Constaining microwave brightness temperatures by radar brightband observations

A. Battaglia, C. Kummerow, Dong Bin Shin, C. Williams

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

Multichannel microwave sensors make it possible to construct physically based rainfall retrieval algorithms. In these schemes, errors arising from the inaccuracy of the physical modeling of the cloud system under observation have to be accounted for. The melting layer has recently been identified as a possible source of bias when stratiform events are considered. In fact, Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations reveal systematic differences in the observed brightness temperatures between similar rain profiles that often differ only by the presence or absence of a bright band. A sensitivity study of the scattering properties of the melting layer with different one-dimensional steady-state microphysical and electromagnetic models is performed. The electromagnetic modeling of the ice particle density and assumption of the ventilation coefficient parameterization is found to have the greatest impact on the extinction profiles. Data taken from a 0.915-GHz National Oceanic and Atmospheric Administration (NOAA) profiler during the Kwajalein Experiment (KWAJEX) field campaign are used to reduce the uncertainties in the modeling of the bright band. The profiler data reduce the number of viable parameterizations, which in turn leads to a reduction in the variability of the upwelling radiances (simulated at TMI angle) for different cloud simulations. Using the parameterizations that best match the profiler data, the brightness temperatures TH generally increase if mixed-phase precipitation is included in the model atmosphere. The effect is most pronounced for systems with low freezing levels, such as a midlatitude cold front simulation. For TMI footprints at 10.65 GHz. the increase in the TB from the bright band generally increases with rain rate and changes by as much as ∼15-20 K. At 19.35 GHz the maximum effect is found around 3-5 mm h-1 (∼15 K), and at 37 GHz the maximum effect is around 1 mm h-1 (∼10 K), while at 85.5 GHz the effect is always lower than 3 K. Despite the reduction of uncertainties achieved by using 915-MHz profiler data, differences between parameterizations are still significant, especially for the higher TMI frequencies. A validation experiment is proposed to solve this issue and to further reduce the uncertainties in brightband modeling.

Original languageEnglish
Pages (from-to)856-871
Number of pages16
JournalJournal of Atmospheric and Oceanic Technology
Volume20
Issue number6
DOIs
Publication statusPublished - 2003 Jun 1

Fingerprint

Parameterization
Image sensors
brightness temperature
TRMM
Rain
profiler
Luminance
Radar
Microwaves
radar
parameterization
Melting
modeling
Microwave sensors
Temperature
melting
Freezing
cold front
Ventilation
Ice

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Atmospheric Science

Cite this

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title = "Constaining microwave brightness temperatures by radar brightband observations",
abstract = "Multichannel microwave sensors make it possible to construct physically based rainfall retrieval algorithms. In these schemes, errors arising from the inaccuracy of the physical modeling of the cloud system under observation have to be accounted for. The melting layer has recently been identified as a possible source of bias when stratiform events are considered. In fact, Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations reveal systematic differences in the observed brightness temperatures between similar rain profiles that often differ only by the presence or absence of a bright band. A sensitivity study of the scattering properties of the melting layer with different one-dimensional steady-state microphysical and electromagnetic models is performed. The electromagnetic modeling of the ice particle density and assumption of the ventilation coefficient parameterization is found to have the greatest impact on the extinction profiles. Data taken from a 0.915-GHz National Oceanic and Atmospheric Administration (NOAA) profiler during the Kwajalein Experiment (KWAJEX) field campaign are used to reduce the uncertainties in the modeling of the bright band. The profiler data reduce the number of viable parameterizations, which in turn leads to a reduction in the variability of the upwelling radiances (simulated at TMI angle) for different cloud simulations. Using the parameterizations that best match the profiler data, the brightness temperatures TH generally increase if mixed-phase precipitation is included in the model atmosphere. The effect is most pronounced for systems with low freezing levels, such as a midlatitude cold front simulation. For TMI footprints at 10.65 GHz. the increase in the TB from the bright band generally increases with rain rate and changes by as much as ∼15-20 K. At 19.35 GHz the maximum effect is found around 3-5 mm h-1 (∼15 K), and at 37 GHz the maximum effect is around 1 mm h-1 (∼10 K), while at 85.5 GHz the effect is always lower than 3 K. Despite the reduction of uncertainties achieved by using 915-MHz profiler data, differences between parameterizations are still significant, especially for the higher TMI frequencies. A validation experiment is proposed to solve this issue and to further reduce the uncertainties in brightband modeling.",
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Constaining microwave brightness temperatures by radar brightband observations. / Battaglia, A.; Kummerow, C.; Shin, Dong Bin; Williams, C.

