MPO 674 Lecture 2 1/20/15

Timeline (continued from Class 1) 1960s: Lorenz papers: finite limit of predictability? 1966: First primitive equations model (6 layers) 1971: First regional system (limited fine mesh model) 1978: Optimal Interpolation 1980: Global Spectral Model 1991: 3d-Var introduced at NCEP (Parrish and Derber 1992) 1993: First ensemble forecast systems at NCEP and ECMWF

Ensemble Forecasts Epstein (1969), Leith (1974) suggested that instead of performing “deterministic” forecasts, stochastic forecasts providing an estimate of the skill of the prediction should be made. Several model forecasts with perturbations in the initial conditions or in the models themselves (will review perturbation methods later in the course)

Ensemble Forecasts Goals: – To provide an ensemble average that is more accurate than individual forecasts, especially beyond the first few days. Components of forecast that are less predictable tend to be averaged out. – To provide forecasters with an estimation of the reliability of the forecast – Data assimilation – Adaptive Observations – Sensitivity Analysis

Ensemble Forecasts Can extend forecasts beyond Lorenz’s 2-week limit of weather predictability ENSO should be predictable a year or more in advance, since slowly varying surface forcing (from SST and land surface) should produce atmospheric anomalies that are longer lasting and more predictable than weather patterns Cane et al. (1986): first experiments

Ensemble Spaghetti Diagrams

108 h ECMWF Ensemble Forecast of pre-Karl, init UTC 10 Sept 2010 CIRC THICK MSLP Probability (TC at 108 h) = 68% CIRC (x s -1 ) THICK (m)

Ensemble prediction skill

Timeline (since 1993) 1993: Nonhydrostatic mesoscale models: MM5, CAPS, RAMS etc. 1997: ECMWF introduced 4d-Var operationally, most other centers (except NCEP) followed 2005: Canadian Meteorological Center introduced Ensemble Kalman Filter (EnKF) into operations 2012: NCEP introduced Hybrid 3d-Var / EnKF 2015 (Jan 14): NCEP GFS 13 km resolution

Current and Future Detailed short-range forecasts (severe weather, rain and snow bands etc) Sophisticated, flow-dependent, continuous DA Adaptive observing systems Improving medium- and long-range forecasts, primarily through ensembles Fully coupled systems (atmosphere-ocean- wave-land-ice-hydrology) Public guidance: air pollution, UV radiation, flooding levels, local winds, fires etc.