# The Combined ASTER MODIS Emissivity over Land (CAMEL) Part 2: Uncertainty and Validation
## 5 Conclusions  
The NASA CAMEL product reports monthly global land surface emissivity at 13 hinge points between 3.6-14.3 \(\upmu\)m and provides software which uses a PCA approach to compute 417 channel high spectral emissivity spectra from the 13 hinge point product for the same wavelength region. The uncertainty provided with the product is available at the 13 hinge point resolution for every month and grid point and is a combination of 3 separate components of variability--a spatial, temporal, and algorithm component. This work presented the methodology behind the uncertainty estimates included in the product and a comprehensive validation of the CAMEL product which included laboratory measurements, product intercomparisons, and radiative transfer calculations. Comparisons of CAMEL to validation data, the 8-year averaged IASI dataset, and the previous UW BF emissivity show an improvement of CAMEL in the characterization of snow, quartz, and carbonate spectral features. The monthly and inter-annual variations of the emissivity reveal dynamic land surface changes, for example, snow in the mountains. Comparison of the CAMEL 13 hinge point product to the 8-year averaged IASI dataset at 0. 25\({}^{\circ}\) spatial resolution showed maximum differences were located in the shortwave 3.6 \(\upmu\)m region, where they reached over 0.15 magnitude in emissivity for some geographic locations, typically dry desert regions. Differences at 8.6 \(\upmu\)m were primarily less than 0.1 and at wavelengths of 10.8 \(\upmu\)m or larger they were predominantly under 0.02. Assessment of the CAMEL RTTOV emissivity module was made using IASI brightness temperature observations as a reference. Calculated minus observed BT biases were computed for both the CAMEL emissivity and a constant 0.98 emissivity spectra, a commonly used simplification for a land surface emissivity estimate. The use of a de-biased spectral variance over three spectral regions was used as a measure of emissivity spectral accuracy. The average of the de-biased variances was found over IGBP land classification schemes for four days which represented four seasons. Land classifications which showed improvement with the use of the CAMEL emissivity for all three spectral regions were the open shrub and barren/desert land categories. In general, the 3.6-5 and 8-9 \(\upmu\)m region statistics showed the CAMEL to be a better emissivity estimate than the constant 0.98 value, while the 10-13 \(\upmu\)m region showed an improvement only for barren or partially barren surfaces. As expected, the percentage decreases in the 3.6-5 and 8-9 \(\upmu\)m four day-averaged variances were larger than the percent increases for the 10-13 \(\upmu\)m region when comparing CAMEL with respect to the 0.98 emissivity. This two-part paper has described the methodology, applications, uncertainty, and validation of the first release of the CAMEL dataset available from a NASA MEASUUREs project at [[https://lpdaac.usgs.gov/dataset_discovery/measures/measures_products_table/cam5k30](https://lpdaac.usgs.gov/dataset_discovery/measures/measures_products_table/cam5k30) em_v001]([https://lpdaac.usgs.gov/dataset_discovery/measures/measures_products_table/cam5k30](https://lpdaac.usgs.gov/dataset_discovery/measures/measures_products_table/cam5k30) em_v001). Future work will include version updates to improve some known issues, for example, snow fraction in mixed scenes, and the development of a 16-year CAMEL climatology and covariance for use in NWP applications. The ASTER GED version 4 (v4) product used in this study was produced at JPL and is available courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), United States Geological Survey/Earth Resources Observation and Science Center, Sioux Falls, South Dakota, [[[https://lpdaac.usgs.gov/dataset_discovery/aster](https://lpdaac.usgs.gov/dataset_discovery/aster)]([https://lpdaac.usgs.gov/dataset_discovery/aster](https://lpdaac.usgs.gov/dataset_discovery/aster))]. This work was done under grant number: NNX08 AF8A.