skip to main content

SciTech ConnectSciTech Connect

Title: The Role of Moist Processes in the Intrinsic Predictability of Indian Ocean Cyclones

The role of moist processes and the possibility of error cascade from cloud scale processes affecting the intrinsic predictable time scale of a high resolution convection permitting model within the environment of tropical cyclones (TCs) over the Indian region are investigated. Consistent with past studies of extra-tropical cyclones, it is demonstrated that moist processes play a major role in forecast error growth which may ultimately limit the intrinsic predictability of the TCs. Small errors in the initial conditions may grow rapidly and cascades from smaller scales to the larger scales through strong diabatic heating and nonlinearities associated with moist convection. Results from a suite of twin perturbation experiments for four tropical cyclones suggest that the error growth is significantly higher in cloud permitting simulation at 3.3 km resolutions compared to simulations at 3.3 km and 10 km resolution with parameterized convection. Convective parameterizations with prescribed convective time scales typically longer than the model time step allows the effects of microphysical tendencies to average out so convection responds to a smoother dynamical forcing. Without convective parameterizations, the finer-scale instabilities resolved at 3.3 km resolution and stronger vertical motion that results from the cloud microphysical parameterizations removing super-saturation at each model timemore » step can ultimately feed the error growth in convection permitting simulations. This implies that careful considerations and/or improvements in cloud parameterizations are needed if numerical predictions are to be improved through increased model resolution. Rapid upscale error growth from convective scales may ultimately limit the intrinsic mesoscale predictability of the TCs, which further supports the needs for probabilistic forecasts of these events, even at the mesoscales.« less
; ; ; ; ;
Publication Date:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Geophysical Research. D. (Atmospheres), 119(13):8032–8048
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
Sponsoring Org:
Country of Publication:
United States
predictability; moist processes; cyclones; Indian Ocean