars, first on TRMM and then the Global Precipitation Measurement Mission (GPM), provide a continuous record of LH. However, the temporal resolution is too coarse to have significant impacts on forecast models. In operational forecast models such as High-Resolution Rapid Refresh (HRRR), convection is initiated from LH derived from ground-based radars. Despite the high spatial and temporal resolution of ground-based radars, their data are only available over well-observed land areas. This study develops a method to derive LH from the Geostationary Operational Environmental Satellite-16 (GOES-16) in near-real time. Even though the visible and infrared channels on the Advanced Baseline Imager (ABI) provide mostly cloud top information, rapid changes in cloud top visible and infrared properties, when formulated as an LUT similar to those used by the TRMM and GPM radars, can successfully be used to derive LH profiles for convective regions based on model simulations with a convective classification scheme and channel 14 (11.2 µm) brightness temperatures. Convective regions detected by GOES-16 are assigned LH profiles from a predefined LUT, and they are compared with LH used by the HRRR model and one of the dual-frequency precipitation radar (DPR) products, the Goddard convective–stratiform heating (CSH). LH obtained from GOES-16 shows similar magnitude to LH derived from the Next Generation Weather Radar (NEXRAD) and CSH, and the vertical distribution of LH is also very similar with CSH. A three-month analysis of total LH from convective clouds from GOES-16 and NEXRAD shows good correlation between the two products. Finally, LH profiles from GOES-16 and NEXRAD are applied to WRF simulations for convective initiation, and their results are compared to investigate their impacts on precipitation forecasts. Results show that LH from GOES-16 has similar impacts to NEXRAD in terms of improving the forecast. While only a proof of concept, this study demonstrates the potential of using LH derived from GOES-16 for convective initialization.
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