[1] Anderson, J., T. Hoar, K. Raeder, et al., 2009: The Data Assimilation Research Testbed: A community facility. Bull. Amer. Meteor. Soc., 90, 1283–1296. doi: 10.1175/2009BAMS2618.1
[2] Andersson, E., J. Haseler, P. Undén, et al., 1998: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). III: Experimental results. Quart. J. Roy. Meteor. Soc., 124, 1831–1860. doi: 10.1002/qj.49712455004
[3] Atlas, R., and R. N. Hoffman, 2000: The use of satellite surface wind data to improve weather analysis and forecasting at the NASA Data Assimilation Office. Elsevier Oceanography Series, 63, 57–78. doi: 10.1016/S0422-9894(00)80005-7
[4] Atlas, R., R. N. Hoffman, S. M. Leidner, et al., 2001: The effects of marine winds from scatterometer data on weather analysis and forecasting. Bull. Amer. Meteor. Soc., 82, 1965–1990. doi: 10.1175/1520-0477(2001)082<1965:TEOMWF>2.3.CO;2
[5] Barker, D., X.-Y. Huang, Z. Q. Liu, et al., 2012: The Weather Research and Forecasting Model’s Community Variational/Ensemble Data Assimilation System: WRFDA. Bull. Amer. Meteor. Soc., 93, 831–843. doi: 10.1175/BAMS-D-11-00167.1
[6] Barker, D. M., W. Huang, Y.-R. Guo, et al., 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897–914. doi: 10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2
[7] Bi, L., J. A. Jung, M. C. Morgan, et al., 2011: Assessment of assimilating ASCAT surface wind retrievals in the NCEP Global Data Assimilation System. Mon. Wea. Rev., 139, 3405–3421. doi: 10.1175/2011MWR3391.1
[8] Bonavita, M., M. Dahoui, P. Lopez, et al., 2017: On the Initialization of Tropical Cyclones. ECMWF Technical Memorandum No. 810, ECMWF, Shinfield Park, Reading, 39 pp.
[9] Candy, B., 2001: The Assimilation of Ambiguous Scatterometer Winds Using a Variational Technique: Method and Forecast Impact. Forecasting Research Technical Report No. 349, Met Office, Exeter, UK, 23 pp. Available online at https://library.metoffice.gov.uk/Portal/Default/en-GB/RecordView/Index/46757. Accessed on 24 May 2021.
[10] Dee, D. P., S. M. Uppala, A. J. Simmons, et al., 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597. doi: 10.1002/qj.828
[11] Dobson, F., L. Hasse, and R. Davis, 1980: Air–Sea Interaction: Instruments and Methods. Springer, Boston, 1–4, doi: 10.1007/978-1-4615-9182-5.
[12] Ebuchi, N., H. C. Graber, and M. J. Caruso, 2002: Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. J. Atmos. Oceanic Technol., 19, 2049–2062. doi: 10.1175/1520-0426(2002)019<2049:EOWVOB>2.0.CO;2
[13] Gao, F., X. Y. Zhang, N. A. Jacobs, et al., 2012: Estimation of TAMDAR observational error and assimilation experiments. Wea. Forecasting, 27, 856–877. doi: 10.1175/WAF-D-11-00120.1
[14] Hilton, F., A. Collard, V. Guidard, et al., 2009: Assimilation of IASI radiances at European NWP centres. Proc. Workshop on the Assimilation of IASI in NWP, ECMWF/EUMETSAT Numerical Weather Prediction-Satellite Application Facility (NWP-SAF), Reading, UK, 73 pp.
[15] Huang, X.-Y., F. Gao, N. A. Jacobs, et al., 2013: Assimilation of wind speed and direction observations: A new formulation and results from idealised experiments. Tellus A, 65, 19936. doi: 10.3402/tellusa.v65i0.19936
[16] Isaksen, L., and A. Stoffelen, 2000: ERS scatterometer wind data impact on ECMWF’s tropical cyclone forecasts. IEEE Trans. Geosci. Remote Sens., 38, 1885–1892. doi: 10.1109/36.851771
[17] Lin, W. M., M. Portabella, A. Stoffelen, et al., 2017: On the improvement of ASCAT wind data assimilation in global NWP. Proc. 2017 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Fort Worth, TX, 402–405, doi: 10.1109/IGARSS.2017.8126980.
[18] Ochoa, B., and S. Belongie, 2006: Covariance propagation for guided matching. Proc. Workshop on Statistical Methods in Multi-Image and Video Processing, University of California, San Diego, USA, 12 pp.
[19] Plant, W. J., 2000: Effects of wind variability on scatterometry at low wind speeds. J. Geophys. Res. Oceans, 105, 16,899–16,910. doi: 10.1029/2000JC900043
[20] Ricciardulli, L., and F. Wentz, 2012: Development of consistent geophysical model functions for different scatterometer missions: Ku and C-band. Proc. 2012 NASA International Ocean Vector Wind Science Team Meeting, NASA, Utrecht, Netherlands, 28 pp.
[21] Ricciardulli, L., and F. J. Wentz, 2016: Remote Sensing Systems ASCAT C-2015 Daily Ocean Vector Winds on 0.25 Deg Grid, Version 02.1. Remote Sensing Systems, Santa Rosa. Available online at www.remss.com/missions/ascat. Accessed on 12 May 2021.
[22] Schwartz, B., and S. G. Benjamin, 1995: A comparison of temperature and wind measurements from ACARS-equipped aircraft and rawinsondes. Wea. Forecasting, 10, 528–544. doi: 10.1175/1520-0434(1995)010<0528:ACOTAW>2.0.CO;2
[23] Stoffelen, A., and P. van Beukering, 1997: Implementation of Improved ERS Scatterometer Data Processing and Its Impact on HIRLAM Short Range Weather Forecasts. HIRLAM Technical Report 31, IMET, Dublin, Ireland, 77 pp. Available online at http://www.hirlam.org/index.php/hirlam-documentation/doc_download/1322-hirlam-technical-report-no-31. Accessed on 24 May 2021.
[24] Stoffelen, A. C. M., and G. J. Cats, 1991: The impact of Seasat-A scatterometer data on high-resolution analyses and forecasts: The development of the QE II storm. Mon. Wea. Rev., 119, 2794–2802. doi: 10.1175/1520-0493(1991)119<2794:TIOASD>2.0.CO;2
[25] Wang, X. G., D. M. Barker, C. Snyder, et al., 2008: A hybrid ETKF–3DVAR data assimilation scheme for the WRF model. Part I: Observing system simulation experiment. Mon. Wea. Rev., 136, 5116–5131. doi: 10.1175/2008MWR2444.1
[26] Ying, M., W. Zhang, H. Yu, et al., 2014: An overview of the China Meteorological Administration tropical cyclone database. J. Atmos. Oceanic Technol., 31, 287–301. doi: 10.1175/JTECH-D-12-00119.1
[27] Zhang, F. Q., Y. H. Weng, J. A. Sippel, et al., 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 2105–2125. doi: 10.1175/2009MWR2645.1