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The new 3rd generation geostationary (GEO) imagers will have many of the same NPP-VIIRS imager spectral bands, thereby offering the opportunity to apply the VIIRS cloud, aerosol, and land use retrieval algorithms on the new GEO imager measurements. Climate quality retrievals require multi-channel calibrated radiances that are stable over time. The deep convective cloud calibration technique (DCCT) is a large ensemble statistical technique that assumes that the DCC reflectance is stable over time. Because DCC are found in sufficient numbers across all GEO domains, they provide a uniform calibration stability evaluation across the GEO constellation. The baseline DCCT has been successful in calibrating visible and near-infrared channels. However, for shortwave infrared (SWIR) channels the DCCT is not as effective to monitor radiometric stability. The DCCT was optimized as a function wavelength in this paper. For SWIR bands, the greatest reduction of the DCC response trend standard error was achieved through deseasonalization. This is effective because the DCC reflectance exhibits small regional seasonal cycles that can be characterized on a monthly basis. On the other hand, the inter-annually variability in DCC response was found to be extremely small. The Met-9 0.65-mu m channel DCC response was found to have a 3% seasonal cycle. Deseasonalization reduced the trend standard error from 1% to 0.4%. For the NPP-VIIRS SWIR bands, deseasonalization reduced the trend standard error by more than half. All VIIRS SWIR band trend standard errors were less than 1%. The DCCT should be able to monitor the stability of all GEO imager solar reflective bands across the tropical domain with the same uniform accuracy.