Goldberg M. D.,D. S. Crosby, and L. H. Zhou, 2001: The limb adjustment of AMSU-A observations: Methodology and validation. J. Appl. Meteor., 40(1), 70-83, https://doi.org/10.1175/1520-0450(2001)040<0070:TLAOAA>2.0.CO;2
Li J.,G. Q. Liu, 2016: Assimilation of Chinese Fengyun-3B Microwave Temperature Sounder radiances into the Global GRAPES system with an improved cloud detection threshold. Front. Earth Sci., 10(1), 145-158, https://doi.org/10.1007/s11707-015-0499-2
Li J.,Z. K. Qin, and G. Q. Liu, 2016: A new generation of Chinese FY-3C microwave sounding measurements and the initial assessments of its observations. Int. J. Remote Sens., 37(17), 4035-4058, https://doi.org/10.1080/01431161.2016.1207260
Tian X. X.,X. L. Zou, 2016: ATMS- and AMSU-A-derived hurricane warm core structures using a modified retrieval algorithm. J. Geophys. Res. Atmos., 121(21), 12 630-12 646, https://doi.org/10.1002/2016JD025042
Tian, X. and X. Zou, 2018: Capturing size and intensity changes of hurricanes Irma and Maria (2017) from polar-orbiting satellite microwave radiometers. J. Atmos. Sci., 75, 2509-2522, https://doi.org/10.1175/JAS-D-17-0315.1
Wang X.,X. Li, 2014: Preliminary investigation of FengYun-3C microwave temperature sounder (MWTS) measurements. Remote Sens. Lett.,5(12), 1002-1011, https://doi.org/10.1080/2150704X.2014.988305
Wark D. Q.,1993: Adjustment of TIROS Operational Vertical Sounder data to a vertical view. NESDIS-64, NOAA, Washington DC, 44 pp.900e5368b56cdfca45446d40eefda9achttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993atov.book.....Whttp://adsabs.harvard.edu/abs/1993atov.book.....WIn an earlier study, observations from the Special Sensor, Meteorological/Temperature (SSM/T) on the Defense Meteorological Satellite Program satellites have been used to calculate limb adjustment coefficients to transform all SSM/T data to the values they would have in a vertical view. Application of the same methods to the TIROS Operational Vertical Sounder (TOVS) measurements in the infrared regions was hampered by the irregularities of clouds and their influence on radiance temperatures. To overcome this difficulty, the angular distributions of measurements for each spectral interval were smoothed by a simple quadratic expression. The much greater number of channels in the TOVS allows a broader range of eligible channels in the algorithm for angle adjustment, although each eligible channel must be related physically rather than only statistically. Selection of channels was performed by computing all possible combinations of channels with one, two, and three associated channels and applying two criteria: minimization of the RMS fit and minimization of noise amplification. Estimated errors of fit to the data are generally less than the electrical noise of the instruments. It is shown that the smoothed latitudinal means represent individual sets of observations over a broad range of meteorological conditions and therefore satisfy the angular and universality of requirements placed on the algorithm.
Zhang K. X.,L. H. Zhou, M. Goldberg, X. P. Liu, W. Wolf, C. Y. Tan, and Q. H. Liu, 2017: A methodology to adjust ATMS observations for limb effect and its applications. J. Geophys. Res. Atmos., 122(21), 11 347-11 356, https://doi.org/10.1002/2017JD026820
Zou X.,F. Weng, B. Zhang, L. Lin, Z. Qin, and V. Tallapragada, 2013: Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of 2012 four landfall hurricanes. J. Geophys. Res. Atmos., 118(20), 11 558-11 576, https://doi.org/10.1002/2013JD020405