Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: William M. Lapenta x
  • Bulletin of the American Meteorological Society x
  • Refine by Access: All Content x
Clear All Modify Search
Louis W. Uccellini
,
Richard W. Spinrad
,
Dorothy M. Koch
,
Craig N. McLean
, and
William M. Lapenta

Abstract

NOAA has launched the Earth Prediction Innovation Center (EPIC) in partnership with the Weather Enterprise (academia, government, and industry) to bring the power of distributed innovation to bear on one of the greatest challenges of our time. EPIC provides a collaborative framework building upon the community-driven Unified Forecast System (UFS) to accelerate innovative improvements to the nation’s forecast system in order to save lives, protect property, and enhance the economy. This article describes NOAA’s strategic, tactical, and organizational approaches to utilize EPIC to transform the world-leading U.S. national forecast systems into an even stronger and more effective community-based, computationally advanced Earth prediction system to meet the expanding and pressing needs of national and international societies.

Full access
Thomas M. Hamill
,
Gary T. Bates
,
Jeffrey S. Whitaker
,
Donald R. Murray
,
Michael Fiorino
,
Thomas J. Galarneau Jr.
,
Yuejian Zhu
, and
William Lapenta

A multidecadal ensemble reforecast database is now available that is approximately consistent with the operational 0000 UTC cycle of the 2012 NOAA Global Ensemble Forecast System (GEFS). The reforecast dataset consists of an 11-member ensemble run once each day from 0000 UTC initial conditions. Reforecasts are run to +16 days. As with the operational 2012 GEFS, the reforecast is run at T254L42 resolution (approximately 1/2° grid spacing, 42 levels) for week +1 forecasts and T190L42 (approximately 3/4° grid spacing) for the week +2 forecasts. Reforecasts were initialized with Climate Forecast System Reanalysis initial conditions, and perturbations were generated using the ensemble transform with rescaling technique. Reforecast data are available from 1985 to present.

Reforecast datasets were previously demonstrated to be very valuable for detecting and correcting systematic errors in forecasts, especially forecasts of relatively rare events and longer-lead forecasts. What is novel about this reforecast dataset relative to the first-generation NOAA reforecast is that (i) a modern, currently operational version of the forecast model is used (the previous reforecast used a model version from 1998); (ii) a much larger set of output data has been saved, including variables relevant for precipitation, hydrologic, wind energy, solar energy, severe weather, and tropical cyclone forecasting; and (iii) the archived data are at much higher resolution.

The article describes more about the reforecast configuration and provides a few examples of how this second-generation reforecast data may be used for research and a variety of weather forecast applications.

Full access