Biases’ Characteristics Assessment of the HY-2B Scanning Microwave Radiometer (SMR)’s Observations
The second Chinese ocean dynamic environment satellite Haiyang-2B (HY-2B), carrying a scanning microwave radiometer (SMR) to provide information on the ocean and atmosphere, was successfully launched on 25 October 2018. Before the data assimilation, it is necessary to characterize and evaluate the b...
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Published in | Remote sensing (Basel, Switzerland) Vol. 15; no. 4; p. 889 |
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Abstract | The second Chinese ocean dynamic environment satellite Haiyang-2B (HY-2B), carrying a scanning microwave radiometer (SMR) to provide information on the ocean and atmosphere, was successfully launched on 25 October 2018. Before the data assimilation, it is necessary to characterize and evaluate the biases of the HY-2B SMR observations. This study is the first to conduct a systematic assessment of the SMR radiance data based on observation minus background simulation (O-B). Three types of numerical weather prediction (NWP) datasets, including ECMWF Reanalysis v5 (ERA5), the analysis fields from the NCEP Global Forecast System (NCEP-GFS), and the analysis fields from the Global Regional Assimilation and Prediction System-Global Forecast System (GRAPES-GFS), were used as input information for RTTOV v12.3 to simulate the SMR’s observed brightness temperature (TB) under clear-sky conditions. Study results showed that the O-B biases and IQR of the SMR for most channels were within −2.5–0.4 K and smaller than 4 K, respectively. The SMR observations were generally consistent with the RTTOV simulations, even based on the different NWP fields. These results indicate a good prospect for the assimilated application of HY-2B SMR radiance data. However, due to the impact of RFI, the SMR’s descending data for two 10.7 GHz channels showed some significant positive biases larger than 50 K over the seas of the European region. In addition, it seems that the bias characteristics of the SMR’s ascending data were obviously different from those of the descending data. It was also found that the variation trend of scan-position-dependent bias was generally stable for the SMR’s ascending data but fluctuates significantly for the descending data, with a maximum amplitude greater than 0.7 K for some channels. |
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AbstractList | The second Chinese ocean dynamic environment satellite Haiyang-2B (HY-2B), carrying a scanning microwave radiometer (SMR) to provide information on the ocean and atmosphere, was successfully launched on 25 October 2018. Before the data assimilation, it is necessary to characterize and evaluate the biases of the HY-2B SMR observations. This study is the first to conduct a systematic assessment of the SMR radiance data based on observation minus background simulation (O-B). Three types of numerical weather prediction (NWP) datasets, including ECMWF Reanalysis v5 (ERA5), the analysis fields from the NCEP Global Forecast System (NCEP-GFS), and the analysis fields from the Global Regional Assimilation and Prediction System-Global Forecast System (GRAPES-GFS), were used as input information for RTTOV v12.3 to simulate the SMR’s observed brightness temperature (TB) under clear-sky conditions. Study results showed that the O-B biases and IQR of the SMR for most channels were within −2.5–0.4 K and smaller than 4 K, respectively. The SMR observations were generally consistent with the RTTOV simulations, even based on the different NWP fields. These results indicate a good prospect for the assimilated application of HY-2B SMR radiance data. However, due to the impact of RFI, the SMR’s descending data for two 10.7 GHz channels showed some significant positive biases larger than 50 K over the seas of the European region. In addition, it seems that the bias characteristics of the SMR’s ascending data were obviously different from those of the descending data. It was also found that the variation trend of scan-position-dependent bias was generally stable for the SMR’s ascending data but fluctuates significantly for the descending data, with a maximum amplitude greater than 0.7 K for some channels. |
Audience | Academic |
Author | Han, Wei Li, Zeting Xie, Hejun Xu, Haiming Zou, Juhong |
