Using a meteorological similarity comparison method (MSCM), we performed a mutual and simultaneous evaluation of the surface radiative flux datasets from the International Satellite Cloud Climatology Project-FD and the new radiative-flux-analysis-processed surface observations (RFA-PSO). For downward shortwave (SW), diffuse (Dif), and direct (Dir) fluxes, matching cloud fraction (CF) reduces the flux difference between FD and RFA-PSO by up to a factor of 2. Decreasing the aerosol optical depth values used in the FD calculations accounts for much of the remaining difference. For downward longwave (LW) flux, matching either surface air temperature or CF reduces the flux difference to nearly zero. For the total downward SW diurnal variations, there is excellent agreement for both clear and cloudy sky, but less good agreement for the Dif and Dir components. The latter agree much better for clear sky when the FD aerosol optical depth is reduced and for cloudy sky when matching CF and cloud optical depth jointly. For LW diurnal variations, the agreement is best for clear sky, but FD has a larger amplitude by 3–7 W/m2 for cloudy sky because of differing sensitivities to cirrus and low clouds in the two datasets. These results confirm that the source of the FD surface flux uncertainty of ∼10–15 W/m2 is the input quantities, not the radiative transfer model. An important limitation of the RFA-PSO cloud parameters (not the fluxes) is the inhomogeneous diurnal sampling and the retrieval difficulties with broken clouds (SW) and cirrus clouds (LW).