Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar

Iguchi, Toshio; Kozu, Toshiaki; Kwiatkowski, John; Meneghini, R.; Awaka, Jun; Okamoto, Ken‐ichi

doi:10.2151/jmsj.87a.1

Cited by 278 publications

(237 citation statements)

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“…While the statistical properties of rain DSDs are broadly consistent over time whether measured in situ (Marshall and Palmer, 1948;Tokay and Short, 1996) or estimated by radar remote sensing (Wilson et al, 1997;Illingworth and Blackman, 2002), the instantaneous microphysical properties of rain are observed to vary over many orders of magnitude (Testud et al, 2001). Assumptions about the drop number concentration in particular have been identified as a major source of uncertainty in TRMM and CloudSat estimates of rain rate (Iguchi et al, 2009;. To improve upon the uncertainties of satellite remote-sensed rain rate, there is a need for additional radar measurements with which to better characterize the rain DSD.…”

Section: Introductionmentioning

confidence: 76%

“…In light rain with negligible PIA, mean Doppler velocity provides sufficient constraint, suggesting the possibility of using Doppler radar for retrievals of light rain over land; however, in moderate rain rates PIA provides a necessary constraint on the rain rate. Satisfactory retrievals of rain rate over land may be achieved by assuming that N w is constant, especially for cold stratiform rain; alternatively, PIA could be estimated from the land surface as in Iguchi et al (2009), which may provide sufficient information to resolve the ambiguity between weakly and strongly attenuating profiles even with large observational uncertainties. A robust method of using Doppler radar to estimate rain rate over land will be the subject of future work.…”

Section: Discussionmentioning

confidence: 99%

“…This formulation is a function of three independent, physically meaningful parameters for the shape µ, median drop size D 0 , and normalized drop number concentration intercept N w of the DSD (Testud et al, 2001;Illingworth and Blackman, 2002). The shape factor µ is of secondary importance to D 0 and N w in terms of the radar reflectivity (Testud et al, 2001) and is poorly constrained by observations (e.g.…”

Section: Rain State Variablesmentioning

confidence: 99%

“…Moisseev and Chandrasekar, 2007). In this retrieval we use µ = 5, a value derived from both radar and distrometer studies (Wilson et al, 1997;Illingworth and Blackman, 2002). This simplifies the DSD to a two-parameter function of D 0 and N w .…”

Section: Rain State Variablesmentioning

confidence: 99%

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Improved rain rate and drop size retrievals from airborne Doppler radar

2017

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Abstract. Satellite remote sensing of rain is important for quantifying the hydrological cycle, atmospheric energy budget, and cloud and precipitation processes; however, radar retrievals of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94 GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced retrievals of the raindrop size distribution.We demonstrate the capability to retrieve rain rate as a function of drop size and drop number concentration from airborne 94 GHz Doppler radar measurements using CAP-TIVATE, the variational retrieval algorithm developed for EarthCARE. For a range of rain regimes observed during the Tropical Composition, Cloud and Climate Coupling field campaign, we explore the contributions of mean Doppler velocity and path-integrated attenuation (PIA) measurements to the retrieval of rain rate, and the retrievals are evaluated against independent measurements from an independent 9.6 GHz Doppler radar. The retrieved drop number concentrations vary over 5 orders of magnitude between very light rain from melting ice and warm rain from liquid clouds. In light rain conditions mean Doppler velocity facilitates estimates of rain rate without PIA, suggesting the possibility of EarthCARE rain rate estimates over land; in moderate warm rain, drop number concentration can be retrieved without mean Doppler velocity, with possible applications to CloudSat.

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Section: Introductionmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Section: Rain State Variablesmentioning

confidence: 99%

Section: Rain State Variablesmentioning

confidence: 99%

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Improved rain rate and drop size retrievals from airborne Doppler radar

2017

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“…Practically, any nonuniformity will result in error when Z-R and Z-kext power laws are used to correct for attenuation and retrieve rainfall. As shown by Iguchi et al (2000Iguchi et al ( , 2009, even if everywhere in a volume, R=aZ b is strictly followed, if Z is not uniform within the volume then the volume mean value of R will be less than that implied by the volume mean value of Z:…”

