TRMM PR Standard Algorithm 2A23 and its Performance on Bright Band Detection

Awaka, Jun; Iguchi, Toshio; Okamoto, Ken‐ichi

doi:10.2151/jmsj.87a.31

Cited by 135 publications

(123 citation statements)

References 20 publications

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“…The heights of both freezing level and BB rose again in regions near 37 • S. These discrepancies and unexpected increases in height may be attributed to the limited sample size. Since the detection of BB is done within a search window whose center was about 0.5 km below the freezing level, and just exactly the freezing level for GPM DPR and TRMM PR, respectively [26,40], the trend for the distribution curves of averaged BB height of the two radars corresponded well with those curves of averaged freezing level height. However, around 25 • N, speaking of GPM DPR, the curve of averaged BB height was higher than that of averaged freezing level height.…”

Section: Latitudinal Distribution Analysismentioning

confidence: 93%

“…Two single-band algorithms, the vertical profile method (V-method) [47] and the horizontal pattern method (H-method) [48], have been established in TRMM PR to distinguish rain types, according to these differences [35,39,40]. Details can be found in [26,41,43,47]. The type "other" means there is only cloud (ice) and/or maybe the signal is simply noise [41].…”

Section: Trmm Prmentioning

confidence: 99%

“…We used 2A23 and 2ADPR datasets to draw maps of the distribution of average BB height and the average height of freezing level, which is closely related to the BB (Figures 5 and 6) because BB is detected in a search window with the freezing level at its center [26,40]. In general, GPM DPR gives slightly higher estimates of the freezing level height in tropical regions, and lower estimates in the middle latitudes compared with TRMM PR.…”

Section: Global Distribution Of Freezing Level and Bb Heightsmentioning

confidence: 99%

See 2 more Smart Citations

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

2017

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Spaceborne precipitation radars are powerful tools used to acquire adequate and highquality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM) mission, which deployed the first spaceborne Ka-and Ku-dual frequency radar (DPR), was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM). This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR's improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h) detected by GPM DPR are~1.7 and~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku) and single frequency (Ku) methods performed similarly. In both inner (the central 25 beams) and outer swaths (1-12 beams and 38-49 beams) of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type "other" from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02%) of stratiform (convective) precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB) height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne radar precipitation retrievals and benefit hydrological and meteorological research.

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Section: Latitudinal Distribution Analysismentioning

confidence: 93%

Section: Trmm Prmentioning

confidence: 99%

Section: Global Distribution Of Freezing Level and Bb Heightsmentioning

confidence: 99%

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Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

2017

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“…Since the rain-type classification algorithm is based on the spatial distribution of radar reflectivity factors, rain classification should not change as a result of sensitivity degradation. Awaka et al (2009) reported that the percentage of the convective count remains almost the same after the boost. Therefore, we do not need to worry about changes in the rain estimates due to changes in rain-type classification caused by sensitivity degradation.…”

Section: Sensitivity Degradationmentioning

confidence: 96%

Evaluation of the Effects of the Orbit Boost of the TRMM Satellite on PR Rain Estimates

Shimizu

Oki

Tagawa

et al. 2009

Journal of the Meteorological Society of Japan

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The Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite, which was launched on 28 November 1997, has been collecting global rainfall data for more than 10 years. The monthly estmated-surface rainfall (e_SurfRain) amounts estimated by PR have decreased on average since the satellite altitude was changed from 350 km to 402.5 km in August 2001 to extend its lifetime. There is no significant decrease in e_SurfRain in the five angle bins around the nadir (near-nadir) or in rainfall amounts at a 2-km height. The major causes of the changes in rain estimates due to the orbit boost are (1) sensitivity degradation, owing to the increase of satellite altitude, (2) an increase in the range of surface clutter owing to the increase in the footprint size, and (3) a mismatch between the transmission and reception angles of adjacent radar beams for one in every 32 pulses.The decrease in the echo from a distributed target near the surface attributable to the change of the satellite altitude from 350 km to 402.5 km is 1.21 dB (= 20log(402.5/350)). From a simulation result, we estimate a decrease of 0.5% in surface-rainfall estimates due to the sensitivity degradation. Because the height of the clutter-free bottom increases at off-nadir angles due to the increase in the footprint size from 4.3 km to 5.0 km, the sampling range bins for near-surface rain have been raised, causing the PR to miss low-rain systems more often after the boost than before the boost. Although a beam-mismatch correction is executed in the current 1B21 algorithm, the correction algorithm still results in a negative bias in rain-rate estimates near the surface in the second half of the PR scan. The changes in the surface-rainfall estimates after the boost due to the second and third causes can be estimated as -2.5% and -2.9% by comparing the estimates at off-nadir bins with those at near-nadir bins with the assumption that the true rain rates measured at all angle bins should be the same, on average. It is concluded that the total effect of the orbit boost is a decrease of 5.9% (= 0.5 + 2.5 + 2.9%) in the e_SurfRain amounts in PR version 6 products.

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“…The TRMM 2A23 algorithmʼs principle task, detailed by Awaka et al (1997Awaka et al ( , 2007Awaka et al ( , 2009, is to classify radar retrievals into one of three types on a per-pixel basis: stratiform, convective, and other. Important applications of the 2A23 algorithm include the characterization of convective and stratiform rain across the tropics (e.g., Schumacher and Houze 2003b) and the estimation of diabatic heating and drying profiles associated with convection (e.g., Shige et al 2007Shige et al , 2008.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Rain Classifications over the Tropics by Version 7 of the TRMM PR 2A23 Algorithm

Funk

Schumacher

Awaka

2013

Journal of the Meteorological Society of Japan

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The Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) 2A23 algorithm attempts to classify rain echo as stratiform or convective. Updates to the 2A23 algorithm for Version 7 (V7) have resulted in an increase (decrease) in the fraction of rain echo classified as convective (stratiform) compared with the previous version of the algorithm. This is caused in part by more shallow non-isolated echoes, which exhibit strong concentrations over the Pacific intertropical convergence zone (ITCZ), being classified as convective in V7. The tropics-wide (20°N̶20°S) stratiform rain fraction has decreased correspondingly from 40% to 38% between Version 5 (V5) and V7. It is suggested that two additional stratiform categories could be considered convective because of the prevalence of warmrain processes in each, particularly, higher altitude rain over mountainous terrain and shallow non-isolated rain over tropical oceans; this would decrease the tropics-wide stratiform rain fraction to 35%.

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TRMM PR Standard Algorithm 2A23 and its Performance on Bright Band Detection

Cited by 135 publications

References 20 publications

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Evaluation of the Effects of the Orbit Boost of the TRMM Satellite on PR Rain Estimates

Analysis of Rain Classifications over the Tropics by Version 7 of the TRMM PR 2A23 Algorithm

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