Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165
Climate Statistics in Global Simulations of the Atmosphere, from 80 to 2.5 km Grid Spacing
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JOURNALS FREE ACCESS Advance online publication

Article ID: 2020-005


 Basic climate statistics, such as water and energy budgets, location and width of the InterTropical Convergence Zone (ITCZ), trimodal tropical cloud distribution, position of the polar jet and land-sea contrast remain either biased in coarse-resolution General Circulation Models or are tuned. Here we examine the horizontal resolution dependency of such statistics in a set of global convection-permitting simulations integrated with the ICOsahedral Non-hydrostatic (ICON) model, explicit convection and grid spacings ranging from 80 km down to 2.5 km. The impact of resolution is quantified by comparing the resolution-induced differences to the spread obtained in an ensemble of eight distinct global storm-resolving models.

 Using this metric, we find that, at least by 5 km, the resolution-induced differences become smaller than the spread in 26 out of the 27 investigated statistics. Even for 9 (18) of these statistics, a grid spacing of 80 (10) km does not lead to significant differences. Resolution down to 5 km matters especially for net shortwave radiation, which systematically increases with resolution due to reductions in low cloud amount over the subtropical oceans. Further resolution dependencies can be found in the land-to-ocean precipitation ratio, in the latitudinal position and width of the Pacific ITCZ and in the longitudinal position of the Atlantic ITCZ. Also in the tropics, the deep convective cloud population systematically increases at the expense of the shallow one, whereas the partition of congestus clouds remains fairly constant. Finally, refining the grid spacing systematically moves the simulations closer to observations, but climate statistics exhibiting weaker resolution dependencies are not necessarily associated with smaller biases.

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© The Author(s) 2020. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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