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Since October 2013 a convective-scale weather prediction model has been used operationally to provide short-term forecasts covering large parts of the Nordic region. The model is now operated by a bilateral cooperative effort [Meteorological Cooperation on Operational Numerical Weather Prediction (MetCoOp)] between the Norwegian Meteorological Institute and the Swedish Meteorological and Hydrological Institute. The core of the model is based on the convection-permitting Applications of Research to Operations at Mesoscale (AROME) model developed by Météo-France. In this paper the specific modifications and updates that have been made to suit advanced high-resolution weather forecasts over the Nordic regions are described. This includes modifications in the surface drag description, microphysics, snow assimilation, as well as an update of the ecosystem and surface parameter description. Novel observation types are introduced in the operational runs, including ground-based Global Navigation Satellite System (GNSS) observations and radar reflectivity data from the Norwegian and Swedish radar networks. After almost two years’ worth of experience with the AROME-MetCoOp model, the model’s sensitivities to the use of specific parameterization settings are characterized and the forecast skills demonstrating the benefit as compared with the global European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (ECMWF-IFS) are evaluated. Furthermore, case studies are provided to demonstrate the ability of the model to capture extreme precipitation and wind events.

A global deterministic wave prediction system (GDWPS) is used to improve regional forecasts of waves off the Canadian coastline and help support the practice of safe marine activities in Canadian waters. The wave model has a grid spacing of ¼° with spectral resolution of 36 frequency bins and 36 directional bins. The wave model is driven with hourly 10-m winds generated by the operational global atmospheric prediction system. Ice conditions are updated every three hours using the ice concentration forecasts generated by the Global Ice–Ocean Prediction System. Wave forecasts are evaluated over two periods from 15 August to 31 October 2014 and from 15 December 2014 to 28 February 2015, as well as over select cases during the fall of 2012. The global system is shown to improve wave forecast skill over regions where forecasts were previously produced using limited-area models only. The usefulness of a global expansion is demonstrated for large swell events affecting the northeast Pacific. The first validation of a Canadian operational wave forecast system in the Arctic is presented. Improvements in the representation of forecast wave fields associated with tropical cyclones are also demonstrated. Finally, the GDWPS is shown to result in gains of at least 12 h of lead time.

Navy Operational Global Atmospheric Prediction System (NOGAPS) analysis and operational forecasts are evaluated against the Interim ECMWF Re-Analysis (ERA-Interim; ERAI) and satellite data, and compared with the Global Forecast System (GFS) analysis and forecasts, using both performance- and physics-based metrics. The NOGAPS analysis captures realistic Madden–Julian oscillation (MJO) signals in the dynamic fields and the low-level premoistening leading to active convection, but the MJO signals in the relative humidity (RH) and diabatic heating rate (Q1) fields are weaker than those in the ERAI or the GFS analysis. The NOGAPS forecasts, similar to the GFS forecasts, have relatively low prediction skill for the MJO when the MJO initiates over the Indian Ocean and when active convection is over the Maritime Continent. The NOGAPS short-term precipitation forecasts are broadly consistent with the Climate Prediction Center (CPC) morphing technique (CMORPH) precipitation results with regionally quantitative differences. Further evaluation of the precipitation and column water vapor (CWV) indicates that heavy precipitation develops too early in the NOGAPS forecasts in terms of the CWV, and the NOGAPS forecasts show a dry bias in the CWV increasing with forecast lead time. The NOGAPS underpredicts light and moderate-to-heavy precipitation but overpredicts extremely heavy rainfall. The vertical profiles of RH and Q1 reveal a dry bias within the marine boundary layer and a moist bias above. The shallow heating mode is found to be missing for CWV < 50 mm in the NOGAPS forecasts. The diabatic heating biases are associated with weaker trade winds, weaker Hadley and Walker circulations over the Pacific, and weaker cross-equatorial flow over the Indian Ocean in the NOGAPS forecasts.

