Status of GCOM-W1/AMSR2 development and science activities

Kachi, Misako; Imaoka, Keiji; Fujii, Hideyuki; Shibata, Akira; Kasahara, Marehito; Iida, Yasuhiko; Ito, Nobuyasu; Nakagawa, Kyuya; Shimoda, Haruhisa

doi:10.1117/12.801228

Cited by 16 publications

(11 citation statements)

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“…All-time and near all-weather detection make microwave imager data unique for the retrieval of surface meteorological parameters [3]. Currently, spaceborne microwave imagers include the Global Precipitation Measurement (GPM) Microwave Imager (GMI) [4], the full polarization microwave radiometer (WindSat) onboard the experimental Coriolis satellite of the U.S. Department of Defense, the Microwave Radiation Imager (MWRI) onboard the second-generation Polar Orbiting Meteorological Satellite FY-3 [5], and the Advanced Microwave Scanning Radiometer 2 (AMSR-2) onboard Japan's Phase I Global Change Observation Satellite for the Water Cycle (GCOM-W1) [6], which are installed on polar-orbiting meteorological satellites to improve the detection ability of surface remote sensing. Measurements over oceans from microwave imagery can be used to retrieve total atmospheric water vapor content [7] and sea surface temperature (SST) [8].…”

Section: Introductionmentioning

confidence: 99%

A New Restoration Method for Radio Frequency Interference Effects on AMSR-2 over North America

2019

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Observations from spaceborne microwave imagers are important sources of land surface information. However, the low-frequency channels of microwave imagers are easily interfered with by active radio signals with similar frequencies. Radio frequency interference (RFI) signals are widely distributed because of the lack of frequency protection, which seriously hinders the application of microwave imager data in data assimilation and retrieval research. In this paper, a new data restoration method is proposed based on principal component analysis (PCA). Both the ideal and real reconstruction experiments show that the new method can effectively repair abnormal observations interfered by RFI compared with the commonly used Cressman interpolation method because observation information over the whole selected domain is used for restoration in the new method, whereas Cressman interpolation uses only a selection of data around the target observation. The observation errors in the data with RFI can be reduced by one order of magnitude by means of the new method and little artificial information is introduced. One-week restoration validation also proves that the new method has a stable accuracy and broad application prospects.

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Section: Introductionmentioning

confidence: 99%

A New Restoration Method for Radio Frequency Interference Effects on AMSR-2 over North America

2019

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“…These include observations from the Special Sensor Microwave Imager onboard the Defense Meteorological Satellite Program series of satellites (Weng & Grody, 1994), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and its successor, the Global Precipitation Measurement (GPM) microwave imager (Duncan & Kummerow, 2016;Kummerow et al, 2001), and the Advanced Microwave Scanning Radiometer EOS (AMSR-E) carried by the Aqua satellite and its successor, the AMSR2 onboard the Global Change Observation Mission-Water 1 satellite (Kachi et al, 2008 FengYun-3B/C MWRI observations from both midmorning and afternoon orbits are available for the first time. These include observations from the Special Sensor Microwave Imager onboard the Defense Meteorological Satellite Program series of satellites (Weng & Grody, 1994), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and its successor, the Global Precipitation Measurement (GPM) microwave imager (Duncan & Kummerow, 2016;Kummerow et al, 2001), and the Advanced Microwave Scanning Radiometer EOS (AMSR-E) carried by the Aqua satellite and its successor, the AMSR2 onboard the Global Change Observation Mission-Water 1 satellite (Kachi et al, 2008 FengYun-3B/C MWRI observations from both midmorning and afternoon orbits are available for the first time.…”

Section: Introductionmentioning

confidence: 99%

“…Satellite microwave imager observations have been widely used to retrieve LWP from around the globe. These include observations from the Special Sensor Microwave Imager onboard the Defense Meteorological Satellite Program series of satellites (Weng & Grody, 1994), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and its successor, the Global Precipitation Measurement (GPM) microwave imager (Duncan & Kummerow, 2016;Kummerow et al, 2001), and the Advanced Microwave Scanning Radiometer EOS (AMSR-E) carried by the Aqua satellite and its successor, the AMSR2 onboard the Global Change Observation Mission-Water 1 satellite (Kachi et al, 2008) FengYun-3B/C MWRI observations from both midmorning and afternoon orbits are available for the first time.…”

