doi:10.1007/s00376-020-0080-0

Bedka, K. M., C. S. Velden, R. A. Petersen, W. F. Feltz, and J. R. Mecikalski, 2008: Comparisons of satellite-derived atmospheric motion vectors, rawinsondes, and NOAA wind profiler observations. J. Appl. Meteorol. Climatol., 48, 1542−1561, https://doi.org/10.1175/2009jamc1867.1.

Benjamin, S. G., B. E. Schwartz, and R. E. Cole, 1998: Accuracy of ACARS wind and temperature observations determined by collocation. Wea. Forecasting, 14, 1032−1038, https://doi.org/10.1175/1520-0434(1999)014<1032:AOAWAT>2.0.CO;2.

Berger, H., R. Langland, C. S. Velden, C. A. Reynolds, and P. M. Pauley, 2011: Impact of enhanced satellite-derived atmospheric motion vector observations on numerical tropical cyclone track forecasts in the Western North Pacific during TPARC/TCS-08. J. Appl. Meteorol. Climatol., 50, 2309−2318, https://doi.org/10.1175/jamc-d-11-019.1.

Bormann, N., S. Saarinen, G. Kelly, and J.-N. Thépaut, 2003: The spatial structure of observation errors in atmospheric motion vectors from geostationary satellite data. Mon. Wea. Rev., 131, 706−718, https://doi.org/10.1175/1520-0493(2003)131<0706:TSSOOE>2.0.CO;2.

Chen, M., M. X. Chen, and S. Y. Fan, 2014: The real-time radar radial velocity 3DVar assimilation experiments for application to an operational forecast model in North China. Acta Meteorological Sinica, 72, 658−677, https://doi.org/10.11676/qxxb2014.070. (in Chinese with English abstract)

Cordoba, M., S. L. Dance, G. A. Kelly, N. K. Nichols, and J. A. Waller, 2017: Diagnosing atmospheric motion vector observation errors for an operational high-resolution data assimilation system. Quart. J. Roy. Meteor. Soc., 143, 333−341, https://doi.org/10.1002/qj.2925.

Deb, S. K., C. M. Kishtawal, I. Kaur, P. K. Pal, and A. S. Kiran Kumar, 2015: Assessment of a new quality control technique in the retrieval of atmospheric motion vectors. Meteorological Applications, 22, 178−186, https://doi.org/10.1002/met.1433.

Deb, S. K., P. Kumar, P. K. Pal, and P. C. Joshi, 2011: Assimilation of INSAT data in the simulation of the recent tropical Cyclone Aila. Int. J. Remote Sens., 32, 5135−5155, https://doi.org/10.1080/01431161.2010.494640.

Desroziers, G., L. Berre, B. Chapnik, and P. Poli, 2005: Diagnosis of observation, background and analysis-error statistics in observation space. Quart. J. Roy. Meteor. Soc., 131, 3385−3396, https://doi.org/10.1256/qj.05.108.

Dong, Y.-H., 2016: FY-4 meteorological satellite and its application prospect. Aerospace Shanghai, 33, 1−8, https://doi.org/10.19328/j.cnki.1006-1630.2016.02.001. (in Chinese with English abstract)

Errico, R. M., D. J. Stensrud, and K. D. Raeder, 2001: Estimation of the error distributions of precipitation produced by convective parametrization schemes. Quart. J. Roy. Meteor. Soc., 127, 2495−2512, https://doi.org/10.1002/qj.49712757802.

Fan, S. Y., H. L. Wang, M. Chen, and H. Gao, 2013: Study of the data assimilation of radar reflectivity with the WRF 3D-Var. Acta Meteorological Sinica, 71, 527−537, https://doi.org/10.11676/qxxb2013.032. (in Chinese with English abstract)

Feng, W., Q. L. Wan, Z. T. Chen, W. Y. Ding, and Y. Y. Huang, 2008: Hourly assimilation of cloud motion winds and its impact on torrential rain forecast. Acta Meteorological Sinica, 66, 500−512, https://doi.org/10.3321/j.issn:0577-6619.2008.04.003. (in Chinese with English abstract)

Gao, F., X. Y. Zhang, N. A. Jacobs, X.-Y. Huang, X. Zhang, and P. P. Childs, 2012: Estimation of TAMDAR observational error and assimilation experiments. Wea. Forecasting, 27, 856−877, https://doi.org/10.1175/WAF-D-11-00120.1.

Goerss, J. S., 2009: Impact of satellite observations on the tropical cyclone track forecasts of the navy operational global atmospheric prediction system. Mon. Wea. Rev., 137, 41−50, https://doi.org/10.1175/2008mwr2601.1.