Tropical cyclone (TC) forecasts rely heavily on output from global numerical models. While considerable research has investigated the skill of various models with respect to track and intensity, few studies have considered how well global models forecast TC genesis in the North Atlantic basin. This paper analyzes TC genesis forecasts from five global models [Environment Canada's Global Environment Multiscale Model (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF) global model, the Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Met Office global model (UKMET)] over several seasons in the North Atlantic basin. Identifying TCs in the model is based on a combination of methods used previously in the literature and newly defined objective criteria. All model-indicated TCs are classified as a hit, false alarm, early genesis, or late genesis event. Missed events also are considered. Results show that the models' ability to predict TC genesis varies in time and space. Conditional probabilities when a model predicts genesis and more traditional performance metrics (e.g., critical success index) are calculated. The models are ranked among each other, and results show that the best-performing model varies from year to year. A spatial analysis of each model identifies preferred regions for genesis, and a temporal analysis indicates that model performance expectedly decreases as forecast hour (lead time) increases. Consensus forecasts show that the probability of genesis noticeably increases when multiple models predict the same genesis event. Overall, this study provides a climatology of objectively identified TC genesis forecasts in global models. The resulting verification statistics can be used operationally to help refine deterministic and probabilistic TC genesis forecasts and potentially improve the models examined.

This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

This study is Part II of the effort to improve the forecasting of sudden stratospheric warming (SSW) events by using a version of the Navy Operational Global Atmospheric Prediction System (NOGAPS) that covers the full stratosphere. In Part I, extended-range (3 week) hindcast experiments (without data assimilation) for the January 2009 Arctic major SSW were performed using NOGAPS with a unified orographic drag parameterization that consists of the schemes employed by Webster et al., as well as Kim and Arakawa and Kim and Doyle. Part I demonstrated that the model with upgraded middle-atmospheric orographic drag physics better forecasts the magnitude and evolution of the SSW and better simulates the trend of the Arctic Oscillation (AO) index. In this study (Part II), a series of 5-day hindcast experiments is performed with cycling data assimilation using the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR), a four-dimensional variational data assimilation (4DVAR) system. Further efforts are made to improve the hindcasting of SSW by improving the satellite radiance bias correction process that strongly affects the data assimilation. The innovation (observation minus background) limit is optimally determined to reduce the rejection of useful radiance data. It is found that when the innovation limit is properly set, both the analysis and forecast of the SSW event can be improved, and that the orographic drag helps improve the SSW forecast.

A very strong Arctic major sudden stratospheric warming (SSW) event occurred in late January 2009. The stratospheric temperature climbed abruptly and the zonal winds reversed direction, completely splitting the polar stratospheric vortex. A hindcast of this event is attempted by using the Navy Operational Global Atmospheric Prediction System (NOGAPS), which includes the full stratosphere with its top at around 65 km. As Part I of this study, extended-range (3 week) forecast experiments are performed using NOGAPS without the aid of data assimilation. A unified parameterization of orographic drag is designed by combining two parameterization schemes; one by Webster et al., and the other by Kim and Arakawa and Kim and Doyle. With the new unified orographic drag scheme implemented, NOGAPS is able to reproduce the salient features of this Arctic SSW event owing to enhanced planetary wave activity induced by more comprehensive subgrid-scale orographic drag processes. The impact of the SSW on the tropospheric circulation is also investigated in view of the Arctic Oscillation (AO) index, which calculated using 1000-hPa geopotential height. The NOGAPS with upgraded orographic drag physics better simulates the trend of the AO index as verified by the Met Office analysis, demonstrating its improved stratosphere–troposphere coupling. It is argued that the new model is more suitable for forecasting SSW events in the future and can serve as a tool for studying various stratospheric phenomena.

Part I of this two-part paper examined the satellite-derived rainfall accumulation and rain potential history of Hurricanes Isidore and Lili (2002). This paper (Part II) uses analyses from the Navy Operational Global Atmospheric Prediction System (NOGAPS) to examine the water budget and environmental parameters and their relationship to the precipitation for these two storms. Factors other than storm size are found to account for large volumetric differences in storm total rainfall between Lili and Isidore. It is found that the horizontal moisture convergence was crucial to the initiation and maintenance of Isidore’s intense rainfall before and during its landfall. When the storm was over the ocean, the ocean moisture flux (evaporation) was the second dominant term among the moisture sources that contribute to precipitation. During Isidore’s life history, the strong horizontal moisture flux convergence corresponded to the large storm total precipitable water. The large difference in budget-derived stored cloud ice and liquid water between Isidore and Lili is corroborated from Tropical Rainfall Measuring Mission (TRMM) measurements. During Isidore’s landfall, the decrease in environmental water vapor contributed to rainfall in a very small amount. These results indicate the importance of the environmental precipitable water and moisture convergence and ocean surface moisture flux in generating Isidore’s large rainfall volume and inland flooding as compared with Lili’s water budget history. Both the moisture convergence and ocean flux were small for Lili.

