| Adam, S., A. Behrendt, T. Schwitalla, E. Hammann, and V. Wulfmeyer, 2016: First assimilation of temperature lidar data into an NWP model: Impact on the simulation of the temperature field, inversion strength and PBL depth. Quart. J. Roy. Meteor. Soc., 142, 2882−2896, https://doi.org/10.1002/qj.2875. |
| Atlas, R., 1997: Atmospheric observations and experiments to assess their usefulness in data assimilation. J. Meteor. Soc. Japan, 75, 111−130, https://doi.org/10.2151/jmsj1965.75.1B_111. |
| Atlas, R., L. Bucci, B. Annane, R. Hoffman, and S. Murillo, 2015: Observing system simulation experiments to assess the potential impact of new observing systems on hurricane forecasting. Marine Technology Society Journal, 49, 140−148, https://doi.org/10.4031/MTSJ.49.6.3. |
| Bachmann, K., C. Keil, and M. Weissmann, 2018: Impact of radar data assimilation and orography on predictability of deep convection. Quart. J. Roy. Meteor. Soc., 145, 117−130, https://doi.org/10.1002/qj.3412. |
| Balogh, W., and T. Kurino, 2020: The world meteorological organization and space-based observations for weather, climate, water and related environmental services. Space Capacity Building in the XXI Century, S. Ferretti, Ed., Springer, 223-232. |
| Bauer, P., and Coauthors, 2011: Satellite cloud and precipitation assimilation at operational NWP centres. Quart. J. Roy. Meteor. Soc., 137, 1934−1951, https://doi.org/10.1002/qj.905. |
| Benjamin, S. G., and Coauthors, 2016: A North American hourly assimilation and model forecast cycle: The rapid refresh. Mon. Wea. Rev., 144, 1669−1694, https://doi.org/10.1175/MWR-D-15-0242.1. |
| Bessho, K., and Coauthors, 2016: An introduction to Himawari-8/9—Japan’s new-generation geostationary meteorological satellites. J. Meteor. Soc. Japan, 94, 151−183, https://doi.org/10.2151/jmsj.2016-009. |
| Carbone, R. E., J. D. Tuttle, D. A. Ahijevych, and S. B. Trier, 2002: Inferences of predictability associated with warm season precipitation episodes. J. Atmos. Sci., 59, 2033−2056, https://doi.org/10.1175/1520-0469(2002)059<2033:IOPAWW>2.0.CO;2. |
| Cardinali, C., 2009: Monitoring the observation impact on the short-range forecast. Quart. J. Roy. Meteor. Soc., 135, 239−250, https://doi.org/10.1002/qj.366. |
| Chen, Y., Y. Han, P. Van Delst, and F. Z. Weng, 2010: On water vapor Jacobian in fast radiative transfer model. J. Geophys. Res., 115, D12303, https://doi.org/10.1029/2009JD013379. |
| Chen, Y., Y. Han, and F. Z. Weng, 2012: Comparison of two transmittance algorithms in the community radiative transfer model: Application to AVHRR. J. Geophys. Res., 117, D06206, https://doi.org/10.1029/2011JD016656. |
| Chen, Y., Y. Han, and F. Z. Weng, 2013: Detection of earth-rotation Doppler shift from suomi national polar-orbiting partnership cross-track infrared sounder. Appl. Opt., 52, 6250−6257, https://doi.org/10.1364/AO.52.006250. |
| Cucurull, L., R. A. Anthes, and L.-L. Tsao, 2014: Radio occultation observations as anchor observations in numerical weather prediction models and associated reduction of bias corrections in microwave and infrared satellite observations. J. Atmos. Oceanic Technol., 31, 20−32, https://doi.org/10.1175/JTECH-D-13-00059.1. |
| Eicker, A., L. Jensen, V. Wöhnke, H. Dobslaw, A. Kvas, T. Mayer-Gürr, and D. Robert, 2020: Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses. Scientific Reports, 10, 4504, https://doi.org/10.1038/s41598-020-61166-0. |
| Errico, R. M., 1997: What is an adjoint model? Bull. Amer. Meteor. Soc., 78, 2577−2592, https://doi.org/10.1175/1520-0477(1997)078<2577:WIAAM>2.0.CO;2. |
| Errico, R. M., T. Vukicevic, P. Courtier, J. Derber, and J. F. Louis, 1993a: Workshop on adjoint applications in dynamic meteorology 23-28 August 1992, pacific grove, California. Bull. Amer. Meteor. Soc., 74, 845−847. |
| Errico, R. M., T. VukiĆEviĆ, and K. Raeder, 1993b: Examination of the accuracy of a tangent linear model. Tellus A: Dynamic Meteorology and Oceanography, 45, 462−477, https://doi.org/10.3402/tellusa.v45i5.15046. |
