Operational Global Atmospheric Prediction System Research Articles

A three-component decomposition is applied to global analysis data to show the existence of a beta gyre, which causes Tropical Cyclone (TC) to drift from a large-scale environmental steering current. Analyses from the Global Data Assimilation and Prediction System (GDAPS) of the Korea Meteorological Administration (KMA), the Global Forecast System (GFS) of NCEP, and the Navy Operational Global Atmospheric Prediction System (NOGAPS) are used in this study.

Abstract Singular vectors (SVs) are used to study the sensitivity of 2-day forecasts of recurving tropical cyclones (TCs) in the western North Pacific to changes in the initial state. The SVs are calculated using the tangent and adjoint models of the Navy Operational Global Atmospheric Prediction System (NOGAPS) for 72 forecasts for 18 TCs in the western North Pacific during 2006. In addition to the linear SV calculation, nonlinear perturbation experiments are also performed in order to examine 1) the similarity between nonlinear and linear perturbation growth and 2) the downstream impacts over the North Pacific and North America that result from changes to the 2-day TC forecast. Both nonrecurving and recurving 2-day storm forecasts are sensitive to changes in the initial state in the near-storm environment (in an annulus approximately 500 km from the storm center). During recurvature, sensitivity develops to the northwest of the storm, usually associated with a trough moving in from the west. These upstream sensitivities can occur as far as 4000 km to the northwest of the storm, over the Asian mainland, which has implications for adaptive observations. Nonlinear perturbation experiments indicate that the linear calculations reflect case-to-case variability in actual nonlinear perturbation growth fairly well, especially when the growth is large. The nonlinear perturbations show that for recurving tropical cyclones, small initial perturbations optimized to change the 2-day TC forecast can grow and propagate downstream quickly, reaching North America in 5 days. The fastest 5-day perturbation growth is associated with recurving storm forecasts that occur when the baroclinic instability over the North Pacific is relatively large. These results suggest that nonlinear forecasts perturbed using TC SVs may have utility for predicting the downstream impact of TC forecast errors over the North Pacific and North America.

Optimizing surface winds using QuikSCAT measurements in the Mediterranean Sea during 2000–2006

Abstract The major stratospheric sudden warming (SSW) of January 2006 is examined using meteorological fields from Goddard Earth Observing System version 4 (GEOS-4) analyses and forecast fields from the Navy Operational Global Atmospheric Prediction System–Advanced Level Physics, High Altitude (NOGAPS-ALPHA). The study focuses on the upper tropospheric forcing that led to the major SSW and the vertical structure of the subtropic wave breaking near 10 hPa that moved low tropical values of potential vorticity (PV) to the pole. Results show that an eastward-propagating upper tropospheric ridge over the North Atlantic with its associated cold temperature perturbations (as manifested by high 360-K potential temperature surface perturbations) and large positive local values of meridional heat flux directly forced a change in the stratospheric polar vortex, leading to the stratospheric subtropical wave breaking and warming. Results also show that the anticyclonic development, initiated by the subtropical wave breaking and associated with the poleward advection of the low PV values, occurred over a limited altitude range of approximately 6–10 km. The authors also show that the poleward advection of this localized low-PV anomaly was associated with changes in the Eliassen–Palm (EP) flux from equatorward to poleward, suggesting an important role for Rossby wave reflection in the SSW of January 2006. Similar upper tropospheric forcing and subtropical wave breaking were found to occur prior to the major SSW of January 2003.

Abstract The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.

Abstract : Matsoukas et al. [2007] present a monthly analysis of heat fluxes in relation to heat budget in the Red and Black Seas to provide further insight for air-sea exchange processes in the small ocean basins. Components of net surface heat flux are illustrated during 1984-1995. In computing latent and sensible heat fluxes, Matsoukas et al. [2007] apply traditional bulk formulations. A heat balance method that is based on the available energy for evaporation flux is also presented to compare latent heat fluxes with those from the bulk formulations. All near-surface atmospheric variables, including wind speed at 10 m, used in the heat balance method are obtained from reanalysis of a numerical weather product (NWP). Initial input data for radiation flux calculations are at resolutions of 1.0-degrees and 2-degrees, depending on the availability. Monthly means of heat budget components are computed on the basis of monthly means of atmospheric variables during 1984-2000.

