1. Earth Science Data Systems (ESDS) Program
  2. Competitive Programs
  3. Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program
  4. A Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR) for Earth Science

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

Principal Investigator (PI): Simon Hook, NASA's Jet Propulsion Laboratory (JPL)

NASA has identified Land Surface Temperature and Emissivity (LST&E) data as an important Earth System Data Record (ESDR) along with other international organizations (e.g., Global Climate Observing System (GCOS), 2003; Climate Change Science Program (CCSP), 2006).

LST&E data are essential for a wide variety of studies such as monitoring the effects of climate change, calculating the evapotranspiration (ET) of plant canopies, and retrieving atmospheric water vapor. LST&E products are currently produced by low Earth orbit (LEO) sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection (ASTER) on NASA's Terra and Aqua satellites), and also from geostationary Earth orbit (GEO) platforms (e.g., Geostationary Operational Environmental Satellites [GOES]). Although these products represent the same measure, they are produced at different spatial, spectral, and temporal resolutions using different scientific approaches resulting in discrepancies between the standard products.

In 2014, we began the integration of different LST&E data streams from the LEO and GEO observations to develop a unified set of LST&E ESDRs that are more accurate and informative than the original input datasets and include a complete set of uncertainty statistics. We will continue generating these LST&E ESDRs in order to extend the data record more than two decades (2000-2024) and provide the first long-term climate quality LST&E data record for Earth science.

We will continue to generate two unified Land Surface Temperature (LST) ESDR products: one at high spatial resolution (1km) using LEO satellites, and one at high temporal resolution (hourly over North America) using GEO satellites. The LEO-LST product combines two existing MODIS products, using an uncertainty analysis approach to optimize accuracy over different land cover classes.

Validation of these approaches for retrieving LST have shown that they are complementary, with the split-window approach (MxD11) being more stable over heavily vegetated regions and the physics-based approach (MxD21) demonstrating higher accuracy in semiarid and arid regions where the largest variations in emissivity exist, both spatially and spectrally. The GEO LST-ESDR product uses the emissivity product described below for improved temperature-emissivity separation and the same atmospheric correction as the LEO LST product to ensure consistency across all three data records.

We will continue production of the unified LEO Land Surface Emissivity (LSE)-ESDR at 5km on monthly time-steps by merging two current state-of-the-art emissivity databases, the University of Wisconsin Madison MODIS Infrared emissivity database (UWIREMIS), and the JPL ASTER Global Emissivity Dataset (GED). The LSE-ESDR, now termed the Combined ASTER MODIS Emissivity for Land (CAMEL), will continue with production based on MxD21C3 emissivity data in Collection 6, and updates to the ASTER GED using monthly MODIS snow and vegetation index products for the adjustments. CAMEL is available at the Land Processes Distributed Active Archive Center (LP DAAC).

Several research groups have already begun implementing CAMEL in their atmospheric sounder retrieval schemes (e.g. NUCAPS, AIRS), and data assimilation systems (UK Metoffice, NRL, Meteo-France).

The unified LST and LSE-ESDRs will benefit numerous applications, including improved land surface modeling and estimates of evapotranspiration, monitoring climate changes over urban and rural landscapes, atmospheric retrievals of atmospheric water vapor (MODIS, AIRS, IASI), and in data assimilation systems and radiative transfer models

Last Updated: Aug 29, 2019 at 11:06 AM EDT