2003
DOI: 10.1029/2002jd002551
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A method for estimating momentum fluxes of deep precipitating convection using profiling Doppler radar

Abstract: [1] This paper outlines a novel approach for obtaining estimates of momentum fluxes for deep precipitating convection. This method relies on data collected by vertically incident profiling Doppler radars but may be applied to aircraft-or space-based radar systems. This work represents a significant step forward toward the evaluation of convective momentum transports across regional scales using data from operational satellite systems (e.g., the Tropical Rainfall Measuring Mission (TRMM) instrument . The method… Show more

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Cited by 1 publication
(4 citation statements)
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“…Therefore, the use of this model is very appropriate for the simulation of atmospheric convection. The convective momentum budgets produced by the UW‐NMS are domain averaged without the Coriolis terms included [ Mecikalski , 2003]. The momentum budget is given by This equation is ideal for numerical simulations because the first term on the right‐hand side (RHS) closes off the calculation on a square grid, which represents the horizontal advection across the model domain.…”
Section: Datamentioning
confidence: 99%
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“…Therefore, the use of this model is very appropriate for the simulation of atmospheric convection. The convective momentum budgets produced by the UW‐NMS are domain averaged without the Coriolis terms included [ Mecikalski , 2003]. The momentum budget is given by This equation is ideal for numerical simulations because the first term on the right‐hand side (RHS) closes off the calculation on a square grid, which represents the horizontal advection across the model domain.…”
Section: Datamentioning
confidence: 99%
“…Therefore, the use of this model is very appropriate for the simulation of atmospheric convection. The convective momentum budgets produced by the UW-NMS are domain averaged without the Coriolis terms included [Mecikalski, 2003]. The momentum budget is given by…”
Section: University Of Wisconsin Nonhydrostatic Modeling Systemmentioning
confidence: 99%
See 2 more Smart Citations