Articles | Volume 12, issue 9
https://doi.org/10.5194/amt-12-4903-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-4903-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Sep 2019
Research article |
| 11 Sep 2019
| 11 Sep 2019
All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud
ECMWF, Shinfield Park, Reading RG2 9AX, UK
Stefano Migliorini
Met Office, FitzRoy Road, Exeter EX1 3PB, UK
Marco Matricardi
ECMWF, Shinfield Park, Reading RG2 9AX, UK
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- A Bias Correction Scheme with the Symmetric Cloud Proxy Variable and Its Influence on Assimilating All-Sky GOES-16 Brightness Temperatures C. Feng & Z. Pu 10.1175/MWR-D-21-0333.1
- Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall L. Xu et al. 10.1007/s00376-022-1380-3
- Assimilation of All-Sky SEVIRI Infrared Brightness Temperatures in a Regional-Scale Ensemble Data Assimilation System J. Otkin & R. Potthast 10.1175/MWR-D-19-0133.1
- Hyperspectral Infrared Atmospheric Sounder (HIRAS) Atmospheric Sounding System S. Li et al. 10.3390/rs14163882
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- Assimilation of SEVIRI Water Vapor Channels With an Ensemble Kalman Filter on the Convective Scale A. Hutt et al. 10.3389/feart.2020.00070
- Correlated observation error models for assimilating all-sky infrared radiances A. Geer 10.5194/amt-12-3629-2019
37 citations as recorded by crossref.
- A Machine Learning-Based Bias Correction Scheme for the All-Sky Assimilation of AGRI Infrared Radiances in a Regional OSSE Framework X. Zhang et al. 10.1109/TGRS.2024.3427434
- All-sky infrared radiance data assimilation of FY-4A AGRI with different physical parameterizations for the prediction of an extremely heavy rainfall event D. Xu et al. 10.1016/j.atmosres.2023.106898
- Editorial: The use of unconventional observations in numerical weather prediction J. Waller 10.1002/met.1948
- Impact of the Detection Channels Added by Fengyun Satellite MWHS-II at 183 GHz on Global Numerical Weather Prediction Y. Ju et al. 10.3390/rs15174279
- On the impact of dropsondes on the ECMWF Integrated Forecasting System model (CY47R1) analysis of convection during the OTREC (Organization of Tropical East Pacific Convection) field campaign S. Sentić et al. 10.5194/gmd-15-3371-2022
- Performances between the FY‐4A/GIIRS and FY‐4B/GIIRS Long‐Wave InfraRed (LWIR) channels under clear‐sky and all‐sky conditions Z. Niu et al. 10.1002/qj.4473
- Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China D. Xu et al. 10.1007/s00376-020-0219-z
- Enhancing Severe Weather Prediction With Microwave All‐Sky Radiance Assimilation: The 10 August 2020 Midwest Derecho Y. Zhang et al. 10.1029/2023GL106602
- Error Model for the Assimilation of All-Sky FY-4A/AGRI Infrared Radiance Observations D. Pu & Y. Wu 10.3390/s24082572
- Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework E. Villeneuve et al. 10.5194/amt-17-3567-2024
- The Impact of MERRA-2 and CAMS Aerosol Reanalysis Data on FengYun-4B Geostationary Interferometric Infrared Sounder Simulations W. Peng et al. 10.3390/rs17050761
- Nonlinear Bias Correction of the FY-4A AGRI Infrared Radiance Data Based on the Random Forest X. Zhang et al. 10.3390/rs15071809
- A 3-D Cloud Detection Method for FY-4A GIIRS and Its Application in Operational Numerical Weather Prediction System X. Yan et al. 10.1109/TGRS.2023.3307563
- Impact of Adaptively Thinned GOES-16 Cloud Water Path in an Ensemble Data Assimilation System S. Mallick 10.3390/meteorology1040032
- An Evaluation of Radiative Transfer Simulations of Cloudy Scenes from a Numerical Weather Prediction Model at Sub-Millimetre Frequencies Using Airborne Observations S. Fox 10.3390/rs12172758
- The Impact of Aerosols on Satellite Radiance Data Assimilation Using NCEP Global Data Assimilation System S. Wei et al. 10.3390/atmos12040432
