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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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Naomi Surgi, Hua-Lu Pan, and Stephen J. Lord


An evaluation of the performance of the National Centers for Environmental Prediction Medium-Range Forecast Model was made for the large-scale tropical forecasts and hurricane track forecasts during the 1995 hurricane season. The assessment of the model was based on changes to the deep convection and planetary boundary layer parameterizations to determine their impact on some of the model deficiencies identified during previous hurricane seasons. Some of the deficiencies in the hurricane forecasts included a weakening of the storm circulation with time that seriously degraded the track forecasts. In the larger-scale forecasts, an upper-level easterly wind bias was identified in association with the failure of the model to maintain the midoceanic upper-tropical upper-tropospheric trough.

An overall modest improvement is shown in the large-scale upper-level tropical winds from root-mean-square-error calculations. Within a diagnostic framework, an improved simulation of the midoceanic tropical trough has contributed to a better forecast of the upper-level westerly flow. In the hurricane forecasts, enhanced diabatic heating in the model vortex has significantly improved the vertical structure of the forecast storm. This is shown to contribute to a substantial improvement in the track forecasts.

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James L. Franklin, Katsuyuki V. Ooyama, and Stephen J. Lord


A one-dimensional local spline smoothing technique is applied to Omega navigational signals for the purpose of windfinding. Wind profiles so produced depend largely on two parameters of the smoothing procedure: the nodal spacing, which determines the smallest resolvable scale, and a filtering wavelength, which produces the necessary smoothing of the phase data, and prevents representational distortion of any power from the unresolved scales. Phase “noise” from stationary test sondes is superimposed on synthetic Omega signals to compare wind profiles obtained with this new procedure with profiles computed using other techniques.

Is it shown that the effect of aircraft maneuvers on Omega wind accuracy is not completely removed by the normal practice of evaluating all phase derivatives at a common time. Additional improvements in accuracy of 2–3 m s−1 can be obtained by a “rate-aiding” technique using aircraft navigational data.

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John C. Derber, David F. Parrish, and Stephen J. Lord


At the National Meteorological Center (NMC), a new analysis system was implemented into the operational Global Data Assimilation System on 25 June 1991. This analysis system is referred to as Spectral Statistical Interpolation (SSI) because the spectral coefficients used in the NMC spectral model are analyzed directly using the same basic equations as statistical (optimum) interpolation. The major differences between the SSI analysis system and the conventional optimum interpolation (OI) analysis system previously used operationally at NMC are:

  • –The analysis variables are closely related to the coefficients of the NMC spectral model.

  • –Temperature observations are used, not heights as in the previous procedure. As a result, aircraft temperatures are being used for the first time at NMC.

  • –Nonstandard observations, such as satellite estimates of total precipitable water and ocean-surface wind speeds, can be easily included.

  • –No data selection is necessary. All observations are used simultaneously.

  • –The dynamical constraint between the wind and mass fields is more realistic and applied globally.

  • –Model initialization has been eliminated. The analysis is used directly as the forecast model initial condition.

Extensive pre-implementation testing demonstrated that the SSI consistently produced superior analyses and forecasts when compared to the previous OI system. Improvement in skill is shown not only for the 3–5-day forecasts, but also in one-day aviation forecasts.

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James L. Franklin, Stephen J. Lord, and Frank D. Marks Jr.


Two soundings from the eye of Hurricane Gloria (1985) during a period of rapid deepening are described. The soundings were made by Omega dropwindsondes (ODWs) during research flights of the NOAA Hurricane Research Division on 24–25 September 1985. During the 4.7 hours between the two ODW drops. Gloria's minimum sea-level pressure fell from 932 to 922 mb.

The ODWs indicate substantial warming due to dry-adiabatic descent from 580 to 660 mb. Descent rates are estimated to be about 11 cm s−1. Near 500 mb, ascent is indicated. Approximately 60% of the 10 mb pressure fall is associated with thermodynamic changes below 500 mb.

