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This paper presents a rapid regression algorithm for the retrieval of methane (CH) profile from Atmospheric Infrared Sounder (AIRS) based on empirical orthogonal functions (EOF) and its validation. This algorithm was trained using the simulated radiance from an assemble of atmospheric profiles and can be utilized to derive the CH profile rapidly with the input of the AIRS cloud-clear radiance. Validation using hundreds of aircraft profiles demonstrates that the root mean square error (RMSE) is about 1.5 % in the AIRS sensitive region of 359-596 hPa, which is smaller than AIRS-V5 product (except in high latitudes). Comparison with the ground-based solar Fourier transform spectrometry observations showed that the RMSE of the retrieved CH total column amount is less than 3 %. This EOF-based regression method can be easily applied to other thermal infrared sounders for deriving CH and some other gases, and the derived profiles can be used as the first guess for further physical retrieval. [ABSTRACT FROM AUTHOR]

It has been found that the concentration of atmospheric methane (CH4) has rapidly increased since 2007 after a decade of nearly constant concentration in the atmosphere. As an important greenhouse gas, such an increase could enhance the threat of global warming. To better quantify this increasing trend, a novel statistic method, i.e. the Ensemble Empirical Mode Decomposition (EEMD) method, was used to analyze the CH4 trends from three different measurements: the mid–upper tropospheric CH4 (MUT) from the space-borne measurements by the Atmospheric Infrared Sounder (AIRS), the CH4 in the marine boundary layer (MBL) from NOAA ground-based in-situ measurements, and the column-averaged CH4 in the atmosphere (XCH4) from the ground-based up-looking Fourier Transform Spectrometers at Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). Comparison of the CH4 trends in the mid–upper troposphere, lower troposphere, and the column average from these three data sets shows that, overall, these trends agree well in capturing the abrupt CH4 increase in 2007 (the first peak) and an even faster increase after 2013 (the second peak) over the globe. The increased rates of CH4 in the MUT, as observed by AIRS, are overall smaller than CH4 in MBL and the column-average CH4. During 2009–2011, there was a dip in the increase rate for CH4 in MBL, and the MUT-CH4 increase rate was almost negligible in the mid-high latitude regions. The increase of the column-average CH4 also reached the minimum during 2009–2011 accordingly, suggesting that the trends of CH4 are not only impacted by the surface emission, however that they also may be impacted by other processes like transport and chemical reaction loss associated with [OH]. One advantage of the EEMD analysis is to derive the monthly rate and the results show that the frequency of the variability of CH4 increase rates in the mid–high northern latitude regions is larger than those in the tropics and southern hemisphere. [ABSTRACT FROM AUTHOR]