Comparison of S-Band Radar Attenuation Prediction With Beacon Measurements

Yeo, Jun Xiang; Lee, Yee Hui; Kumar, Lakshmi Sutha; Ong, Jin

doi:10.1109/tap.2012.2207346

Cited by 13 publications

(11 citation statements)

References 28 publications

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“…[11] presents the relationship between reflectivity and all parameters and coefficients in all data in all places and all times of precipitation, respectively. However, previous studies have determined the relationship between reflectivity and rainfall amount based on power regression [3,4,14,17,24,25,27,[31][32][33][34]. But, it is possible that the relationship could be manifested in other matrix form such as; logarithmic or exponential regression.…”

Section: Calibration Processmentioning

confidence: 99%

“…More than 100 relationships are available for different rainfall forms such as strait form, tropical, convective, thunderstorm, shower, monsoon and hurricanes [9]. The sensitivity variation of Z-R relationships are the main uncertainty sources [17], especially in rainfall calculation based on drop size distribution (DSD). Because of radar measurements carry many uncertainty sources depending on dissimilarities of radar reflectivity in the atmosphere; radar calibration is unavoidable, in order to estimate the amount of rainfall precisely [18,19].…”

Section: Introductionmentioning

confidence: 99%

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An improved algorithm in unipolar weather radar calibration for rainfall estimation

Nikahd

Hashim

Nazemosadat

2016

Innov. Infrastruct. Solut.

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Weather unipolar ground-based radar estimation can experience momentous changes by using other effective parameters such as distance from radar, altitudes and rainfall time duration that directly compromise the accuracy of the hydrometeorology applications. These radar measurements however, need to be calibrated for more accurate rainfall estimation. In addition to the radar-rainfall (Z-R) relationship, this is a pragmatic approach based on careful analyses of other parameters. This article introduces a new calibration approach using altitude parameters and time-stepwise processing of reflectivityrainfall (Z-R) rate relationship. This research leads to introduce a new effective parameter and generate two new empirical coefficients in radar-rainfall relationship. Two consecutive years unipolar ground-based radar data sets with 190 occurrences of rainfall from 43 stations in calibration window of 3 h; and the corresponding rainfall measured from registered rain gauges were used in this study. The results indicated that radar-rainfall relationship Z ¼ AR b is better improvised with altitudes effect (H) and empirical coefficient (c), such that Z ¼ AR b H c . It therefore is concluded that the use of other effective parameters (distance from radar, altitudes and rainfall time duration) leads to optimum accuracy of Z-R relationship.

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Section: Calibration Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An improved algorithm in unipolar weather radar calibration for rainfall estimation

Nikahd

Hashim

Nazemosadat

2016

Innov. Infrastruct. Solut.

View full text Add to dashboard Cite

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“…Table 3 shows the parameters of selected Z-R relations. Yeo et al (2012) had identified that the root mean square (RMS) error between beacon measurements and radar-estimated attenuation using the Z-R relation proposed by Kumar et al (2011) is the smallest compared to that of others. Due to climatic similarity and the short distance of about 200 km between Singapore and our location of interest (Kuala Lumpur), the Z-R relation proposed by Kumar et al (2011) is adopted in this analysis.…”

Section: Selection Of Z-r Relationmentioning

confidence: 99%

Estimating tropical rain attenuation on the Earth-satellite path using radar data

Badron

Ismail

Ismail³

2015

International Journal of Remote Sensing

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Radar-return echoes, known as 'reflectivity', are exploited in the course of estimating rain attenuation along a slant path. Relevant radar gates or 'range bins' are identified to correlate a specific satellite path. The reflectivity value of each range bin is converted to rainfall rate using established radar reflectivity values -rainfall rates, (Z-R relation). Specific attenuation is then derived for all associated range bins. The attenuation for each bin is the product of specific attenuation and its effective path length. The summation of attenuation endured by all range bins is inferred as the attenuation along the slant path. In this study, an X-band slant path rain attenuation was estimated using 2.85 GHz (S-band) Terminal Doppler Weather Radar (TDWR) data. A technique to estimate rain attenuation by exploitation of radar information is elaborated in this article. Comparisons between the radar-derived attenuation estimations and actual satellite signal measurements are also presented. The findings were verified by comparing the generated values to the directly measured rain attenuation from the Razak satellite (RazakSAT). Radar reflectivity data were obtained from Kuala Lumpur International Airport (KLIA) radar station operated by the Malaysian Meteorology Department (MMD). Preliminary findings using the most recent Z-R relation (i.e. the generated radar-derived rain attenuation estimations) appear to show lower values than the actual measurements.

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“…More than 100 relationships are available for different rainfall form such as strait form, tropical, convective, thunderstorm, shower, monsoon and hurricanes [7]. The sensitivity variation of Z-R relationships are the main uncertainty sources [13], especially in rainfall calculation based on DSD. Because of radar measurements carry many uncertainty sources depending on dissimilarities of radar reflectivity in the atmosphere; Radar calibration is unavoidable to estimate the amount of rainfall precisely [14].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2018

ETOAJ

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Unipolar ground-based weather radar has been a widely-used instrument for rainfall measurement. These radar measurements however need to be calibrated for more accurate rainfall estimation. This article introduces a new calibration approach using time-stepwise processing of reflectivity-rainfall rate (Z-R) relationship. Based on previous work utilizing the radar-rainfall relationship; this article hypothesizes that the rainfall measurement from ground based radar are affected by distance from radar, altitudes and rainfall time duration. Two consecutive years unipolar ground-based radar data sets with 77 occurrences of rainfall from 39 stations in calibration window of three hours; and the corresponding rainfall measured from registered rain gauges were used in this study. The results indicated that radar-rainfall relationship Z=aR b is better improvise with altitudes effect (H) and empirical coefficient (c), such that (Z=aR b H c ). The changes in 'distance from the radar' and 'duration of precipitation' were evidently significant. For radar-rainfall relationship individually (R 2 =min88, max97) with altitude effect (H) in relationship (R 2 =min70, max97). It is therefore concluded that the use of other effective parameters (distance from radar, altitudes and rainfall time duration) leads to optimum accuracy of Z-R relationship.

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Comparison of S-Band Radar Attenuation Prediction With Beacon Measurements

Cited by 13 publications

References 28 publications

An improved algorithm in unipolar weather radar calibration for rainfall estimation

An improved algorithm in unipolar weather radar calibration for rainfall estimation

Estimating tropical rain attenuation on the Earth-satellite path using radar data

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