Preprints
https://doi.org/10.5194/hess-2020-652
https://doi.org/10.5194/hess-2020-652

  23 Feb 2021

23 Feb 2021

Review status: this preprint is currently under review for the journal HESS.

Evaluation of Asian summer precipitation in different configurations of a high-resolution GCM at a range of decision-relevant spatial scales

Mark R. Muetzelfeldt1, Reinhard Schiemann1, Andrew G. Turner1, Nicholas P. Klingaman1, Pier Luigi Vidale1, and Malcolm J. Roberts2 Mark R. Muetzelfeldt et al.
  • 1National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK
  • 2Met Office Hadley Centre, Exeter, UK

Abstract. High-resolution general circulation models (GCMs) can provide new insights into the simulated distribution of global precipitation. We evaluate how summer precipitation is represented over Asia in global simulations with a grid length of 14 km. Three simulations were performed: one with a convection parametrization, one with convection represented explicitly by the model's dynamics, and a hybrid simulation with only shallow and mid-level convection parametrized. We evaluate the mean simulated precipitation and the diurnal cycle of the amount, frequency and intensity of the precipitation against satellite observations of precipitation from the Climate Prediction Center morphing method (CMORPH). We also compare the high-resolution simulations with coarser simulations that use parametrized convection.

The simulated and observed precipitation is averaged over spatial scales defined by the hydrological catchment basins; these provide a natural spatial scale for performing decision-relevant analysis that is tied to the underlying regional physical geography. By selecting basins of different sizes, we evaluate the simulations as a function of the spatial scale. A new BAsin-Scale Model Assessment ToolkIt (BASMATI) is described, which facilitates this analysis.

We find that there are strong wet biases (locally up to 72 mm day−1 at small spatial scales) in the mean precipitation over mountainous regions such as the Himalayas. The explicit convection simulation worsens existing wet and dry biases compared to the parametrized convection simulation. When the analysis is performed at different basin scales, the precipitation bias decreases as the spatial scales increase for all simulations; the lowest-resolution simulation has the smallest root mean squared error compared to CMORPH.

In the simulations, a positive mean precipitation bias over China is primarily found to be due to too frequent precipitation for the parametrized convection simulation, and too intense precipitation for the explicit convection simulation. The simulated diurnal cycle of precipitation is strongly affected by the representation of convection: parametrized convection produces a peak in precipitation too close to midday over land, whereas explicit convection produces a peak that is closer to the late afternoon peak seen in observations. At increasing spatial scale, the representation of the diurnal cycle in the explicit and hybrid convection simulations improves when compared to CMORPH; this is not true for any of the parametrized simulations.

Some of the strengths and weaknesses of simulated precipitation in a high-resolution GCM are found: the diurnal cycle is improved at all spatial scales with convection parametrization disabled; the interaction of the flow with orography exacerbates existing biases for mean precipitation in the high-resolution simulations; and parametrized simulations produce similar diurnal cycles regardless of their resolution. The need for tuning the high-resolution simulations is made clear. Our approach for evaluating simulated precipitation across a range of scales is widely applicable to other GCMs.

Mark R. Muetzelfeldt et al.

Status: open (extended)

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  • RC1: 'Comment on hess-2020-652', Anonymous Referee #1, 09 Apr 2021 reply

Mark R. Muetzelfeldt et al.

Mark R. Muetzelfeldt et al.

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Short summary
Simulating East-Asian Summer Monsoon (EASM) rainfall poses many challenges because of its multi-scale nature. We evaluate 3 setups of a 14-km global climate model against observations to see if they improve simulated rainfall. We do this over catchment basins of different sizes to estimate how model performance depends on spatial scale. Using explicit convection improves rainfall diurnal cycle, yet more model tuning is needed to improve mean and intensity biases in simulated summer rainfall.