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Eugenia Kalnay
,
Stephen J. Lord
, and
Ronald D. McPherson

In 1939 Rossby demonstrated the usefulness of the linearized perturbation of the equations of motion for weather prediction and thus made possible the first successful numerical forecasts of the weather by Charney et al. In 1951 Charney wrote a paper on the science of numerical weather prediction (NWP), where he predicted with remarkable vision how NWP would evolve until the present. In the 1960's Lorenz discovered that the chaotic nature of the atmosphere imposes a finite limit of about two weeks to weather predictability. At that time this fundamental discovery was “only of academic interest” and not really relevant to operational weather forecasting, since at that time the accuracy of even a 2-day forecast was rather poor. Since then, however, computer-based forecasts have improved so much that Lorenz's limit of predictability is starting to become attainable in practice, especially with ensemble forecasting, and the predictabilty of longer-lasting phenomena such as El Niño is beginning to be successfully exploited.

The skill of operational weather forecasts has at least doubled over the last two decades. This improvement has taken place relatively steadily, driven by a large number of scientific and computational developments, especially in the area of NWP. It has taken place in all the operational NWP centers, as friendly competition and information sharing make scientific improvements take place faster than they would in a single center. Because the improvements have occurred steadily, rather than suddenly, the overall increase in forecast skill due to NWP has not been clearly recognized by the media and the public despite the impact that improved forecasts have on the national economy and on the lives of every American.

In this paper the authors review several measures of operational forecast skill that quantify improvements in NWP at the National Centers for Environmental Prediction (NCEP, formerly the National Meteorological Center) of the National Weather Service, although they are representative of improvements in all major NWP operational centers. The authors point out that there are three major requirements for improved numerical weather prediction: better atmospheric models, better observational data, and better methods for data assimilation. These improvements are generally very computer intensive and can only be made operational with the availability of more powerful supercomputers. Operational forecasts are compared with “reforecasts” from the NCEP–NCAR 40-Year Reanalysis, showing that, if the present-day NWP systems had been available many decades ago, skillful 5-day forecasts would have been possible in the Northern Hemisphere with the upper-air network of the late 1950s. The authors discuss new approaches in the use of observations (variational assimilation of remote observations) and of numerical weather prediction guidance (ensemble forecasting) that have allowed the recent extension of operational predictions into longer ranges and the possibility of adaptive observing systems. The extension of operational forecast skill into seasonal predictions of the El Niño–Southern Oscillation phenomena using coupled ocean-atmosphere models is also discussed. In the last section the authors attempt to “forecast” the future of NWP.

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Morris A. Bender
,
Timothy Marchok
,
Robert E. Tuleya
,
Isaac Ginis
,
Vijay Tallapragada
, and
Stephen J. Lord

Abstract

The hurricane project at the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) was established in 1970. By the mid-1970s pioneering research had led to the development of a new hurricane model. As the reputation of the model grew, GFDL was approached in 1986 by the director of the National Meteorological Center about establishing a collaboration between the two federal organizations to transition the model into an operational modeling system. After a multiyear effort by GFDL scientists to develop a system that could support rigorous requirements of operations, and multiyear testing had demonstrated its superior performance compared to existing guidance products, operational implementation was made in 1995. Through collaboration between GFDL and the U.S. Navy, the model was also made operational at Fleet Numerical Meteorology and Oceanography Center in 1996. GFDL scientists continued to support and improve the model during the next two decades by collaborating with other scientists at GFDL, the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), the National Hurricane Center, the U.S. Navy, the University of Rhode Island (URI), Old Dominion University, and the NOAA Hurricane Research Division. Scientists at GFDL, URI, and EMC collaborated to transfer key components of the GFDL model to the NWS new Hurricane Weather Research and Forecasting Model (HWRF) that became operational in 2007. The purpose of the article is to highlight the critical role of these collaborations. It is hoped that the experiences of the authors will serve as an example of how such collaboration can benefit the nation with improved weather guidance products.

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Robert W. Burpee
,
James L. Franklin
,
Stephen J. Lord
,
Robert E. Tuleya
, and
Sim D. Aberson

Since 1982, the Hurricane Research Division (HRD) has conducted a series of experiments with research aircraft to enhance the number of observations in the environment and the core of hurricanes threatening the United States. During these experiments, the National Oceanic and Atmospheric Administration WP-3D aircraft crews release Omega dropwindsondes (ODWs) at 15–20-min intervals along the flight track to obtain profiles of wind, temperature, and humidity between flight level and the sea surface. Data from the ODWs are transmitted back to the aircraft and then sent via satellite to the Tropical Prediction Center and the National Centers for Environmental Prediction (NCEP), where the observations become part of the operational database.

