A Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR) for Earth Science Research

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 7 January 2015
Pierre C. Guillevic, Jet propulsion Laboratory, Pasadena, CA; and G. Hulley, S. Hook, C. Hain, E. Borbas, R. T. Pinker, M. C. Anderson, and R. Knuteson

NASA has identified a major need to develop long-term, consistent products valid across multiple missions, with well-defined uncertainty statistics addressing specific Earth science questions. These types of data sets are termed Earth System Data Records (ESDRs) and are defined as long-term, well calibrated and validated data records for Earth Science research. Land surface temperature and emissivity (LST&E) data have been identified as an important ESDR by NASA and many other international organizations, e.g. GCOS. LST&E data are essential for a wide variety of surface-atmosphere studies, from calculating the evapotranspiration of plant canopies to retrieving atmospheric water vapor. LST&E products are currently generated from sensors in low Earth orbit (LEO) such as the NASA-EOS MODIS instruments on the Terra and Aqua satellites as well as from sensors in geostationary Earth orbit (GEO) such as GOES. Sensors in LEO orbits provide global coverage at moderate spatial resolutions (~1-km) but more limited temporal coverage (twice-daily), while sensors in GEO orbits provide more frequent measurements (hourly) at lower spatial resolutions (~3-4 km) over a geographically restricted area. LST&E products from these instruments are currently produced using different emissivities, atmospheric correction, and algorithmic approaches, and usually do not include a full set of uncertainty metrics. NASA has recognized this general lack of consistency between science products and has identified the need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. We address this problem by generating three self-consistent LST&E ESDRs from 2000-2018 with well defined uncertainties; 1) a unified global LEO LST-ESDR at 1-km spatial resolution and resampled to daily, 8-day and monthly; 2) a unified N. and S. America GEO LST-ESDR at 5-km spatial resolution and resampled to hourly temporal resolution; 3) a unified global Emissivity-ESDR at 5-km spatial resolution and monthly temporal resolution. Initial results and methodologies will be discussed, including validation and inter-comparisons with heritage products.