Starting from 2003, a new typhoon surveillance program, Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR), was launched. During 2004, 10 missions for eight typhoons were conducted successfully with 155 dropwindsondes deployed. In this study, the impact of these dropwindsonde data on tropical cyclone track forecasts has been evaluated with five models (four operational and one research models). All models, except the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model, show the positive impact that the dropwindsonde data have on tropical cyclone track forecasts. During the first 72 h, the mean track error reductions in the National Centers for Environmental Prediction’s (NCEP) Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS) of the Fleet Numerical Meteorology and Oceanography Center (FNMOC), and the Japanese Meteorological Agency (JMA) Global Spectral Model (GSM) are 14%, 14%, and 19%, respectively. The track error reduction in the Weather Research and Forecasting (WRF) model, in which the initial conditions are directly interpolated from the operational GFS forecast, is 16%. However, the mean track improvement in the GFDL model is a statistically insignificant 3%. The 72-h-average track error reduction from the ensemble mean of the above three global models is 22%, which is consistent with the track forecast improvement in Atlantic tropical cyclones from surveillance missions. In all, despite the fact that the impact of the dropwindsonde data is not statistically significant due to the limited number of DOTSTAR cases in 2004, the overall added value of the dropwindsonde data in improving typhoon track forecasts over the western North Pacific is encouraging. Further progress in the targeted observations of the dropwindsonde surveillances and satellite data, and in the modeling and data assimilation system, is expected to lead to even greater improvement in tropical cyclone track forecasts.

Because the Joint Typhoon Warning Center (JTWC) has only four dynamical models for guidance in making 96- and 120-h track forecasts, an opportunity exists for improving the consensus forecast by the proper removal of a likely erroneous forecast to form a selective consensus (SCON). Forecast fields from all four models [the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS), the U.S. Navy version of the Geophysical Fluid Dynamics Laboratory model (GFDN), the Met Office (UKMO) model, and the Global Forecast System (GFS)] were available during the 2005 western North Pacific season to evaluate for the first time the error mechanisms leading to large track errors. As shown previously for the NOGAPS and GFDN models during the 2004 season, error sources related to the midlatitude circulations accounted for about 90% of all large 120-h track errors by all four models during the 2005 season. This dominance of midlatitude-related error source is a major shift from the 72-h errors, which include more errors related to tropical circulations. In the GFS model, 95% of the large errors occurred because of an incorrect depiction of the vertical structure of the tropical cyclone. A systematic error in the GFDN model was identified in which a false anticyclogenesis was predicted downstream of the Tibetan Plateau, which accounted for over 50% of the large GFDN track errors. The consensus spread versus consensus error relationship is examined to isolate those 20%–25% of cases with large spreads and large errors that are candidates for forming an SCON. If the model tracks that contributed to the large errors are eliminated, the average improvement of the SCON forecasts relative to the nonselective consensus is 222 (239) n mi during 2005 (2004), and the corresponding average improvement relative to the JTWC forecasts is 382 (203) n mi. This application of SCON is considered the potential “forecastability” in that it represents the optimum use of the present numerical guidance for consensus forecasting.

