Jupiter Great Red Spot Velocity Fields from HST/WFC3 (GRS-WFC3)
Primary Investigator: Michael H. Wong
Contributing Program PIs: Amy A. Simon, Imke de Pater, Glenn Schneider
HLSP Authors: Michael H. Wong
Released: 15 April 2021
Updated: 14 July 2021
Primary Reference(s): Wong et al. 2021
Citations: See ADS Statistics
High precision velocity fields of Jupiter's Great Red Spot (GRS) have been created by correlating sequences of WFC3/UVIS images spanning typical sequence durations of 10 hours. The analysis, results, and high-level science products are described in a paper by Wong et al. (2021), entitled "Evolution of the Horizontal Winds in Jupiter's Great Red Spot from One Jovian Year of HST/WFC3 Maps." Velocities were measured using the Advection Corrected Correlation Image Velocimetry (ACCIV) software, which was described in Asay-Davis et al. (2009) and is available at GitHub.
Three products are provided for each velocity field in the form of .tar.gz files. Each tar file contains groups of additional data files, as
described in the Supporting Information of Wong et al. (2021). The tar file naming convention is as follows:
- <timestamp> = The fractional year, example, "2019.48".
- <dataset> = The label of the dataset, example, "grs19opal-d12". Consult the Supplemental Information PDF file available from the primary reference (Wong et al. (2021)) for additional information. The general format is "grs" for Great Red Spot, a two-digit year corresponding to the midpoint time of observation, and an additional designation. "opal" means the observations were taken as part of the OPAL program. "pj" refers to the Juno perijove number. "d12" and "d21" relate to the relative timing of the data used to construct the velocity fiels.
- <filter> = The name of the HST filter used, example, "f631n".
- <bundle> = The type of data files in this bundle, one of "inputs", "output-analysis", or "output-data".
Data file types:
These collections of text and HDF5-format binary data are required as input to the ACCIV velocity retrieval code. ACCIV uses an iterative approach, and parameter files included in this bundle describe all parameter values needed to control the successive iterations of the retrieval. Binary grid files are included to specify the geometry of the data, and the cylindrically-projected HST data, after application of limb darkening corrections, are included as numbered frames. A full description of the parameters and the format of the HDF5 input data can be found at the ACCIV GitHub repository.
There is only one set of input HDF5 binary files for each epoch, although every candidate velocity field at that epoch has its own separate input text files. It is recommended to download all the _inputs.tar.gz files for the desired epoch; only one of these will include the binary input files.
These bundles contain human-readable plots and maps (in PDF format), along with text files containing some tabular data used to generate the plots plus other quantities measured from the velocity fields.
These bundles contain two binary files in HDF5 format. These data files describe the velocity field retrieved by the ACCIV process. These are the files most likely to be directly useful for further analysis. The ACCIV GitHub repository and primary reference (Asay-Davis et al. 2009) should be consulted to understand how these data fiiles are derived.
Briefly, the included data files are:
outScatteredVelocity.h5 - Individual velocity vectors are given, prior to gridding.
|Fractional Year||Dataset Label||High Level Science Products|
|2009-09-22 16:37||2009.72||grs09||input | output-data | output-analysis|
|2012-09-20 15:42||2012.72||grs12||input | output-data | output-analysis|
|2015-01-19 13:53||2015.05||grs15p4||input | output-data | output-analysis|
|2015-01-19 13:53||2015.05||grs15p5||input | output-data | output-analysis|
|2016-02-09 16:03||2016.11||grs16opal-d12||input | output-data | output-analysis|
|2016-02-09 16:03||2016.11||grs16opal-d21||input | output-data | output-analysis|
|2016-12-11 19:42||2016.94||grs16pj03||input | output-data | output-analysis|
|2017-02-01 22:50||2017.09||grs17pj04-d12||input | output-data | output-analysis|
|2017-02-01 22:50||2017.09||grs17pj04-d21||input | output-data | output-analysis|
|2017-02-01 22:50||2017.09||grs17pj04-long||input | output-data | output-analysis|
|2017-04-03 08:08||2017.25||grs17opal-long||input | output-data | output-analysis|
|2018-04-17 07:49||2018.29||grs18opal-d12||input | output-data | output-analysis|
|2018-04-17 07:49||2018.29||grs18opal-d21||input | output-data | output-analysis|
|2019-04-09 18:44||2019.27||grs19pj19||input | output-data | output-analysis|
|2019-06-26 12:46||2019.48||grs19opal-d12||input | output-data | output-analysis|
|2019-06-26 12:46||2019.48||grs19opal-d23||input | output-data | output-analysis|
|2020-09-20 08:15||2020.72||grs20||input | output-data | output-analysis|