| Garand, L., M. Buehner, S. Heilliette, S. R. Macpherson, and A. Beaulne, 2013: Satellite radiance assimilation impact in new Canadian ensemble-variational system. Proc. EUMETSAT Meteorological Satellite Conf., Vienna, Austria, EUMETSAT. |
| Geer, A. J., and Coauthors, 2018: All-sky satellite data assimilation at operational weather forecasting centres. Quart. J. Roy. Meteor. Soc., 144, 1191−1217, https://doi.org/10.1002/qj.3202. |
| Graham, R. J., S. R. Anderson, and M. J. Bader, 2000: The relative utility of current observation systems to global-scale NWP forecasts. Quart. J. Roy. Meteor. Soc., 126, 2435−2460, https://doi.org/10.1002/qj.49712656805. |
| Han, H., J. Li, M. Goldberg, P. Wang, J. L. Li, Z. L. Li, B.-J. Sohn, and J. Li, 2016a: Microwave sounder cloud detection using a collocated high-resolution imager and its impact on radiance assimilation in tropical cyclone forecasts. Mon. Wea. Rev., 144, 3927−3959, https://doi.org/10.1175/MWR-D-15-0300.1. |
| Han, Y., P. van Delst, Q. H. Liu, F. Z. Weng, B. H. Yan, R. Treadon, and J. Derber, 2006b: JCSDA community radiative transfer model (CRTM): Version 1. NOAA Tech. Rep. 122. |
| Hersbach, H., and D. Dee, 2017: ERA5 reanalysis is in production. ECMWF Newsletter 147, ECMWF. |
| Hilton, F., N. C. Atkinson, S. J. English, and J. R. Eyre, 2009: Assimilation of IASI at the Met Office and assessment of its impact through observing system experiments. Quart. J. Roy. Meteor. Soc., 135, 495−505, https://doi.org/10.1002/qj.379. |
| Hoffman, R. N., and R. Atlas, 2016: Future observing system simulation experiments. Bull. Amer. Meteor. Soc., 97, 1601−1616, https://doi.org/10.1175/BAMS-D-15-00200.1. |
| Hooker, J., G. Duveiller, and A. Cescatti, 2018: A global dataset of air temperature derived from satellite remote sensing and weather stations. Scientific Data, 5, 180246, https://doi.org/10.1038/sdata.2018.246. |
| Hu, M., G. Q. Ge, C. H. Zhou, D. Stark, H. Shao, K. Newman, J. Beck, and X. Zhang, 2018: Gridpoint Statistical Interpolation (GSI): User’s guide version 3.7. Development Testbed Center. |
| Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944. |
| Jones, T. A., S. Koch, and Z. L. Li, 2017: Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts. Atmospheric Research, 186, 9−25, https://doi.org/10.1016/j.atmosres.2016.11.004. |
| Joo, S., J. Eyre, and R. Marriott, 2013: The impact of MetOp and other satellite data within the met office global NWP system using an adjoint-based sensitivity method. Mon. Wea. Rev., 141, 3331−3342, https://doi.org/10.1175/MWR-D-12-00232.1. |
| Kalinga, O. A., and T. Y. Gan, 2010: Estimation of rainfall from infrared-microwave satellite data for basin-scale hydrologic modelling. Hydrological Processes, 24, 2068−2086, https://doi.org/10.1002/hyp.7626. |
| Kazumori, M., 2018: Assimilation of Himawari-8 clear sky radiance data in JMA’s global and mesoscale NWP systems. J. Meteor. Soc. Japan, 96B, 173−192, https://doi.org/10.2151/jmsj.2018-037. |
| Lee, J.-R., J. Li, Z. L. Li, P. Wang, and J. L. Li, 2018: ABI water vapor radiance assimilation in a regional NWP model by accounting for the surface impact. Earth and Space Science, 6, 1652−1666, https://doi.org/10.1029/2019EA000711. |
| Li, J., J. L. Li, J. Otkin, T. J. Schmit, and C.-Y. Liu, 2011: Warning information in a preconvection environment from the geostationary advanced infrared sounding system - A simulation study using the IHOP case. J. Appl. Meteor. Climatol., 50, 776−783, https://doi.org/10.1175/2010JAMC2441.1. |
| Li, J., C.-Y. Liu, P. Zhang, and T. J. Schmit, 2012: Applications of full spatial resolution space-based advanced infrared soundings in the preconvection environment. Wea. Forecasting, 27, 515−524, https://doi.org/10.1175/WAF-D-10-05057.1. |