The Joint Typhoon Warning Center has been issuing 96- and 120-h track forecasts since May 2003. It uses four dynamical models that provide guidance at these forecast intervals and relies heavily on a consensus of these four models in producing the official forecast. Whereas each of the models has skill, each occasionally has large errors. The objective of this study is to provide a characterization of these errors in the western North Pacific during 2004 for two of the four models: the Navy Operational Global Atmospheric Prediction System (NOGAPS) and the U.S. Navy’s version of the Geophysical Fluid Dynamics Laboratory model (GFDN). All 96- and 120-h track errors greater than 400 and 500 n mi, respectively, are examined following the approach developed recently by Carr and Elsberry. All of these large-error cases can be attributed to the models not properly representing the physical processes known to control tropical cyclone motion, which were classified in a series of conceptual models by Carr and Elsberry for either tropical-related or midlatitude-related mechanisms. For those large-error cases where an error mechanism could be established, midlatitude influences caused 83% (85%) of the NOGAPS (GFDN) errors. The most common tropical influence is an excessive direct cyclone interaction in which the tropical cyclone track is erroneously affected by an adjacent cyclone. The most common midlatitude-related errors in the NOGAPS tracks arise from an erroneous prediction of the environmental flow dominated by a ridge in the midlatitudes. Errors in the GFDN tracks are caused by both ridge-dominated and trough-dominated environmental flows in the midlatitudes. Case studies illustrating the key error mechanisms are provided. An ability to confidently identify these error mechanisms and thereby eliminate likely erroneous tracks from the consensus would improve the accuracy of 96- and 120-h track forecasts.

The Weber barotropic model (WBAR) was originally developed using predefined 850–200-hPa analyses and forecasts from the NCEP Global Forecasting System. The WBAR tropical cyclone (TC) track forecast performance was found to be competitive with that of more complex numerical weather prediction models in the North Atlantic. As a result, WBAR was revised to incorporate the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecasts for use at the Joint Typhoon Warning Center (JTWC). The model was also modified to analyze its own storm-dependent deep-layer mean fields from standard NOGAPS pressure levels. Since its operational installation at the JTWC in May 2003, WBAR TC track forecast performance has been competitive with the performance of other more complex NWP models in the western North Pacific. Its TC track forecast performance combined with its high availability rate (93%–95%) has warranted its inclusion in the JTWC operational consensus. The impact of WBAR on consensus TC track forecast performance has been positive and WBAR has added to the consensus forecast availability (i.e., having at least two models to provide a consensus forecast).

The current version of the Statistical Typhoon Intensity Prediction Scheme (STIPS) used operationally at the Joint Typhoon Warning Center (JTWC) to provide 12-hourly tropical cyclone intensity guidance through day 5 is documented. STIPS is a multiple linear regression model. It was developed using a “perfect prog” assumption and has a statistical–dynamical framework, which utilizes environmental information obtained from Navy Operational Global Analysis and Prediction System (NOGAPS) analyses and the JTWC historical best track for development. NOGAPS forecast fields are used in real time. A separate version of the model (decay-STIPS) is produced that accounts for the effects of landfall by using an empirical inland decay model. Despite their simplicity, STIPS and decay-STIPS produce skillful intensity forecasts through 4 days, based on a 48-storm verification (July 2003–October 2004). Details of this model’s development and operational performance are presented.

A set of criteria is developed to identify tropical cyclone (TC) formations in the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecast fields. Then the NOGAPS forecasts of TC formations from 1997 to 1999 are verified relative to a formation time defined to be the first warning issued by the Joint Typhoon Warning Center. During these three years, the spatial distributions of TC formations were strongly affected by an El Nino–Southern Oscillation event. The successful NOGAPS predictions of formation within a maximum separation threshold of 4° latitude are about 70%–80% for 24-h forecasts, and drop to about 20%–30% for 120-h forecasts. The success rate is higher for formations in the South China Sea and between 160°E and 180° but is generally lower between 120° and 160°E. The composite 850-hPa large-scale flow for the formations between 120° and 160°E is similar to a monsoon confluence region with marked cross-equatorial flow. Therefore, it is concluded that the skil...

All highly erroneous (>300 n mi or 555 km at 72 h) Navy Operational Global Atmospheric Prediction System (NOGAPS) and U.S. Navy version of the Geophysical Fluid Dynamics Laboratory model (GFDN) tropical cyclone track forecasts in the western North Pacific during 1997 are examined. Responsible error mechanisms are described by conceptual models that are all related to known tropical cyclone motion processes that are being misrepresented in the dynamical models. Error mechanisms that predominantly occur while the tropical cyclone is still in the Tropics are described in this paper, and those errors that are more related to midlatitude circulations are addressed in a companion paper. Of the 69 NOGAPS large-error cases, 39 were attributed to excessive direct cyclone interaction (E-DCI), 12 cases of excessive ridge modification by the tropical cyclone (E-RMT), and 10 cases of excessive reverse trough formation (E-RTF). Of the 50 GFDN large-error cases, 31 were E-DCI, and only two E-RMT and two E-RTF c...

