Control of interannual and longer-term variability of stratospheric water vapor

[1] We use trajectory calculations based on 40-year European Reanalysis (ERA- 40) data to predict the water mixing ratio of air entering the stratosphere in the tropics ([H2O](e)) and thereby to examine interannual and longer-term changes. [H2O](e) is determined from the saturation mixing ratio of the coldest point during ascent from the troposphere to the stratosphere ( the Lagrangian cold point). These model predictions for the time variation of [H2O](e) agree very well with a broad range of measurements (Stratospheric Aerosol and Gas Experiment (SAGE) II, Halogen Occultation Experiment (HALOE), Microwave Limb Sounder (MLS), and Atmospheric Trace Molecule Spectroscopy (ATMOS)). During periods when measurements are consistent among various sensors and ERA- 40 temperatures show good agreement with radiosondes ( 1995 - 2002), the correlation between model predictions and HALOE water vapor anomalies in the tropical lower stratosphere is r = 0.81, as high as that between HALOE and SAGE II ( r = 0.8). The model predictions suggest that the stratospheric quasi-biennial oscillation, El Nino-Southern Oscillation, and possibly volcanic eruptions all play a significant role in modulating [H2O](e), leading to interannual anomalies of order 0.5 ppmv with timescales of several months to years. Although the Lagrangian calculations show substantial interannual variability of transport pathways into the stratosphere, the results show that the interannual anomalies of [H2O](e) are dominated by anomalies of the zonal mean temperature rather than by transport changes or localized temperature anomalies. This reinforces the paradox of apparently increasing stratospheric water vapor concentrations alongside, if anything, slightly decreasing temperatures at the tropical tropopause. The combination of measurement uncertainties and relatively strong interannual variability with periods of several months to years, on the one hand, limits our ability to detect, attribute, and verify long-term trends and, on the other hand, raises the question as to whether the previously published estimates of long-term trends are too large.