ensembleBMA (version 5.1.8)

srftGrid: Gridded Surface Temperature Ensemble Forecasts

Description

This data set gives 48-hour forecasts of 2-m surface temperature on a grid of locations in the US Pacific Northwest initialized on January 29, 2004 00UTC and valid on January 31, 2004 00UTC. The ensemble forecasts come from an eight member version of the University of Washington Mesoscale Ensemble (Grimit and Mass 2002; Eckel and Mass 2005). Temperatures are measured in kelvins.
Note that forecasts are not available for some of the interim dates.

Format

A data frame with 10098 rows and 10 columns:
CMCG,ETA,GASP,GFS,JMA,NGAPS,TCWB,UKMO forecasts from the 8 members of the ensemble (numeric).
latitude the latitude of each forecast (numeric).
longitude the longitude of each forecast (numeric).

References

F. A. Eckel and C. F. Mass, Effective mesoscale, short-range ensemble forecasting, Weather and Forecasting 20:328--350, 2005.

E. P. Grimit and C. F. Mass, Initial results of a mesoscale short-range ensemble forecasting system over the Pacific Northwest, Weather and Forecasting 17:192--205, 2002.

V. J. Berrocal, A. E. Raftery and T. Gneiting, Combining spatial and ensemble information in probabilistic weather forecasts, Monthly Weather Review 133:1386--1402, 2007.

V. J. Berrocal, A. E. Raftery, T. Gneiting and R. C. Steed, Probabilistic Weather Forecasting for Winter Road Maintenance, Journal of the American Statistical Association, 2010 (to appear).

C. Fraley, A. E. Raftery, T. Gneiting and J. M. Sloughter, ensembleBMA: An R Package for Probabilistic Forecasting using Ensembles and Bayesian Model Averaging, Technical Report No. 516R, Department of Statistics, University of Washington, 2007 (revised 2010).

Examples

if (FALSE)  # R check
  data(srft)
  data(srftGrid)

  labels <- c("CMCG","ETA","GASP","GFS","JMA","NGPS","TCWB","UKMO")

  srftData <- ensembleData( forecasts = srft[ ,labels],
                            dates = srft$date,
                            observations = srft$obs,
                            latitude = srft$lat,
                            longitude = srft$lon,
                            forecastHour = 48,
                            initializationTime = "00")

  srftFit <- ensembleBMAnormal( srftData, date = "2004013100",
                                trainingDays = 25)


  srftGridData <- ensembleData( forecasts = srftGrid[ ,labels],
                                latitude = srftGrid$lat,
                                longitude = srftGrid$lon,
                                forecastHour = 48,
                                initializationTime = "00")

   CRPS( srtGridData, srftFit)