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Abstract A 6.5-month, convection-permitting simulation is conducted over Argentina covering the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations and Clouds, Aerosols, and Complex Terrain Interactions (RELAMPAGO-CACTI) field campaign and is compared with observations to evaluate mesoscale convective system (MCS) growth prediction. Observed and simulated MCSs are consistently identified, tracked, and separated into growth, mature, and decay stages using top-of-the-atmosphere infrared brightness temperature and surface rainfall. Simulated MCS number, lifetime, seasonal and diurnal cycles, and various cloud-shield characteristics including growth rate are similar to those observed. However, the simulation produces smaller rainfall areas, greater proportions of heavy rainfall, and faster system propagations. Rainfall area is significantly underestimated for long-lived MCSs but not for shorter-lived MCSs, and rain rates are always overestimated. These differences result from a combination of model and satellite retrieval biases, in which simulated MCS rain rates are shifted from light to heavy, while satellite-retrieved rainfall is too frequent relative to rain gauge estimates. However, the simulation reproduces satellite-retrieved MCS cloud-shield evolution well, supporting its usage to examine environmental controls on MCS growth. MCS initiation locations are associated with removal of convective inhibition more than maximized low-level moisture convergence or instability. Rapid growth is associated with a stronger upper-level jet (ULJ) and a deeper northwestern Argentinean low that causes a stronger northerly low-level jet (LLJ), increasing heat and moisture fluxes, low-level vertical wind shear, baroclinicity, and instability. Sustained growth corresponds to similar LLJ, baroclinicity, and instability conditions but is less sensitive to the ULJ, large-scale vertical motion, or low-level shear. Growth sustenance controls MCS maximum extent more than growth rate.
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Can Pre-Storm Errors in the Low-Level Inflow Help Predict Spatial Displacement Errors in MCS Initiation?
The Great Plains low-level jet (LLJ) is a contributing factor to the initiation and evolution of nocturnal Mesoscale Convective Systems (MCSs) in the central United States by supplying moisture, warm air advection, and a source of convergence. Thus, the ability of models to correctly depict thermodynamics in the LLJ likely influences how accurately they forecast MCSs. In this study, the Weather Research and Forecasting (WRF) model was used to examine the relationship between spatial displacement errors for initiating simulated MCSs, and errors in forecast thermodynamic variables up to three hours before downstream MCS initiation in 18 cases. Rapid Update Cycle (RUC) analyses in 3 layers below 1500 m above ground level were used to represent observations. Correlations between simulated MCS initiation spatial displacements and errors in the magnitude of forecast thermodynamic variables were examined in regions near and upstream of both observed and simulated MCSs, and were found to vary depending on the synoptic environment. In strongly-forced cases, large negative moisture errors resulted in simulated MCSs initiating further downstream with respect to the low-level flow from those observed. For weakly-forced cases, correlations were weaker, with a tendency for smaller negative moisture errors to be associated with larger displacement errors to the right of the inflow direction for initiating MCSs.
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- Award ID(s):
- 2022888
- PAR ID:
- 10229048
- Date Published:
- Journal Name:
- Atmosphere
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2073-4433
- Page Range / eLocation ID:
- 7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/atmos12010007
