Articles | Volume 17, issue 14
Research article
26 Jul 2017
Research article |  | 26 Jul 2017

Intraseasonal to interannual variability of Kelvin wave momentum fluxes as derived from high-resolution radiosonde data

Jeremiah P. Sjoberg, Thomas Birner, and Richard H. Johnson

Abstract. Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remain challenging. Here we extend a method based on linear wave theory to estimate daily time series of these momentum fluxes from high-resolution radiosonde data. Daily time series are produced for sounding sites operated by the US Department of Energy (DOE) and from the recent Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing and in quantitative agreement with estimates from prior studies. Testing the sensitivity to vertical resolution, our estimated momentum fluxes are found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Climatological analysis is performed over a selected 11-year span of data from DOE Atmospheric Radiation Measurement (ARM) radiosonde sites. Analyses of this 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer, and variability associated with the quasi-biennial oscillation of maxima during easterly phase and minima during westerly phase. Comparison between periods with active convection that is either strongly or weakly associated with the Madden–Julian Oscillation (MJO) suggests that the MJO provides a nontrivial increase in the lowermost stratospheric momentum fluxes.

Short summary
Observational estimates of tropical, large-scale fluxes of zonal momentum from troposphere to stratosphere remain challenging. We present an extended technique for estimating the daily amplitudes of these fluxes using data captured from balloon-borne radiosondes. Climatological analysis of our time series matches expectations of annual and interannual variability, indicating reliability in our estimates. Vertical resolution less than 1 km is found to be important for precise estimation.
Final-revised paper