INTRODUCTION Kinetic temperature exerts a measurable effect on most physical processes, and is explicitly used as an input to model both plant water stress and evapotranspiration . Kinetic temperature exerts a measurable effect on most physical processes, and is explicitly used as an input to model ecological processes such as photosynthesis , leaf litter decomposition , and evapotranspiration . Evapotranspiration is a process of particular interest to farmers and water managers in arid drought prone regions such as California, where the 2012 nut and fruit crop receipts alone totaled 18.7 billion dollars (CDFA, 2013-2014). The economic impact from the 2014 California drought is not yet known, but caps on total water allotment (30% of 2013 levels) to the San Joaquin Valley forces difficult decisions for farmers: inefficient watering may bring a particular crop to harvest, at the cost of available water to other fields; water a crop too little and it will undergo cavitation and wilt, ruining the harvest. Severe cavitation due to under watering requires replanting, with loss of productivity stretching over years for perennial crops such as vineyards. Accurate modeling of temperature and evapotranspiration can provide farmers with robust estimates of water demand and enable more conservative agricultural water use to salvage a harvest or keep orchards alive, reducing the human impact of drought. While in situ measurements are valuable tools for farmers, the size and scope of agriculture25.4 million acres and 80,500 farms in 2012 for California alone (CDFA, 2013-2014)underscore the necessity for regional scale remotely sensed temperature estimates that are accurate. The accuracy of temperature estimates are particularly important for physical processes like evapotranspiration, which is driven by the temperature gradient between the air and leaves, and can be less than 1K . Current remotely sensed temperature estimates typically have errors on the order of 1K when averaged over all surface types ; however, errors up to 4K are typical for spectral greybodies such as vegetation , due to both uncertainty in emissivity and moister atmospheric profiles present over large contiguous vegetation patches. Errors as large as 3K-8K can occur over vegetation in humid conditions , and even in less humid mediterranean climates robust atmospheric correction of thermal data is essential to provide operational data to farmers and resource managers.