He, J., M. Chen, J. Q. Zhong, and X. Y. Hong, 2019: A study of three-dimensional radar reflectivity mosaic assimilation in the regional forecasting model for North China. Acta Meteorological Sinica, 77, 210−232, https://doi.org/10.11676/qxxb2019.005. (in Chinese with English abstract)

Hollingsworth, A., and P. Lönnberg, 1986: The statistical structure of short-range forecast errors as determined from radiosonde data. Part I: The wind field. Tellus A: Dynamic Meteorology and Oceanography, 38, 111−136, https://doi.org/10.1111/j.1600-0870.1986.tb00460.x.

Holmlund, K., 1998: The utilization of statistical properties of satellite-derived atmospheric motion vectors to derive quality indicators. Wea. Forecasting, 13, 1093−1104, https://doi.org/10.1175/1520-0434(1998)013<1093:TUOSPO>2.0.CO;2.

Honda, T., S. Kotsuki, G.-Y. Lien, Y. Maejima, K. Okamoto, and T. Miyoshi, 2018: Assimilation of Himawari-8 all-sky radiance every 10 minutes: Impact on precipitation and flood risk prediction. J. Geophys. Res., 123, 965−976, https://doi.org/10.1002/2017JD027096.

Hsiao, L.-F., D.-S. Chen, Y.-H. Kuo, Y.-R. Guo, T.-C. Yeh, J.-S. Hong, C.-T. Fong, and C.-S. Lee, 2012: Application of WRF 3DVAR to operational typhoon prediction in Taiwan: Impact of outer loop and partial cycling approaches. Wea. Forecasting, 27, 1249−1263, https://doi.org/10.1175/WAF-D-11-00131.1.

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(D13), D13103, https://doi.org/10.1029/2008JD009944.

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.

Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteorol., 43, 170−181, https://doi.org/10.1175/1520-0450(2004)043<0170:tkcpau>2.0.co;2.

Kaur, I., P. Kumar, S. K. Deb, C. M. Kishtawal, P. K. Pal, and R. Kumar, 2015: Impact of Kalpana-1 retrieved atmospheric motion vectors on mesoscale model forecast during summer monsoon 2011. Theor. Appl. Climatol., 120, 587−599, https://doi.org/10.1007/s00704-014-1197-9.

Kim, D.-H., and H. M. Kim, 2018: Effect of assimilating Himawari-8 atmospheric motion vectors on forecast errors over East Asia. J. Atmos. Oceanic Technol., 35, 1737−1752, https://doi.org/10.1175/JTECH-D-17-0093.1.

Kirby, S. F., 2004: Model evaluation tool. ARL-TR-3373, White Sands Missile Range, NM, 1−23.

Kunii, M., M. Otsuka, K. Shimoji, and H. Seko, 2016: Ensemble data assimilation and forecast experiments for the September 2015 heavy rainfall event in Kanto and Tohoku Regions with atmospheric motion vectors from Himawari-8. SOLA, 12, 209−214, https://doi.org/10.2151/sola.2016-042.

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.

Lu, F., and Coauthors, 2017: FY-4 geostationary meteorological satellite imaging characteristics and its application prospects. Journal of Marine Meteorology, 37, 1−12, https://doi.org/10.19513/j.cnki.issn2096-3599.2017.02.001. (in Chinese with English abstract)

Menzel, W. P., 2001: Cloud tracking with satellite imagery: From the pioneering work of Ted Fujita to the present. Bull. Amer. Meteor. Soc., 82, 33−48, https://doi.org/10.1175/1520-0477(2001)082<0033:CTWSIF>2.3.CO;2.

Nieman, S. J., J. Schmetz, and W. P. Menzel, 1993: A comparison of several techniques to assign heights to cloud tracers. J. Appl. Meteorol., 50, 1559−1568, https://doi.org/10.1175/1520-0450(1993)032<1559:ACOSTT>2.0.CO;2.

Otsuka, M., H. Seko, K. Shimoji, and K. Yamashita, 2018: Characteristics of Himawari-8 rapid scan atmospheric motion vectors utilized in mesoscale data assimilation. J. Meteor. Soc. Japan, 96B, 111−131, https://doi.org/10.2151/jmsj.2018-034.

Otsuka, M., M. Kunii, H. Seko, K. Shimoji, M. Hayashi, and K. Yamashita, 2015: Assimilation experiments of MTSAT rapid scan atmospheric motion vectors on a heavy rainfall event. J. Meteor. Soc. Japan, 93, 459−475, https://doi.org/10.2151/jmsj.2015-030.

Ren, S. L., J. Y. Jiang, and J. M. Xu, 2014: Application of upper troposphere circulation revealed by the satellite IR3 channel to heavy rainfall events analysis in the east side of South Asia High. Meteorological Monthly, 40, 697−705, https://doi.org/10.7519/j.issn.1000-0526.2014.06.006. (in Chinese with English abstract)

Schmetz, J., K. Holmlund, J. Hoffman, B. Strauss, B. Mason, V. Gaertner, A. Koch, and L. Berg, 1993: Operational cloud-motion winds from meteosat infrared images. J. Appl. Meteorol., 32, 1206−1225, https://doi.org/10.1175/1520-0450(1993)032<1206:OCMWFM>2.0.CO;2.

