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  • Author or Editor: Roman Krzysztofowicz x
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Roman Krzysztofowicz

Abstract

A probabilistic quantitative precipitation forecast (PQPF) is prepared judgmentally by a meteorologist based on a guidance PQPF. The predictand of a judgmental PQPF is the spatially averaged precipitation amount. The predictand of a guidance PQPF produced by a statistical model is the point precipitation amount. Therefore, a procedure is needed for point-to-area rescaling of the PQPF. Theoretically based equations for rescaling are presented. The equations incorporate two predictive parameters, which characterize the precipitation field being forecast: the quotient of the area covered by a precipitation cell to the area of averaging (cell/area quotient), and the degree of certainty about the precipitation pattern (pattern certainty factor). Both parameters can be judgmentally quantified by the meteorologist during PQPF preparation. The same parameters can be entered into an inverse procedure for area-to-point rescaling of the judgmental PQPF.

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Roman Krzysztofowicz and Thomas A. Pomroy

Abstract

Disaggregative invariance refers to stochastic independence between the total precipitation amount and its temporal disaggregation. This property is investigated herein for areal average and point precipitation amounts accumulated over a 24-h period and disaggregated into four 6-h subperiods. Statistical analyses of precipitation records from 1948 to 1993 offer convincing empirical evidence against the disaggregative invariance and in favor of the conditional disaggregative invariance, which arises when the total amount and its temporal disaggregation are conditioned on the timing of precipitation within the diurnal cycle.

The property of conditional disaggregative invariance allows the modeler or the forecaster to decompose the problem of quantitative precipitation forecasting into three tasks: (i) forecasting the precipitation timing; (ii) forecasting the total amount, conditional on timing; and (iii) forecasting the temporal disaggregation, conditional on timing. Tasks (ii) and (iii) can be performed independently of one another, and this offers a formidable advantage for applications.

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