The Stalker method for increased predictability of fluids by moving beyond state variable measurements to enabling underlying physical processes

Authors

  • James R Stalker RESPR

Keywords:

Fluid state depiction, numerical weather prediction, cloud modeling, weather modification research, weather modification project design, weather modification project operation, weather modification project evaluation, generic fluid depiction and predictio

Abstract

Physical processes are not usually measured nor are adequately simulated using the current numerical weather prediction (NWP) models due to the inadequate spatial and temporal resolution such models employ. The state variables, such as wind speed and temperature, are often measured only at relatively fewer number of locations compared to a larger number of measurement locations theoretically required for more accurate fluid depiction and predictability. Because of such fewer measurement locations, the available measurements of the state variables are usually inter(extra)polated to many of these unmeasured locations, without accounting for the underlying physical processes that shape the state variables to start with. These background physical processes may occur at any given fluid location, with collective influences emanating in all of the spatial scales around that location or in the context of the NWP models they occur in both grid-resolvable and subgrid scales. Since sparse information of the state variables is heavily relied upon for depicting the fluid behavior and predictability today, both grid-resolvable and subgrid physical processes are usually unaccounted for in the current fluid simulation efforts. Also, the subgrid physical processes and many other physical process parameterization schemes and methods (e.g., data assimilation) are usually defined in terms of the grid-resolvable state variables. The absence of a detailed treatment of the physical processes in the current NWP methods (or approaches) points to rather large data gaps many fluid sciences deal with and thus is the limitation within such sciences. A scientifically valid method, the Stalker method, to overcome that limitation by filling such data gaps is the crux of this note. The importance of the noted physical process influences is even more critical for the weather modification efforts, as even deeper data gaps exist when resolutions finer than 1-km are required for fluid depiction and predictability.

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Published

2020-07-30

Issue

Section

Technical Notes and Correspondence