Shoichi Shige

Bio: Shoichi Shige is an academic researcher from Kyoto University. The author has contributed to research in topics: Precipitation & Latent heat. The author has an hindex of 28, co-authored 86 publications receiving 3321 citations. Previous affiliations of Shoichi Shige include Osaka Prefecture University & Japan Aerospace Exploration Agency.

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

Abstract: 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.

A Kalman Filter Approach to the Global Satellite Mapping of Precipitation (GSMaP) from Combined Passive Microwave and Infrared Radiometric Data

Abstract: A system has been developed and implemented that integrates passive microwave radiometer data with infrared radiometer data in order to have high temporal (1 hour) and spatial (0.1 degree) resolution global precipitation estimates. The product (GSMaP_MVK) is produced based on a Kalman filter model that refines the precipitation rate propagated based on the atmospheric moving vector derived from two successive IR images. The proposed method was evaluated and compared with other high-resolution precipitation products and the ground-based data collected by the Automated Meteorological Data Acquisition System (AMeDAS) near Japan. It was clearly shown that the approach described in this paper performed better than without the Kalman filter, and the time series of the hourly global precipitation pattern demonstrated the potential capabilities for weather monitoring and typhoon tracking. The GSMaP_MVK product achieved a score comparable to the CMORPH and the 3B42RT products.

GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation

Abstract: This paper describes a precipitation-retrieval algorithm for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) that was developed under the Global Satellite Mapping of Precipitation project (GSMaP) by improving the authors' previous algorithm. The basic idea of the GSMaP algorithm is to find the optimal precipitation for which the brightness temperatures (TBs) calculated by the radiative-transfer model (RTM) fit best with the observed TBs. The main improvements of the GSMaP algorithm over the authors' previous work are as follows: (1) use of precipitation-related variable models (precipitation profiles, drop-size distribution, etc.) and precipitation detection and inhomogeneity estimation methods based on TRMM observation studies; (2) use of scattering signals of the TMI Polarization-Corrected Temperature (PCT) at 37 and 85 GHz (PCT37, PCT85) and scattering-signal correction for tall precipitation (thickness between precipitation top level and freezing level (Dtop) larger than 6 km) over land and coastal areas. In order to validate the GSMaP algorithm, we compared its retrievals from TMI TBs in 1998 with the TRMM Precipitation Radar (PR) and Goddard Profiling Algorithm (GPROF) retrievals (2A12 version 6). The results show that (1) over land and coastal areas, the GSMaP retrievals agreed better with PR than GPROF for tall precipitation (Dtop>4 km) weaker than 10 mm h-1, while both GSMaP and GPROF underestimated PR precipitation rates for precipitation heavier than 10 mm h-1; (2) over ocean, the GSMaP retrievals agreed better with PR than GPROF for precipitation heavier than 10 mm h-1, while GSMaP slightly overestimated precipitation weaker than 10 mm h-1 compared to PR and GPROF; (3) The GSMaP algorithm failed to detect some precipitation areas weaker than 2 mm h-1 over sub-tropical oceans. Experimental algorithms with different precipitation-related variable models and retrieval methods using scattering signals were applied to TMI TBs in July 1998 to examine the effect of the above improvements to the GSMaP algorithm. The results show that the improvement of the precipitation profile alleviated the underestimation of precipitation heavier than 10 mm h-1 over land and coastal areas, that the combined use of new physical-related variable models alleviated the underestimation of precipitation heavier than 10 mm h-1 over ocean, and that the use of PCT37 and scattering-signal correction reduced the overestimation of tall precipitation (Dtop>4 km) weaker than 10 mm h-1 over land and coastal areas.

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part I: Development of a Model-Based Algorithm

Abstract: An algorithm, the spectral latent heating (SLH) algorithm, has been developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission precipitation radar with a cloud-resolving model (CRM). Heating-profile lookup tables for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were produced with numerical simulations of tropical cloud systems in the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. For convective and shallow stratiform regions, the lookup table refers to the precipitation-top height (PTH). For the anvil region, on the other hand, the lookup table refers to the precipitation rate at the melting level instead of PTH. A consistency check of the SLH algorithm was also done with the CRM-simulated outputs. The first advantage of this algorithm is that differences of heating profiles between the shallow convective stage and the deep convective stage can be retrieved. This is a r...

Retrieval of Latent Heating from TRMM Measurements

Abstract: Precipitation, in driving the global hydrological cycle, strongly influences the behavior of the Earth's weather and climate systems and is central to their variability. Two-thirds of the global rainfall occurs over the Tropics, which leads to its profound effect on the general circulation of the atmosphere. This is because its energetic equivalent, latent heating (LH), is the tropical convective heat engine's primary fuel source as originally emphasized by Riehl and Malkus (1958). At low latitudes, LH stemming from extended bands of rainfall modulates large-scale zonal and meridional circulations and their consequent mass overturnings (e.g., Hartmann et al. 1984; Hack and Schubert 1990). Also, LH is the principal energy source in the creation, growth, vertical structure, and propagation of long-lived tropical waves (e.g., Puri 1987; Lau and Chan 1988). Moreover, the distinct vertical distribution properties of convective and stratiform LH profiles help influence climatic outcomes via their tight control on large-scale circulations (Lau and Peng 1987; Nakazawa 1988; Sui and Lau 1988; Emanuel et al. 1994; Yanai et al. 2000; Sumi and Nakazawa 2002; Schumacher et al. 2004). The purpose of this paper is to describe how LH profiles are being derived from satellite precipitation rate retrievals, focusing on those being made with Tropical Rainfall Measuring Mission (TRMM) satellite measurements.

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

The Global Precipitation Measurement Mission

Abstract: Precipitation affects many aspects of our everyday life. It is the primary source of freshwater and has significant socioeconomic impacts resulting from natural hazards such as hurricanes, floods, droughts, and landslides. Fundamentally, precipitation is a critical component of the global water and energy cycle that governs the weather, climate, and ecological systems. Accurate and timely knowledge of when, where, and how much it rains or snows is essential for understanding how the Earth system functions and for improving the prediction of weather, climate, freshwater resources, and natural hazard events. The Global Precipitation Measurement (GPM) mission is an international satellite mission specifically designed to set a new standard for the measurement of precipitation from space and to provide a new generation of global rainfall and snowfall observations in all parts of the world every 3 h. The National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) ...

APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges

Abstract: A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, ...

A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons

Abstract: In this paper, we present a comprehensive review of the data sources and estimation methods of 30 currently available global precipitation data sets, including gauge-based, satellite-related, and reanalysis data sets. We analyzed the discrepancies between the data sets from daily to annual timescales and found large differences in both the magnitude and the variability of precipitation estimates. The magnitude of annual precipitation estimates over global land deviated by as much as 300 mm/yr among the products. Reanalysis data sets had a larger degree of variability than the other types of data sets. The degree of variability in precipitation estimates also varied by region. Large differences in annual and seasonal estimates were found in tropical oceans, complex mountain areas, northern Africa, and some high-latitude regions. Overall, the variability associated with extreme precipitation estimates was slightly greater at lower latitudes than at higher latitudes. The reliability of precipitation data sets is mainly limited by the number and spatial coverage of surface stations, the satellite algorithms, and the data assimilation models. The inconsistencies described limit the capability of the products for climate monitoring, attribution, and model validation.