The convective-to-total precipitation ratio and the "drizzling" bias in climate models

Chen, Di; Dai, Aiguo; Hall, Alex

doi:10.1002/essoar.10504728.1

Cited by 2 publications

(2 citation statements)

References 34 publications

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“…The simulated differences in regional precipitation reflect the combined effects of higher spatial resolution and physics retuning in AM4VR, modulating the partitioning of total precipitation between parameterized deep convective precipitation and resolved large‐scale precipitation, along with associated changes in atmospheric circulation (Figures 5g and 5h). The zonal mean ratio of parameterized convective to total precipitation in the tropics (20°S–20°N) decreases from 0.66 in C96 to 0.61 in AM4VR with ε 1 = 0.5 km −1 and to 0.57 with ε 1 = 0.6 km −1 (Figure S10 in Supporting Information ), bringing it closer to ∼0.45 from satellite estimates (Chen et al., 2021).…”

Section: Results: Physical Climate Simulationmentioning

confidence: 68%

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

Lin,

Horowitz,

Zhao

et al. 2024

J Adv Model Earth Syst

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We present a variable‐resolution global chemistry‐climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban‐to‐rural chemical regimes, mesoscale convective systems, and land‐surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi‐decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25‐km uniform‐resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal‐to‐diurnal cycles and extremes, notably reducing the central US dry‐and‐warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process‐level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land‐biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

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Section: Results: Physical Climate Simulationmentioning

confidence: 68%

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

Lin,

Horowitz,

Zhao

et al. 2024

J Adv Model Earth Syst

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“…Different deep convection schemes have different light‐rain generation efficiencies but CMIP5&6 GCMs equipped with them all have the same issue of “too much light rain and too little heavy rain” resulting from too frequent convection (Chen et al., 2021; Na et al., 2020). This implies that all the convective schemes thought with different formulations share similar generation rates of light rain.…”

Section: Discussionmentioning

confidence: 99%

Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale‐Aware Convection Schemes

Xia

Wang

Zhang

et al. 2022

Geophysical Research Letters

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Atmospheric aerosols in global climate models (GCMs) can be removed by both large‐scale and convective precipitation. As the horizontal resolution of GCMs increases, it is expected that large‐scale precipitation increases and convective precipitation decreases if scale‐aware convection schemes are well developed. To explore its impact on aerosol burdens, this study develops a novel method and applies it to the National Center for Atmospheric Research Community Atmosphere Model version 5.3 to mimic the behavior of scale‐aware convective schemes. Surprisingly, it is found that aerosol burden increases globally as convective precipitation decreases and large‐scale precipitation increases, which can be attributed to the reduced light rain. In the light‐rain intensity category, the decreased frequency of convective precipitation is not offset by the increased frequency of large‐scale precipitation. Therefore, for aerosol simulations in high‐resolution GCMs using scale‐aware convection schemes, subgrid convection and large‐scale condensation should be coordinated to assure light rain stays the same.

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The convective-to-total precipitation ratio and the "drizzling" bias in climate models

Abstract: Global climate models (GCMs) are known to have a "drizzling" bias that is, characterized by unrealistically high precipitation frequency (F) and duration (D) but low intensity (I), even though precipitation amount (A) is realistic (

Cited by 2 publications

References 34 publications

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale‐Aware Convection Schemes

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