Statistical analysis of global variations of atmospheric relative humidity as observed by AIRS

Abstract

Atmospheric water vapor plays a key role in the climate. Numerical model calculations suggest that global mean relative humidity (RH) stays approximately constant in global warming scenarios. Here, we analyze the September 2002 to April 2011 daily mean free tropospheric relative humidity (RH) data from the Atmospheric Infrared Sounder (AIRS), version 5 level 3 data at a spatial resolution of 1°/1° longitude/latitude. We perform a multiple linear regression analysis with annual harmonics, trend and an El‐Niño–Southern Oscillation (ENSO) index. For the mean annual cycle, we find strong compensation of local variability upon global averaging, leaving an amplitude for the global mean of about 4% RH (peak to peak) at 300 hPa, with the minimum in February. The amplitude decreases to about 2.5%RH at 500 hPa (with minimum shifted to boreal summer/early fall) and less than 2%RH further below. For ENSO, the local changes compensate strongly upon global averaging. Computational limitations restrict detailed analysis of the residual to the zonal mean residual, which we interpret with a stochastic model that takes the latitudinal covariance into account. We find that the relation between zonal mean residual RH variations (understood as the consequence of ‘weather’ and subseasonal variability) and their global mean is equivalent to that of about 9 independent random time series with appropriate variances. The residual contributes more to the variance of the global mean than the harmonics and ENSO on all free tropospheric levels except 400 hPa. Our results apply to the AIRS version 5 data as reported, and possible problems in that data are discussed.