| Li, J., P. Wang, H. J. Han, J. L. Li, and J. Zheng, 2016: On the assimilation of satellite sounder data in cloudy skies in numerical weather prediction models. Journal of Meteorological Research, 30, 169−182, https://doi.org/10.1007/s13351-016-5114-2. |
| Li, J., Z. L. Li, P. Wang, T. J. Schmit, W. G. Bai, and R. Atlas, 2017: An efficient radiative transfer model for hyperspectral IR radiance simulation and applications under cloudy‐sky conditions. J. Geophys. Res., 122, 7600−7613, https://doi.org/10.1002/2016JD026273. |
| Li, J. L., J. Li, C. Velden, P. Wang, T. J. Schmit, and J. Sippel, 2020: Impact of rapid-scan-based dynamical information from GOES-16 on HWRF hurricane forecasts. J. Geophys. Res., 125, e2019JD031647, https://doi.org/10.1029/2019JD031647. |
| Li, Z. L., and Coauthors, 2018: Value-added impact of geostationary hyperspectral infrared sounders on local severe storm forecasts - via a quick regional OSSE. Advances in Atmospheric Sciences, 35, 1217−1230, https://doi.org/10.1007/s00376-018-8036-3. |
| Lin, H. D., S. S. Weygandt, A. H. N. Lim, M. Hu, J. M. Brown, and S. G. Benjamin, 2017: Radiance preprocessing for assimilation in the hourly updating rapid refresh mesoscale model: A study using AIRS data. Wea. Forecasting, 32, 1781−1800, https://doi.org/10.1175/WAF-D-17-0028.1. |
| Lopez, P., and P. Bauer, 2007: “1D+4DVAR” assimilation of NCEP stage-IV radar and gauge hourly precipitation data at ECMWF. Mon. Wea. Rev., 135, 2506−2524, https://doi.org/10.1175/MWR3409.1. |
| Ma, Z., Z. Li, J. Li, T. J. Schmit, L. Cucurull, R. Atlas, and B. Sun, 2020: Enhance low level temperature and moisture profiles through combining NUCAPS, ABI and surface data. Submitted to Earth and Space Sciences. |
| Ma, Z. Z., E. S. Maddy, B. L. Zhang, T. Zhu, and S. A. Boukabara, 2017: Impact assessment of Himawari-8 AHI data assimilation in NCEP GDAS/GFS with GSI. J. Atmos. Oceanic Technol., 34, 797−815, https://doi.org/10.1175/JTECH-D-16-0136.1. |
| Menzel, W. P., T. J. Schmit, P. Zhang, and J. Li, 2018: Satellite-based atmospheric infrared sounder development and applications. Bull. Amer. Meteor. Soc., 2018, 99, 583−603, https://doi.org/10.1175/BAMS-D-16-0293.1. |
| Okamoto, K., and Coauthors, 2020: Assessment of the potential impact of a hyperspectral infrared sounder on the Himawari follow-on geostationary satellite. SOLA, 16, 162−168, https://doi.org/10.2151/sola.2020-028. |
| Pangaud, T., N. Fourrie, V. Guidard, M. Dahoui, and F. Rabier, 2009: Assimilation of AIRS radiances affected by mid- to low-level clouds. Mon. Wea. Rev., 137, 4276−4292, https://doi.org/10.1175/2009MWR3020.1. |
| Pavelin, E. G., S. J. English, and J. R. Eyre, 2008: The assimilation of cloud-affected infrared satellite radiances for numerical weather prediction. Quart. J. Roy. Meteor. Soc., 134, 737−749, https://doi.org/10.1002/qj.243. |
| Reen, B. P., and R. E. Dumais, 2018: Assimilation of aircraft observations in high-resolution mesoscale modeling. Advances in Meteorology, 2018, 8912943, https://doi.org/10.1155/2018/8912943. |
| Schmit, T. J., and Coauthors, 2019: Legacy atmospheric profiles and derived products from GOES-16: Validation and applications. Earth and Space Science, 6, 1730−1748, https://doi.org/10.1029/2019EA000729. |
| Schmit, T. J., M. M. Gunshor, W. P. Menzel, J. J. Gurka, J. Li, and A. S. Bachmeier, 2005: Introducing the next-generation advanced baseline imager on GOES-R. Bull. Amer. Meteor. Soc., 86, 1079−1096, https://doi.org/10.1175/BAMS-86-8-1079. |
| Schmit, T. T., J. Li, S. A. Ackerman, and J. J. Gurka, 2009: High-spectral-and high-temporal-resolution infrared measurements from geostationary orbit. J. Atmos. Oceanic Technol., 26, 2273−2292, https://doi.org/10.1175/2009JTECHA1248.1. |
| Seo, D. J., and J. P. Breidenbach, 2002: Real-time correction of spatially nonuniform bias in radar rainfall data using rain gauge measurements. J. Hydrometeorology, 3, 93−111, https://doi.org/10.1175/1525-7541(2002)003<0093:RTCOSN>2.0.CO;2. |