All highly erroneous (>300 n mi or 555 km at 72 h) Navy Operational Global Atmospheric Prediction System (NOGAPS) and U.S. Navy version of the Geophysical Fluid Dynamics Laboratory model (GFDN) tropical cyclone track forecasts in the western North Pacific during 1997 are examined. Error mechanisms that are more related to midlatitude circulations are described in this paper and those errors that predominantly occur while the tropical cyclone (TC) is still in the Tropics are addressed in a companion paper. Responsible error mechanisms are described by conceptual models that are all related to known tropical cyclone motion processes that are being misrepresented in the dynamical models. As in the companion paper, characteristics and symptoms in the forecast tracks and model fields that accompany these frequently recurring error mechanisms are documented and illustrative case studies are presented. Whereas 21 GFDN forecasts were degraded by an improper prediction of a midlatitude system evolution, o...

Extratropical transition (ET) in the western North Pacific is defined here in terms of two stages: transformation, in which the tropical cyclone evolves into a baroclinic storm; and reintensification, where the transformed storm then deepens as an extratropical cyclone. In this study, 30 ET cases occurring during 1 June–31 October 1994–98 are reviewed using Navy Operational Global Atmospheric Prediction System analyses; hourly geostationary visible, infrared, and water vapor imagery; and microwave imagery. A brief climatology based on these cases is presented for the transformation stage and the subsequent cyclone characteristics of the reintensification stage. A three-dimensional conceptual model of the transformation stage of ET in the western North Pacific Ocean is proposed that describes how virtually all 30 cases evolved into an incipient, baroclinic low. The three-step evolution of the transformation of Typhoon (TY) David (September 1997) is described as a prototypical example. Four importa...

The Marine Meteorology Division of the Naval Research Laboratory (NRL), assisted by the Fleet Numerical Meteorology and Oceanography Center, has performed global and mesoscale reanalyses to support the study of Gulf War illness. Realistic and quantitatively accurate atmospheric conditions are needed to drive dispersion models that can predict the transport and dispersion of chemical agents that may have affected U.S. and other coalition troops in the hours and days following the demolition of chemical weapons at Khamisiyah, Iraq, at approximately 1315 UTC 10 March 1991. The reanalysis was conducted with the navy’s global and mesoscale analysis and prediction systems: the Navy Operational Global Atmospheric Prediction System and the NRL Coupled Ocean–Atmosphere Mesoscale Prediction System. A comprehensive set of observations has been collected and used in the reanalysis, including unclassified and declassified surface reports, ship and buoy reports, observations from pibal and rawinsonde, and retr...

In June 1990, the assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System (NOGAPS) was initiated at Fleet Numerical Oceanography Center (FNOC). These observations are derived directly from the information contained in the tropical cyclone warnings issued by the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center. This paper describes these synthetic observations, the evolution of their use at FNOC, and the details of their assimilation into NOGAPS. The results of a comprehensive evaluation of the 1991 NOGAPS tropical cyclone forecast performance in the western North Pacific are presented. NOGAPS analysis and forecast position errors were determined for all tropical circulations of tropical storm strength or greater. It was found that, after the assimilation of synthetic observations, the NOGAPS spectral forecast model consistently maintained the tropical circulations as evidenced by detection percentages of 96%, 90% ...

The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones.

Seventy-two-hour forecasts of sea level cyclones from the Navy Operational Global Atmospheric Prediction System are examined. Cyclones that formed over the North Pacific region of maximum cyclogenesis frequency are included for study. The analysis is oriented to assist the forecaster in evaluating the numerical model guidance by emphasizing verification of operationally oriented factors (i.e., cyclogenesis, explosive deepening). Initially, systematic errors in forecast intensities and positions are identified. Maximum underforecasting errors (forecast central pressure higher than actual central pressure) occur over the central North Pacific region of climatological maximum cyclone deepening. Maximum overforecasting errors (forecast central pressure lower than the actual central pressure) occur over the region of climatological cyclone dissipation. Maximum position errors also occur over the central North Pacific region of climatological maximum deepening. These systematic error distributions indi...