Section: [[H1]] Effects Of Non-uniform Beam Fillingmentioning

confidence: 99%

Remote Sensing of Precipitation from Airborne and Spaceborne Radar

Munchak

2018

Remote Sensing of Aerosols, Clouds, and Precipitation

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Weather radar measurements from airborne or satellite platforms can be an effective remote sensing tool for examining the three-dimensional structures of clouds and precipitation. This chapter describes some fundamental properties of radar measurements and their dependence on the particle size distribution (PSD) and radar frequency. The inverse problem of solving for the vertical profile of PSD from a profile of measured reflectivity is stated as an optimal estimation problem for single-and multi-frequency measurements. Phenomena that can change the measured reflectivity Zm from its intrinsic value Ze, namely attenuation, non-uniform beam filling, and multiple scattering, are described and mitigation of these effects in the context of the optimal estimation framework is discussed. Finally, some techniques involving the use of passive microwave measurements to further constrain the retrieval of the PSD are presented. [[H1]] IntroductionThe ability of weather radar to measure the location and intensity of precipitation was rapidly realized in the late 1940s following World War II. However, ground-based radars are limited in their ability to directly detect precipitation close to the ground far from the radar site due to ground clutter, refraction of the radar beam, and the curvature of the earth. Beam blockage by terrain also poses problems for radar coverage in mountainous areas. Coverage over oceans and other remote areas, where maintaining a ground radar would be difficult and costly, is also impractical, yet the precipitation that falls in these regions has important impacts on the global https://ntrs.nasa.gov/search.jsp?R=20180000191 2018-05-12T19:37:19+00:00Z atmospheric circulations via latent heating (e.g., Hoskins and Karoly, 1981, Hartmann et al., 1984, Matthews et al., 2004 and can have a profound influence on weather patterns thousands of kilometers away. Likewise, knowledge of precipitation over land, particularly in the form of snow, is a crucial component of the mass balance equation for glaciers and ice sheets, which must be properly characterized for realistic climate simulations (Shepherd et al., 2012).Airborne radar systems can provide high sensitivity and finely resolved vertical profiles to characterize precipitation microphysics for the benefit of model parameterizations and process understanding (e.g., Reinhardt et al, 2010, Heymsfield et al., 2013, Rauber et al., 2016.However, in order to achieve true global coverage, it had been proposed from nearly the beginning of the space age to put a weather radar in space (Kreigler and Kawitz, 1960), and efforts to do so began in earnest in the late 1970s and 1980s with the planning of the Tropical Rainfall Measuring Mission satellite (TRMM; Simpson et al., 1987, Okamoto et al., 1988 increased accuracy, sensitivity, and extension to higher latitudes. Both the TRMM PR and GPM DPR were intended not only to estimate precipitation directly from the radar data but also to construct a database of precipitation profiles to unify precipitation retri...

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The variability of vertical structure of precipitation in Huaihe River Basin of China: Implications from long-term spaceborne observations with TRMM precipitation radar

Cao

2014

Water Resour. Res.

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The current study investigates the variability of vertical structure of precipitation in the Huaihe River Basin (HRB) of China. The precipitation characteristics have been revealed by the long-term observations of vertical profile of reflectivity (VPR) from the first spaceborne precipitation radar (PR) onboard the National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission (TRMM) satellite. This study has statistically analyzed the latest TRMM 2A-23 and 2A-25 products (version 7, released in 2012) with 15 years time span (from 11 December 1997 to 19 August 2012). First, the spatial and seasonal variations of storm height and freezing level have been investigated. The results show a climatological relation connecting the storm height with the rainfall rate in HRB. Second, mean VPRs have been studied for the stratiform and convective precipitation. The VPR variability has been analyzed for different seasons and rain intensities. Third, the characteristics of rain intensification and weakening in the vertical direction have been examined by the statistical analysis of VPR slope below the melting layer. The results show that the rainfall tends to be reduced (or intensified) with the height changing downward in the light (or moderate and heavy) precipitating clouds, no matter stratiform or convection. Finally, the S-band climatological VPRs have been characterized by converting the VPR from Ku-band to S-band. Considering the wide application of national radar network for weather surveillance in China, the developed S-band climatological VPRs can be potentially applied in a VPR correction scheme to improve the ground radar-based quantitative precipitation estimation (QPE) in this river basin.

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Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar

Cited by 278 publications

References 15 publications

Improved rain rate and drop size retrievals from airborne Doppler radar

Improved rain rate and drop size retrievals from airborne Doppler radar

Remote Sensing of Precipitation from Airborne and Spaceborne Radar

The variability of vertical structure of precipitation in Huaihe River Basin of China: Implications from long-term spaceborne observations with TRMM precipitation radar

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