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Abstract Precipitation amount (A), frequency (F), intensity (I), and duration (D) are important properties of precipitation, but their estimates are sensitive to data resolution. This study investigates this resolution dependence, and the influences of different model physics, by analyzing simulations by the Community Atmospheric Model (CAM) version 4 (CAM4) and version 5 (CAM5) with varying grid sizes from ~0.25 to 2.0°. Results show that both CAM4 and CAM5 greatly overestimate F and D but underestimate I at all resolutions, despite realistic A. These biases partly result from too much parameterized (convective) precipitation with high F and D but low I. Different cloud microphysics schemes contribute to the precipitation differences between CAM4 and CAM5. The A, F, I, and D of convective and nonconvective precipitation react differently to grid‐size decreases, leading to the large decreases in F and D but increases in the I for total precipitation as model resolution increases. This resolution dependence results from the increased probability of precipitation over a larger area (area aggregation effect, which is smaller than in observations) and the varying performance of model physics under changing resolution (model adjustment effect), which roughly enhances the aggregation‐induced dependence. Finer grid sizes not only increase resolved precipitation, which has higher intensity and thus improves overall precipitation intensity in CAM, but also reduce the area aggregation effect. Thus, the long‐standingdrizzlingproblem in climate models may be mitigated by increasing model resolution and modifying model physics to suppress parameterized convective precipitation and enhance resolved nonconvective precipitation.
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The Convective‐To‐Total Precipitation Ratio and the “Drizzling” Bias in Climate Models
Abstract Overestimation of precipitation frequency and duration while underestimating intensity, that is, the “drizzling” bias, has been a long‐standing problem of global climate models. Here we explore this issue from the perspective of precipitation partitioning. We found that most models in the Climate Model Intercomparison Project Phase 5 (CMIP5) have high convective‐to‐total precipitation (PC/PR) ratios in low latitudes. Convective precipitation has higher frequency and longer duration but lower intensity than non‐convective precipitation in many models. As a result, the high PC/PR ratio contributes to the “drizzling” bias over low latitudes. The PC/PR ratio and associated “drizzling” bias increase as model resolution coarsens from 0.5° to 2.0°, but the resolution's effect weakens as the grid spacing increases from 2.0° to 3.0°. Some of the CMIP6 models show reduced “drizzling” bias associated with decreased PC/PR ratio. Thus, more reasonable precipitation partitioning, along with finer model resolution should alleviate the “drizzling” bias within current climate models.
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- PAR ID:
- 10448322
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 126
- Issue:
- 16
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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