Profiler Contributions to Tropical Rainfall Measuring Mission (TRMM) Ground Validation Field Campaigns

Gage, K. S.; Williams, C. R.; Clark, W. L.; Johnston, Paul E.; Carter, David A.

doi:10.1175/1520-0426(2002)019<0843:pcttrm>2.0.co;2

Cited by 26 publications

(25 citation statements)

References 55 publications

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“…The aircraft motion adds an along-track dimension, so EDOP essentially provides vertical cross sections. These sections are similar to those obtained from profiling ground-based radars (e.g., Gage et al 2002), except that the latter combine evolution and translation whereas EDOP transects are quasi instantaneous. In comparison with the TRMM PR, which does provide a horizontal context, EDOP has both a better vertical resolution and Doppler information.…”

Section: Rain-type Classificationsupporting

confidence: 66%

Classification and Characterization of Tropical Precipitation Based on High-Resolution Airborne Vertical Incidence Radar. Part I: Classification

Geerts

Dawei

2004

Journal of Applied Meteorology

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Airborne measurements of vertical incidence radar reflectivity and radial velocity are analyzed for some 21 231 km of high-altitude flight tracks over tropical precipitation systems, in order to describe their characteristic vertical structure. The strength of the radar dataset lies in its superb vertical resolution, sufficient to detect unambiguously a bright band and the coincident Doppler velocity change, which identify the melting layer in stratiform precipitation. In this first of a two-part study, a technique based on the detection of this stratiform precipitation signature is developed to classify hydrometer profiles as convective, stratiform, or shallow. Even though the profiles are classified individually, stratiform and convective regions emerge, whose characteristics are described. The hydrometeor vertical velocity variability is smaller in stratiform profiles, which is consistent with the physical concept of a stratiform region. The purpose of the classification is to describe, in Part II, the composite vertical structure of the various rain types in hurricanes, as well as in isolated to organized precipitating convection sampled in Florida and Brazil.

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Section: Rain-type Classificationsupporting

confidence: 66%

Classification and Characterization of Tropical Precipitation Based on High-Resolution Airborne Vertical Incidence Radar. Part I: Classification

Geerts

Dawei

2004

Journal of Applied Meteorology

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“…(g) There are two Joss-Waldvogel disdrometers at Kwajalein Atoll. We use the Legan site disdrometer (Gage et al 2002). The PR-and disdrometer-derived a values do not agree well, with the disdrometerderived a values being systematically higher.…”

Section: Pr-derived Dsd Validation With Disdro Meter Datamentioning

confidence: 97%

Feasibility of Raindrop Size Distribution Parameter Estimation with TRMM Precipitation Radar

Kozu

Iguchi

Kubota

et al. 2009

Journal of the Meteorological Society of Japan

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This paper studies the feasibility of estimating raindrop size distribution (DSD) parameters from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. A methodology is described for DSD estimation with PR, in which parameter "e " or "a " in the Z-R relation Z = aR b is used as a DSD parameter. The e parameter is an adjustment factor for a in the relation between the attenuation coefficient k and the effective radar reflectivity factor Ze (k = a Ze b ) that makes the attenuation correction stable by using the path-integrated attenuation estimated from the surface echo as a reference. e is also recognized as a path-averaged DSD parameter. Large (small) e corresponds to small (large) a, i.e., to small (large) median volume diameters (D 0 s) with the assumption of the gamma DSD model. e exhibits a clear diurnal variation over land suggesting that afternoon convection causes DSDs with large D 0 s. In contrast, there is no significant diurnal variation over the ocean. e also exhibits a clear negative correlations with the storm-top height deduced from the PR and with the lightning flash rate, both of which again suggest that deep convections over land produce large D 0 s. There are several error sources that may produce bias errors in the DSD estimates: non-uniform beam filling (NUBF) within the PR antenna beam, non-liquid hydrometeors aloft (such as hail), and variation in the Normalized Radar Cross Section (NRCS) under rain as compared with no-rain conditions. Preliminary evaluations are performed on these error sources, which generally cause negative errors in e (i.e., overestimation of raindrop size). Nevertheless, comparisons of PR-and disdrometer-estimated a (in Z=aR b ) generally are in agreement at various locations over both land and oceanic sites. This result suggests the feasibility of PR estimation of DSD. It is concluded that,

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“…1c for the locations). The stationary vertically pointing antenna enables profilers to study the vertical structure of precipitation systems as they pass over the radar site [Gage et al, 2002]. In order for the S-PROF radars to observe both high altitude anvil clouds and low altitude heavy precipitation, the S-PROF radars sequence through three operating modes [White et al, 2000].…”

Section: Event Description and Observationsmentioning

confidence: 99%

Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements

et al. 2013

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[1] Using observations from a space-borne radiometer and a ground-based precipitation profiling radar, the impact of cloud microphysics schemes in the WRF model on the simulation of microwave brightness temperature (T b ), radar reflectivity, and Doppler velocity (V dop ) is studied for a winter storm in California. The unique assumptions of particles size distributions, number concentrations, shapes, and fall speeds in different microphysics schemes are implemented into a satellite simulator and customized calculations for the radar are performed to ensure consistent representation of precipitation properties between the microphysics schemes and the radiative transfer models. [2] Simulations with four different schemes in the WRF model, including the Goddard scheme (GSFC), the WRF single-moment 6-class scheme (WSM6), the Thompson scheme (THOM), and the Morrison double-moment scheme (MORR), are compared directly with measurements from the sensors. Results show large variations in the simulated radiative properties. General biases of~20 K or larger are found in (polarization-corrected) T b , which is linked to an overestimate of the precipitating ice aloft. The simulated reflectivity with THOM appears to agree well with the observations, while high biases of~5À10 dBZ are found in GSFC, WSM6 and MORR. Peak reflectivity in MORR exceeds other schemes. These biases are attributable to the snow intercept parameters or the snow number concentrations. Simulated V dop values based on GSFC agree with the observations well, while other schemes appear to have a~1 m s -1 high bias in the ice layer. In the rain layer, the model representations of Doppler velocity vary at different sites.Citation: Han, M., S. A. Braun, T. Matsui, and C. R. Williams (2013), Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements,

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Profiler Contributions to Tropical Rainfall Measuring Mission (TRMM) Ground Validation Field Campaigns

Cited by 26 publications

References 55 publications

Classification and Characterization of Tropical Precipitation Based on High-Resolution Airborne Vertical Incidence Radar. Part I: Classification

Classification and Characterization of Tropical Precipitation Based on High-Resolution Airborne Vertical Incidence Radar. Part I: Classification

Feasibility of Raindrop Size Distribution Parameter Estimation with TRMM Precipitation Radar

Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements

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