One of the by-products of cloud data sets such as that of the International Satellite Cloud Climatology Project (ISCCP) is global information on longwave window brightness temperatures for clear skies. These brightness temperatures depend mainly on the actual surface temperature with only a slight dependence on atmospheric water vapor. Thus, it may be possible to monitor long-term temperature variations using such data. The current methods for such monitoring depend on conventional surface observations and are subject to uncertainties due to inadequate spatial sampling. To test this idea monthly clear sky brightness temperatures from the six-year Nimbus-7 cloud data set are analyzed and compared to conventional estimates of surface temperature fluctuations.