In: Journal of Atmospheric and Oceanic Technology, Vol. 20, No. 6, 01.06.2003, p. 856-871.

Research output: Contribution to journalArticle

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T1 - Constaining microwave brightness temperatures by radar brightband observations

AU - Battaglia, A.

AU - Kummerow, C.

AU - Shin, Dong Bin

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N2 - Multichannel microwave sensors make it possible to construct physically based rainfall retrieval algorithms. In these schemes, errors arising from the inaccuracy of the physical modeling of the cloud system under observation have to be accounted for. The melting layer has recently been identified as a possible source of bias when stratiform events are considered. In fact, Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations reveal systematic differences in the observed brightness temperatures between similar rain profiles that often differ only by the presence or absence of a bright band. A sensitivity study of the scattering properties of the melting layer with different one-dimensional steady-state microphysical and electromagnetic models is performed. The electromagnetic modeling of the ice particle density and assumption of the ventilation coefficient parameterization is found to have the greatest impact on the extinction profiles. Data taken from a 0.915-GHz National Oceanic and Atmospheric Administration (NOAA) profiler during the Kwajalein Experiment (KWAJEX) field campaign are used to reduce the uncertainties in the modeling of the bright band. The profiler data reduce the number of viable parameterizations, which in turn leads to a reduction in the variability of the upwelling radiances (simulated at TMI angle) for different cloud simulations. Using the parameterizations that best match the profiler data, the brightness temperatures TH generally increase if mixed-phase precipitation is included in the model atmosphere. The effect is most pronounced for systems with low freezing levels, such as a midlatitude cold front simulation. For TMI footprints at 10.65 GHz. the increase in the TB from the bright band generally increases with rain rate and changes by as much as ∼15-20 K. At 19.35 GHz the maximum effect is found around 3-5 mm h-1 (∼15 K), and at 37 GHz the maximum effect is around 1 mm h-1 (∼10 K), while at 85.5 GHz the effect is always lower than 3 K. Despite the reduction of uncertainties achieved by using 915-MHz profiler data, differences between parameterizations are still significant, especially for the higher TMI frequencies. A validation experiment is proposed to solve this issue and to further reduce the uncertainties in brightband modeling.

AB - Multichannel microwave sensors make it possible to construct physically based rainfall retrieval algorithms. In these schemes, errors arising from the inaccuracy of the physical modeling of the cloud system under observation have to be accounted for. The melting layer has recently been identified as a possible source of bias when stratiform events are considered. In fact, Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations reveal systematic differences in the observed brightness temperatures between similar rain profiles that often differ only by the presence or absence of a bright band. A sensitivity study of the scattering properties of the melting layer with different one-dimensional steady-state microphysical and electromagnetic models is performed. The electromagnetic modeling of the ice particle density and assumption of the ventilation coefficient parameterization is found to have the greatest impact on the extinction profiles. Data taken from a 0.915-GHz National Oceanic and Atmospheric Administration (NOAA) profiler during the Kwajalein Experiment (KWAJEX) field campaign are used to reduce the uncertainties in the modeling of the bright band. The profiler data reduce the number of viable parameterizations, which in turn leads to a reduction in the variability of the upwelling radiances (simulated at TMI angle) for different cloud simulations. Using the parameterizations that best match the profiler data, the brightness temperatures TH generally increase if mixed-phase precipitation is included in the model atmosphere. The effect is most pronounced for systems with low freezing levels, such as a midlatitude cold front simulation. For TMI footprints at 10.65 GHz. the increase in the TB from the bright band generally increases with rain rate and changes by as much as ∼15-20 K. At 19.35 GHz the maximum effect is found around 3-5 mm h-1 (∼15 K), and at 37 GHz the maximum effect is around 1 mm h-1 (∼10 K), while at 85.5 GHz the effect is always lower than 3 K. Despite the reduction of uncertainties achieved by using 915-MHz profiler data, differences between parameterizations are still significant, especially for the higher TMI frequencies. A validation experiment is proposed to solve this issue and to further reduce the uncertainties in brightband modeling.

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