Kazumasa Aonashi

Global Precipitation Map using Satelliteborne Microwave Radiometers by the GSMaP Project : Production and Validation

This paper documents the production and validation of retrieved rainfall data obtained from satellite-borne microwave radiometers by the Global Satellite Mapping of Precipitation (GSMaP) Project. Using various attributes of precipitation derived from Tropical Rainfall Measuring Mission (TRMM) satellite data, the GSMaP has implemented hydrometeor profiles derived from Precipitation Radar (PR), statistical rain/no-rain classification, and scattering algorithms using polarization-corrected temperatures (PCTs) at 85.5 and 37 GHz. Combined scattering-based surface rainfalls are computed depending on rainfall intensities. PCT85 is not used for stronger rainfalls, because strong depressions of PCT85 are related to tall precipitation-top heights. Therefore, for stronger rainfalls, PCT37 is used, with PCT85 used for weaker rainfalls. With the suspiciously strong rainfalls retrieved from PCT85 deleted, the combined rainfalls correspond well to the PR rain rates over land. The GSMaP algorithm for the TRMM Microwave Imager (TMI) is validated using the TRMM PR, ground radar [Kwajalein (KWAJ) radar and COBRA], and Radar Automated Meteorological Data Acquisition System (AMeDAS) precipitation analysis (RA). Monthly surface rainfalls retrieved from six microwave radiometers (GSMaP_MWR) are compared with the gauge-based dataset. Rain rates retrieved from the TMI (GSMaP_TMI) are in better agreement with the PR estimates over land everywhere except over tropical Africa in the boreal summer. Validation results of the KWAJ radar and COBRA show a good linear relationship for instantaneous rainfall rates, while validation around Japan using the RA shows a good relationship in the warm season. Poor results, connected to weak-precipitation cases, are found in the cold season around Japan.

Results of WetNet PIP-2 Project

The second WetNet Precipitation Intercomparison Project (PIP-2) evaluates the performance of 20 satellite precipitation retrieval algorithms, implemented for application with Special Sensor Microwave/Imager (SSM/I) passive microwave (PMW) measurements and run for a set of rainfall case studies at full resolution‐instantaneous space‐timescales. The cases are drawn from over the globe during all seasons, for a period of 7 yr, over a 608N‐ 178S latitude range. Ground-based data were used for the intercomparisons, principally based on radar measurements but also including rain gauge measurements. The goals of PIP-2 are 1) to improve performance and accuracy of different SSM/I algorithms at full resolution‐instantaneous scales by seeking a better understanding of the relationship between microphysical signatures in the PMW measurements and physical laws employed in the algorithms; 2) to evaluate the pros and cons of individual algorithms and their subsystems in order to seek optimal ‘‘front-end’’ combined algorithms; and 3) to demonstrate that PMW algorithms generate acceptable instantaneous rain estimates. It is found that the bias uncertainty of many current PMW algorithms is on the order of 630%. This level is below that of the radar and rain gauge data specially collected for the study, so that it is not possible to objectively select a best algorithm based on the ground data validation approach. By decomposing the intercomparisons into effects due to rain detection (screening) and effects due to brightness temperature‐rain rate conversion, differences among the algorithms are partitioned by rain area and rain intensity. For ocean, the screening differences mainly affect the light rain rates, which do not contribute significantly to area-averaged rain rates. The major sources of differences in mean rain rates between individual algorithms stem from differences in how intense rain rates are calculated and the maximum rain rate allowed by a given algorithm. The general method of solution is not necessarily the determining factor in creating systematic rain-rate differences among groups of algorithms, as we find that the severity of the screen is the dominant factor in producing systematic group differences among land algorithms, while the input channel selection is the dominant factor in producing systematic group differences among ocean algorithms. The significance of these issues are examined through what is called ‘‘fan map’’ analysis. The paper concludes with a discussion on the role of intercomparison projects in seeking improvements to algorithms, and a suggestion on why moving beyond the ‘‘ground truth’’ validation approach by use of a calibration-quality forward model would be a step forward in seeking objective evaluation of individual algorithm performance and optimal algorithm design.

Improvement of TMI Rain Retrievals in Mountainous Areas

AbstractHeavy rainfall associated with shallow orographic rainfall systems has been underestimated by passive microwave radiometer algorithms owing to weak ice scattering signatures. The authors improve the performance of estimates made using a passive microwave radiometer algorithm, the Global Satellite Mapping of Precipitation (GSMaP) algorithm, from data obtained by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) for orographic heavy rainfall. An orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. Rainfall estimates made using the revised GSMaP algorithm are in better agreement with e...

Passive Microwave Precipitation Retrievals Using TMI during the Baiu Period of 1998. Part I: Algorithm Description and Validation

Abstract The Baiu front is a subtropical convergence zone that is formed over east Asia in early summer (hereinafter referred to as the Baiu period). In this study, an overocean precipitation retrieval algorithm is developed to retrieve precipitation for the Baiu period from brightness temperatures (TBs) supplied by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The basic idea of the algorithm is to find the optimal precipitation that gives radiative transfer model (RTM)-calculated, field-of-view–averaged TBs that fit best with the TMI TBs at 10.7, 19.7, and 85.5 GHz with vertical polarization. For the RTM calculation, spatial precipitation inhomogeneity and freezing-level height are estimated from TMI TBs. The optimal precipitation with 10-km resolution is obtained by solving the gradient equation of a cost function that is a weighted sum of squares of TB differences between the TMI observation and the RTM calculation. Precipitation retrieved by this algorithm was validated using ...

