2015/2016 Arctic MERRA2 Potential Vorticity
The daily progression through the 2015/2016 season of the various potential vorticity statistics, comparing 2015/2016 to the climatology of all other years. Clicking a link will bring up, in a new window, a PDF vector plot or a plain-text ASCII data file that is suitable for input into any program.
The area of the vortex. (Plot is shown for 1 November–31 December on the 460-K isentropic surface.)
vortex edge potential vorticity
The potential vorticity at the polar vortex edge. (Plot is shown for 1 November–30 April on the 460-K surface.)
maximum potential vorticity
The maximum potential vorticity inside the polar vortex. (Plot is shown for 1 November–30 April on the 460-K surface.)
The Arctic polar vortex acts as a barrier to the exchange of polar and midlatitude air. The potential vorticity (PV) is a conserved quantity that acts as a tracer for motion on an isentropic surface. Plotting contours of PV on an isentropic surface readily shows the extent of the polar vortex. In the Arctic winter, the PV is more positive going from midlatitudes to the pole. The spacing of PV contours is very wide in the midlatitudes, very tight at the polar vortex edge, and then widens again inside of the vortex. The edge of the vortex is defined to be where the contours of PV are closest together. The area inside of this edge can be determined as the area of the polar vortex.
The data are from the Modern-Era Retrospective analysis for Research and Applications, Version 2 ( MERRA-2) assimilation, produced by the Goddard Earth Observing System Data Assimilation System (GEOS DAS). MERRA-2 uses a version of the GEOS model with the Gridpoint Statistical Interpolation (GSI) atmospheric analysis developed jointly with NOAA/NCEP/EMC. Since it takes about two months to incorporate these data into the statistics, we supplement the MERRA-2 assimilation with the GEOS FP assimilation system that provides analyses and forecasts. This assimilation system is also produced by the GEOS DAS. and integrates forefront versions of the GEOS atmospheric general circulation model with advanced data assimilation techniques, using a broad range of satellite observations.