Lightning has been detected on Jupiter by all visiting spacecraft through night-side optical imaging and whistler (lightning-generated radio waves) signatures1,2,3,4,5,6. Jovian lightning is thought to be generated in the mixed-phase (liquid–ice) region of convective water clouds through a charge-separation process between condensed liquid water and water-ice particles, similar to that of terrestrial (cloud-to-cloud) lightning7,8,9. Unlike terrestrial lightning, which emits broadly over the radio spectrum up to gigahertz frequencies10,11, lightning on Jupiter has been detected only at kilohertz frequencies, despite a search for signals in the megahertz range12. Strong ionospheric attenuation or a lightning discharge much slower than that on Earth have been suggested as possible explanations for this discrepancy13,14. Here we report observations of Jovian lightning sferics (broadband electromagnetic impulses) at 600 megahertz from the Microwave Radiometer15 onboard the Juno spacecraft. These detections imply that Jovian lightning discharges are not distinct from terrestrial lightning, as previously thought. In the first eight orbits of Juno, we detected 377 lightning sferics from pole to pole. We found lightning to be prevalent in the polar regions, absent near the equator, and most frequent in the northern hemisphere, at latitudes higher than 40 degrees north. Because the distribution of lightning is a proxy for moist convective activity, which is thought to be an important source of outward energy transport from the interior of the planet16,17, increased convection towards the poles could indicate an outward internal heat flux that is preferentially weighted towards the poles9,16,18. The distribution of moist convection is important for understanding the composition, general circulation and energy transport on Jupiter.

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This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The research at the University of Iowa was supported by NASA through contract 699041X with the Southwest Research Institute. The work of I.K. and O.S. was supported by grants MSM100421701 and LTAUSA17070 and by the Praemium Academiae award.

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Nature thanks U. Dyudina and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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  1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    • Shannon Brown
    • , Michael Janssen
    • , Virgil Adumitroaie
    • , Samuel Gulkis
    • , Steven Levin
    • , Sidharth Misra
    •  & Glenn Orton
  2. Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA

    • Sushil Atreya
  3. Southwest Research Institute, San Antonio, TX, USA

    • Scott Bolton
  4. California Institute of Technology, Pasadena, CA, USA

    • Andrew Ingersoll
    • , Cheng Li
    •  & Fachreddin Tabataba-Vakili
  5. Department of Physics, University of Houston, Houston, TX, USA

    • Liming Li
  6. Department of Astronomy, Cornell University, Ithaca, NY, USA

    • Jonathan Lunine
  7. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

    • Paul Steffes
  8. Department of Space Physics, Institute of Atmospheric Physics, The Czech Academy of Sciences, Prague, Czechia

    • Ivana Kolmašová
    •  & Ondřej Santolík
  9. Faculty of Mathematics and Physics, Charles University, Prague, Czechia

    • Ivana Kolmašová
    •  & Ondřej Santolík
  10. Department of Physics and Astronomy, University of Iowa, Iowa City, IA, USA

    • Masafumi Imai
    • , William Kurth
    • , George Hospodarsky
    •  & Donald Gurnett
  11. NASA/Goddard Spaceflight Center, Greenbelt, MD, USA

    • John Connerney


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S. Br. analysed the MWR data to find and extract the lightning observations. M.J. is the co-investigator lead of the MWR. S.A., A.I., C.L., J.L., L.L., G.O., P.S., S. Bo. and F.T.-V. contributed to the interpretation of the data and the implications for atmospheric processes. S.G., S.M. and V.A. contributed to the interpretation of the radiometric source signal. I.K., M.I. and O.S. calculated whistler rates. W.S.K., G.B.H. and D.A.G advised on data analysis. W.S.K. is responsible for the Juno Waves instrument. J.E.P.C. provided the planetary magnetic field measurements. S. Br. wrote the manuscript with input from all authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Shannon Brown.

Extended data figures and tables

  1. Extended Data Fig. 1 Example of lightning detection in the MWR antenna temperature time series.

    a, Antenna temperature measurements obtained during a spin of the spacecraft. The scan from limb to limb of Jupiter is shown at the centre of the image and enlarged in panel b. The single positive outlier is the additive emission from the lightning discharge above the background emission from the atmosphere.

  2. Extended Data Fig. 2 Illustration of the lightning extraction process.

    a, Smoothed background antenna temperature (TA) and the data. b, Difference between the measurements and the smoothed background antenna temperature for perijove 7. c, Differences between the MWR data and the background antenna temperature for all perijoves. The dotted lines in b and c indicate where the detection threshold is set relative to the variance in the data.

  3. Extended Data Fig. 3 Normalized 600-MHz lightning power, expressed as antenna temperature, as a function of latitude.

    a, Power normalized to the perijove distance by the square of the distance. This normalization is used if the observed power from each detection originates from a single source, which is expected for discharge rates less than 300 km−2 yr−1 near the equator and 0.3 km−2 yr−1 at the poles. b, Power normalized by both the distance and the area covered by the antenna pattern, which is used if the observed power originates from several sources and should be scaled per unit area.

  4. Extended Data Fig. 4 Lightning detections per second by the MWR and the Waves instrument as a function of latitude.

    The same MWR distribution as that shown in Fig. 2, but with the red line showing the distribution with an equalized detection threshold as a function of latitude.

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