Dr. Masahiro Kazumori Profile

Dr. Masahiro Kazumori

at Japan Meteorological Agency

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Proceedings Article | 9 November 2012 Paper

The assimilation of satellite microwave observation in JMA's meso-scale model

Masahiro Kazumori

Proceedings Volume 8528, 85280U (2012) https://doi.org/10.1117/12.977304

KEYWORDS: Microwave radiation, Satellites, Imaging systems, Data modeling, Meteorology, Humidity, Radar, Earth observing sensors, Atmospheric modeling, Clouds

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Accurate Numerical Weather Prediction (NWP) is one of the essential information for natural disaster prevention. Japan Meteorological Agency (JMA) has been operating a Meso-scale model (MSM). The target of the MSM is to provide guidance for issuing warnings or making very short-range forecasts of precipitation to cover Japan and its surrounding areas. In order to produce accurate precipitation forecasts by MSM, realistic moisture fields as initial conditions are necessary. The initial fields are produced in analyses with a four dimensional variational data assimilation method. The initial fields are updated eight times per day to capture rapid change of mesoscale weather conditions. Because Japan is a country surrounded by ocean, moisture information over the ocean is a key for the accurate humidity analysis and the precipitation forecasting. Observations of microwave imagers in space contain the moisture information over the ocean. The microwave imager data are available in wide coverage under all weather conditions and play an important role in the analysis. Microwave brightness temperature in clear sky condition and retrieved precipitation in rainy condition from various microwave imagers are assimilated in the analysis. In this study, Global Change Observation Mission 1st Water (GCOM-W1) / Advanced Microwave Scanning Radiometer-2 (AMSR2) data were newly incorporated in the analysis. From the preliminary AMSR2 data assimilation experiment, improvements of the humidity analysis and the precipitation forecasting were found. The results suggest the use of multiple satellite data is necessary to produce realistic moisture fields as the initial condition for the operational NWP.

Proceedings Article | 13 October 2010 Paper

Status of GCOM-W1 development and expected meteorological applications

Daisaku Uesawa, Keiji Imaoka, Misako Kachi, Hideyuki Fujii, Masahiro Kazumori, Marehito Kasahara, Norimasa Ito, Keizo Nakagawa, Taikan Oki

Proceedings Volume 7826, 782607 (2010) https://doi.org/10.1117/12.866138

KEYWORDS: Satellites, Meteorology, Microwave radiation, Environmental sensing, Climatology, Calibration, Algorithm development, Sensors, Earth observing sensors, Climate change

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The Global Change Observation Mission (GCOM) consists of two polar orbiting satellite observing systems, GCOM-W (Water) and GCOM-C (Climate), and three generations to achieve global and long-term monitoring of the Earth. GCOM-W1 is the first satellite of the GCOM-W series and scheduled to be launched in Japanese fiscal year 2011. The mission instrument will be the Advanced Microwave Scanning Radiometer-2 (AMSR2), which is the successor instrument of AMSR on ADEOS-II and AMSR-E on EOS Aqua platform. Development of the GCOM-W1 system progresses favorably. The mechanical and thermal tests using the GCOM-W1 structural and thermal model were successfully completed. The GCOM-W1 and AMSR2 proto-flight models are under their proto-flight testing. In the middle of 2010, AMSR2 will be delivered to satellite system prior to the system proto-flight test of GCOM-W1. Retrieval algorithms are being developed by collaborating with principal investigators. Algorithm comparisons or integrations are now underway for several algorithms to find best available algorithms for post-launch processing. Also, maintaining and extending the validation sites such as the Mongolian Plateau site for soil moisture is being implemented. In addition to the long-term climate variability monitoring, meteorological applications will be the most important operational utilization of AMSR2 data. Currently, AMSR-E data are being used for numerical prediction through data assimilation at several meteorological agencies. Also, retrieved geophysical parameters such as sea surface temperature are being used for diagnostics of the weather and ocean variations.

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