Mesoscale Convective Systems Represented in High Resolution E3SMv2
Mesoscale convective systems (MCSs) remain difficult to replicate without improved model resolution or improved model physics.
The Science
Mesoscale convective systems (MCSs) consist of an assembly of cumulonimbus clouds on scales of 100 km or more and produce mesoscale circulations. As the largest form of deep convective storms, MCSs contribute to 30% to 70% of annual and warm-season rainfall in the U.S. and in the global tropics. Since MCSs contribute importantly to mean and extreme precipitation in the U.S. and many other regions around the world, understanding how well they are simulated by the recently released U.S. Department of Energy (DOE) Energy Exascale Earth System Model version 2 (E3SMv2) and impact of several new developments in cloud and convection parameterizations for E3SMv3 on MCS may guide future development towards more skillful modeling of convective storms and associated hydrologic effects.
Figure 1. Annual mean MCS precipitation fraction defined using Tb (cloud top brightness temperature) and surface precipitation (a, b) and MCS precipitation fraction defined using Tb only (c, d). The IMERG observation is shown on the left and EAMv2 simulation is shown on the right.
The Impact
This study indicates the challenge in simulating MCSs at a scale that MCSs cannot be fully resolved. Even at a grid spacing of around 25 km, the precipitation generated by MCSs in E3SMv2 is substantially underestimated. This shortfall stems largely from insufficient MCS genesis and too low rain rates in the individual systems. The new cloud and convection parameterizations developed for E3SMv3 show little improvement in the simulation of MCSs. The future direction of improving MCS simulation in E3SM should involve both increasing model resolution to better resolve key dynamical processes and improving model physics to better represent MCSs.
Summary
In this study, the researchers evaluated MCS simulations in E3SMv2. Its atmosphere model (EAMv2) is run at ~25km horizontal resolution. The scientists track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCSs based on both cloud top brightness temperature (Tb) and surface precipitation (Fig. 1a,b). Results from analysis using only Tb to define MCSs are also discussed (Fig. 1c,d). This helps to understand the impact of different MCS tracking algorithms on MCS evaluation and provides additional insights into model errors in simulating MCSs. The results show that EAMv2 simulated MCS precipitation is largely underestimated in tropical and extratropical regions. This is mainly attributed to the underestimated MCS genesis and too low precipitation intensity in EAMv2. Comparing the two MCS tracking methods, simulated MCS precipitation is increased if MCSs are defined with only cloud top Tb. The Tb-based MCS tracking method, however, includes cloud systems with very weak precipitation. This illustrates the model issues in simulating heavy precipitation, even though the convective cloud shield is well simulated from the moist convective processes. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. The new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are not significantly improved. This suggests that simulating MCSs still remains a challenge for the next version of E3SM.
Publication
- Zhang, Meng, Shaocheng Xie, Zhe Feng, Christopher R Terai, Wuyin Lin, Cheng Tao, Chi-Chien-Jack Chen, et al. 2024. “Mesoscale Convective Systems Represented In High Resolution E3Smv2 And Impact Of New Cloud And Convection Parameterizations”. Journal Of Geophysical Research: Atmospheres 129. doi:10.1029/2024JD040828.
Funding
- This work was supported by the Earth System Model Development program area of the Department of Energy, Office of Science, Biological and Environmental Research program.
Contact
- Shaocheng Xie, Lawrence Livermore National Laboratory
This article is a part of the E3SM “Floating Points” Newsletter, to read the full Newsletter check:
