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Post‐processing methods for Task 33042

The objective of Task 33042 is to provide probabilistic uncertainty quantification based on deterministic forecasts generated by the extreme DT. The extreme DT will be run on-demand at hectometric spatial resolution with domains determined by a triggering algorithm and vary depending on the expected weather conditions. In Phase 1 the focus is to implement a set of well-established post-processing methods using the yet limited data available for demonstration and testing.

List of codes with short description

The following repositories are created for the various methods

• DE330_WP42-BQN: Bernstein Quantile Networks (BQN)
• DE330_WP42-SAMOS: Standardised Anomaly Model Output Statistics (SAMOS)
• WP42-nbh-unc: Neighbourhood ensemble method
• DE330_WP42-analogs: Analog method
• DE330_WP42_UDPrecip: Up- and downscaling method for precipitation fields
• DE330_WP42-MOSRF: Model Output Statistics with Random Forest (MOS-RF)
• DE330_WP42-DRF: Distributional Random Forest (DRF)
• DE330_WP42-GRF: Generalised Random Forest (GRF)