Velocity Extraction of the Jovian Winds (Zonal Flows and Vortices)

There is not a great correlation between the clouds governing a planetary vortex and its actual size and shape. To make detailed comparisons with theory and observations it is necessary to determine the atmospheric velocities of vortices and zonal flows. Velocities in the Jovian atmosphere have traditionally been determined by a manual method:  identify a part of a cloud in one image, find the same part (if you can) in a second image taken at a different time; divide the vector displacement of the cloud part by the time between the images, and define the resulting vector to the velocity of the atmosphere at the mean location of the cloud part.  Not only is this method subject to large errors, but also there is no convenient way to quantify the errors of those velocities. (Nor is there a way to easily quantify the errors in the spatial derivatives of those velocities, which are needed to compute the vorticity, potential vorticity, and horizontal divergence. Small errors in the velocities tend to make very large errors in their spatial derivatives.) In addition, for many Jovian vortices, only a few dozen velocity vectors can be manually extracted from the images. For the Great Red Spot, which is one of the largest and best-studied features of Jupiter, only a few thousand velocity vectors have been extracted manually. It may sound as if that is large number of vectors, but in fact it is small because it makes the average separation between the vectors large, ~600 km. That is too large a spacing between vectors to accurately differentiate them and obtain vorticity fields.  To measure velocities in laboratory flows, automatic methods, such as Particle Image Velocimetry and Correlation Image Velocimetry, are used. These methods rely on finding correlations among 2 or more images of the flow. These methods are more accurate than manual methods, provide self-consistent ways of measuring the errors, and moreover, typically produced millions of velocity vectors from image pairs. Until recently automatic methods could not be used successfully to extract the atmospheric velocities of Jupiter or Saturn because they failed to find correlations between images that were separated in time by more than 50 minutes. With such a small separation in time (and consequently such a small displacement of the clouds), the velocities contained very large errors. In 2009, we developed a new automatic method called Advection Corrected Coherent Image Velocimetry (ACCIV) that finds correlations (and iteratively corrects errors in the correlations) among images separated in time by as much as 10 hours. With  ACCIV, millions of velocity vectors with small errors can be extracted for Jupiter’s zonal flows, jet streams, and vortices. In turn, these velocity fields have allowed us to make detailed comparisons with numerical simulations and theory and have also allowed us to track how these features change in time.

Relevant Research:

Michael H. Wong, Philip S. Marcus, Amy A. Simon, Imke de Pater, Joshua W. Tollefson, Xylar S. Asay-Davis (2021) Evolution of the Horizontal Winds in Jupiter's Great Red Spot From One Jovian Year of HST/WFC3 Maps, Geophysical Research Letters 48(18), p. e2021GL093982, pdf, doi:10.1029/2021GL093982

Lawrence A. Sromovsky, Imke De Pater, Patrick M. Fry, Heidi B. Hammel, Philip S. Marcus (2015) High S/N Keck and Gemini AO imaging of Uranus during 2012–2014: New cloud patterns, increasing activity, and improved wind measurements, Icarus 258(1), p. 192-223, url, doi:10.1016/j.icarus.2015.05.029

Sushil Shetty, Philip S. Marcus (2012) Erratum to " Changes in Jupiter's Great Red Spot (1979-2006) and Oval BA (2000-2006)" [Icarus 210 (2010) 182-201], Icarus 217(1), p. 432, pdf, doi:10.1016/j.icarus.2011.10.017

Xylar S. Asay-Davis, Philip S. Marcus, Michael H. Wong, Imke de Pater (2011) Changes in Jupiter’s zonal velocity between 1979 and 2008, Icarus 211(2), p. 1215-1232, pdf, doi:10.1016/j.icarus.2010.11.018

Sushil Shetty, Philip S. Marcus (2010) Changes in Jupiter’s great red spot (1979–2006) and oval BA (2000–2006), Icarus 210(1), p. 182-201, pdf

Xylar S. Asay-Davis, Philip S. Marcus, Michael H. Wong, Imke de Pater (2009) Jupiter’s shrinking Great Red Spot and steady Oval BA: Velocity measurements with the ‘Advection Corrected Correlation Image Velocimetry’ automated cloud-tracking method, Icarus 203(1), p. 164-188, url, doi:10.1016/j.icarus.2009.05.001

Abstracts

Michael H. Wong, Philip S. Marcus, Amy A. Simon, Imke De Pater (2020) Changes in the Velocity Field of Jupiter's Great Red Spot on Short and Long Timescales, AAS/Division for Planetary Sciences Meeting Abstracts 52, p. 100-101, url

K. M. Sayanagi, J. Mitchell, A. P. Ingersoll, S. P. Ewald, Philip S. Marcus, Imke De Pater, Michael H. Wong, D. S. Choi, M. Sussman, K. Ogohara (2010) A benchmark for cloud tracking wind measurements, AGU Fall Meeting Abstracts 2010, p. P11A--1335

Xylar S. Asay-Davis, Michael H. Wong, Imke de Pater, Philip S. Marcus (2010) Variability of Jupiter's zonal winds on multiple timescales, EGU General Assembly Conference Abstracts, p. 7369, pdf

Xylar S. Asay-Davis, Philip S. Marcus, Michael H. Wong, Imke de Pater (2008) Velocity Fields of Jovian Dynamical Features using the Advection Corrected Correlation Image Velocimetry Method, APS Division of Fluid Dynamics Meeting Abstracts 61, p. AV-002, pdf

Sushil Shetty, Xylar S. Asay-Davis, Philip S. Marcus (2006) Modeling and Data Assimilation of the Velocity of Jupiter's Great Red Spot and Red Oval, APS Division of Fluid Dynamics Meeting Abstracts 59, p. FG-007, pdf

Xylar S. Asay-Davis, Sushil Shetty, Philip S. Marcus (2006) Extraction of Velocity Fields from Telescope Image Pairs of Jupiter's Great Red Spot, New Red Oval, and Zonal Jet Streams, APS Division of Fluid Dynamics Meeting Abstracts 59, p. FG-006, pdf

Xylar S. Asay-Davis, Sushil Shetty, Philip S. Marcus, Imke De Pater, S Lockwood, Michael H. Wong, Christopher Y. Go (2006) Extraction of Velocity Fields from HST Image Pairs of Jupiter's Great Red Spot, New Red Oval, and Zonal Jet Streams, AAS/Division for Planetary Sciences Meeting Abstracts 38, p. 4-11, pdf