Striping noise mitigation in ATMS brightness temperatures and its impact on cloud LWP retrievals

Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar‐orbiting Partnership (NPP) satellite provides global distributions of microwave brightness temperature measurements at 22 temperature and humidity sounding channels twice daily. However, the differences between observations and brightness temperature simulations exhibit a systematic along‐track striping noise for all channels. In this study, a set of 22 “optimal” filters is designed to remove the striping noise in different channels. It is shown that the original method for ATMS striping noise mitigation developed by Qin et al. ( ) can be simplified and made suitable for use in an operational context. Impacts of striping noise mitigation on small‐scale weather features are investigated by comparing ATMS cloud liquid water path (LWP) retrieved before and after striping noise mitigation. It is shown that the optimal filters do not affect small‐scale cloud features while smoothing out striping noise in brightness temperatures. It is also shown that the striping noise is present in the LWP retrievals if the striping noise in brightness temperatures of ATMS channels 1 and 2 is not removed. The amplitude of the striping noise in LWP is linearly related to the magnitude of striping noise in ATMS brightness temperature observations.

[1]  Joseph Sela,et al.  Spectral Modeling at the National Meteorological Center , 1980 .

[2]  G. Poe,et al.  Sensitivity of the Total Power Radiometer with Periodic Absolute Calibration , 1981 .

[3]  Eugenia Kalnay,et al.  Global Numerical Weather Prediction at the National Meteorological Center , 1990 .

[4]  John Derber,et al.  The National Meteorological Center's spectral-statistical interpolation analysis system , 1992 .

[5]  F. Weng,et al.  Retrieval of cloud liquid water using the special sensor microwave imager (SSM/I) , 1994 .

[6]  Fuzhong Weng,et al.  Advanced microwave sounding unit cloud and precipitation algorithms , 2003 .

[7]  R. Pincus.  A First Course on Atmospheric Radiation , 2004 .

[8]  Fuzhong Weng,et al.  Advanced Technology Microwave Sounder , 2006 .

[9]  Fuzhong Weng,et al.  A fast radiative transfer model for SSMIS upper atmosphere sounding channels , 2007 .

[10]  Norden E. Huang,et al.  Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method , 2009, Adv. Data Sci. Adapt. Anal..

[11]  Norden E. Huang,et al.  The Multi-Dimensional Ensemble Empirical Mode Decomposition Method , 2009, Adv. Data Sci. Adapt. Anal..

[12]  X. Zou,et al.  Introduction to Suomi national polar‐orbiting partnership advanced technology microwave sounder for numerical weather prediction and tropical cyclone applications , 2012 .

[13]  Niels Bormann,et al.  Evaluation and assimilation of ATMS data in the ECMWF system , 2013 .

[14]  Fuzhong Weng,et al.  Analysis of ATMS striping noise from its Earth scene observations , 2013 .

[15]  Fuzhong Weng,et al.  Calibration of Suomi national polar‐orbiting partnership advanced technology microwave sounder , 2013 .

[16]  Fuzhong Weng,et al.  Uncertainty of AMSU-A derived temperature trends in relationship with clouds and precipitation over ocean , 2014, Climate Dynamics.

[17]  Fuzhong Weng,et al.  Improved Quantitative Precipitation Forecasts by MHS Radiance Data Assimilation with a Newly Added Cloud Detection Algorithm , 2013 .