Temporal variability of observed and simulated hyperspectral reflectance

The core information for this publication's citation.: 
Roberts, Y. L., et al. (2014), Temporal variability of observed and simulated hyperspectral reflectance, J. Geophys. Res., 119, 262-280, doi:10.1002/2014JD021566.
Abstract: 

Multivariate analysis techniques were used to quantify and compare the spectral and temporal variability of observed and simulated shortwave hyperspectral Earth reflectance. The observed reflectances were measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument between 2002 and 2010. The simulated reflectances were calculated using climate Observing System Simulation Experiments (OSSEs), which used two Intergovernmental Panel on Climate Change AR4 scenarios (constant CO2 and A2 emission) to drive Moderate Resolution Atmospheric Transmission simulations. Principal component (PC) spectral shapes and time series exhibited evidence of physical variables including cloud reflectance, vegetation and desert albedo, and water vapor absorption. Comparing the temporal variability of the OSSE-simulated and SCIAMACHY-measured hyperspectral reflectance showed that their Intertropical Convergence Zone-like Southern Hemisphere (SH) tropical PC1 ocean time series had a 90° phase difference. The observed and simulated PC intersection quantified their similarity and directly compared their temporal variability. The intersection showed that despite the similar spectral variability, the temporal variability of the dominant PCs differed as in, for example, the 90° phase difference between the SH tropical intersection PC1s. Principal component analysis of OSSE reflectance demonstrated that the spectral and centennial variability of the two cases differed. The A2 PC time series, unlike the constant CO2 time series, exhibited centennial secular trends. Singular spectrum analysis isolated the A2 secular trends. The A2 OSSE PC1 and PC4 secular trends matched those in aerosol optical depth and total column precipitable water, respectively. This illustrates that time series of hyperspectral reflectance may be used to identify and attribute secular climate trends with a sufficiently long measurement record and high instrument accuracy.

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Research Program: 
Radiation Science Program (RSP)
Mission: 
CLARREO