Advanced cloud products from NASA’s PACE mission

Abstract

The sensitivities of cloud properties to changes in the climate and to anthropogenic aerosol emissions are crucial for understanding Earth’s climate but remain highly uncertain. Global cloud observations from satellites are needed to advance our knowledge on processes related to the formation and evolution of clouds and precipitation. While long term satellite data records of cloud microphysical properties exist, largely obtained by multi-spectral imagers, they are known to be substantially biased or failing in particular situations, such as in regions of broken and/or mixed-phase clouds. The cloud products provided by NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, which was launched on 8 February 2024, have several advantages over past missions. PACE caries the Ocean Color Instrument (OCI), which is a multi-spectral imager, the Hyper-angular Rainbow Polarimeter (HARP-2) and the Spectropolarimeter for Planetary Exploration (SPEXone). Advanced, pixel-level cloud microphysical products are produced from the polarimeters, including cloud top phase and full droplet size distributions, while collocated retrievals are provided by OCI using more traditional methods. Instrument-synergy products include liquid water path and droplet number concentrations. We present first global advanced cloud products from PACE. We present validation using airborne campaigns that indicates that the polarimetry products are much less affected by the presence of broken and mixed-phase clouds than OCI observations, consistent with previous studies using simulations and observations. These observations provide new insights on the microphysical properties of global clouds, including their drop size distribution width and bi-modality which may be linked to precipitation formation. Furthermore, we show that the polarimeter retrievals along with OCI’s unique combination of three commonly-used shortwave infrared wavelength bands allows to assess some of the biases in traditional bi-spectral retrievals in unprecedented detail and on a global scale. We show that the biases in bi-spectral results depend on cloud structure and on the wavelength used for the droplet size retrievals. The PACE data provides crucial information to reduce biases in traditional bi-spectral cloud retrievals by essentially all multi-spectral imagers in the program of record that result from, e.g., sub-pixel cloudiness, mixed-phase cases and 3D radiative transfer effects. We make recommendations on how biases in bi-spectral results may be mitigated.

Authors 11

1. Bastiaan van Diedenhoven corresponding Aachen SRON Netherlands Institute for Space Research Earth Science Division

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Netherlands Institute for Space Research, Earth Science Division, Leiden, Netherlands (b.van.diedenhoven@sron.nl)

2. Chamara Rajapakshe

   Goddard Space Flight Center

   Affiliation as printed

   NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

3. Andrzej P. Wasilewski

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, NY 10025, USA

4. A. M. Sayer corresponding

   Goddard Space Flight Center

   Affiliation as printed

   NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

5. Brian Cairns

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, NY 10025, USA

6. Otto Hasekamp corresponding Aachen SRON Netherlands Institute for Space Research Earth Science Division

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Netherlands Institute for Space Research, Earth Science Division, Leiden, Netherlands (b.van.diedenhoven@sron.nl)

7. Kirk David Knobelspiesse corresponding

   Goddard Space Flight Center

   Affiliation as printed

   NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

8. Mikhail D. Alexandrov

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, NY 10025, USA

9. Kenneth Sinclair corresponding

   Goddard Institute for Space Studies

   Affiliation as printed

   NASA Goddard Institute for Space Studies, New York, NY 10025, USA

10. Brent McBride corresponding

    University of Maryland, Baltimore County

    Affiliation as printed

    University of Maryland Baltimore County, Baltimore, MD 21250, United States

11. Vanderlei J. Martins

    University of Maryland, Baltimore County

    Affiliation as printed

    University of Maryland Baltimore County, Baltimore, MD 21250, United States