Simulating North American mesoscale convective systems with a convection-permitting climate model
By Andreas F. Prein, Changhai Liu, Kyoko Ikeda, R. Bullock, R. Rasmussen, G. Holland, M. Clark. Climate Dynamics, 2017
206 citations recorded by the source corpus.
Deep convection is a key process in the climate system and the main source of precipitation in the tropics, subtropics, and mid-latitudes during summer. Furthermore, it is related to high impact weather causing floods, hail, tornadoes, landslides, and other hazards. State-of-the-art climate models have to parameterize deep convection due to their coarse grid spacing. These parameterizations are a major source of uncertainty and long-standing model biases. We present a North American scale convection-permitting climate simulation that is able to explicitly simulate deep convection due to its 4-km grid spacing. We apply a feature-tracking algorithm to detect hourly precipitation from Mesoscale Convective Systems (MCSs) in the model and compare it with radar-based precipitation estimates east of the US Continental Divide. The simulation is able to capture the main characteristics of the observed MCSs such as their size, precipitation rate, propagation speed, and lifetime within observational uncertainties. In particular, the model is able to produce realistically propagating MCSs, which was a long-standing challenge in climate modeling. However, the MCS frequency is significantly underestimated in the central US during late summer. We discuss the origin of this frequency biases and suggest strategies for model improvements.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/4c06c336359bf29c2ec6c797b1ef22b48c3fc9f0
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Citations in the corpus
- Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States (2018, methodology): “Further, while 4-km grid spacing CPMmay be able to resolve mesoscale features associated with MCSs, the effective resolution (typically about seven horizontal grid spacing; e.g., Skamarock, 2004) is insufficient to resolve turbulence.”