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Learn about the evolution, status, and preparation of the FengYun-3 series satellite instruments for Numerical Weather Prediction (NWP). Explore instrument suites, data quality, operational assimilation, collaborations, and more.
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THE STATUS OF FY-3C IN NWP AND THE PREPARATION OF FY-3D FOR NWP luqf@cma.gov.cn Qifeng Lu Chunqiang Wu, Yang Guo, Mi Liao, Shengli Wu, Miao Zhang, Dawei An, Xianjun Xiao, Fangli Dou, Juyang Hu National Satellite Meteorological Center ,CMA
Outline • The evolution of FY-3 for NWP • The status of FY3 in NWP • The preparation of FY-3D for NWP
1. The evolution of FY-3 for NWP Largest positive impact (per system) is obtained from microwave temperature sounding data Forecast sensitivity to observations (FSO) Is an adjoint based technique for assessing the influence of observing systems on forecast accuracy (from C. Cardinali, ECMWF)
ok The FY-3A/B/C/D/E Instrument Suites for NWP WindRAD C ,Ku HH, VV Infrared Atmospheric Sounder (IRAS) 20 channels (~HIRS/3) HIRAS(1370channels) Microwave Temperature Sounder (MWTS) 4 channel (~MSU) 13 channels 17 channels Microwave Radiation Imager 10 channels (~AMSR-E) Microwave Humidity Sounder (MWHS) 5 channel (~MHS) 15channels with channels at 118 GHz GNSS Radio-Occultation Sounder (GNOS) (~GPS)
Microwave temperature and humidity sounder Metop/AMSUA/MHS 90,150,183GHz, launched, 2006, On service. FY-3A/B Aqua/ HSB 90,150,183GHz, launched, 2002, On service. Suomi-NPP/ATMS 50-60,90GHz 150,183GHz, launched, 2009, On service. NOAA/ AMSU-A/B 50-60,90GHz 150,183GHz, launched, 1998, On service. FY-3C/D DMSP/ SSM/T-2 90,150,183GHz(5) launched, 1991, out of service. FY3D/ MWTHS 50-60GHz(17) 89GHz(1) 118GHZ(8) 150/166(1) 183GHZ(5) Launched, 2017 DMSP/ SSM/T 50-60GHz(7), launched, 1979, out of service. TIROS-N/ MSU 50-60GHz, launched, 1978, out of service. FY3C/ MWTHS 50-60GHz(13) 89GHz(1) 118GHZ(8) 150/166(1) 183GHZ(5) launched, 2013 FY3B/ MWTHS 50-60GHz(4) 150 (2) 183GHZ(3) launched, 2010 FY3A/ MWTHS 50-60GHz(4) 150 (2) 183GHZ(3) launched, 2008
2. The status of FY3 in NWP Brief review before FY-3C • Since 2008 FY-3 MWTS-1 has been implemented in CMA GRAPES; • Since 2009, four FY-3 instruments, MWTS-1, MWHS-1, IRAS (with clear sky route) and MWRI (with all-sky route) have been implemented in ECMWF IFS; • FY-3 MW sounders was well characterized, and the work was recognized by WMO award. FY-3A and FY-3B MWTS almost was planed to move to operational assimilation in Grapes and IFS around 2010 and 2011, but unfortunately the two instruments failed to work subsequently; • After 3-year monitoring of the MWHS-1 data quality, the FY-3B MWHS-1 is operationally assimilated since September 2014.
Characterize the MWTS The OMB comparison between FY-3A/MWTS and MetOp/AMSU-A Optimized Passband Specification MetOp AMSU-A Optimization+NonLinearity Correction PreLaunch Measurement Optimizer of Satellite Instrumental Parameters On-orbit (OSIPOn)
Optimizer of Satellite Instrumental Parameters On-orbit (OSIPOn)
Since FY-3C, closer collaborations was encouraged --improve the misunderstanding and fill the gap from requirements Share; early evaluation; preparation before launch Collaboration Team CMA ECMWF UKMO NWP(User) Feedback Improved FengYun Satellite Data Assimilation Manufacturer Feedback CMA/NSMC (Agency) Basic and general support (Cal/Val) The telecommunication conference is held since Dec 2014 to communicate the progress on evaluating, improving and assimilating FY data in NWP models
The comparable data quality of FY-3C sounding instruments to its counterparts MWTS-2 MWHS-2 & ATMS 183 GHz IRAS MWHS-2 Channel 118 GHz MWRI stdev(o - b)/K Channel
GNOS improvement from Mi Liao and Sean Healy • Operationally assimilation by CMA and ECMWF
FY3C MWHS-2 has been operationally assimilated and monitored in the Met Office global model on 15 March 2016, and in ECMWF IFS system on 4 April 2016 . • Operational assimilation of MWHS-2 with 183 GHz channels globally and GNOS in CMA/GRAPES have been activated in April 2016. • The transmittance of bufrized data by GTS started since 2017. • The GNOS wad operationally assimilated by ECMWF since March 2018.
Monitoring OMB against the instrumental parameter to indicate the performance on orbit Server Terminal: http://satellite.nsmc.org.cn Temperature of Black Body 北京华云星地通科技有限公司 Before QC After QC
Monitoring OMB against the instrumental parameter to indicate the performance on orbit 118.750.3 GHz
Monitoring OMB against the instrumental parameter to indicate the performance on orbit 118.750.3 GHz
Client Software 定制统计: 北京华云星地通科技有限公司
original High values of antenna emission have been observed from TMI and SSMIS. adjust the emissivity of hot reflector and cold reflector adjust the emissivity of hot reflector
3. The preparation of FY-3D for NWP Five payloads from FY-3D are of particular interest to NWP community • MicroWave Temperature Sounder 2 (MWTS-2) • MicroWave Humidity Sounder 2 (MWHS-2) • High spectral Infrared Atmospheric Sounder (HIRAS) • Global Navigation Satellite System Occultation SoundeR (GNOS); • Microwave Radiation Imager (MWRI)
3.1 The MWTS-2 NeDT Calibration accuracy (O-B) Calibration accuracy (ATMS Cross comparison )
The Stability of FY-3D MWTS Calibration update
3.2 The FY-3D MWHS-2 of NeDT FY-3C NedT FY-3D NedT Requirement NEDT Channels
CH2 CH1 CH3 CH4 CH5 CH6 CH7 CH8 CH9 CH10 CH11 CH12 CH13 CH14 3.2 The MWHS-2 of NeDT CH15
The FY-3D MWHS-2 of O-B FY-3D FY3D-CRTM FY3D-RTTOV FY3D-CRTM(FNL) Specification FY-3C FY3C-CRTM FY3C-RTTOVSpecification 2018/3/21-25 after cloud screening, ocean +/- 45 latitude
Distribution of A/D Bias (FY-3D/MWRI Before and After Correction)
Long time series data of Amazon(FY-3BCD/MWRI From 2010 to 2018)
3.4 The GNOS :Daily Occ. Number and Stopping Height Data used from 1st July to 15th July,2018
OSSE: Preparing FY-3D for NWP Improve the data precision and stability • Monitor the OMB and instrumental parameters to indicate the data quality • Characterize the instrumental biases • Control the data quality Support the earlier preparation of data assimilation • Generate the initial coefs of the fast radiative transfer modeling for NWP data assimilation • Simulate the sample data by RTM • Release the sample data to cooperative users (after the agreed coordination of CMA and WMO) • Prepare the assimilation in NWP model Optimize the performance • Evaluate/improve the data quality and its impact on NWP model