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Stephen J. Lord, Winston C. Chao, and Akio Arakawa


An application of the Arakawa-Schubert (1974) cumulus parameterization to a prognostic model of the large-scale atmospheric circulations is presented. The cloud subensemble thermodynamical properties are determined from the conservation of mass, moist static energy and total water (vapor, suspended liquid water and precipitation). Algorithms for calculating the large-scale forcing and the mass flux kernel are presented. Several methods for solving the discrete version of the integral equation for the cumulus mass flux are discussed. Equations describing the cumulus feedback on the large-scale thermodynamical fields are presented.

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


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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Huge E. Willoughby, Han-Liang Jin, Stephen J. Lord, and Jacqueline M. Piotrowicz


This paper reports numerical simulations of the hurricane vortex by an axisymmetric, nonhydrostatic numerical model with 2 km maximum horizontal resolution. Moist convection is modeled explicitly using two different microphysical parameterizations. The first simulates liquid water processes only, whereas the second includes ice processes as well.

Although concentric rings of convection associated with local maxima of the tangential wind form in both versions of the model, they are much more common when ice processes are included. As they contract about the vortex center, the outer ones supplant the inner. Their contraction follows the mechanism suggested by balanced-vortex models. Some of the rings appear to form through symmetric instability of the vortex, and others—particularly when ice processes are included—through interactions between precipitation-induced downdrafts and the boundary layer. Both the rings’ evolution and the detailed structure of the vortex core are similar to recent aircraft and radar observations. Among the realistic features are: outward slope of the eyewall updraft and tangential wind maximum; relative location of the updraft, wind maximum, and precipitation maximum; stratiform precipitation and mesoscale downdrafts outside the eye; and midlevel radial inflow.

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Fanglin Yang, Hua-Lu Pan, Steven K. Krueger, Shrinivas Moorthi, and Stephen J. Lord


This study evaluates the performance of the National Centers for Environmental Prediction Global Forecast System (GFS) against observations made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program at the southern Great Plains site for the years 2001–04. The spatial and temporal scales of the observations are examined to search for an optimum approach for comparing grid-mean model forecasts with single-point observations. A single-column model (SCM) based upon the GFS was also used to aid in understanding certain forecast errors. The investigation is focused on the surface energy fluxes and clouds. Results show that the overall performance of the GFS model has been improving, although certain forecast errors remain. The model overestimated the daily maximum latent heat flux by 76 W m−2 and the daily maximum surface downward solar flux by 44 W m−2, and underestimated the daily maximum sensible heat flux by 44 W m−2. The model’s surface energy balance was reached by a cancellation of errors. For clouds, the GFS was able to capture the observed evolutions of cloud systems during major synoptic events. However, on average, the model largely underestimated cloud fraction in the lower and midtroposphere, especially for daytime nonprecipitating low clouds because shallow convection in the GFS does not produce clouds. Analyses of surface radiative fluxes revealed that the diurnal cycle of the model’s surface downward longwave flux (SDLW) was not in phase with that of the ARM-observed SDLW. SCM experiments showed that this error was caused by an inaccurate scaling factor, which was a function of ground skin temperature and was used to adjust the SDLW at each model time step to that computed by the model’s longwave radiative transfer routine once every 3 h. A method has been proposed to correct this error in the operational forecast model. It was also noticed that the SDLW biases changed from mostly negative in 2003 to slightly positive in 2004. This change was traced back to errors in the near-surface air temperature. In addition, the SDLW simulated with the newly implemented Rapid Radiative Transfer Model longwave routine in the GFS is usually 5–10 W m−2 larger than that simulated with the previous routine. The forecasts of surface downward shortwave flux (SDSW) were relatively accurate under clear-sky conditions. The errors in SDSW were primarily caused by inaccurate forecasts of cloud properties. Results from this study can be used as guidance for the further development of the GFS.

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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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