Current Issues and Challenges in Ensemble Forecasting
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1 Current Issues and Challenges in Ensemble Forecasting Junichi Ishida (JMA) and Carolyn Reynolds (NRL) With contributions from WGNE members 31 th WGNE Pretoria, South Africa, April 2016 Recent trends in ensemble related research Continued improvements in global EPS High resolution ensembles (issues, improvements) Impact driven products Tropical cyclone ensembles Overview of plans 1
2 Number of Article/Year with These Words in the Abstract* Research in ensemble forecasting and ensemble data assimilation continues its steady climb. *AMS journals only
3 Number of Article/Year with These Words in the Abstract* Research in model uncertainty continues to grow rapidly. Interest in calibration and post processing also substantially larger than in the early 2000s. *AMS journals only 3
4 Continued Improvement in Global EPS ECMWF: 2-m T over Europe: Impact of resolution upgrade NCEP: 500-hPa AC impact from latest model and resolution upgrades, shift from ETR to EnKF based initial perturbations.
5 High Resolution Ensembles ROSHYDROMET: Sensitivity of 2 m T to resolution Understanding why spread is so small in regions of higher topography may help in reducing under dispersion problem.
6 High Resolution Ensembles JMA: More consistency between initial and lateral boundary conditions improves performance (including timing of front, below).
7 Impact driven Products calibration of ensemble output, focus on severe weather event forecast; deterministic and probabilistic methods for prediction of fog and thunderstorm; predictability of severe weather events in an ensemble forecast framework; evaluation of the impact of the different components of an ensemble system on the prediction of the severe weather phenomena, focusing on the representation of the model errors and surface uncertainties. Focus on post processing approaches and downscaling of atmospheric ensemble forecasts, community multimodel endeavors, hydrologic DA (what and how), ensemble verification and value of predictions, post processing of hydrological predictive distributions, uncertainty quantification and user acceptance, communication of forecast services and products, risk based decision making.
8 New Products and Severe Weather MetoFrance: Probability of Thunderstorm Occurrence (12 h range) from Arome EPS (2.5 km) Probabilities of a convection severity index derived from the 3D hydrometeor fields in ensemble members Arome-France EPS domain
9 Tropical Cyclone Ensemble Forecasting Blue : TL639 Red : TCo639 ECMWF increase in resolution substantial decreases intensity error (solid red line) and increases spread (dashed red line). h NOAA Hurricane Forecast Improvement Project 2015 Real time Multi model Ensemble: COAMPS TC & HWRF combination outperforms the two individual models. Multi models show promise, but more cases needed to better assess performance. Intensity error (solid) & bias (dashed) COAMPS-TC HWRF Combo COAMPS TC & HWRF
10 PLANS (beyond increased resolution and # of members) Improved initial conditions: ROSHYDROMET: LETKF and 3d VAR Hybrid NCEP: EnKF replaced ETR CPTEC: EnKF ECMWF: Use ensemble of 4dVARs directly (no recentering) Met Office: replace ETKF with En 4dENVar, convective scale ens. DA NRL: Perturbed obs scheme in atmosphere and ocean CMC: Validation package to test for expected statistical relationships, incremental updates replacing digital filter Improved Model Uncertainty NCEP: (SKEB, SPPT, SHUM) MeteoFrance: extend stochastic physics ECMWF: Revision of SPPT scheme, physically consistent tendency perturbations, consistent at all time ranges. Met Office: Upgrades to random parameters
11 PLANS (beyond increased resolution and # of members) Improved lateral/lower boundary uncertainty NCEP: Stochastic perturbed land surface NRL: SST perturbations, SST diurnal cycle MeteoFrance: Surface perturbations, new surface model (SURFEX) JMA: consistent initial and lateral boundary perturbations CPTEC: Use coupled Brazilian Earth System Model ECMWF: resolution upgrade to NEO ocean model Met Office: Coupled atmo. in all global configurations, parameter perturbations in JULES land surface model JMA Representation of SST Uncertainty: Impact on atmospheric forecast
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