Abstract. The forecast model and three-dimensional variational data assimilation components of the Navy Operational Global Atmospheric Prediction System (NOGAPS) have each been extended into the upper stratosphere and mesosphere to form an Advanced Level Physics High Altitude (ALPHA) version of NOGAPS extending to ~100 km. This NOGAPS-ALPHA NWP prototype is used to assimilate stratospheric and mesospheric temperature data from the Microwave Limb Sounder (MLS) and the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instruments. A 60-day analysis period in January and February 2006, was chosen that includes a well documented stratospheric sudden warming. SABER and MLS temperatures indicate that the SSW caused the polar winter stratopause at ~40 km to disappear, then reform at ~80 km altitude and slowly descend during February. The NOGAPS-ALPHA analysis reproduces this observed stratospheric and mesospheric temperature structure, as well as realistic evolution of zonal winds, residual velocities, and Eliassen-Palm fluxes that aid interpretation of the vertically deep circulation and eddy flux anomalies that developed in response to this wave-breaking event. The observation minus forecast (O-F) standard deviations for MLS and SABER are ~2 K in the mid-stratosphere and increase monotonically to about 6 K in the upper mesosphere. Increasing O-F standard deviations in the mesosphere are expected due to increasing instrument error and increasing geophysical variance at small spatial scales in the forecast model. In the mid/high latitude winter regions, 10-day forecast skill is improved throughout the upper stratosphere and mesosphere when the model is initialized using the high-altitude analysis based on assimilation of both SABER and MLS data.

Through a comprehensive analysis, reliability of 10 m wind speeds is presented near the land‐sea boundaries over the global ocean. Winds from three numerical weather prediction (NWP) centers and two satellite‐based products are analyzed. NWP products are 1.875° × 1.875° National Center Environmental Prediction reanalyses, 1.125° × 1.125° European Centre for Medium‐Range Weather Forecasts 40‐year Reanalysis (ERA‐40), and 1.0° × 1.0° Navy Operational Global Atmospheric Prediction System (NOGAPS) operational product. These are compared to much finer resolution (0.25° × 0.25°) satellite winds, Quick Scatterometer (QSCAT) and Special Sensor Microwave/Imager. Large biases (e.g., >3 m s−1) may exist in NWP products near the land‐sea boundaries, because wind speeds from the uniformly gridded global fields are generally at a spatial scale too coarse to appropriately define the contrast between water and land grid points. This so‐called land contamination of ocean‐only winds varies, and typically depends on the extent of the land‐sea mask. A creeping sea‐fill methodology is introduced to reduce errors in winds. It is based on the elimination of land‐corrupted NWP grid points and replacement by adjacent, purely over‐ocean values. In comparison to winds from many moored buoys, the methodology diminishes RMS errors (from >4 m s−1to <1 m s−1) for NOGAPS and ERA‐40. The creeping sea‐fill is not advised for NCEP winds which have low contrast between land and sea points, thereby resulting in little impact from the land contamination.

