144 Variability and Long-Term Changes in Upper Tropospheric Jets from Reanalyses: Seasonal and Regional Patterns and Relationships to ENSO

Thursday, 29 June 2017
Salon A-E (Marriott Portland Downtown Waterfront)
Gloria L. Manney, NorthWest Research Associates & New Mexico Tech, Socorro, NM; and M. I. Hegglin and Z. D. Lawrence

The JETPAC (JEt and Tropopause Products for Analysis and Characterization) products derived from reanalysis datasets are used to assess interannual variability and long-term changes in upper tropospheric jet latitude, altitude, and strength. These variations are evaluated separately for the subtropical and polar (eddy-driven) jets, and regional and seasonal patterns assessed. The evaluations are done for five modern reanalyses, MERRA and MERRA-2, ERA-Interim, JRA-55, and NCEP-CFSR; the level of agreement among reanalyses provides guidance on the regions and seasons with robust changes. Shifts in the subtropical jets, related to changes in the width of the tropics, show strong regional and seasonal variations; robust indications of tropical widening are seen in global averages only in JJA and SON; narrowing of the tropics is seen in April, May, November, and December. In regions / seasons where there is a robust change in jet altitude, that change is generally an increase. Interannual variability in the subtropical jets is strongly correlated with El Nino/Southern Oscillation (ENSO), and many, but not all, of the long term changes in jet locations are consistent with the predominant phase of ENSO in the earlier versus later years of the record, especially in NH winter. Changes in the polar jets, related to storm track variations, also vary substantially by region and season; while the most common and robust changes in the SH polar jet indicate a poleward shift, regions and seasons with robust changes in the NH polar jet typically show an equatorward shift. Our results highlight the importance of taking regional and seasonal variations into account when quantifying long term changes in jet locations, and demonstrate the value of comparing multiple reanalyses in assessing the robustness of those changes.
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