A procedure to calibrate multiparameter weather radar using properties of the rain medium

Gorgucci, E.; Scarchilli, G.; Chandrasekar, V.

doi:10.1109/36.739161

Cited by 116 publications

(79 citation statements)

References 11 publications

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“…During light precipitation and in the absence of strong winds, the vertical and horizontal return signals of a vertically oriented beam should be the same. Differences between the horizontal and vertical channels may appear due to poor calibration between the channels, random effects, beam-filling, or side-lobe clutter contamination, among other factors (Gorgucci et al, 1999). Although standard calibration was performed, careful examination of the ZDR behaviour before and after the calibration was necessary.…”

Section: Methodsmentioning

confidence: 99%

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

et al. 2018

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Abstract. This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the massweighted mean diameter) were quantified over both seasons.The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only durPublished by Copernicus Publications on behalf of the European Geosciences Union. L. A. T. Machado et al.: Overview: Precipitation characteristics and sensitivities to environmental conditionsing the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

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Section: Methodsmentioning

confidence: 99%

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

et al. 2018

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“…During light precipitation and in the absence of strong winds, the vertical and horizontal returned signal of a vertically-oriented beam should be the same. Differences between 25 the Horizontal-channels and Vertical-channels may appear due to poor calibration between the channels, random effects, beamfilling, or side-lobe clutter contamination, among other factors (Gorgucci et al, 1999). Although the standard calibration was performed, careful examination of the ZDR behaviour before and after these changes was necessary.…”

Section: Data and Methodology 30mentioning

confidence: 99%

Overview: Precipitation Characteristics and Sensitivities to the Environmental Conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

Machado¹,

Calheiros²,

Biscaro³

et al. 2017

Preprint

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Abstract. This is study provides an overview of precipitation processes and their sensitivities to environmental conditions, in the Central Amazon Basin, during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Taking advantage of the numerous measuring platforms and instruments systems operating during both campaigns sampling cloud structure and 30 environmental conditions during 2014 and 2015, the rainfall variability among seasons, aerosol loading, land surface type, and topography have carefully been characterized. Differences between the wet and dry seasons were examined from a variety of different perspectives. The rain rate distribution, the total amount of rainfall, and the raindrop size distribution (the mean massweighted diameter) were quantified for the two seasons. The dry season has a higher average rain rate than the wet season and reflects more intense rain. While the cumulative wet season rainfall amount was four times larger than the total dry season 35 rainfall, reflecting in large total rainfall accumulation. The typical size and life cycle of the Amazon cloud clusters (observed Atmos. Chem. Phys. Discuss., https://doi.org/10. 5194/acp-2017-990 Manuscript under review for journal Atmos. Chem. Phys. Discussion started: 1 November 2017 c Author(s) 2017. CC BY 4.0 License.2 by satellite) and rain cells (observed by radar) were examined, as well their differences among the seasons. Moreover, we analyse the monthly mean thermodynamical and dynamical variables, measured by radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to the atmospheric aerosol loading is discussed with regard to the mean mass-weighted diameter and rain rate. This topic was evaluated during the wet season only due to the insignificant statistics of rainfall events for different ranges of aerosol loadings and the low frequency of precipitation events 5 during the dry season. The aerosol impacts on the cloud droplet diameter is different for small and large drops. For the wet season, we observe no dependence on land surface type on the rain rate. However, during the dry season, urban areas exhibit the largest rain rate tail distribution, and deforested regions have the lowest mean rain rate. Airplane measurements were performed to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. The vertical motion turned out to be uncorrelated with cloud droplet sizes, but the cloud droplets number concentration revealed a 10 linear relationship to the vertical motion. Clouds over forest exhibit larger droplets than clouds over pastures at all cloud levels.Finally, the connections between topography and rain rate were evaluated, showing a higher rain rate over higher elevations for the dry season. 1.Introduction 15 -The Amazon Forest ClimateThe Amazon Forest is a huge area spanning more than 3,000 km in the east-west direction and approximately 2,000 km from north to south. The equator crosses the region, ...

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“…Z DR bias correction is important for the absolute calibration of the radar using a self-consistency method. Gorgucci et al (1999) using a vertical pointing scan of light rain to take advantage of the nearly spherical shape of the raindrops as seen from below. Ryzhkov et al (2005) used the elevation angle dependency of Z DR as an alternative technique and concluded that the high variability of Z DR in rainfall prohibited the method from achieving the required absolute calibration accuracy of 0.2 dB.…”

Section: Z and Z Dr Bias Correction For Bslmentioning

confidence: 99%

“…Polarimetric radar (DPOL) provides a new method for the absolute calibration of reflectivity, which has been a longstanding problem with single polarization radar data. The method is based on the assumptions that Z, differential reflectivity (Z DR ), and specific differential phase (K DP ) are independent of each other and that Z can be estimated from Z DR and K DP , which are insensitive to radar miscalibration (Gorgucci et al, 1992(Gorgucci et al, , 1999Goddard et al, 1994;Scarchilli et al, 1996;Vivekanandan et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Approaches to radar reflectivity bias correction to improve rainfall estimation in Korea

et al. 2016

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Abstract. Three methods for determining the reflectivity bias of single polarization radar using dual polarization radar reflectivity and disdrometer data (i.e., the equidistance line, overlapping area, and disdrometer methods) are proposed and evaluated for two low-pressure rainfall events that occurred over the Korean Peninsula on 25 August 2014 and 8 September 2012. Single polarization radar reflectivity was underestimated by more than 12 and 7 dB in the two rain events, respectively. All methods improved the accuracy of rainfall estimation, except for one case where drop size distributions were not observed, as the precipitation system did not pass through the disdrometer location. The use of these bias correction methods reduced the RMSE by as much as 50 %. Overall, the most accurate rainfall estimates were obtained using the overlapping area method to correct radar reflectivity.

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A procedure to calibrate multiparameter weather radar using properties of the rain medium

Cited by 116 publications

References 11 publications

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

Overview: Precipitation Characteristics and Sensitivities to the Environmental Conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

Approaches to radar reflectivity bias correction to improve rainfall estimation in Korea

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