TRMM Precipitation Radar

Kawanishi, Toneo; Kuroiwa, Hiroshi; Kojima, Masayasu; Oikawa, Koki; Kozu, Toshiaki; Kumagai, Hiroshi; Okamoto, Ken‐ichi; Okumura, Minoru; Nakatsuka, Hirotaka; Nishikawa, K.

doi:10.1016/s0273-1177(99)00932-1

Cited by 68 publications

(35 citation statements)

References 1 publication

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“…It was found that both satellite precipitation products significantly underestimated the gauge precipitation (RB was -0.273 for 3B42 v7 and -0.176 for IMERG v5) and had relatively small r when the gauge stations with zero rainfall were eliminated in Figure 2a, which was mainly due to the absence of the whole rainfall process record of the satellite sensors (the temporal resolutions for IMERG v5 and 3B42 v7 are half-hourly and 3-hourly) leading to the inaccurate monitor of the smaller rainfall events. Usually, the TRMM precipitation radar (PR), whose emission wavelengths are relatively long, has a minimum measurable rain rate as low as 0.7 mm/h [39]. While a key advancement of GPM is the extended capability to measure light rain (less than 0.5 mm/h), solid precipitation, and the microphysical properties of precipitating particles compared to TRMM; the GPM Dual-frequency Precipitation Radar (DPR) is more sensitive to light rain rates and snowfall [10].…”

Section: Discussionmentioning

confidence: 99%

Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China

Chen

Duan

et al. 2018

Remote Sensing

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Abstract:The performance of the latest released Integrated Multi-satellitE Retrievals for GPM mission (IMERG) version 5 (IMERG v5) and the TRMM Multisatellite Precipitation Analysis 3B42 version 7 (3B42 v7) are evaluated and compared at multiple temporal scales over a semi-humid to humid climate transition area (Huaihe River basin) from 2015 to 2017. The impacts of rainfall rate, latitude and elevation on precipitation detection skills are also investigated. Results indicate that both satellite estimates showed a high Pearson correlation coefficient (r, above 0.89) with gauge observations, and an overestimation of precipitation at monthly and annual scales. Mean daily precipitation of IMERG v5 and 3B42 v7 display a consistent spatial pattern, and both characterize the observed precipitation distribution well, but 3B42 v7 tends to markedly overestimate precipitation over water bodies. Both satellite precipitation products overestimate rainfalls with intensity ranging from 0.5 to 25 mm/day, but tend to underestimate light (0-0.5 mm/day) and heavy (>25 mm/day) rainfalls, especially for torrential rains (above 100 mm/day). Regarding each gauge station, the IMERG v5 has larger mean r (0.36 for GPM, 0.33 for TRMM) and lower mean relative root mean square error (RRMSE, 1.73 for GPM, 1.88 for TRMM) than those of 3B42 v7. The higher probability of detection (POD), critical success index (CSI) and lower false alarm ratio (FAR) of IMERG v5 than those of 3B42 v7 at different rainfall rates indicates that IMERG v5 in general performs better in detecting the observed precipitations. This study provides a better understanding of the spatiotemporal distribution of accuracy of IMERG v5 and 3B42 v7 precipitation and the influencing factors, which is of great significance to hydrological applications.

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Section: Discussionmentioning

confidence: 99%

Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China

Chen

Duan

et al. 2018

Remote Sensing

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“…Monthly mean precipitation over the Amazon region was obtained from the algorithm 3B42 of the Tropical Rainfall Measuring Mission (TRMM) merged high quality (HQ)/infrared (IR) precipitation product at a spatial resolution of 0.25-0.25 • (http://trmm.gsfc.nasa.gov/3b42.html; Kummerow et al, 1998;Kawanishi et al, 2000). TRMM 3B42 is derived from retrievals of 3-hourly precipitation amounts from the precipitation radar (PR), TRMM microwave imager (TMI), and visible and infrared scanner (VIRS) aboard the TRMM satellite merged with rain gauge data from the Climate Anomaly Monitoring System (CAMS) and the Global Precipitation Climatology Project (GPCP).…”

