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The hyper-spectral Cross-track Infrared Sounder (CrIS) on board Suomi National Polar-orbiting Partnership (NPP) supports a continuing advance in numerical weather prediction (NWP) for improved short- to medium-range weather forecast skills. The assimilation of CrIS brightness temperature observations in NWP modeling systems requires the data biases be properly estimated and removed from data. Both the solar radiation reflected by sea surface into the satellite viewing direction and the solar pumping that deviates the stratosphere from the local thermal equilibrium (LTE) introduce the significant biases in CrIS infrared shortwave observations. In this study, the effects of sun glint and nonlocal thermal equilibrium (NLTE) on CrIS data biases are assessed quantitatively. It is found that the newly-developed sun glint and NLTE models can dramatically reduce the CrIS data biases at infrared shortwave band during daytime. However, the biases still remain relatively large for CrIS infrared shortwave stratospheric channels after the NLTE correction. A further study confirms that the bias residuals after the NLTE correction mainly come from the input temperature profiles to the Radiative Transfer Model (RTM) not the RTM itself. It is found that the temperature profiles from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS), which serve as input to the Community Radiative Transfer Model (CRTM), have large cold biases in the upper stratosphere, leading to the large bias remnants of stratospheric channels. Compared with the temperature profiles from ERA Interim reanalysis, the cold biases of GFS temperature profiles increase with altitude and reach about 10 K near 1 hPa.