Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

Santos, Sean Patrick; Caldwell, Peter; Bretherton, Christopher S.

doi:10.1029/2020ms002359

Cited by 7 publications

(2 citation statements)

References 35 publications

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“…(2021) and Santos et al. (2021) found large changes in cloud properties when a variety of timesteps were changed in the E3SM Atmospheric Model, including the physics timestep itself and the sub‐cycling of various moist processes within the physics package. Even in superparameterized (Yu & Pritchard, 2015) and convective‐permitting (Barrett et al., 2019) simulations, timestep sensitivity has been noted in the simulation of clouds and precipitation.…”

Section: Introductionmentioning

confidence: 99%

“…Herrington and Reed (2018) argued that long physics timesteps in idealized simulations exacerbated time truncation errors and resulted in a decoupling of analytic relationships between grid spacing and resolved vertical motions. Both Wan et al (2021) and Santos et al (2021) found large changes in cloud properties when a variety of timesteps were changed in the E3SM Atmospheric Model, including the physics timestep itself and the sub-cycling of various moist processes within the physics package. Even in superparameterized (Yu & Pritchard, 2015) and convective-permitting (Barrett et al, 2019) simulations, timestep sensitivity has been noted in the simulation of clouds and precipitation.…”

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Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM

Zarzycki

2022

J Adv Model Earth Syst

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With general circulation models (GCMs) being increasingly used to explore extreme events over short temporal and small spatial scales, understanding how design choices in model configuration impact simulation results is critical. This research shows that the number of spontaneously generated tropical cyclones (TCs) in a version of the Community Atmosphere Model can be controlled by changing the coupling frequency between the dynamical core and physical parameterizations. More frequent coupling (i.e., shorter physics timesteps), even in the presence of an otherwise identical model, leads to large increases in TC activity. It is suggested that this arises due to competition within moist physics subroutines. Simulations with reduced physics timesteps preferentially eliminate instantaneous atmospheric instability via grid‐scale motions, even while producing mean climates similar to those with longer timesteps. These small‐scale variability increases lead to more tropical “seeds,” which are converted to full‐fledged TCs. This behavior is confirmed through a set of sensitivity experiments and highlights the caution needed in studying and generalizing phenomena that depend on both resolved and sub‐grid scales in GCMs and the need for targeting physics‐dynamics coupling as a model improvement strategy.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM

Zarzycki

2022

J Adv Model Earth Syst

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The Impact of Model Horizontal Resolution on Simulating Regional Climate Over East Asia Using Variable‐Resolution CESM2

Wang,

Liu,

Lin

et al. 2024

JGR Atmospheres

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In this study, a variable‐resolution version of the Community Earth System Model (VR‐CESM) with mesh refinement (∼0.125°) over East Asia is used to simulate the regional climate in this region. For the evaluation of model performance and sensitivity to model resolution, the simulated near‐surface temperature and precipitation are compared with observations and simulation results from a globally quasi‐uniform (∼1°) CESM (UN‐CESM). Results show that VR‐CESM better simulates the spatial patterns and seasonal variations of mean temperature and precipitation than UN‐CESM over China. For extreme events, VR‐CESM improves the simulation of the occurrence frequency of wintertime daily minimum temperature and heavy precipitation. In regions with complex terrains, VR‐CESM better resolves the topographic forcing and captures the observed fine‐scale spatial patterns of temperature and precipitation, although precipitation is still overestimated. For East Asian summer monsoon precipitation, both UN‐CESM and VR‐CESM tend to overestimate (underestimate) the precipitation over northern (southern) China, which is associated with too strong meridional water vapor transport in the models and biases in the large‐scale circulation in the middle and upper troposphere. Different from previous studies with different physics parameterizations and refined domains, as the model resolution increases, simulated monsoon precipitation evolution is not obviously improved, and convective precipitation intensity decreases over eastern China. Despite this, our results indicate that VR‐CESM simulates regional climate, topographical forcing, and large‐scale circulations over East Asia reasonably well, and thus it can be applied for the future climate projection in the region.

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How Stable Are Students’ Entrepreneurial Intentions in the COVID-19 Pandemic Context?

et al. 2022

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The purposed longitudinal study analyzes the evolution of students’ Entrepreneurial Intentions (EI) and its antecedents over the COVID-19 pandemic period and explores the inter-individual differences and the intra-individual changes. Our main contribution consists of proposing two-panel estimations techniques: first, a Latent Change Score model (LCS) approach to analyze the stability of our constructs, and second, a Generalized Least Squares (GLS) Random-Effect estimation of a complex network of relationships that we have identified within the Theory of Planned Behavior (TPB) framework. Our empirical results show that students’ EI enrolled in an entrepreneurship education (EE) program increased during the COVID-19 pandemic. Individuals with initial higher scores for EI have changed less than those with lower initial scores, and a gender difference exists in the initial level of EI and its antecedents. Our results also document the moderation effects of entrepreneurial self-efficacy and the importance of inspiration and resources in building students’ EI and provide valuable policy recommendations for universities regarding the design of EE programs to contribute to the economic recovery in the post-pandemic era

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Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

Cited by 7 publications

References 35 publications

Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM

Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM

The Impact of Model Horizontal Resolution on Simulating Regional Climate Over East Asia Using Variable‐Resolution CESM2

How Stable Are Students’ Entrepreneurial Intentions in the COVID-19 Pandemic Context?

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