Land surface temperature (LST) is a key climatological variable and a proxy of the energetic state of the surface. Remote sensing is the only means available to monitor the temperature of the Earth's global surface on a synoptic and regular basis. The National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) has measured the Earth's brightness temperature, a function of LST, at moderate resolution (1.1 km at nadir) on a daily basis for more than 25 years. These data are used operationally to estimate sea surface temperature. However, no equivalent LST product exists. This may in part result from the significant challenges in producing credible LST estimates. For example, NOAA-AVHRR orbit and sensor characteristics can impart temporal and spatial artifacts in the collected data that impair their accuracy, especially as a long-term time series or Climate Data Record (CDR). In this presentation, we will identify the main challenges in developing an LST CDR from AVHRR. These include the temporal correction of orbital drift effects, the observation/illumination directional dependency and its relation to variable surface structural characteristics, the emissivity variability and its uncertainty, and the limited availability of ground validation data. Finally, we will describe efforts underway at NOAA to address these challenges for AVHRR, MODIS and VIIRS data.