Introduction to Passive Microwave Retrieval Methods

Kummerow, Christian D.

doi:10.1007/978-3-030-24568-9_7

Cited by 21 publications

(10 citation statements)

References 50 publications

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“…For high-intensity precipitation, some researchers consider that the underestimation of IMERG stems from the inherent limitations of PMW and infrared (IR) estimation algorithms (Zhang et al, 2019). PMW-based and IR-based algorithms estimate land precipitation from the scattering signal of frozen hydrometeors and cloud top temperature, respectively [75][76][77]. Therefore, they have difficulty in accurately capturing heavy precipitation (such as convective storms) that are weakly linked to cloud top temperature or have no/few ice particles.…”

Section: Evaluation For Different Precipitation Intensitiesmentioning

confidence: 99%

Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China

2022

Remote Sensing

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The intensification of extreme precipitation has aggravated urban flood disasters, which makes timely and reliable precipitation information urgently needed. As the high-quality and widely used satellite precipitation products, Integrated Multi-satellitE Retrievals for GPM (IMERG), have not been well investigated in coastal urban agglomerations where damages from precipitation-related disasters are more severe. With precipitation measurements from local high-density gauge stations, this study evaluates three IMERG runs (IMERG ER, IMERG LR, and IMERG FR) in the southeast coastal urban region of China. The evaluation shows that the three IMERG products severely overestimate weak precipitation and underestimate heavy precipitation. Among the three runs, the post-corrected IMERG FR does not show a substantial improvement compared to the near-real-time IMERG ER and IMERG LR. The performance of IMERG varies depending on the precipitation pattern and intensity, with the best estimation ability occurring in the coastal urban region in summer and in the northern forests in winter. Due to the year-round urban effect on precipitation variability, IMERG cannot detect precipitation events well in the central high-density urban areas, and has its best detection ability on cultivated lands in summer and forests in winter. Within the urban agglomeration, IMERG shows a poorer performance in areas with higher urbanization levels. Thus, the IMERG products for coastal urban areas need considerable improvements, such as regionalized segmental corrections based on precipitation intensity and the adjustment of short-duration estimates by daily or sub-daily precipitation measurements.

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Section: Evaluation For Different Precipitation Intensitiesmentioning

confidence: 99%

Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China

2022

Remote Sensing

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“…Initial schemes used fundamental characteristics of radiation emitted from raindrops over the oceans to convert the observed brightness temperatures (Tbs) into rain rates. Over land, due to higher background emissivities, higher frequency channels had to be utilised such as the 89 GHz that first flew on the Special Sensor Microwave Imager (SSMI) from 1987 (see [9]), exploiting the scattering signal caused by precipitation-sized ice particles. Multi-channel retrieval schemes exploit the emission and scattering responses at different frequencies to improve the retrievals, although separate techniques are often required for ocean vs. land retrievals [18].…”

Section: Precipitation Retrievalsmentioning

confidence: 99%

“…While imagery of cloud tops (which allow measures of reflectivity, cloud top characteristics and cloud top temperature) are useful, the precipitation falling from the base of the cloud must be inferred from these cloud top properties. Consequently, the mainstay of current precipitation observations is based upon passive microwave (PMW) sensors that are sensitive to the hydrometeor particles within and falling from the base of the clouds (see [9]).…”

Section: Introductionmentioning

confidence: 99%

Precipitation Retrievals from Passive Microwave Cross-Track Sensors: The Precipitation Retrieval and Profiling Scheme

2021

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The retrieval of precipitation (snowfall and rainfall) from satellite sensors on a global basis is essential in aiding our knowledge and understanding of the Earth System and for many societal applications. Measurements from surface-based instruments are essentially limited to populated regions, necessitating the use of satellite-based observations to provide estimates of precipitation across the whole of the Earth’s surface. The temporal and spatial variability of precipitation requires adequate sampling, especially at finer resolutions. It is, therefore, necessary to exploit all available data from precipitation-capable satellites to ensure the proper representation of precipitation. To date, the estimation of precipitation using passive microwave observations has been largely concentrated upon the conically scanning imaging instruments, with relatively few techniques exploiting the observations made from the cross-track sounders. This paper describes the development of the Precipitation Retrieval and Profiling Scheme (PRPS) to retrieve precipitation from cross-track sensors, together with its performance against surface radar data and other satellite precipitation retrievals.

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“…Visible and IR techniques are capable of providing estimates of precipitation at relatively fine temporal and spatial scales from geostationary (GEO) and low Earth orbiting (LEO) platforms, but such estimates are indirect since they depend upon relationships between the cloud-top characteristics and precipitation at the surface [1]. Passive microwave (PMW) observations are more direct since hydrometeors are the main source of atmospheric attenuation and scattering [2]. However, since PMW sensors only occupy LEOs, multiple sensors are required to provide sufficient temporal and spatial coverage of the globe.…”

Section: Introductionmentioning

confidence: 99%

Precipitation Estimation from the NASA TROPICS Mission: Initial Retrievals and Validation

et al. 2022

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This paper describes the initial results of precipitation estimates from the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter-wave Sounder (TMS) using the Precipitation Retrieval and Profiling Scheme (PRPS). The TROPICS mission consists of a Pathfinder CubeSat and a constellation of six CubeSats, providing a low-cost solution to the frequent sampling of precipitation systems across the Tropics. The TMS instrument is a 12-channel cross-track scanning radiometer operating at frequencies of 91.655 to 204.8 GHz, providing similar resolutions to current passive microwave sounding instruments. These retrievals showcase the potential of the TMS instrument for precipitation retrievals. The PRPS has been modified for use with the TMS using a database based upon observations from current sounding sensors. The results shown here represent the initial postlaunch version of the retrieval scheme, as analyzed for the Pathfinder CubeSat launched on 30 June 2021. In terms of monthly precipitation estimates, the results fall within the mission specifications and are similar in performance to retrievals from other sounding instruments. At the instantaneous scale, the results are very promising.

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Introduction to Passive Microwave Retrieval Methods

Cited by 21 publications

References 50 publications

Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China

Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China

Precipitation Retrievals from Passive Microwave Cross-Track Sensors: The Precipitation Retrieval and Profiling Scheme

Precipitation Estimation from the NASA TROPICS Mission: Initial Retrievals and Validation

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