| Shao, H., and Coauthors, 2016: Bridging research to operations transitions: Status and plans of community GSI. Bull. Amer. Meteor. Soc., 97, 1427−1440, https://doi.org/10.1175/BAMS-D-13-00245.1. |
| Stettner, D., C. Velden, R. Rabin, S. Wanzong, J. Daniels, and W. Bresky, 2019: Development of enhanced vortex-scale atmospheric motion vectors for hurricane applications. Remote Sensing, 11, 1981, https://doi.org/10.3390/rs11171981. |
| Stith, J. L., and Coauthors, 2018: 100 years of progress in atmospheric observing systems. Meteor. Monogr., 59, 2.1−2.55, https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0006.1. |
| Taylor, J. K., H. E. Revercomb, and D. C. Tobin, 2018: An analysis and correction of polarization induced calibration errors for the cross-track infrared sounder (CrIS) sensor. Proc. Light, Energy and the Environment 2018, Washington, DC, Optical Society of America. |
| Wang, P., J. Li, J. L. Li, Z. L. Li, T. J. Schmit, and W. G. Bai, 2014: Advanced infrared sounder subpixel cloud detection with imagers and its impact on radiance assimilation in NWP. Geophys. Res. Lett., 41, 1773−1780, https://doi.org/10.1002/2013GL059067. |
| Wang, P., J. Li, Z. L. Li, A. H. N. Lim, J. L. Li, T. J. Schmit, and M. D. Goldberg, 2017: The impact of cross‐track infrared sounder (CrIS) cloud‐cleared radiances on hurricane Joaquin (2015) and Matthew (2016) forecasts. J. Geophys. Res., 122, 13 201−13 218, https://doi.org/10.1002/2017JD027515. |
| Wang, P., J. Li, Z. Li, A. H. N. Lim, J. Li, and M. D. Goldberg, 2019: Impacts of observation errors on hurricane forecasts when assimilating hyperspectral infrared sounder radiances in partially cloudy skies. J. Geophys. Res., 124, 10 802−10 813. https://doi.org/10.1029/2019JD031029 |
| Wang. P., J. Li, and T. J. Schmit, 2020: The impact of low latency satellite sounder observations on local severe storm forecasts in regional NWP. Sensors, 20(3), 650. https://doi/org/10.3390/s20030650 |
| Xue, Y. H., J. Li, Z. L. Li, R. Y. Lu, M. M. Gunshor, S. L. Moeller, D. Di, and T. J. Schmit, 2020a: Assessment of upper tropospheric water vapor monthly variation in reanalyses with near-global homogenized 6.5-μm radiances from geostationary satellites. J. Geophys. Res., 125, e2020JD032695, https://doi.org/10.1029/2020JD032695. |
| Xue, Y. H., J. Li, Z. L. Li, M. M. Gunshor, and T. J. Schmit, 2020b: Evaluation of the diurnal variation of upper tropospheric humidity in reanalysis using homogenized observed radiances from international geostationary weather satellites. Remote Sensing, 12, 1628, https://doi.org/10.3390/rs12101628. |
| Yang, J., Z. Q. Zhang, C. Y. Wei, F. Lu, and Q. Guo, 2017: Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bull. Amer. Meteor. Soc., 98, 1637−1658, https://doi.org/10.1175/BAMS-D-16-0065.1. |
| Yin, R. Y., W. Han, Z. Q. Gao, and D. Di, 2020: The evaluation of FY4A’s geostationary interferometric infrared sounder (GIIRS) long-wave temperature sounding channels using the GRAPES global 4D-Var. Qourt. J. Roy. Meteor. Soc., 146, 1459−1476, https://doi.org/10.1002/qj.3746. |
| Zheng, J., J. Li, T. J. Schmit, J. L. Li, and Z. Q. Liu, 2015: The impact of AIRS atmospheric temperature and moisture profiles on hurricane forecasts: Ike (2008) and Irene (2011). Advances in Atmospheric Sciences, 32, 319−335, https://doi.org/10.1007/s00376-014-3162-z. |
| Zhou, L. H., M. Divakarla, X. P. Liu, A. Layns, and M. Goldberg, 2019: An overview of the science performances and calibration/validation of joint polar satellite system operational products. Remote Sensing, 11, 698, https://doi.org/10.3390/rs11060698. |
| Zhu, Y. Q., J. Derber, A. Collard, D. Dee, R. Treadon, G. Gayno, and J. A. Jung, 2014: Enhanced radiance bias correction in the National Centers for Environmental Prediction’s Gridpoint Statistical Interpolation data assimilation system. Quart. J. Roy. Meteor. Soc., 240, 1479−1492, https://doi.org/10.1002/qj.2233. |