The Navy Operational Global Atmospheric Prediction System (NOGAPS) has proven itself to be competitive with any of the large forecast models run by the large operational forecast centers around the world. The navy depends on NOGAPS for an astonishingly wide range of applications, from ballistic winds in the stratosphere to air-sea fluxes to drive ocean general circulation models. Users of these applications will benefit from a better understanding of how a system such as NOGAPS is developed, what physical assumptions and compromises have been made, and what they can reasonably expect in the future as the system continues to evolve. The discussions will be equally relevant for users of products from other large forecast centers, e.g., National Meteorological Center, European Centre for Medium-Range Weather Forecasts. There is little difference in the scientific basis of the models and the development methodologies used for their development. However, the operational priorities of each center and t...

In January of 1988, significant upgrades were made to the Navy Operational Global Atmospheric Prediction System (NOGAPS). Among these improvements was the implementation of a multivariate optimum interpolation analysis scheme. Since that time, this analysis scheme has been improved and expanded to satisfy almost all of the navy's atmospheric analysis requirements. In this paper, we describe the global database available for analysis, the techniques currently used to produce the NOGAPS analyzed fields, and the modification required for other applications.

At the Fleet Numerical Oceanography Center, two computer models, the Navy Operational Global Atmospheric Prediction System, NOGAPS, and the Navy Operational Regional Atmospheric Prediction System, NORAPS, generate a twice-daily suite of atmospheric analyses and forecasts. NOGAPS is the driving force behind many of the center's products and has become a complex, highly structured system designed to run automatically. The execution of NOGAPS and NORAPS within the operational schedule is described. The systems consist of 1) automated data processing and quality control, 2) a multivariate optimum interpolation analysis, 3) initialization and forecast, and 4) output. The data-processing step is shared between the two systems.

The environment is a critical factor to the safe, effective operations of the U.S. Navy. In support of our global peacekeeping mission, the fleet must have timely and accurate forecasts of environmental conditions from the top of the stratosphere to the bottom of the ocean, 24 hours a day, 7 days a week. The hub of this support is the Fleet Numerical Oceanography Center (FLENUMOCEANCEN) located at Monterey, California. As the navy's primary operational processing center for global oceanographic and atmospheric analyses and predictions, FLENUMOCEANCEN provides numerical environmental products to meet the needs of the navy, as well as a full spectrum of oceanographic products to support the Department of Defense. All products are based on the center's extensive global atmospheric and oceanographic database, sophisticated long-range forecast models, and tailored tactical decision aids in support of specific weapons and sensor systems. This paper briefly describes FLENUMOCEANCEN's data sources, compu...

The first modern numerical weather prediction (NWP) models were developed for the computer that was announced in 1932 at the Institute for Advanced Study, in Princeton, New Jersey. Within 3 yr three agencies of the United States Government jointly created a numerical weather prediction service, but it was quickly discovered that current models had very serious defects. After considerable research, the first operationally effective model was achieved in 1958—a barotropic model covering most of the Northern Hemisphere. Over the years, models have evolved through multilevel filtered equation models and several primitive equation models. Analysis and data assimilation systems necessary for timeliness were also developed, and have likewise evolved. The result has been a revolution in weather forecasting.

The production of interpretive weather element forecasts from dynamical model output variables is now an integral part of the centralized guidance systems of weather services throughout the world. The statistical forecasting system in the United States probably generates the most extensive suite of operational products, although other nations including Australia, Canada, France, Italy, The Netherlands, and the United Kingdom also routinely provide guidance for many weather elements and locations. The United States' statistical guidance system has evolved throughout the past 20 yr. The two principal formulation methods that have been employed are the model output statistics (MOS) and “perfect prog” approaches. These techniques have advantages and disadvantages that influence both aggregate and specific day-to-day performance characteristics of the associated weather element forecasts. Verification results indicate that forecasts from both statistical approaches provide useful guidance for most wea...