Probabilistic forecasting
A probabilistic forecast takes the form of a predictive probability distribution over future
quantities or events of interest. Probabilistic forecasting aims to maximize the sharpness of …
quantities or events of interest. Probabilistic forecasting aims to maximize the sharpness of …
[HTML][HTML] Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world
Statistical postprocessing techniques are nowadays key components of the forecasting
suites in many national meteorological services (NMS), with, for most of them, the objective …
suites in many national meteorological services (NMS), with, for most of them, the objective …
A review on statistical postprocessing methods for hydrometeorological ensemble forecasting
Computer simulation models have been widely used to generate hydrometeorological
forecasts. As the raw forecasts contain uncertainties arising from various sources, including …
forecasts. As the raw forecasts contain uncertainties arising from various sources, including …
Uncertainty quantification in complex simulation models using ensemble copula coupling
R Schefzik, TL Thorarinsdottir, T Gneiting - 2013 - projecteuclid.org
Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling
Page 1 Statistical Science 2013, Vol. 28, No. 4, 616–640 DOI: 10.1214/13-STS443 © Institute of …
Page 1 Statistical Science 2013, Vol. 28, No. 4, 616–640 DOI: 10.1214/13-STS443 © Institute of …
Combining predictive distributions
T Gneiting, R Ranjan - 2013 - projecteuclid.org
In probabilistic forecasting combination formulas for the aggregation of predictive
distributions need to be estimated based on past experience and training data. We study …
distributions need to be estimated based on past experience and training data. We study …
A review of predictive uncertainty estimation with machine learning
Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …
distributions, aiming to increase the quantity of information communicated to end users …
Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales
The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in
the mean, spread and forecast probabilities, and how these biases propagate to streamflow …
the mean, spread and forecast probabilities, and how these biases propagate to streamflow …
Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes
A daily stochastic spatiotemporal precipitation generator that yields spatially consistent
gridded quantitative precipitation realizations is described. The methodology relies on a …
gridded quantitative precipitation realizations is described. The methodology relies on a …
A review of geospatial exposure models and approaches for health data integration
LP Clark, D Zilber, C Schmitt, DC Fargo… - Journal of Exposure …, 2024 - nature.com
Background Geospatial methods are common in environmental exposure assessments and
increasingly integrated with health data to generate comprehensive models of …
increasingly integrated with health data to generate comprehensive models of …
Comparison of non-homogeneous regression models for probabilistic wind speed forecasting
In weather forecasting, non-homogeneous regression (NR) is used to statistically post-
process forecast ensembles in order to obtain calibrated predictive distributions. For wind …
process forecast ensembles in order to obtain calibrated predictive distributions. For wind …