University of Tasmania
Browse
142664 - Calibrating hourly precipitation forecasts with daily observations.pdf (2.03 MB)

Calibrating hourly precipitation forecasts with daily observations

Download (2.03 MB)
journal contribution
posted on 2023-05-20, 20:39 authored by Cattoen, C, Robertson, DE, Bennett, JC, Wang, QJ, Carey-Smith, TK
Calibrated high-temporal-resolution precipitation forecasts are desirable for a range of applications, for example, flood prediction in fast-rising rivers. However, high-temporal-resolution precipitation observations may not be available to support the establishment of calibration methods, particularly in regions with low population density or in developing countries. We present a new method to produce calibrated hourly precipitation ensemble forecasts from daily observations. Precipitation forecasts are taken from a high-resolution convective-scale numerical weather prediction (NWP) model run at the hourly time step. We conduct three experiments to develop the new calibration method: (i) calibrate daily precipitation totals and disaggregate daily forecasts to hourly; (ii) generate pseudohourly observations from daily precipitation observations, and use these to calibrate hourly precipitation forecasts; and (iii) combine aspects of (i) and (ii). In all experiments, we use the existing Bayesian joint probability model to calibrate the forecasts and the well-known Schaake shuffle technique to instill realistic spatial and temporal correlations in the ensembles. As hourly observations are not available, we use hourly patterns from the NWP as the template for the Schaake shuffle. The daily member matching method (DMM), method (iii), produces the best-performing ensemble precipitation forecasts over a range of metrics for forecast accuracy, bias, and reliability. The DMM method performs very similarly to the ideal case where hourly observations are available to calibrate forecasts. Overall, valuable spatial and temporal information from the forecast can be extracted for calibration with daily data, with a slight trade-off between forecast bias and reliability.

History

Publication title

Journal of Hydrometeorology

Volume

21

Issue

7

Pagination

1655-1673

ISSN

1525-755X

Department/School

Institute for Marine and Antarctic Studies

Publisher

Amer Meteorological Soc

Place of publication

45 Beacon St, Boston, USA, Ma, 02108-3693

Rights statement

Copyright 2020 American Meteorological Society. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

Repository Status

  • Open

Socio-economic Objectives

Effects of climate change on Australia (excl. social impacts)

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC