Precipitation estimation over radar gap areas based on satellite and adjacent radar observations

Dong Bin Shin, Yu Ri Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS). The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a-priori databases. The databases were built with the temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 μm) and radar rain rate estimations. The databases were updated with collocated datasets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on the optimal weights that were determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates.

Original languageEnglish
Title of host publication2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789090086286
DOIs
Publication statusPublished - 2015 Oct 21
Event1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015 - Gran Canaria, Spain
Duration: 2015 May 162015 May 24

Other

Other1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015
CountrySpain
CityGran Canaria
Period15/5/1615/5/24

Fingerprint

Radar
Satellites
Rain
Weather satellites
trend
Merging
communication
Luminance
natural disaster
Geostationary satellites
coverage
Precipitation (meteorology)
Communication
monitoring
Landslides
Mean square error
event
Temperature
Monitoring
Sensors

All Science Journal Classification (ASJC) codes

  • Communication
  • Computer Networks and Communications

Cite this

Shin, D. B., & Lee, Y. R. (2015). Precipitation estimation over radar gap areas based on satellite and adjacent radar observations. In 2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015 [7303068] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URSI-AT-RASC.2015.7303068
Shin, Dong Bin ; Lee, Yu Ri. / Precipitation estimation over radar gap areas based on satellite and adjacent radar observations. 2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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abstract = "Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS). The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a-priori databases. The databases were built with the temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 μm) and radar rain rate estimations. The databases were updated with collocated datasets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on the optimal weights that were determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates.",
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Shin, DB & Lee, YR 2015, Precipitation estimation over radar gap areas based on satellite and adjacent radar observations. in 2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015., 7303068, Institute of Electrical and Electronics Engineers Inc., 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015, Gran Canaria, Spain, 15/5/16. https://doi.org/10.1109/URSI-AT-RASC.2015.7303068

Precipitation estimation over radar gap areas based on satellite and adjacent radar observations. / Shin, Dong Bin; Lee, Yu Ri.

2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7303068.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS). The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a-priori databases. The databases were built with the temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 μm) and radar rain rate estimations. The databases were updated with collocated datasets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on the optimal weights that were determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates.

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PB - Institute of Electrical and Electronics Engineers Inc.

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Shin DB, Lee YR. Precipitation estimation over radar gap areas based on satellite and adjacent radar observations. In 2015 1st URSI Atlantic Radio Science Conference, URSI AT-RASC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7303068 https://doi.org/10.1109/URSI-AT-RASC.2015.7303068