- A preliminary evaluation of FY-4A visible radiance data assimilation by the WRF (ARW v4.1.1)/DART (Manhattan release v9.8.0)-RTTOV (v12.3) system for a tropical storm case Y. Zhou et al. 10.5194/gmd-15-7397-2022
- Impact of all‐sky water vapour channel radiance from INSAT‐3D/3DR satellite over South Asia region using WRF model P. Kumar et al. 10.1002/qj.4323
- Evaluation of Modeled Hyperspectral Infrared Spectra Against All‐Sky AIRS Observations Using Different Cloud Overlap Schemes T. Le et al. 10.1029/2022EA002245
- Impacts of cloud scattering properties on FY-3D HIRAS simulations B. Yi et al. 10.1016/j.jqsrt.2020.106902
- The Potential Value of Combining Assimilation of Water Vapor Radiances and Cloud Liquid/Ice Water Path From ABI on Analyses and Forecasts for Hurricane Irma (2017) D. Meng et al. 10.1029/2022JD036910
- Global Evaluation of the Fidelity of Clouds in the ECMWF Integrated Forecast System H. Aumann et al. 10.1029/2022EA002652
- Exploring the Assimilation of All-Sky FY-4A GIIRS Radiances and Its Forecasts for Binary Typhoons Q. Xie et al. 10.1109/JSTARS.2025.3540209
- Satellite All-sky Infrared Radiance Assimilation: Recent Progress and Future Perspectives J. Li et al. 10.1007/s00376-021-1088-9
- Assimilation of SEVIRI Water Vapour Radiances in HARMONIE-AROME at Large Satellite Zenith Angles D. Schönach et al. 10.16993/tellusa.4106
- Atmospheric Observations of Weather and Climate H. Bluestein et al. 10.1080/07055900.2022.2082369
- An accurate and computationally cheap microwave scattering method for ice aggregates: the Independent Monomer Approximation K. McCusker et al. 10.1002/qj.3967
- A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images F. Baur et al. 10.5194/amt-16-5305-2023
- Physical characteristics of frozen hydrometeors inferred with parameter estimation A. Geer 10.5194/amt-14-5369-2021
- Impact of adaptively thinned GOES-16 all-sky radiances in an ensemble Kalman filter based WoFS S. Mallick & T. Jones 10.1016/j.atmosres.2022.106304
- Improving the prediction of heavy rainfall with rapid-update dual-resolution hybrid En3DVar assimilation of all-sky AHI infrared water vapor radiances Y. Wang et al. 10.1016/j.atmosres.2022.106352
- Assimilating FY-4B AGRI Three Water Vapor Channels in Operational Shanghai Typhoon Model (SHTM) Using GSI-Based 3-DVar Approach Z. Niu et al. 10.1109/JSTARS.2024.3522056
- A Bias Correction Scheme with the Symmetric Cloud Proxy Variable and Its Influence on Assimilating All-Sky GOES-16 Brightness Temperatures C. Feng & Z. Pu 10.1175/MWR-D-21-0333.1
- Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall L. Xu et al. 10.1007/s00376-022-1380-3
- Assimilation of All-Sky SEVIRI Infrared Brightness Temperatures in a Regional-Scale Ensemble Data Assimilation System J. Otkin & R. Potthast 10.1175/MWR-D-19-0133.1
- Hyperspectral Infrared Atmospheric Sounder (HIRAS) Atmospheric Sounding System S. Li et al. 10.3390/rs14163882
- Development of New Observation Operators for Assimilating GOES-R Geostationary Lightning Mapper Flash Extent Density Data Using GSI EnKF: Tests with Two Convective Events over the United States R. Kong et al. 10.1175/MWR-D-21-0326.1
Latest update: 09 May 2025
Short summary
Satellite radiance observations have only recently become usable in conditions of cloud and precipitation for the initialization of weather forecasts. The move to
all-skyassimilation started with data from the microwave part of the spectrum, with substantial benefit to the quality of operational forecasts. The current work shows a framework in which cloudy infrared data, with its stronger and more non-linear sensitivity, can also benefit operational-quality forecasts.
Satellite radiance observations have only recently become usable in conditions of cloud and...
