GC51I-07
Uncertainty Estimates of NASA Satellite LST over the Greenland and Antarctic Plateau: 2003-2015

Friday, 18 December 2015: 09:30
3001 (Moscone West)
Robert Knuteson, University of Wisconsin Madison, Space Science and Engineering Center, Madison, WI, United States
Abstract:
Jin and Dickinson (2010) identify three reasons why LST has not been adopted as a climate variable. Paraphrasing the authors, the three roadblocks for use of satellite LST products in climate studies are; 
1) unknown accuracy (What are surface emissivity and atmospheric correction uncertainties?)
2) spatial scale ambiguity (Are satellite footprints too large to be physically meaningful?)
3) lack of consistency over decadal time scales (How far backward/forward can we go in time?).
These issues apply particularly to the cryosphere where the lack of surface measurement sites make the proper use of satellite observations critical for monitoring climate change. This paper will address each of these three issues but with a focus on the high and dry Greenland and Antarctic plateaus and the contrast in trends between the two. Recent comparisons of MODIS LST products with AIRS version 6 LST products show large differences over Greenland (Lee et al. 2014). In this paper we take the logical next step of creating a bottoms up uncertainty budget for a new synergistic AIRS/MODIS LST product for ice and snow conditions. This new product will address the issue of unknown accuracy by providing a local LST uncertainty along with each estimate of surface temperature. The combination of the high spatial resolution of the MODIS and the high spectral resolution of the AIRS observations of radiance allow the combination of the two sensors to provide information with lower uncertainty than what is possible from the current separate operational products. The issue of surface emissivity and atmospheric correction uncertainties will be addressed explicitly using spectrally resolved models that cover the infrared region. The issue of spatial scale ambiguity is overcome by creating a classification of the results based on the spatial homogenity of surface temperatures. The issue of lack of consistency over long time scales is addressed by demonstrating an algorithm using collocated NASA MODIS and AIRS radiance that can be applied forward in time with the VIIRS and CrIS sensors on the SNPP and JPSS platforms. In principle this will provide a 30+ year historical record of LST at Greenland and Antarctica all with a consistent data processing algorithm and uncertainty estimates which can be used to characterize climate changes.