Sensitivity of Calibrated Week-2 Probabilistic Forecast Skill to Reforecast Sampling of the NCEP Global Ensemble Forecast System
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Sensitivity of Calibrated Week-2 Probabilistic Forecast Skill to Reforecast Sampling of the NCEP Global Ensemble Forecast System

Filetype[PDF-2.63 MB]


Details You May Also Like

Details:

  • Journal Title:
    Weather and Forecasting
  • Personal Author:
  • NOAA Program & Office:
    NWS (National Weather Service)
  • Description:
    CPC requires the reforecast-calibrated Global Ensemble Forecast System (GEFS) to support the production of their official 6-10- and 8-14-day temperature and precipitation forecasts. While a large sample size of forecast-observation pairs is desirable to generate the necessary model climatology and variances, and covariances to observations, sampling by reforecasts could be done to use available computing resources most efficiently. A series of experiments was done to assess the impact on calibrated forecast skill of using a smaller sample size than the current available reforecast dataset. This study focuses on the skill of week-2 probabilistic forecasts of the 7-day-mean 2-m temperature and accumulated precipitation. The tercile forecasts are expressed as being below-, near-, and above-normal temperature/median precipitation over the continental United States (CONUS). Calibration statistics were calculated using an ensemble regression technique from 25 yr of daily, 11-member GEFS reforecasts for 1986-2010, which were then used to postprocess the GEFS model forecasts for 2011-13. In assessing the skill of calibrated model output using a reforecast dataset with fewer years and ensemble members, and an ensemble run less frequently than daily, it was determined that reductions in the number of ensemble members to six or fewer and reductions in the frequency of reforecast runs from daily to once a week were achievable with minimal loss of skill. However, reducing the number of years of reforecasts to less than 25 resulted in a greater skill degradation. The loss of skill was statistically significant using only 18 yr of reforecasts from 1993 to 2010 to generate model statistics.
  • Source:
    Weather and Forecasting, 31(4), 1093-1107.
  • DOI:
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files
More +

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.27.1