Section: Precipitationmentioning

confidence: 99%

Modeling the radiative effects of biomass burning aerosols on carbon fluxes in the Amazon region

et al. 2017

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Abstract. Every year, a dense smoke haze covers a large portion of South America originating from fires in the Amazon Basin and central parts of Brazil during the dry biomass burning season between August and October. Over a large portion of South America, the average aerosol optical depth at 550 nm exceeds 1.0 during the fire season, while the background value during the rainy season is below 0.2. Biomass burning aerosol particles increase scattering and absorption of the incident solar radiation. The regional-scale aerosol layer reduces the amount of solar energy reaching the surface, cools the near-surface air, and increases the diffuse radiation fraction over a large disturbed area of the Amazon rainforest. These factors affect the energy and CO 2 fluxes at the surface. In this work, we applied a fully integrated atmospheric model to assess the impact of biomass burning aerosols in CO 2 fluxes in the Amazon region during 2010. We address the effects of the attenuation of global solar radiation and the enhancement of the diffuse solar radiation flux inside the vegetation canopy. Our results indicate that biomass burning aerosols led to increases of about 27 % in the gross primary productivity of Amazonia and 10 % in plant respiration as well as a decline in soil respiration of 3 %. Consequently, in our model Amazonia became a net carbon sink; net ecosystem exchange during September 2010 dropped from +101 to −104 TgC when the aerosol effects are considered, mainly due to the aerosol diffuse radiation effect. For the forest biome, our results point to a dominance of the diffuse radiation effect on CO 2 fluxes, reaching a balancePublished by Copernicus Publications on behalf of the European Geosciences Union. 14786 D. S. Moreira et al.: Modeling the radiative effects of biomass burning aerosols of 50-50 % between the diffuse and direct aerosol effects for high aerosol loads. For C3 grasses and savanna (cerrado), as expected, the contribution of the diffuse radiation effect is much lower, tending to zero with the increase in aerosol load. Taking all biomes together, our model shows the Amazon during the dry season, in the presence of high biomass burning aerosol loads, changing from being a source to being a sink of CO 2 to the atmosphere.

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“…• (obtained from http://trmm.gsfc.nasa.gov/) (Kummerow et al, 1998;Kawanishi et al, 2000). TRMM 3B43 is derived from retrievals of 3-hourly precipitation amount from the precipitation radar (PR), TRMM microwave imager (TMI), and visible and infrared scanner (VIRS) aboard the TRMM satellite, merged with rain gauge data from the Climate Anomaly Monitoring System (CAMS) and the Global Precipitation Climatology Project (GPCP).…”

Section: Satellite and Ground-based O 3 And Meteorological Datamentioning

confidence: 99%

Ozone production and transport over the Amazon Basin during the dry-to-wet and wet-to-dry transition seasons

et al. 2015

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Abstract. The Regional Carbon Balance in Amazonia (BARCA) campaign provided the first Amazon Basin-wide aircraft measurements of ozone (O 3 ) during both the dry-towet (November and December 2008) and wet-to-dry (May 2009) transition seasons. Extremely low background values (< 20 ppb) were observed to the west and north of Manaus in both seasons and in all regions during the wet-to-dry transition. On the other hand, elevated O 3 levels (40-60 ppb) were seen during the dry-to-wet transition to the east and south of Manaus, where biomass burning emissions of O 3 precursors were present. Chemistry simulations with the CCATT-BRAMS and WRF-Chem models are within the error bars of the observed O 3 profiles in the boundary layer (0-3 km a.s.l.) in polluted conditions. However, the models overestimate O 3 in the boundary layer in clean conditions, despite lacking the predominant NO source from soil. In addition, O 3 simulated by the models was either within the error bars or lower than BARCA observations in mid-levels (3-5 km a.s.l.), and lower than total tropospheric O 3 retrieved from the OMI/MLS instruments, which is primarily comprised of middle troposphere O 3 and thus reflects long-range transport processes. Therefore, the models do a relatively poor job of representing the free troposphere-boundary layer gradient in O 3 compared with aircraft and satellite observations, which could be due to missing long-range and convective transport of O 3 at mid-levels. Additional simulations with WRF-Chem showed that the model O 3 production is very sensitive to both the O 3 deposition velocities and the NO x emissions, which were both about one-half of observed values. These results indicate the necessity of more realistic model representations of emissions, deposition, and convective processes for accurate monitoring and prediction of increases in O 3 production in the Amazon Basin as the regional population grows.

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TRMM Precipitation Radar

Cited by 68 publications

References 1 publication

Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China

Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China

Modeling the radiative effects of biomass burning aerosols on carbon fluxes in the Amazon region

Ozone production and transport over the Amazon Basin during the dry-to-wet and wet-to-dry transition seasons

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