In a recent study (Haddad and Park, 2009), a method was proposed to use co-located simultaneous observations by the space-borne Tropical Rainfall Measuring Mission (TRMM) precipitation radar and microwave imager to train the microwave radiometer to retrieve vertical profiles of precipitation in the absence of radar observations. This radartrained passive-microwave approach was developed for mid...

A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ...

This paper presents a new scheme that classifies convective and stratiform (C/S) precipitation areas over oceans using microwave brightness temperature. In this scheme, data are first screened to eliminate nonraining pixels. For raining pixels, C/S indices are computed from brightness temperatures and their variability for emission (19 and 37 GHz) and scattering (85 GHz). Since lower-resolution...

A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (TB) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated TBs for stratiform precipitation events owing to...

MnZnFe2O4 ferrite nanoparticles were prepared by co-precipitation method using a microwave heating system at temperature of 100 C. X-ray diffraction reveals the samples as prepared are pure ferrite nanocrystalline phase, transmission electron microscopy image analysis shows particles are in agglomeration state with an average size of about 10 nm, furthermore, crystal size of samples are increas...

Artificial Neural Network (ANN) technique has been used for the estimation of precipitation, mainly from passive and active microwave measurements from space. ANN has been used to estimate precipitation using TRMM Microwave Imager (TMI) onboard Tropical Rainfall Measuring Mission (TRMM) satellite. A precipitation algorithm designed to generate rainfall estimates using a combination of TMI and T...

[1] Using existing data sets of spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios....

Highlights of the 6th International GEWEX Science Conference and Joint GEWEX/iLEAPS Sessions Melbourne, Australia, 24–28 August 2009 See page 11 Global Precipitation Climatology Project (GPCP) Version 2.1 precipitation climatology, 1979–2008, in mm/day. This combination of satellite estimates based on infrared, microwave, and sounding data, together with gauge analyses, yields a global average ...

We develop an over-ocean rainfall retrieval algorithm for the Advanced Microwave Sounding Unit (AMSU) based on the Global Satellite Mapping of Precipitation (GSMaP) microwave radiometer algorithm. This algorithm combines an emissionbased estimate from brightness temperature (Tb) at 23 GHz and a scattering-based estimate from Tb at 89 GHz, depending on a scattering index (SI) computed from Tb at...

Precipitation is one of the most important parameters on the earth system, and the global distribution of precipitation and its change are essential data for modeling the water cycle, maintaining the ecosystem environment, agricultural production, improvements of the weather forecast precision, flood warning and so on. In the GPM (Global Precipitation Measurement) project, the microwave radiome...