Extending the Limits of Ensemble Forecast Verification with the Minimum Spanning Tree

Smith, Leonard A.; Hansen, James A.
June 2004
Monthly Weather Review;Jun2004, Vol. 132 Issue 6, p1522
Academic Journal
Uncertainty in the initial condition is one of the factors that limits the utility of single-model-run predictions of even deterministic nonlinear systems. In practice, an ensemble of initial conditions is often used to generate forecasts with the dual aims of 1) estimating the reliability of the forecasts and 2) estimating the probability distribution of the future state of the system. Current rank histogram ensemble verification techniques can only evaluate scalars drawn from ensembles and associated verification; a new method is presented that allows verification in high-dimensional spaces, including those of the verifications for 106 dimensional numerical weather prediction forecasts.


Related Articles

  • Assessing the Usefulness of Probabilistic Forecasts. Cusack, Stephen; Arribas, Alberto // Monthly Weather Review;Apr2008, Vol. 136 Issue 4, p1492 

    The errors in both the initialization and simulated evolution of weather and climate models create significant uncertainties in forecasts at lead times beyond a few days. Modern prediction systems sample the sources of these uncertainties to produce a probability distribution function of future...

  • Using Bayesian Model Averaging to Calibrate Forecast Ensembles. Raftery, Adrian E.; Gneiting, Tilmann; Balabdaoui, Fadoua; Polakowski, Michael // Monthly Weather Review;May2005, Vol. 133 Issue 5, p1155 

    Ensembles used for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive. This paper proposes a statistical method for postprocessing ensembles based on Bayesian model averaging (BMA), which is a standard method for combining predictive...

  • Calibrating ensemble reliability whilst preserving spatial structure. Flowerdew, Jonathan // Tellus: Series A;2014, Vol. 66, p1 

    Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the...

  • 300 BILLION SERVED. Lazo, Jeffrey K.; Morss, Rebecca E.; Demuth, Julie L. // Bulletin of the American Meteorological Society;Jun2009, Vol. 90 Issue 6, p785 

    Understanding the public's sources, perceptions, uses, and values of weather forecasts is integral to providing those forecasts in the most societally beneficial manner. To begin developing this knowledge, we conducted a nationwide survey with more than 1,500 respondents to assess 1) where,...

  • Measuring the Ensemble Spread–Error Relationship with a Probabilistic Approach: Stochastic Ensemble Results. Grimit, Eric P.; Mass, Clifford F. // Monthly Weather Review;Jan2007, Vol. 135 Issue 1, p203 

    One widely accepted measure of the utility of ensemble prediction systems is the relationship between ensemble spread and deterministic forecast accuracy. Unfortunately, this relationship is often characterized by spread–error linear correlations, which oversimplify the true...

  • The Early History of Probability Forecasts: Some Extensions and Clarifications MURPHY, ALLAN H. // Weather & Forecasting;Mar1998, Vol. 13 Issue 1, p5 

    Heretofore it has been widely accepted that the contributions of W. E. Cooke in 1906 represented the first works related to the explicit treatment of uncertainty in weather forecasts. Recently, however, it has come to light that at least some aspects of the rationale for quantifying the...

  • On the Proper Order of Markov Chain Model for Daily Precipitation Occurrence in the Contiguous United States. Schoof, J. T.; Pryor, S. C. // Journal of Applied Meteorology & Climatology;Sep2008, Vol. 47 Issue 9, p2477 

    Markov chains are widely used tools for modeling daily precipitation occurrence. Given the assumption that the Markov chain model is the right model for daily precipitation occurrence, the choice of Markov model order was examined on a monthly basis for 831 stations in the contiguous United...

  • Bayesian Retrieval of Complete Posterior PDFs of Oceanic Rain Rate from Microwave Observations. Chiu, J. Christine; Petty, Grant W. // Journal of Applied Meteorology & Climatology;Aug2006, Vol. 45 Issue 8, p1073 

    A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for...

  • Comments on �Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons from a Case Study�. Glahn, Bob // Bulletin of the American Meteorological Society;Oct2005, Vol. 86 Issue 10, p1484 

    This paper comments on the article ""Understanding user decision making and the value of improved precipitation forecasts: Lessons from a Case Study." It is an interesting study of a particular decision-making activity that is critically dependent on weather and weather forecasts. In regard to...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics