Atmospheric and land surface characterization using a land surface emissivity database derived from AMSR-E and MODIS

Author: Jean-Luc Moncet, Pan Liang, John F. Galantowicz, Alan E. Lipton and Gennady Uymin
October 8, 2011

Moncet, J.-L., P. Liang, J. F. Galantowicz, A. E. Lipton, and G. Uymin, 2011:  Atmospheric and land surface characterization using a land surface emissivity database derived from AMSR-E and MODIS.  Final Report NASA Contract NNH08CC96C.

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This Final Report describes work performed under AER Project 1342 (P1342) on “Atmospheric and land surface characterization using a land surface emissivity database derived from AMSR-E and MODIS” funded by NASA (contract NNH08CC96C). Time period: April 2008 – October 2011.

Microwave measurements from space have great potential to contribute to the detection and understanding of climate trends, due largely to the stability of their calibration and their unique ability to detect surface and atmosphere properties through clouds. Microwave products thus minimize the “cloud bias” that occurs with infrared-based analysis, in which the datasets systematically exclude cloudy areas. These biases can be particularly damaging when analyzing trends in parameters like land surface temperature and water vapor, which are strongly correlated with cloudiness.

This project is the continuation of work under our former NASA grant (contract # NNH04CC43C) of developing and utilizing a microwave emissivity database with data from AMSR-E and other EOS instruments. The tasks accomplished under the current grant include

(1) completing the implementation of our Version 1 AMSR-E emissivity retrieval algorithm and producing one full-year of global monthly mean emissivity data complemented by spatially and temporally matched infrared emissivities from the MODIS V.4 MYB11 daily LST product

(2) assessing the potential for meeting internally set requirements for application of the database to characterization of climate sensitive parameters such as land surface emissivity and temperature, and atmospheric water vapor

(3) refining emissivity retrieval procedure (to improve yield and quality of the emissivity estimates) and assessing potential impact of upgrades in external data sources on the quality of the emissivity product

(4) application of the data base to estimation of land surface temperature over vegetated surfaces and deserts and validation of emissivity product.

The primary goal of this study is to make the preparatory work that will lead to a second improved version of the database that is particularly well suited for retrieval/assimilation applications and routine production of accurate climate related products, and identify particular areas where future development might be needed.


In this report, we provided a description of the Version1 AMSR-E land surface emissivity retrieval algorithm and products. The data base produced as part of this NASA funded effort represents a significant step forward compared to previous attempts to build similar microwave emissivity atlases. In particular, the improved treatment of penetration effects combined with the high degree of consistency between the MODIS LST product and AMSR-E observations results in a better separation of surface emissivities and thermal effects over arid areas. As a result our AMSR-E estimated emissivities are more stable in time than those produced in the past using SSM/I and ISCCP while neglecting penetration effects (Prigent 1997). Our advanced quality control procedure also results in better quality surface emissivity estimates over vegetated areas. Detailed description of this work can be found in Moncet et al. 2011a, Galantowicz et al., 2011 and Moncet et al. 2011b.

As part of this phase we also proposed a number of key enhancements aimed at improving the quality of the emissivity product and yield in preparation of Version 2 of the emissivity atlas. These enhancements include:
- Mapping the AMSR-E Tb product on a fixed Earth grid which should minimize impact of surface inhomogeneity and provide temporally consistent infrared and microwave surface temperature estimates.
- Development of a R11-based time segmentation (RTS) which results in higher yield and higher quality surface emissivity estimates in stable areas
- Addition of the Terra MODIS Tskin products for improved characterization of surface forcing in 1b algorithm reduces noise in estimated thermal model parameters over deserts