Operational time and in-sample density forecasting

A Practioner’s Guide to Operational Real Time Earthquake Forecasting

Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting

Operational flood forecasting requires that accurate estimates of the uncertainty associated with modelgenerated streamflow forecasts be provided along with the probable flow levels. This paper demonstrates a stochastic ensemble implementation of the Sacramento model used routinely by the National Weather Service for deterministic streamflow forecasting. The approach, the simultaneous optimizat...

Forecasting and operational research: a review

From its foundation, operational research (OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scop...

Sample-Optimal Density Estimation in Nearly-Linear Time

We design a new, fast algorithm for agnostically learning univariate probability distributions whose densities are well approximated by piecewise polynomial functions. Let f be the density function of an arbitrary univariate distribution, and suppose that f is OPT close in L1-distance to an unknown piecewise polynomial function with t interval pieces and degree d. Our algorithm draws n = O(t(d+...

Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation

Abstract. The Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) has been producing operational flow forecasts of the northeastern Levantine Basin since 2002 and has been substantially improved in 2005. CYCOFOS uses the POM flow model, and recently, within the frame of the MFSTEP project, the flow model was upgraded to use the hourly SKIRON atmospheric forcing, and its resolution w...