DOI: 10.5061/dryad.3j9kd51vs
title: Lightning data for Jupiter's stealth superstorms in 2021-2022

description: The Juno spacecraft recorded lightning radio pulses in channel 1 (600 MHz
 or 50 cm) of the Microwave Radiometer (MWR). The data come from four
 orbital passes that encountered meteorologically unique "stealth
 superstorms" in 2021-2022. The data are the foundation for an article
 finding that the power emitted by Jupiter's lightning pulses in these
 storms may be similar to that coming from storms on Earth. This dataset
 consists of binary files containing lightning intensity and geometrical
 data, and Jupyter notebooks used to read the binaries and generate the
 plots in the manuscript.
description: The data were collected by the MWR (Janssen et
 al. 2017) on the Juno spacecraft (Bolton et
 al. 2017). Processing for lightning identification was described
 in Oyafuso
 et al. (2020). Calculation of lightning power under the
 cluster-source assumption is described in the associated manuscript by
 Wong et al. 
description: # Lightning data for Jupiter's stealth superstorms in 2021-2022
 [https://doi.org/10.5061/dryad.3j9kd51vs](https://doi.org/10.5061/dryad.3j9kd51vs) ## Description of the data and file structure ##### HDF5 data files The `clusterstats_PJ*.h5` data files contain the processed Juno lightning data. The `*.ipynb` files are Jupyter Notebooks, which are annotated Python scripts. For preservation and readability, there are also non-executable PDF versions of these notebooks, `*.ipynb.pdf`. These are the elements of the HDF5 files: * `EIRP_boresight` Lightning power (W), dim: {n_samples} * `EIRP_cluster` Lightning power (W), dim: {n_samples} * `NELP_binfloors` Bin floors for NELP statistics * `NELP_boresight` Lightning noise floor (W), dim: {n_samples} * `NELP_cluster` Lightning noise floor (W), dim: {n_samples} * `T_A` Antenna temperature (K), dim: {n_samples} * `alpha_cluster` Attenuation factor, dim: {n_samples} * `area_footprints` Coverage of each footprint, dim: {n_lats, n_nelpbins, n_samples} * `area_surveyed` Cumulative coverage, dim: {n_lats, n_nelpbins} * `cluster_lat` Latitude of the cluster source {SCALAR} * `cluster_lon` Longitude of the cluster source {SCALAR} * `cluster_proximity_tolerance` Parameter {SCALAR} * `clusterproc_codedate` Pipeline version information {SCALAR} * `clusterproc_comment` Pipeline version information {SCALAR} * `clusterproc_version` Pipeline version information {SCALAR} * `dT_A` Anomalous antenna temperature due to lightning (K), dim: {n_samples} * `flag_cluster` Flag: is the cluster in view during this sample? dim: {n_samples} * `flag_clusterzap` Flag: is the cluster in view + lightning detected during this sample? dim: {n_samples} * `flag_lightning` Flag: is lightning detected during this sample? dim: {n_samples} * `latbins` Latitude values for area bins, dim: {n_lats} * `latitude_boresight` Latitude of boresight intersection with Jupiter 1-bar surface, dim: {n_samples} * `latitude_spacecraft` Latitude of sub-spacecraft point, dim: {n_samples} * `latres` Lattude resolution {SCALAR} * `longitude_boresight` Longitude of boresight intersection with Jupiter 1-bar surface, dim: {n_samples} * `longitude_spacecraft` Longitude of sub-spacecraft point, dim: {n_samples} * `n_NELPbins` Number of NELP bins {SCALAR} * `n_latbins` Number of latitude bins {SCALAR} * `perijove` Juno perijove number {SCALAR} * `range_boresight` Range from spacecraft to boresight intersection with Jupiter 1-bar surface, dim: {n_samples} * `range_cluster` Range from spacecraft to cluster location, dim: {n_samples} * `range_spacecraft` Range from spacecraft to subspacecraft point on Jupiter 1-bar surface, dim: {n_samples} * `sig_K` Value of 1-sigma noise level, dim: {n_samples} * `resid` Intensity of lightning in units of `sig_K`, dim: {n_samples} * `theta_cluster` Angular offset from boresight to cluster, dim: {n_samples} ## Code/software Jupyter Notebook is needed, along with Python 3 and the packages listed at the top of each notebook. If this is the future and Python 3 is no longer available, the PDF versions of the notebooks enable the operation of the code to be followed. ## Access information Data was derived from the following sources: * [PDS Atmospheres](https://pds-atmospheres.nmsu.edu/data_and_services/atmospheres_data/JUNO/microwave.html) * [Hubble Space Telescope](https://mast.stsci.edu/search/ui/#/hst)