Section: Introductionmentioning

confidence: 99%

Diurnal Variation of Liquid Water Path Derived From Two Polar‐Orbiting FengYun‐3 MicroWave Radiation Imagers

Tang

Zou

2018

Geophysical Research Letters

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MicroWave Radiation Imagers (MWRIs) onboard the afternoon FengYun‐3B (FY‐3B) and midmorning FengYun‐3C (FY‐3C) satellites provide global observations almost 4 times a day at any location. This study examines the diurnal cycle of the liquid water path (LWP) over the southeast Pacific Ocean using MWRI data. A double‐difference calibration method is first used to evaluate the MWRI calibration bias based on Tropical Rainfall Measuring Mission Microwave Imager (TMI) measurements. LWP diurnal cycle characteristics are derived from FY‐3B/C MWRI data measured in 2014. The diurnal variation of LWP from combined FY‐3B/C MWRI measurements are consistent with that derived from Tropical Rainfall Measuring Mission Microwave Imager data. Maximum and minimum LWPs occurred in the early morning and afternoon, respectively. The largest diurnal amplitude (~40% of the mean LWP) was located near 85°W/20°S. The diurnal amplitude varied from season to season. MWRI data can provide important constraints for models simulating the cloud diurnal cycle.

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“…This conical scan mechanism allows AMSR2 to acquire a set of daytime and nighttime data with more than 99% coverage of the Earth every 2 days. In addition, the AMSR2 instrument is a dual polarized total power microwave radiometer system with six frequency bands ranging from 7 GHz to 89 GHz [44]. Therefore, the AMSR2 contributes to daily soil moisture monitoring, regardless of cloud cover during the day and night.…”

Section: Multi-sensor Collaborationmentioning

confidence: 99%

Spatial Pattern and Temporal Variation Law-Based Multi-Sensor Collaboration Method for Improving Regional Soil Moisture Monitoring Capabilities

Zhang

Chen

2014

Remote Sensing

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Abstract:Regional soil moisture distributions and changes are critical for agricultural production and environmental modeling. Currently, hundreds of satellite sensors exist with different soil moisture observation capabilities. However, multi-sensor collaborative observation mechanisms for improving regional soil moisture monitoring capabilities are lacking. In this study, a Spatial pattern and Temporal variation law-based Multi-sensor Collaboration (STMC) method is proposed to solve this problem. The first component of the STMC method deduces the regional soil moisture distribution and variation patterns based on time stability theory and long-term statistical analyses. The second component of the STMC method detects potential anomalous soil moisture events and immediately triggers the high spatial resolution sensor with the soonest pass-over time. In the detection phase, an anomalous soil moisture judgment (ASMJ) algorithm and high temporal resolution sensors (the Advanced Microwave Scanning Radiometer 2 (AMSR2)) were utilized. Experiments conducted in Hubei province, China, demonstrated that the proposed STMC method was capable of accurately identifying of anomalous soil moisture conditions caused by waterlogging and drought events. Additionally, we observed that the STMC method combined the advantages of different long-term observation, high temporal, and high spatial resolution sensors synergistically for monitoring purposes.

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Status of GCOM-W1/AMSR2 development and science activities

Cited by 16 publications

References 0 publications

A New Restoration Method for Radio Frequency Interference Effects on AMSR-2 over North America

A New Restoration Method for Radio Frequency Interference Effects on AMSR-2 over North America

Diurnal Variation of Liquid Water Path Derived From Two Polar‐Orbiting FengYun‐3 MicroWave Radiation Imagers

Spatial Pattern and Temporal Variation Law-Based Multi-Sensor Collaboration Method for Improving Regional Soil Moisture Monitoring Capabilities

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