This paper tests the hypothesis that additional observations improve the objective track forecast models that provide operational guidance to the hurricane forecasters. The testing evaluates differences in forecast tracks from models run with and without the ODW data in a research mode at HRD, NCEP, and the Geophysical Fluid Dynamics Laboratory. The middle- and lower-tropospheric ODW data produce statistically significant reductions in 12–60-h mean forecast errors. The error reductions, which range from 16% to 30%, are at least as large as the accumulated improvement in operational forecasts achieved over the last 20–25 years. This breakthrough provides strong experimental evidence that more comprehensive observations in the hurricane environment and core will lead to immediate improvements in operational forecast guidance.

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Robert W. Burpee
,
Sim D. Aberson
,
Peter G. Black
,
Mark DeMaria
,
James L. Franklin
,
Joseph S. Griffin
,
Samuel H. Houston
,
John Kaplan
,
Stephen J. Lord
,
Frank D. Marks Jr.
,
Mark D. Powell
, and
Hugh E. Willoughby

The Hurricane Research Division (HRD) is NOAA's primary component for research on tropical cyclones. In accomplishing research goals, many staff members have developed analysis procedures and forecast models that not only help improve the understanding of hurricane structure, motion, and intensity change, but also provide operational support for forecasters at the National Hurricane Center (NHC). During the 1993 hurricane season, HRD demonstrated three important real-time capabilities for the first time. These achievements included the successful transmission of a series of color radar reflectivity images from the NOAA research aircraft to NHC, the operational availability of objective mesoscale streamline and isotach analyses of a hurricane surface wind field, and the transition of the experimental dropwindsonde program on the periphery of hurricanes to a technology capable of supporting operational requirements. Examples of these and other real-time capabilities are presented for Hurricane Emily.

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Richard Rotunno
,
Leonard J. Pietrafesa
,
John S. Allen
,
Bradley R. Colman
,
Clive M. Dorman
,
Carl W. Kreitzberg
,
Stephen J. Lord
,
Miles G. McPhee
,
George L. Mellor
,
Christopher N. K. Mooers
,
Pearn P. Niiler
,
Roger A. Pielke Sr.
,
Mark D. Powell
,
David P. Rogers
,
James D. Smith
, and
Lian Xie

U.S. Weather Research Program (USWRP) prospectus development teams (PDTs) are small groups of scientists that are convened by the USWRP lead scientist on a one-time basis to discuss critical issues and to provide advice related to future directions of the program. PDTs are a principal source of information for the Science Advisory Committee, which is a standing committee charged with the duty of making recommendations to the Program Office based upon overall program objectives. PDT-1 focused on theoretical issues, and PDT-2 on observational issues; PDT-3 is the first of several to focus on more specialized topics. PDT-3 was convened to identify forecasting problems related to U.S. coastal weather and oceanic conditions, and to suggest likely solution strategies.

There were several overriding themes that emerged from the discussion. First, the lack of data in and over critical regions of the ocean, particularly in the atmospheric boundary layer, and the upper-ocean mixed layer were identified as major impediments to coastal weather prediction. Strategies for data collection and dissemination, as well as new instrument implementation, were discussed. Second, fundamental knowledge of air–sea fluxes and boundary layer structure in situations where there is significant mesoscale variability in the atmosphere and ocean is needed. Companion field studies and numerical prediction experiments were discussed. Third, research prognostic models suggest that future operational forecast models pertaining to coastal weather will be high resolution and site specific, and will properly treat effects of local coastal geography, orography, and ocean state. The view was expressed that the exploration of coupled air-sea models of the coastal zone would be a particularly fruitful area of research. PDT-3 felt that forecasts of land-impacting tropical cyclones, Great Lakes-affected weather, and coastal cyclogenesis, in particular, would benefit from such coordinated modeling and field efforts. Fourth, forecasting for Arctic coastal zones is limited by our understanding of how sea ice forms. The importance of understanding air-sea fluxes and boundary layers in the presence of ice formation was discussed. Finally, coastal flash flood forecasting via hydrologic models is limited by the present accuracy of measured and predicted precipitation and storm surge events. Strategies for better ways to improve the latter were discussed.

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