Future deep-space communications will require the collection and transmission of data from high-bandwidth links. NASA's Jet Propulsion Laboratory (JPL) is investigating the utility of laser communications for future missions to Mars and for future communication stations on the moon. Cloud cover impacts the availability of space to ground optical communications. Mitigating these impacts requires a geographically diverse network of ground communication. Selecting the number and location of stations for a network requires an optimization algorithm that can distinguish and rank site availability based on multi-year cloud climatologies for many locations around the globe. The optimization algorithm must also consider the movement and location of a space-borne probe. In this JPL-funded study, the TASC Lasercom Network Optimization Tool (LNOT) is used to determine optimal networks of receiving stations by analyzing cloud mask data from the continental United States, Hawaii, South America, Europe, northern and southern Africa, the Middle East, central and eastern Asia, and Australia. To generate cloud masks, raw visible and infrared radiance data from GOES (Geostationary Operational Environmental Satellite) and Meteosat satellites are compared to predicted clear sky background values. Several threshold tests in the Cloud Mask Generator (CMG) involving radiance-derived cloud identification tools (e.g., fog product, albedo product) are used to estimate the probability of cloud cover for a given pixel of a satellite image. When stations are chosen from a list of sites of interest, six stations are needed to achieve a network availability of 90 % or better.