The radiative impact of high stratospheric water vapor levels: implications for remote sensing data and in situ data interpretation

Abstract:

The origin of observed high water vapor levels (exceeding 8 ppmv) over North America during summe in the observational record of the MLS satellite is in dispute. One hypothesis, based on an analysis of a Lagrangian chemical transport model validated with MLS data, is that the water vapor is the result of isentropic transport from lower latitudes that is associated with the Asian monsoon. Under this hypothesis, the observations are well-explained exclusive of any significant contribution from local mid-latitude deep convection. Conversely, measurements of isotopic analogs (isotopologues) of water vapor suggest different hypotheses about cross-tropopause water vapor transport that do not find the Asian monsoon as the dominant source for high LS water vapor over North America. Satellite measurements from the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (FTS) sensor show elevated levels in the LS of the water vapor isotopologue HDO in the region of the North American monsoon relative to the region of the Asian monsoon, a finding in conflict with an Asian monsoonal source for the North American measurements. It has been argued that HDO is a very effective tracer for deep convection. Analysis of aircraft measurements of HDO had led to a competing hypothesis, that local mid-latitude deep convection is a significant source of elevated LS water vapor observed over North America.

This paper will examine the potential for using a case study approach within a trajectory modeling framework to clarify potential mechanistic and physical explanations for the disagreements in identification of the source of the observed high water vapor values. The potential contribution of diabatic heating at small scale to relevant trajectories will receive particular attention. Quantitative interpretation of the modeled test cases will be undertaken, based on a comparison of the final trajectory positions with the expected errors due to known limitations in trajectory models.