Determining the level of zero net radiative heating (LZH) is critical to understanding parcel trajectory in the Tropical Tropopause Layer (TTL) and associated stratospheric hydration processes. Previous studies of the TTL radiative balance have focused on using radiosonde data, but remote sensing measurements from polar-orbiting satellites may provide the relevant horizontal and vertical information for assessing TTL solar heating and infrared cooling rates, especially across the Pacific Ocean. CloudSat provides a considerable amount of vertical information about the distribution of cloud properties relevant to heating rate analysis. The ability of CloudSat measurements and ancillary information to constrain LZH is explored. We employ formal error propagation analysis for derived heating rate uncertainty given the CloudSat cloud property retrieval algorithms. Estimation of the LZH to within approximately 0.5 to 1 km is achievable with CloudSat, but it has a low-altitude bias because the radar is unable to detect thin cirrus. This can be remedied with the proper utilization of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar backscatter information. By utilizing an orbital simulation with the GISS data set, we explore the representativeness of non-cross-track scanning active sounders in terms of describing the LZH distribution. In order to supplement CloudSat, we explore the ability of Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) to constrain LZH and find that these passive sounders are useful where the cloud top height does not exceed 7 km. The spatiotemporal distributions of LZH derived from CloudSat and CALIPSO measurements are presented which suggest that thin cirrus have a limited effect on LZH mean values but affect LZH variability.