Performance assessment of a triple-frequency spaceborne cloud–precipitation radar concept using a global cloud-resolving model
書誌事項
- 公開日
- 2015-08-26
- 資源種別
- journal article
- 権利情報
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- https://creativecommons.org/licenses/by/3.0/
- DOI
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- 10.5194/amt-8-3493-2015
- 10.5194/amtd-8-4137-2015
- 公開者
- Copernicus GmbH
説明
<jats:p>Abstract. Multi-frequency radars offer enhanced detection of clouds and precipitation compared to single-frequency systems, and are able to make more accurate retrievals when several frequencies are available simultaneously. An evaluation of a spaceborne three-frequency Ku-/Ka-/W-band radar system is presented in this study, based on modeling radar reflectivities from the results of a global cloud-resolving model with a 875 m grid spacing. To produce the reflectivities, a scattering model has been developed for each of the hydrometeor types produced by the model, as well as for melting snow. The effects of attenuation and multiple scattering on the radar signal are modeled using a radiative transfer model, while nonuniform beam filling is reproduced with spatial averaging. The combined effects of these are then quantified both globally and in six localized case studies. Two different orbital scenarios using the same radar are compared. Overall, based on the results, it is expected that the proposed radar would detect a high-quality signal in most clouds and precipitation. The main exceptions are the thinnest clouds that are below the detection threshold of the W-band channel, and at the opposite end of the scale, heavy convective rainfall where a combination of attenuation, multiple scattering and nonuniform beam filling commonly cause significant deterioration of the signal; thus, while the latter can be generally detected, the quality of the retrievals is likely to be degraded.</jats:p>
収録刊行物
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- Atmospheric Measurement Techniques
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Atmospheric Measurement Techniques 8 (8), 3493-3517, 2015-08-26
Copernicus GmbH
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詳細情報 詳細情報について
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- CRID
- 1360002221114525696
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- ISSN
- 18678548
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- 資料種別
- journal article
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- データソース種別
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- Crossref
- KAKEN
- OpenAIRE

