Editorial Type:
Article
Article Type:
Research Article

TRMM Sampling of Radar–AMeDAS Rainfall Using the Threshold Method

Riko Oki NASA/Goddard Space Flight Center, Laboratory for Atmospheres, Greenbelt, Maryland

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Akimasa Sumi Center for Climate System Research, University of Tokyo, Meguro, Tokyo, Japan

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David A. Short NASA/Goddard Space Flight Center, Laboratory for Atmospheres, Greenbelt, Maryland

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Print Publication:
01 Nov 1997
DOI:
https://doi.org/10.1175/1520-0450(1997)036<1480:TSORAR>2.0.CO;2
Page(s):
1480–1492
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Abstract

It is known that spatially averaged rainfall rate 〈R〉 is highly correlated with the fractional area (F) of rain rate exceeding a preset threshold (τ), when the area is large enough to include numerous convective systems in various stages of their life cycles. Using this fact, a method to estimate area-averaged rain rate from F(τ), which is obtained from satellite observations, is proposed for Tropical Rainfall Measuring Mission (TRMM). There have been numerous studies investigating F–〈R〉 relationships and optimal thresholds at several radar observation sites around the world but no studies to confirm the performance of the method within Japan. In this study an analysis of radar–AMeDAS (Automatic Meteorological Data Acquisition System) precipitation data is presented. The F–〈R〉 relationships of radar–AMeDAS rain data have been examined systematically, with the result that the optimum threshold that maximizes the correlation between 〈R〉 and F(τ) is near 3.5 mm h−1 in every year and season of available data.

Using the threshold method with the average coefficients obtained when the threshold is set to 3.5 mm h−1, TRMM sampling of radar–AMeDAS rainfall is simulated. Fixing 5° × 5° areas, monthly mean area-averaged rain rate is estimated from the observational coverage that would be obtained by TRMM during a month. The errors from the threshold method are only 3%–4% larger than the sampling errors (14%–19% on average) obtained by using the full dynamic range of observed rain rates. Considering the dynamic range of TRMM sensors, the threshold method would be an effective method to estimate area-average rain rate.

* Additional affiliation: Universities Space Research Association.

Corresponding author address: David A. Short, Code 910.1, NASA/GSFC, Greenbelt, MD 20771.

Abstract

It is known that spatially averaged rainfall rate 〈R〉 is highly correlated with the fractional area (F) of rain rate exceeding a preset threshold (τ), when the area is large enough to include numerous convective systems in various stages of their life cycles. Using this fact, a method to estimate area-averaged rain rate from F(τ), which is obtained from satellite observations, is proposed for Tropical Rainfall Measuring Mission (TRMM). There have been numerous studies investigating F–〈R〉 relationships and optimal thresholds at several radar observation sites around the world but no studies to confirm the performance of the method within Japan. In this study an analysis of radar–AMeDAS (Automatic Meteorological Data Acquisition System) precipitation data is presented. The F–〈R〉 relationships of radar–AMeDAS rain data have been examined systematically, with the result that the optimum threshold that maximizes the correlation between 〈R〉 and F(τ) is near 3.5 mm h−1 in every year and season of available data.

Using the threshold method with the average coefficients obtained when the threshold is set to 3.5 mm h−1, TRMM sampling of radar–AMeDAS rainfall is simulated. Fixing 5° × 5° areas, monthly mean area-averaged rain rate is estimated from the observational coverage that would be obtained by TRMM during a month. The errors from the threshold method are only 3%–4% larger than the sampling errors (14%–19% on average) obtained by using the full dynamic range of observed rain rates. Considering the dynamic range of TRMM sensors, the threshold method would be an effective method to estimate area-average rain rate.

* Additional affiliation: Universities Space Research Association.

Corresponding author address: David A. Short, Code 910.1, NASA/GSFC, Greenbelt, MD 20771.

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Journal of Applied Meteorology and Climatology

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