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Insights into the Microwave Instruments Onboard the Fengyun 3D Satellite:Data Quality and Assimilation in the Met Office NWP System 被引量:4
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作者 Fabien CARMINATI Nigel ATKINSON +1 位作者 brett candy Qifeng LU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2021年第8期1379-1396,共18页
This paper evaluates the microwave instruments onboard the latest Chinese polar-orbiting satellite, Fengyun 3D (FY- 3D). Comparing three months of observations from the Microwave Temperature Sounder 2 (MWTS-2), the Mi... This paper evaluates the microwave instruments onboard the latest Chinese polar-orbiting satellite, Fengyun 3D (FY- 3D). Comparing three months of observations from the Microwave Temperature Sounder 2 (MWTS-2), the Microwave Humidity Sounder 2 (MWHS-2), and the Microwave Radiation Imager (MWRI) to Met Office short-range forecasts, we characterize the instrumental biases, show how those biases have changed with respect to their predecessors onboard FY- 3C, and how they compare to the Advanced Technology Microwave Sounder (ATMS) onboard NOAA-20 and the Global Precipitation Measurement Microwave Imager (GMI). The MWTS-2 global bias is much reduced with respect to its predecessor and compares well to ATMS at equivalent channel frequencies, differing only by 0.36 ± 0.28 K (1σ) on average. A suboptimal averaging of raw digital counts is found to cause an increase in striping noise and an ascending- descending bias. MWHS-2 benefits from a new calibration method improving the 183-GHz humidity channels with respect to its predecessor and biases for these channels are within ± 1.9 K to ATMS. MWRI presents the largest improvements, with reduced global bias and standard deviation with respect to FY-3C;although, spurious, seemingly transient, brightness temperatures have been detected in the observations at 36.5 GHz (vertical polarization). The strong solar-dependent bias that affects the instrument on FY-3C has been reduced to less than 0.2 K on average for FY-3D MWRI. Experiments where radiances from these instruments were assimilated on top of a full global system demonstrated a neutral to positive impact on the forecasts, as well as on the fit to the background of independent instruments. 展开更多
关键词 microwave remote sensing numerical weather prediction data assimilation
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Assessment and Assimilation of FY-3 Humidity Sounders and Imager in the UK Met Office Global Model 被引量:3
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作者 Fabien CARMINATI brett candy +1 位作者 William BELL Nigel ATKINSON 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2018年第8期46-58,共13页
China's FengYnn 3 (FY-3) polar orbiting satellites axe set to become an important sonrce of observational data for nu- merical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies over... China's FengYnn 3 (FY-3) polar orbiting satellites axe set to become an important sonrce of observational data for nu- merical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies over the next two decades. As part of the Climate Science for Service Partnership China (CSSP China) prograln, FY-3B Microwave Humidity Sounder 1 (MWHS-1) and FY-3C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation. This represents the first time observations from China's polar orbiting satellites have been used in the UK's global NWP model. Since 2016, continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies. Nonetheless, MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%, respectively, and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%. The observations from the Microwave Radiation Imager (MWRI) also are a potentially significant source of benefits for NWP models, but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation. This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data. 展开更多
关键词 Microwave Humidity Sounder Microwave Radiation Imager numerical weather prediction
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Remote sensing and analysis of tropical cyclones:Current and emerging satellite sensors 被引量:1
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作者 Lucrezia Ricciardulli Brian Howell +14 位作者 Christopher R.Jackson Jeff Hawkins Joe Courtney Ad Stoffelen Sebastian Langlade Chris Fogarty Alexis Mouche William Blackwell Thomas Meissner Julian Heming brett candy Tony McNally Masahiro Kazumori Chinmay Khadke Maria Ana Glaiza Escullar 《Tropical Cyclone Research and Review》 2023年第4期267-293,共27页
This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Orga... This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Organization(WMO)report prepared for the 10th International Workshop on Tropical Cyclones(IWTC),held in Bali in December 2022,and its objective is to present updates in TC research and operation every four years.Here we focus on updates regarding the most recent space-based TC observations,and we cover new methodologies and techniques using polar orbiting sensors,such as C-band synthetic aperture radars(SARs),L-band and combined C/X-band radiometers,scatterometers,and microwave imagers/sounders.We additionally address progress made with the new generation of geostationary and small satellites,and discuss future sensors planned to be launched in the next years.We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research,and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future. 展开更多
关键词 Tropical cyclones Surface wind Satellite sensors Operations
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