Study and Tests of Improved Rain Estimates from the TRMM Precipitation Radar

Ferreira, F.; Amayenc, P.; Oury, Stéphane; Testud, J.

doi:10.1175/1520-0450(2001)040<1878:satoir>2.0.co;2

Cited by 34 publications

(25 citation statements)

References 24 publications

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“…When the quantity qS(r s ) is greater than or equal to 1, (8) cannot be applied. Iguchi and Meneghini (1994) proposed the adjustment of qS(r s ) by a factor «, while Durden and Haddad (1998) and Ferreira et al (2001) showed the importance of relating this type of adjustment to changes in the assumptions regarding the particle size distributions. Indeed, if the intercepts in the particle size distributions at all levels are changed by dN, then qS(r s ) (where r s is the range to the surface) changes dN (12b) , which implies that dN (12b) 5 «.…”

Section: B Single-frequency Retrievalmentioning

confidence: 99%

A Robust Dual-Frequency Radar Profiling Algorithm

Grecu¹,

Lin²,

Olson³

et al. 2011

J. Appl. Meteor. Climatol.

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In this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar-radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dualfrequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth's surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld-Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference techniquebased path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

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Section: B Single-frequency Retrievalmentioning

confidence: 99%

A Robust Dual-Frequency Radar Profiling Algorithm

Grecu¹,

Lin²,

Olson³

et al. 2011

J. Appl. Meteor. Climatol.

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“…The main cause of this low correlation could be attributed to the spatial and temporal offset errors emanating from co-llocating TRMM (low-earth orbiting passive microwave) with MGS (Geostationary thermal infrared) satellite observations (Turk et al, 2003) which has an average time difference of about 10 min within the tropical regions. In order to minimize the effects of these offset errors on rainfall estimation, artificial neural networks (Grecu and Anagnostou, 2001;Hong et al, 2004)) or temporal averaging techniques of instantaneous rain rates (Ferreira et al, 2001;Heinemann et al, 2002;Turk et al, 2005) can be applied.…”

Section: Mgs and Trmm Relationshipmentioning

confidence: 99%

Estimation of spatial–temporal rainfall distribution using remote sensing techniques: A case study of Makanya catchment, Tanzania

Jeniffer¹,

Su²,

Woldai³

et al. 2010

International Journal of Applied Earth Observation and Geoinfor

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“…Both theoretical and observational evidence indicates that m and n are only weakly dependent on ; therefore, most precipitation-related relationships (e.g., radar reflectivity versus precipitation water content, radar reflectivity versus rain rate, reflectivity versus attenuation) strongly depend on N* 0 and only weakly depend on for a specific particle density. This property AUGUST 2006 J I A N G A N D Z I P S E R has been exploited in many radar-only and radarradiometer-combined profiling algorithms (Ferreira et al 2001;Grecu and Anagnostou 2002;GP;Viltard et al 2000), including the official TRMM precipitation radar (PR) 2A25 algorithm (Iguchi et al 2000). The -dependent m and n in (4) can be computed from fits to experimental data.…”

Section: B Hydrometeor Content Calculationsmentioning

confidence: 99%

Retrieval of Hydrometeor Profiles in Tropical Cyclones and Convection from Combined Radar and Radiometer Observations

Jiang

Zipser

2006

Journal of Applied Meteorology and Climatology

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A retrieval algorithm is described to estimate vertical profiles of precipitation ice water content and liquid water content in tropical cyclones and convection over ocean from combined spaceborne radar and radiometer measurements. In the algorithm, the intercept parameter N 0 s in the exponential particle size distribution for rain, snow, and graupel are adjusted iteratively to minimize the difference between observed brightness temperatures and simulated ones by using a simulated annealing optimization method. Sensitivity tests are performed to understand the effects of the input parameters. The retrieval technique is investigated using the Earth Resources (ER)-2 aircraft Doppler radar and Advanced Microwave Precipitation Radiometer data in tropical cyclones and convection. An indirect validation is performed by comparing the measured and retrieved 50-GHz (independent channel) brightness temperature. The global agreement shows not only the quality of the inversion procedure, but also the consistency of the retrieved parameters with observations. The direct validation of the ice water content retrieval by using the aircraft in situ microphysical measurements indicates that the algorithm can provide reliable ice water content estimates, especially in stratiform regions. In convective regions, the large variability of the microphysical characteristics causes a large uncertainty in the retrieval, although the mean difference between the retrieved ice water content and aircraft-derived ice water content is very small. The ice water content estimated by a radar-only empirical relationship is higher than those retrieved by the combined algorithm and derived by the aircraft in situ observations. The new combined algorithm contains information that should improve ice water content estimates from either radar-only or passive microwave-only measurements.

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Study and Tests of Improved Rain Estimates from the TRMM Precipitation Radar

Cited by 34 publications

References 24 publications

A Robust Dual-Frequency Radar Profiling Algorithm

A Robust Dual-Frequency Radar Profiling Algorithm

Estimation of spatial–temporal rainfall distribution using remote sensing techniques: A case study of Makanya catchment, Tanzania

Retrieval of Hydrometeor Profiles in Tropical Cyclones and Convection from Combined Radar and Radiometer Observations

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