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On the Emergence of Frequency Bias from Accumulating or Disaggregating Bias-Corrected Quantitative Precipitation Forecasts
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2022
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Source: Weather and Forecasting (2022)
[PDF-2.44 MB]
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Journal Title:Weather and Forecasting
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Description:Quantitative precipitation forecast (QPF) applications often demand accumulations of precipitation for both long and short duration time intervals. It is desired that the shorter duration forecasts sum to the longer duration accumulations spanning the same time period. In the context of calibration, it is further desired that both the subinterval and longer interval accumulations be similarly corrected to have near unit frequency bias on a spatial domain. This study examines two methods of achieving these goals for 6-h and 24-h accumulation intervals: 1) the accumulation method bias corrects the 6-h forecasts and accumulates them to create the 24-h accumulations; and 2) the disaggregation method bias corrects the 24-h accumulation and then proportionately disaggregates the 24-h accumulation back into 6-h accumulations. The experiments for the study are done retrospectively so that a “perfect” bias correction is possible for each method. The results of the study show that neither method accomplishes the stated goal for the calibration because QPF placement and/or timing errors contribute to frequency bias in the course of accumulation or disaggregation. However, both methods can improve the frequency bias for both the subinterval and longer interval accumulations. The choice of method may hinge most strongly on the relative tolerance of bias for the subinterval accumulations versus the longer interval accumulation.
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Source:Weather and Forecasting (2022)
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DOI:
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ISSN:0882-8156;1520-0434;
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Rights Information:Other
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