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The National Centers for Environmental Prediction (NCEP), Air Force Weather Agency (AFWA), Fleet Numerical Meteorology and Oceanography Center (FNMOC), National Weather Association, and American Meteorological Society (AMS) cosponsored a “Symposium on the 50th Anniversary of Operational Numerical Weather Prediction,” on 14–17 June 2004 at the University of Maryland, College Park in College Park, Maryland. Operational numerical weather prediction (NWP) in the United States started with the Joint Numerical Weather Prediction Unit (JNWPU) on 1 July 1954, staffed by members of the U.S. Weather Bureau, the U.S. Air Force and the U.S. Navy. The origins of NCEP, AFWA, and FNMOC can all be traced to the JNWPU. The symposium celebrated the pioneering developments in NWP and the remarkable improvements in forecast skill and support of the nation's economy, well being, and national defense achieved over the last 50 years. This essay was inspired by the presentations from that symposium.

We appreciate the clarification of prior work of Leslie and Bennett, provided by the authors in their comments on our article. If our references to their work led to misinterpretation, we apologize for being too brief in our discussion. Reviewing the format of their work on systematic error correction is a useful contribution to research in this area. DOI: 10.1034/j.1600-0870.1992.t01-2-00007.x

A comprehensive hydrostatic quality control (CHQC) procedure for rawinsonde heights and temperatures was implemented into operational use at the National Meteorological Center (NMC) in December 1988. The CHQC uses a sophisticated decision-making algorithm to detect so-called rough errors in rawinsonde observations and to confidently correct many of them. Statistics gathered over a two-year period are presented to provide information on the frequency, geographical distribution, and origin of these errors. During this period, approximately 7% of the rawinsonde reports received at the NMC contained a hydrostatically detectable error. The number of errors has stayed relatively constant over the two-year period. The geographic distribution of the errors is uneven, with most of them originating in countries where many of the steps involved in computing and coding the reports are performed manually. Other characteristics as well indicate that almost all problems that are detected by the CHQC are caused ...

Results of a thorough study of the correlation structure of observation-minus-forecast increments for mandatory pressure level radiosonde observations of zonal and meridional wind components and geopotential, differenced with NMC's 6-hour global forecasts, are reported. Our work focused on the selection of a representation for spatial lag-correlations to be used in updating the multivariate statistical objective analysis algorithm of the global data assimilation system, with attention given to regional and seasonal dependence of the correlation structure, and on the degree to which the increments are in the same geostrophic balance as the signal and forecast fields individually. We compare the performance of several candidates for representing autocorrelations of geopotential increments, on the one hand, and the auto- and cross-correlations of the wind component increments, on the other, for five mandatory pressure levels, for four regions of the Northern Hemisphere and for the Southern Hemispher...

We have found spatial and temporal coherencies in the departures of short-range-forecasts from observed and analysed geopotential fields, which can be used diagnostically and as the basis for adjustment of forecast products. We identify characteristics of the differences between forecast and observed, and forecast and analysed values, and we demonstrate the significant impact on forecast accuracy which may be gained through the routine estimation and removal of these discrepancies. The removal of these discrepancies in the data assimilation step of the forecast cycle was found to have little impact, in contrast with the effect of direct correction of forecast products in conjunction with post processing. DOI: 10.1034/j.1600-0870.1990.00001.x

Data collected from aircraft equipped with AIDS (Aircraft Integrated Data System) instrumentation during the Global Weather Experiment year of 1979 are used to estimate the observational error of winds at flight level from this and other aircraft automated wind-reporting systems. Structure functions are computed from reports that are paired using specific criteria. The value of this function extrapolated to zero separation distance is an estimate of twice the random measurement-error variance of the AIDS-measured winds. Component-wind errors computed in this way range from 2.1 to 3.1 m · s−1 for the two months of data examined, January and August 1979. Observational error, specified in optimum-interpolation analyses to allow the analysis to distinguish among observations of differing quality, is composed of both measurement error and the error of unrepresentativeness. The latter type of error is a function of the resolvable scale of the analysis-prediction system. The structure function, which measures the variability of a field as a function of separation distance, includes both of these types of error. If the resolvable scale of an analysis procedure is known, an estimate of the observational error can be computed from the structure function at that particular distance. An observational error of 5.3 m · s−1 was computed for the u and v wind components for a sample resolvable scale of 300 km. The errors computed from the structure functions are compared to colocation statistics from radiosondes. The errors associated with automated wind reports are found to compare favorably with those estimated for radiosonde winds at that level.

A number of changes were made to the National Meteorological Center global data assimilation system (GDAS) during 1982 and 1983. The most significant of these changes was the replacement of the quasi-univariate, sigma-coordinate optimum interpolation analysis procedure by a version that performs a fully multivariate analysis on mandatory pressure surfaces. The new analysis technique is described in some detail. The impact of this and other changes made during 1982 and 1983 on the performance of the GDAS is evaluated.