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Verification of Quantitative Precipitation Forecasts from Operational Numerical Weather Prediction Models over Australia

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  • 1 Bureau of Meteorology Research Centre, Melbourne, Australia
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Abstract

Real-time gridded 24-h quantitative precipitation forecasts from seven operational NWP models are verified over the Australian continent. All forecasts have been mapped to a 1° latitude–longitude grid and have been verified against an operational daily rainfall analysis, mapped to the same grid. The verification focuses on two large subregions: the northern tropical monsoon regime and the southeastern subtropical regime. Statistics are presented of the bias score, probability of detection, and false alarm ratio for a range of rainfall threshold values. The basic measure of skill used in this study, however, is the Hanssen and Kuipers (HK) score and its two components: accuracy for events and accuracy for nonevents.

For both regimes the operational models tend to overestimate rainfall in summer and to underestimate it in winter. In the southeastern region the models have HK scores ranging from 0.5 to 0.7, and easily outperform a forecast of persistence. Thus for the current operational NWP models, the 24-h rain forecasts can be considered quite skillful in the subtropics. On the other hand, model skill is quite low in the northern regime with HK values of only 0.2–0.6. During the summer wet season the low skill is associated with an inability to simulate the behavior of tropical convective rain systems. During the winter dry season, it is associated with a low probability of detection for the occasional rainfall event. Thus it could be said that models have no real skill at rainfall forecasts in this monsoonal wet season regime.

Model skill falls dramatically for occurrence thresholds greater than 10 mm day−1. This implies that the models are much better at predicting the occurrence of rain than they are at predicting the magnitude and location of the peak values.

Corresponding author address: Dr. John L. McBride, Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne 3001, Australia.

Email: J.Mcbride@bom.gov.au

Abstract

Real-time gridded 24-h quantitative precipitation forecasts from seven operational NWP models are verified over the Australian continent. All forecasts have been mapped to a 1° latitude–longitude grid and have been verified against an operational daily rainfall analysis, mapped to the same grid. The verification focuses on two large subregions: the northern tropical monsoon regime and the southeastern subtropical regime. Statistics are presented of the bias score, probability of detection, and false alarm ratio for a range of rainfall threshold values. The basic measure of skill used in this study, however, is the Hanssen and Kuipers (HK) score and its two components: accuracy for events and accuracy for nonevents.

For both regimes the operational models tend to overestimate rainfall in summer and to underestimate it in winter. In the southeastern region the models have HK scores ranging from 0.5 to 0.7, and easily outperform a forecast of persistence. Thus for the current operational NWP models, the 24-h rain forecasts can be considered quite skillful in the subtropics. On the other hand, model skill is quite low in the northern regime with HK values of only 0.2–0.6. During the summer wet season the low skill is associated with an inability to simulate the behavior of tropical convective rain systems. During the winter dry season, it is associated with a low probability of detection for the occasional rainfall event. Thus it could be said that models have no real skill at rainfall forecasts in this monsoonal wet season regime.

Model skill falls dramatically for occurrence thresholds greater than 10 mm day−1. This implies that the models are much better at predicting the occurrence of rain than they are at predicting the magnitude and location of the peak values.

Corresponding author address: Dr. John L. McBride, Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne 3001, Australia.

Email: J.Mcbride@bom.gov.au

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