Author_xml | – sequence: 1 givenname: Zeting surname: Li fullname: Li, Zeting – sequence: 2 givenname: Wei orcidid: 0000-0002-1966-446X surname: Han fullname: Han, Wei – sequence: 3 givenname: Haiming orcidid: 0000-0003-3363-2779 surname: Xu fullname: Xu, Haiming – sequence: 4 givenname: Hejun surname: Xie fullname: Xie, Hejun – sequence: 5 givenname: Juhong orcidid: 0000-0002-9245-7045 surname: Zou fullname: Zou, Juhong |
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Cites_doi | 10.1109/LGRS.2015.2420120 10.1007/s00376-020-0010-1 10.1007/s00376-021-1304-7 10.1109/TGRS.2005.862504 10.3402/tellusa.v68.30917 10.1109/IGARSS.2019.8900439 10.1109/TGRS.2018.2881094 10.5194/essd-12-647-2020 10.1002/qj.4228 10.1175/MWR-D-12-00232.1 10.1109/IGARSS.2015.7326998 10.1109/TGRS.2010.2040186 10.1175/2007MWR2147.1 10.1080/01431161.2021.1899330 10.1007/s13351-020-9122-x 10.1109/IGARSS.2019.8900252 10.1007/s11434-008-0419-x 10.1109/TGRS.2004.836867 10.1002/qj.3654 10.1002/qj.2669 10.1109/IGARSS.2012.6351421 10.1109/IGARSS.2019.8898014 10.1109/36.905249 10.1175/MWR-D-13-00135.1 10.3390/s20092674 10.1109/IGARSS.2019.8898386 10.1109/TGRS.2010.2064779 10.1016/j.atmosres.2017.06.007 10.1016/j.jqsrt.2020.107239 |
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References | Eyre (ref_1) 2020; 146 Draper (ref_23) 2015; 8 ref_14 ref_36 ref_13 Li (ref_18) 2017; 196 ref_34 Kazumori (ref_2) 2014; 142 Yang (ref_7) 2016; 68 ref_10 ref_19 ref_17 Xie (ref_20) 2019; 57 Fennig (ref_38) 2020; 12 ref_15 ref_37 Zabolotskikh (ref_33) 2015; 12 Wentz (ref_25) 2001; 39 Liu (ref_16) 2021; 42 Gaiser (ref_24) 2004; 42 Carminati (ref_21) 2020; 38 ref_22 Xiao (ref_8) 2020; 34 Bettenhausen (ref_30) 2006; 44 Kazumori (ref_9) 2016; 142 Liu (ref_28) 2010; 49 Eyre (ref_5) 2022; 148 Wang (ref_26) 2022; 60 Joo (ref_4) 2013; 141 Kazumori (ref_6) 2008; 136 ref_29 ref_27 Geer (ref_35) 2010; 48 Guo (ref_31) 2017; 35 Yu (ref_11) 2022; 60 Zhang (ref_12) 2021; 39 Lu (ref_32) 2020; 255 Zhu (ref_3) 2008; 53 |
References_xml | – volume: 12 start-page: 1705 year: 2015 ident: ref_33 article-title: Radio-frequency interference identification over oceans for C-and X-band AMSR2 channels publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2015.2420120 – volume: 38 start-page: 1379 year: 2020 ident: ref_21 article-title: Insights into the Microwave Instruments Onboard the Fengyun 3D Satellite: Data Quality and Assimilation in the Met Office NWP System publication-title: Adv. Atmos. Sci. doi: 10.1007/s00376-020-0010-1 – volume: 39 start-page: 1 year: 2021 ident: ref_12 article-title: FY-3E: The first operational meteorological satellite mission in an early morning orbit publication-title: Adv. Atmos. Sci. doi: 10.1007/s00376-021-1304-7 – volume: 44 start-page: 597 year: 2006 ident: ref_30 article-title: A nonlinear optimization algorithm for WindSat wind vector retrievals publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2005.862504 – volume: 8 start-page: 3452 year: 2015 ident: ref_23 article-title: The global precipitation measurement (GPM) microwave imager (GMI): Instrument overview and early on-orbit performance publication-title: IEEE J.-Stars – volume: 60 start-page: 5301213 year: 2022 ident: ref_11 article-title: Instrument Design and Early In-Orbit Performance of HY-2B Scanning Microwave Radiometer publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 68 start-page: 30917 year: 2016 ident: ref_7 article-title: AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system publication-title: Tellus A Dyn. Meteorol. Oceanogr. doi: 10.3402/tellusa.v68.30917 – ident: ref_15 doi: 10.1109/IGARSS.2019.8900439 – volume: 57 start-page: 3126 year: 2019 ident: ref_20 article-title: Ascending–Descending Bias Correction of Microwave Radiation Imager on Board FengYun-3C publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2881094 – volume: 12 start-page: 647 year: 2020 ident: ref_38 article-title: A fundamental climate data record of SMMR, SSM/I, and SSMIS brightness temperatures publication-title: Earth Syst. Sci. Data doi: 10.5194/essd-12-647-2020 – volume: 148 start-page: 521 year: 2022 ident: ref_5 article-title: Assimilation of satellite data in numerical weather prediction. Part II: Recent years publication-title: Q. J. R. Meteorl. Soc. doi: 10.1002/qj.4228 – ident: ref_37 – volume: 60 start-page: 5303916 year: 2022 ident: ref_26 article-title: Stability of the HY-2B Scanning Microwave Radiometer (SMR) Brightness Temperature Using a Modified Vicarious Cold Reference publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 141 start-page: 3331 year: 2013 ident: ref_4 article-title: The impact of MetOp and other satellite data within the Met Office global NWP system using an adjoint-based sensitivity method publication-title: Mon. Weather Rev. doi: 10.1175/MWR-D-12-00232.1 – ident: ref_34 doi: 10.1109/IGARSS.2015.7326998 – volume: 48 start-page: 2660 year: 2010 ident: ref_35 article-title: Solar biases in microwave imager observations assimilated at ECMWF publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2010.2040186 – volume: 136 start-page: 541 year: 2008 ident: ref_6 article-title: Impact study of AMSR-E radiances in the NCEP global data assimilation system publication-title: Mon. Weather Rev. doi: 10.1175/2007MWR2147.1 – volume: 42 start-page: 4621 year: 2021 ident: ref_16 article-title: Retrieval of sea surface temperature from the scanning microwave radiometer aboard HY-2B publication-title: Int. J. Remote Sens. doi: 10.1080/01431161.2021.1899330 – ident: ref_29 – ident: ref_27 – volume: 34 start-page: 836 year: 2020 ident: ref_8 article-title: Impact of FY-3D MWRI Radiance Assimilation in GRAPES 4DVar on Forecasts of Typhoon Shanshan publication-title: J. Meteorol. Res. doi: 10.1007/s13351-020-9122-x – ident: ref_17 doi: 10.1109/IGARSS.2019.8900252 – volume: 53 start-page: 3465 year: 2008 ident: ref_3 article-title: Direct assimilation of satellite radiance data in GRAPES variational assimilation system publication-title: Chin. Sci. Bull. doi: 10.1007/s11434-008-0419-x – volume: 42 start-page: 2347 year: 2004 ident: ref_24 article-title: The WindSat spaceborne polarimetric microwave radiometer: Sensor description and early orbit performance publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2004.836867 – volume: 35 start-page: 124 year: 2017 ident: ref_31 article-title: Retrieving near sea surface air temperature by AMSR2 radiometer publication-title: Adv. Mar. Sci. – volume: 146 start-page: 49 year: 2020 ident: ref_1 article-title: Assimilation of satellite data in numerical weather prediction. Part I: The early years publication-title: Q. J. R. Meteor. Soc. doi: 10.1002/qj.3654 – volume: 142 start-page: 721 year: 2016 ident: ref_9 article-title: Effects of All-sky Assimilation of GCOM-WI/AMSR2 Radiances in the ECMWF System: European Centre for Medium-Range Weather Forecasts publication-title: Q. J. R. Meteorol. Soc. doi: 10.1002/qj.2669 – ident: ref_22 doi: 10.1109/IGARSS.2012.6351421 – ident: ref_14 doi: 10.1109/IGARSS.2019.8898014 – volume: 39 start-page: 415 year: 2001 ident: ref_25 article-title: Post-launch calibration of the TRMM microwave imager publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/36.905249 – volume: 142 start-page: 1361 year: 2014 ident: ref_2 article-title: Satellite radiance assimilation in the JMA operational mesoscale 4DVAR system publication-title: Mon. Weather Rev. doi: 10.1175/MWR-D-13-00135.1 – ident: ref_36 – ident: ref_10 doi: 10.3390/s20092674 – ident: ref_19 – ident: ref_13 doi: 10.1109/IGARSS.2019.8898386 – volume: 49 start-page: 1238 year: 2010 ident: ref_28 article-title: An improved fast microwave water emissivity model publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2010.2064779 – volume: 196 start-page: 164 year: 2017 ident: ref_18 article-title: Bias characterization of CrIS radiances at 399 selected channels with respect to NWP model simulations publication-title: Atmos. Res. doi: 10.1016/j.atmosres.2017.06.007 – volume: 255 start-page: 107239 year: 2020 ident: ref_32 article-title: Monitoring the performance of the Fengyun satellite instruments using radiative transfer models and NWP fields publication-title: J. Quant. Spectrosc. Radiat. Transf. doi: 10.1016/j.jqsrt.2020.107239 |
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SubjectTerms | Artificial satellites in remote sensing Bias Bias (Statistics) bias characterization Brightness temperature Calibration Channels Data assimilation Data collection Data processing Datasets Europe Evaluation Humidity HY-2B Measurement Meteorological satellites Microwave radiometers Numerical prediction Numerical weather forecasting O-B prediction Quality control Radiance Radiometers RFI RTTOV satellites Scanning Simulation SMR Temperature Testing Weather forecasting |
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Title | Biases’ Characteristics Assessment of the HY-2B Scanning Microwave Radiometer (SMR)’s Observations |
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