EGU2020-11878
https://doi.org/10.5194/egusphere-egu2020-11878
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Diurnal Self-Aggregation

Jan O. Haerter, Bettina Meyer, and Silas Boye Nissen
Jan O. Haerter et al.
  • Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

Convective self-aggregation is a modelling paradigm for thunderstorm organisation over a constant-temperature tropical sea surface. This setup can give rise to cloud clusters over timescales of weeks. In reality, sea surface temperatures do oscillate diurnally, affecting the atmospheric state. Over land, surface temperatures vary more strongly, and rain rate is significantly influenced. Here, we carry out a substantial suite of cloud-resolving numerical experiments, and find that even weak surface temperature oscillations enable qualitatively different dynamics to emerge: the spatial distribution of rainfall is only homogeneous during the first day. Already on the second day, the rain field is firmly structured. In later days, the clustering becomes stronger and alternates from day to day. We show that these features are robust to changes in resolution, domain size, and surface temperature, but can be removed by a reduction of the amplitude of oscillation, suggesting a transition to a clustered state. Maximal clustering occurs at a scale of lmax≈180 km, a scale we relate to the emergence of mesoscale convective systems. At lmax rainfall is strongly enhanced and far exceeds the rainfall expected at random. We explain the transition to clustering using simple conceptual modelling. Our results may help clarify how continental extremes build up and how cloud clustering over the tropical ocean could emerge much faster than through conventional self-aggregation alone.

How to cite: Haerter, J. O., Meyer, B., and Nissen, S. B.: Diurnal Self-Aggregation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11878, https://doi.org/10.5194/egusphere-egu2020-11878, 2020

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