Statistically and Dynamically Downscaled Calibrated Probabilistic 10-m Wind Vector Forecasts Using Ensemble Model Output Statistics
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

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

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

i

Statistically and Dynamically Downscaled Calibrated Probabilistic 10-m Wind Vector Forecasts Using Ensemble Model Output Statistics

Filetype[PDF-3.85 MB]


Details You May Also Like

Details:

  • Journal Title:
    Monthly Weather Review
  • Personal Author:
  • NOAA Program & Office:
    NWS (National Weather Service)
  • Description:
    A computationally efficient method is developed that performs gridded postprocessing of ensemble 10-m wind vector forecasts. An expansive set of idealized WRF Model simulations are generated to provide physically consistent, high-resolution winds over a coastal domain characterized by an intricate land/water mask. The ensemble model output statistics (EMOS) technique is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. In a yearlong study, the method is applied to 24-h wind forecasts from the Global Ensemble Forecast System (GEFS) at 28 east-central Florida stations. Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicates that the postprocessed forecasts are calibrated. A downscaling case study illustrates the method as applied to a quiescent easterly flow event. Strengths and weaknesses of the approach are presented and discussed.
  • Keywords:
  • Source:
    Monthly Weather Review, 146(9), 2859-2880
  • DOI:
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA14NWS4680014
  • Rights Information:
    Other
  • Compliance:
    CHORUS
  • 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 3.24