EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Juno MWR Revealed Points-of-interest from Error Analysis

Zhimeng Zhang1, Virgil Adumitroaie3, Michael Allison8, John Arballo3, Sushil Atreya4, Gordon Bjoraker8, Scott Bolton2, Shannon Brown3, Leigh Fletcher9, Tristan Guillot7, Samuel Gulkis3, Andrew Ingersoll1, Michael Janssen3, Steven Levin3, Cheng Li4, Jonathan Lunine5, Glenn Orton3, Fabiano Oyafuso3, Paul Steffes6, and Michael Wong10
Zhimeng Zhang et al.
  • 1California Institute of Technology, Geological & Planetary Sciences, United States of America (
  • 2Southwest Research Institute, San Antonio TX, 78228, United States of America
  • 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA, 91109, United States of America
  • 4University of Michigan, Ann Arbor MI, 48109, United States of America
  • 5Cornell University, Ithaca NY, 14850, United States of America
  • 6Georgia Institute of Technology, Atlanta GA, 30332, United States of America
  • 7Universite Cote d’Azur, COA, Lagrange CNRS, 06304 Nice, France
  • 8Goddard Institute for Space Studies, New York NY, 10025, United States of America
  • 9School of Physics and Astronomy, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.
  • 10SETI Institute, Mountain View CA 94043, United States of America

Jupiter has ubiquitous clouds and enormous surface structures shrouding the planet. Juno MWR provides the unprecedented chance to answer remaining major questions about the composition and dynamical properties of the great bulk of the atmosphere that lies beneath. Since the launch of Juno, there has been a large effort to collect complementary ground- and space-based observations to help interpret the MWR data. The Jovian Infrared Auroral Mapper (JIRAM) onboard Juno complements the observations of MWR, by giving alternative and reference tropospheric measurements that provides the boundary condition for the interpretation of the MWR data [Adriani et al 2014]. Similarly, HST has a 6-month overlap with 13 Juno orbits and color images were constructed from images of Jupiter in red, green, and blue filters by JunoCam [Hansen et al., 2014]. We study the dynamics within the atmosphere by relating the exterior information provided by these surface maps to the deep interior detected by MWR.

During Aug 27, 2016 to October 24, 2017, MWR obtained 8 perijoves (PJ1, 3, 4, 5, 6, 7, 8, 9), all scanning Jupiter’s atmosphere from North to South, covering various longitudes. By combing observations from these perijoves, we are able to study the global-averaged atmosphere and the anomalies to be compared with top atmosphere maps. The success of such a study depends on the stability of calibration between different perijoves. In order to combine those data, we investigate and remove the calibration drift with respect to time using our error analysis process. We report two outcomes from the error analysis: 1) The atmosphere stability with respect to longitude and time, as compared to the latitudinal belt and zone structures. 2) The spotted points-of-interest which lie 2 standard deviations away from the global-averaged atmosphere. We compare them with Jupiter’s surface atmosphere images taken by JunoCam, HST and JIRAM, and retrieve the corresponding NH3 volume mixing ratio from surface to over 100 bars.

How to cite: Zhang, Z., Adumitroaie, V., Allison, M., Arballo, J., Atreya, S., Bjoraker, G., Bolton, S., Brown, S., Fletcher, L., Guillot, T., Gulkis, S., Ingersoll, A., Janssen, M., Levin, S., Li, C., Lunine, J., Orton, G., Oyafuso, F., Steffes, P., and Wong, M.: Juno MWR Revealed Points-of-interest from Error Analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1389,, 2022.