Improvement of High-Resolution Satellite Rainfall Product for Typhoon Morakot (2009) over Taiwan

The authors improve the high-resolution Global Satellite Mapping of Precipitation (GSMaP) product for Typhoon Morakot (2009) over Taiwan by using an orographic/nonorographic rainfall classification scheme. For the estimation of the orographically forced upward motion used in the orographic/nonorographic rainfall classification scheme, the optimal horizontal length scale for averaging the elevation data is examined and found to be about 50km. It is inferred that as the air ascends en masse on the horizontal scale, it becomes unstableandconvectiondevelops.Theorographic/nonorographic rainfallclassification schemeis extendedto the GSMaP algorithm for all passive microwave radiometers in orbit, including not just microwave imagers butalsomicrowavesounders. Theretrievedrainfallrates,togetherwithinfraredimages,areusedforthehighresolution rainfall products, which leads to much better agreement with rain gauge observations.

A Comparison of Cloud and Rainfall Information from Instantaneous Visible and Infrared Scanner and Precipitation Radar Observations over a Frontal Zone in East Asia during June 1998

Abstract The comparison between cloud information and rainfall is studied using infrared and radar data from the Tropical Rainfall Measuring Mission. Cloud information from the visible and infrared scanner was compared with rain information from precipitation radar (PR) for rain cases assembled during June 1998 over a frontal zone in east Asia. The authors selected the following four parameters: 1) radiance ratio of 0.6 and 1.6 μm [channel 1/channel 2 (Ch1/Ch2)], 2) brightness temperature difference between 11 and 12 μm (BTD45), 3) brightness temperature difference between 3.8 and 11 μm (BTD34), and 4) brightness temperature (TBB) in channel 4 (Ch4) as the cloud information. The flags of “rain certain,” stratiform rain, brightband existence, and convective rain observed by PR, and integrated rain rate from the rain bottom to rain top were used as the rainfall information. From the comparison between rain–no-rain information by PR and the four cloud parameters, it is found that values of the radiance ratio...

The GSMaP Precipitation Retrieval Algorithm for Microwave Sounders—Part I: Over-Ocean Algorithm

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 emission-based 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 both 89 and 150 GHz. Precipitation inhomogeneities are also taken into account. The GSMaP-retrieved rainfall from the AMSU (GSMaP_AMSU) is compared with the National Oceanic and Atmospheric Administration (NOAA) standard algorithm (NOAA_AMSU)-retrieved data using Tropical Rainfall Measuring Mission (TRMM) data as a reference. Rain rates retrieved by GSMaP_AMSU have better agreement with TRMM estimates over midlatitudes during winter. Better estimates over multitudes over winter are given by the use of Tb at 23 GHz in the GSMaP_AMSU algorithm. It was also shown that GSMaP_AMSU has higher rain detection than NOAA_AMSU.

The use of GPS measurements for water vapor determination

Abstract A workshop on the use of Global Positioning System (GPS) measurements in weather and climate with emphasis on water vapor determination, was organized by the National Environmental Research Councils (NERC) Environmental Systems Science Centre (ESSC), at the University of Reading, Reading, United Kingdom, and took place there 29–31 August 2001. This paper gives a broad overview and general background of the use of GPS data for weather and climate. It outlines the objectives of the workshop and presents ongoing national, regional, and international activities both for ground-based and satellite-based systems. This includes work in the United States, China, and Japan, and different European efforts, including activities under European Community programs. Data assimilation of GPS data for weather prediction and climate is discussed as are ways in which to develop GPS-based systems to become an integrated part of the World Weather Watch. This includes ways of systematically using GPS data from the in...

Gauge adjusted global satellite mapping of precipitation (GSMaP_Gauge)

Precipitation is one of the most important resources for human activity, and global distribution of precipitation amount and its change are essential data for modeling the water cycle and global energy cycle. Space-borne Passive Microwave Radiometers (PMRs) are working on many satellites. PMR observes emission and scattering from precipitation and provide uniform global data. The Global Satellite Mapping of Precipitation Moving Vector with Kalman-filter (GSMaP_MVK) estimates hourly and 0.1 degree gridded precipitation map from PMRs. Because land is radiometrically warm region, estimation of precipitation over land is difficult. Global precipitation over land, however, is most important for human activity, such as management of water and flood warning. We are developing a gauge adjusted algorithm for GSMaP (GSMaP_Gauge). In this paper, we show performance of the algorithm and some initial evaluation tests. We introduce the GSMaP_Gauge algorithm and show the validation of the algorithm.

Wakasa Bay: An AMSR Precipitation Validation Campaign

The “ Wakasa Bay Experiment” was conducted in order to refine error models for oceanic precipitation from the Advanced Microwave Sounding Radiometer-Earth Observing System (AMSR-E) measurements and to develop algorithms for snowfall. The NASA P-3 aircraft was equipped with microwave radiometers, covering a frequency range of 10.7–340 GHz, and radars at 13.4, 35.6, and 94 GHz, and was deployed to Yokota Air Base in Japan for flights from 14 January to 3 February 2003. For four flight days (27–30 January) a Gulfstream II aircraft provided by Core Research for Environmental Science and Technology (CREST), carrying an extensive cloud physics payload and a two-frequency (23.8 and 31.4 GHz) microwave radiometer, joined the P-3 for coordinated flights. The Gulfstream II aircraft was part of the “Winter Mesoscale Convective Systems Observations over the Sea of Japan in 2003” (“WMO-03”) field campaign sponsored by Japan Science and Technology Corporation (JST). Extensive data were taken, which addressed all of the...