Soden, J. B., C. S. Velden, and R. E. Tuleya, 2001: The impact of satellite winds on experimental GFDL hurricane model forecasts. Mon. Wea. Rev., 129, 835−852, https://doi.org/10.1175/1520-0493(2001)129<0835:TIOSWO>2.0.CO;2.

Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part Ⅱ: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 5095−5115, https://doi.org/10.1175/2008MWR2387.1.

Velden, C. S., T. L. Olander, and S. Wanzong, 1998: The impact of multispectral GOES-8 wind information on Atlantic tropical cyclone track forecasts in 1995. Part I: Dataset methodology, description, and case analysis. Mon. Wea. Rev., 126, 1202−1218, https://doi.org/10.1175/1520-0493(1998)126<1202:TIOMGW>2.0.CO;2.

Velden, C. S., C. M. Hayden, S. J. W. Nieman, W. P. Menzel, S. Wanzong, and J. S. Goerss, 1997: Upper-tropospheric winds derived from geostationary satellite water vapor observations. Bull. Amer. Meteor. Soc., 78, 173−196, https://doi.org/10.1175/1520-0477(1997)078<0173:UTWDFG>2.0.CO;2.

Velden, C., W. E. Lewis, W. Bresky, D. Stettner, J. Daniels, and S. Wanzong, 2017: Assimilation of high-resolution satellite-derived atmospheric motion vectors: Impact on HWRF forecasts of tropical cyclone track and intensity. Mon. Wea. Rev., 145, 1107−1125, https://doi.org/10.1175/MWR-D-16-0229.1.

Wan, X. M., W. Han, W. H. Tian, and X. H. He, 2018: The application of intensive FY-2G AMVs in GRAPES_RAFS. Plateau Meteorology, 37, 1083−1093, https://doi.org/10.7522/j.issn.1000-0534.2017.00089. (in Chinese with English abstract)

Wan, X. M., J. D. Gong, W. Han, and W. H. Tian, 2019: The evaluation of FY-4A AMVs in GRAPES_RAFS. Meteorological Monthly, 45, 458−468, https://doi.org/10.7519/j.issn.1000-0526.2019.04.002. (in Chinese with English abstract)

Wang, D. L., X. D. Liang, Y. H. Duan, and J. C. L. Chan, 2006: Impact of four-dimensional variational data assimilation of atmospheric motion vectors on tropical cyclone track forecasts. Wea. Forecasting, 21, 663−669, https://doi.org/10.1175/waf940.1.

Wang, G. Q., and X. Shen, 2018: The FY-4 radiometer imager and the application of its data in the satellite meteorology. Chinese Journal of Nature, 40, 1−11, https://doi.org/10.3969/j.issn.0253-9608.2018.01.001.(inChinesewithEnglishabstract). (in Chinese with English abstract)

Wu, T.-C., H. Liu, S. J. Majumdar, C. S. Velden, and J. L. Anderson, 2014: Influence of assimilating satellite-derived atmospheric motion vector observations on numerical analyses and forecasts of tropical cyclone track and intensity. Mon. Wea. Rev., 142, 49−71, https://doi.org/10.1175/mwr-d-13-00023.1.

Xie, Y. H., S. Y. Fan, M. Chen, J. C. Shi, J. Q. Zhong, and X. Y. Zhang, 2019: An assessment of satellite radiance data assimilation in RMAPS. Remote Sensing, 11, 54, https://doi.org/10.3390/rs11010054.

Yamashita, K., 2012: An observing system experiment of MTSAT rapid scan AMV using JMA meso-scale operational NWP system. Proc. 11th International Winds Workshop, Auckland, New Zealand, S4−15.

Yang, L., Z. H. Wang, Y. L. Chu, H. Zhao, and M. Tang, 2014: Water vapor motion signal extraction from FY-2E longwave infrared window images for cloud-free regions: The temporal difference technique. Adv. Atmos. Sci., 31, 1386−1394, https://doi.org/10.1007/s00376-014-3165-9.

Zhang, Z. Q., and Coauthors, 2017: Application and development of FY-4 meteorological satellite. Aerospace Shanghai, 34, 8−19, https://doi.org/10.19328/j.cnki.1006-1630.2017.04.002. (in Chinese with English abstract)

Zhao, L., J. Shang, X. H. Feng, and Z. Q. Zhang, 2019: Typical observation area design of FY-4 geostationary meteorological satellite Imager. Advances in Meteorological Science and Technology, 9, 37−40, https://doi.org/10.3969/j.issn.2095-1973.2019.01.006. (in Chinese with English abstract)