Details:

Journal Title:
Journal of Applied Meteorology and Climatology
Personal Author:
Prakash, Satya ; Norouzi, Hamid ; Azarderakhsh, Marzi ; Blake, Reginald ; Prigent, Catherine ; ... More +
Prakash, Satya ; Norouzi, Hamid ; Azarderakhsh, Marzi ; Blake, Reginald ; Prigent, Catherine ; Khanbilvardi, Reza Less -
NOAA Program & Office:
CREST (Center for Earth System Sciences and Remote Sensing Technologies and Tech Center at City College of CUNY)
Description:
Accurate estimation of passive microwave land surface emissivity (LSE) is crucial for numerical weather prediction model data assimilation, for microwave retrievals of land precipitation and atmospheric profiles, and for a better understanding of land surface and subsurface characteristics. In this study, global instantaneous LSE is estimated for a 9-yr period from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and for a 5-yr period from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors. Estimates of LSE from both sensors were obtained by using an updated algorithm that minimizes the discrepancy between the differences in penetration depths from microwave and infrared remote sensing observations. Concurrent ancillary datasets such as skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) and profiles of air temperature and humidity from the Atmospheric Infrared Sounder are used. The latest collection 6 of MODIS skin temperature is used for the LSE estimation, and the differences between collections 6 and 5 are also comprehensively assessed. Analyses reveal that the differences between these two versions of infrared-based skin temperatures could lead to approximately a 0.015 difference in passive microwave LSE values, especially in arid regions. The comparison of global mean LSE features from the combined use of AMSR-E and AMSR2 with an independent product—Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2)—shows spatial pattern correlations of order 0.92 at all frequencies. However, there are considerable differences in magnitude between these two LSE estimates, possibly because of differences in incidence angles, frequencies, observation times, and ancillary datasets.
Keywords:
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Microwave Remote Sensing Weather Forecasting
Source:
Journal of Applied Meteorology and Climatology, 57(4), 907-919
DOI:
https://doi.org/10.1175/JAMC-D-17-0213.1
Document Type:
Journal Article
Funding:
Grant no. NA16SEC4810008
Rights Information:
Other
Compliance:
Submitted
Main Document Checksum:
[+]
urn:sha256:ac2c42bf7d5714bbc53a5ef3d21c97b1360c6f233efc60e003074a1b2e886f12
Download URL:
https://repository.library.noaa.gov/view/noaa/27315/noaa_27315_DS1.pdf
File Type:

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