Achieving effective calibration of precipitation forecasts over a continental scale

Abstract

Study region: Australia. Study focus: We developed the Seasonally Coherent Calibration (SCC) model to post-process precipitation forecasts from numerical weather prediction (NWP) models. The SCC model is capable of generating high-quality calibrated forecasts which are coherent in climatology, including seasonality, consistent with observations, despite only a short period of forecasts being available. In this study, we post-process deterministic precipitation forecasts from the Australian Bureau of Meteorology’s Australian Community Climate and Earth System Simulator G2 version (ACCESS-G2) NWP model to generate calibrated ensemble forecasts across Australia. We evaluate the effectiveness, robustness, and computational feasibility of forecast post-processing with the SCC model at a high spatial resolution across the continental scale. New hydrological insights for the region: Inadequate representation of forecast seasonality in calibration models poses a challenge for the calibration of NWP forecasts. Through this investigation, the statistical assumptions and reparameterization algorithms of the SCC model are confirmed to be effective and robust in addressing the challenge. Calibrated precipitation forecasts could be used to support operational water balance forecasting in Australia. Post-processing of NWP precipitation forecasts with the SCC model will also benefit a broad range of forecast users in Australia by providing accurate, skillful, and reliable ensemble forecasts. Computation strategies adopted in this study will help develop effective procedures for future post-processing of NWP forecasts with sophisticated calibration models at a large spatial scale.

Keywords

• Post-processing
• Seasonally coherent calibration
• Forecast evaluation
• Large scale application