Development of Nonuniform Beamfilling Correction Method in Rainfall Retrievals for Passive Microwave Radiometers over Ocean Using TRMM Observations

Kubota, Takuji; Shige, Shoichi; Aonashi, Kazumasa; Okamoto, Ken‐ichi

doi:10.2151/jmsj.87a.153

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…In this section, we focus on the effects of the precipitation-related variable models and the scattering-retrieval method on the precipitation retrievals. (Precipitation-detection and inhomogeneity estima- tion methods have already been reported by Seto et al 2005;Kubota et al 2007Kubota et al , 2009and Kida et al 2009. ) To evaluate these effects, we developed experimental algorithms by switching off some of the above improvements.…”

Section: Retrieval Experimentsmentioning

confidence: 84%

GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation

Aonashi¹,

Awaka

Hirose

et al. 2009

Journal of the Meteorological Society of Japan

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287

152

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Section: Retrieval Experimentsmentioning

confidence: 84%

GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation

Aonashi¹,

Awaka

Hirose

et al. 2009

Journal of the Meteorological Society of Japan

Self Cite

287

152

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“…6). Some recent studies also show that the TRMM PR data cannot capture rainfall from shallow clouds in mountainous regions adequately, associated with local mountain-valley circulations (Kwon et al 2008;Kubota et al 2009). Some previous studies reported the same tendency in rainfall between satellite and in situ data over the land except the coastal region (Nair et al 2009;Yuan et al 2012).…”

Section: Summary and Discussionmentioning

confidence: 99%

Modulation of the Diurnal Cycle of Rainfall Associated with the MJO Observed by a Dense Hourly Rain Gauge Network at Sarawak, Borneo

2013

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This study investigates spatiotemporal characteristics of the diurnal cycle (DC) of rainfall over Sarawak in northwest Borneo Island, associated with large-scale intraseasonal disturbances represented by the Madden-Julian oscillation (MJO). This is accomplished using a dense hourly rain gauge network and satellite data. The spatial pattern of the DC is classified into two major groups, coastal and interior regions, based on remarkable differences in rainfall peak times and amplitudes. Amplitudes of the DC and daily rainfall amount increase in active MJO phases at all sites, but the MJO has a stronger effect in the coastal region than the interior region. This modulation of rainfall by the MJO disturbance is largely attributed to rainfall frequency in the interior region, but to both frequency and intensity of rainfall in the coastal region. The low-level westerly wind anomaly enhances convergence, the land-sea breeze, and a midnight rainfall peak in the coastal region during the active MJO phase. Analysis of moisture flux divergence and moist static instability suggests the different dynamics of this modulation of the DC between coastal and interior regions.

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“…Kieper and Jiang (2012) used satellite observations to show that the formation of an eyewall ring consisting of low-level water clouds and warm rain is related to subsequent rapid intensification (RI). More recently, Shimada et al (2017) showed that future intensity change increases with increasing axisymmetry of the inner-core rainfall distribution, using a microwave satellite-based rainfall product, the Global Satellite Mapping of Precipitation (GSMaP; Kubota et al 2007Kubota et al , 2009.…”

Section: Introductionmentioning

confidence: 99%

Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

Shimada

Owada

Yamaguchi

et al. 2018

Weather and Forecasting

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The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%–5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.

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Development of Nonuniform Beamfilling Correction Method in Rainfall Retrievals for Passive Microwave Radiometers over Ocean Using TRMM Observations

Cited by 14 publications

References 33 publications

GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation

GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation

Modulation of the Diurnal Cycle of Rainfall Associated with the MJO Observed by a Dense Hourly Rain Gauge Network at Sarawak, Borneo

Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

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