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite supplemented with the Defense Meteorological Satellites Program (DMSP) microwave dataset provides accurate rain-rate estimates. Furthermore, infrared radiances from the geostationary satellites provide the possibility for mapping the diurnal change of tropical rainfall. Modeling of the phase and amplitude of the tropical rainfall is the theme of this paper. The present study utilizes a suite of global multimodels that are identical in all respects except for their cumulus parameterization algorithms. Six different cumulus parameterizations are tested in this study. These include the Florida State University (FSU) Modified Kuo Scheme (KUO), Goddard Space Flight Center (GSFC) Relaxed Arakawa–Schubert Scheme (RAS1), Naval Research Laboratory–Navy Operational Global Atmospheric Prediction System (NRL–NOGAPS) Relaxed Arakawa–Schubert Scheme (RAS2), NCEP Simplified Arakawa–Schubert Scheme (SAS), NCAR Zhang–McFarlane Scheme (ZM), and NRL–NOGAPS Emanuel Scheme (ECS). The authors carried out nearly 600 experiments with these six versions of the T170 Florida State University global spectral model. These are 5-day NWP experiments where the diurnal change datasets were archived at 3-hourly intervals. This study includes the estimation of skills of the phase and amplitudes of the diurnal rain using these member models, their ensemble mean, a multimodel superensemble, and those from a single unified model. Test results are presented for the global tropics and for some specific regions where the member models show difficulty in predicting the diurnal change of rainfall. The main contribution is the considerable improvement of the modeling of diurnal rain by deploying a multimodel superensemble and by constructing a single unified model. The authors also present a comparison of these findings on the modeling of diurnal rain from another suite of multimodels that utilized different versions of cloud radiation algorithms (instead of different cumulus parameterization schemes) toward defining the suite of multimodels. The principal result is that the superensemble does provide a future forecast for the total daily rain and for the diurnal change of rain through day 5 that is superior to forecasts provided by the best model. The training of the superensemble with good observed estimates of rain, such as those from TRMM, is necessary for such forecasts.

The Atchafalaya Bay system consists of a series of five shallow bays in southern Louisiana (U.S.A.) that are dominated by the circulation of the Atchafalaya River plume. Winter cold fronts have a significant impact on the resuspension and transport of sediments in this region, and a better understanding of the circulation during these events is absolutely necessary for determining the sediment transport patterns of the Atchafalaya Bay system and the adjacent shelf area. Understanding the circulation of this region is also crucial for environmental studies as well. This work describes the implementation of the Navy Coastal Ocean Model (NCOM), a three-dimensional numerical circulation model for tide, river, and wind-forced circulation in the Atchafalaya Bay system. The model has a cell size (Δx) of ∼800 m and is nested to a northern Gulf of Mexico model (Δx ∼5000 m), which is itself nested to the global NCOM (Δx =1/8°). Atmospheric forcing is supplied by the Navy Operational Global Atmospheric Prediction System (NOGAPS) (Δx =1°). These models are used to simulate the hydrodynamics of the Atchafalaya Bay system and Atchafalaya river plume between December 1997 and January 1998 during the passage of three winter cold fronts. The water levels, salinity, and currents predicted by NCOM are in reasonable agreement with available measurements and tide-gauge elevation data. Errors in ebb tides and wind-driven circulation are attributable to uncertainties in the bathymetry and the low spatial and temporal resolution of the NOGAPS wind fields.

Abstract Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.

Abstract The ensemble transform (ET) scheme changes forecast perturbations into analysis perturbations whose amplitudes and directions are consistent with a user-provided estimate of analysis error covariance. A practical demonstration of the ET scheme was undertaken using Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS) analysis error variance estimates and the Navy Operational Global Atmospheric Prediction System (NOGAPS) numerical weather prediction (NWP) model. It was found that the ET scheme produced forecast ensembles that were comparable to or better in a variety of measures than those produced by the Fleet Numerical and Oceanography Center (FNMOC) bred-growing modes (BGM) scheme. Also, the demonstration showed that the introduction of stochastic perturbations into the ET forecast ensembles led to a substantial improvement in the agreement between the ET and NAVDAS analysis error variances. This finding is strong evidence that even a small-sized ET ensemble is capable of obtaining good agreement between the ET and NAVDAS analysis error variances, provided that NWP model deficiencies are accounted for. Last, since the NAVDAS analysis error covariance estimate is diagonal and hence ignores multivariate correlations, it was of interest to examine the ET analysis perturbations’ spatial correlation. Tests showed that the ET analysis perturbations exhibited statistically significant, realistic multivariate correlations.

Abstract In this paper it is argued that ensemble prediction systems can be devised in such a way that physical parameterizations of subgrid-scale motions are utilized in a stochastic manner, rather than in a deterministic way as is typically done. This can be achieved within the context of current physical parameterization schemes in weather and climate prediction models. Parameterizations are typically used to predict the evolution of grid-mean quantities because of unresolved subgrid-scale processes. However, parameterizations can also provide estimates of higher moments that could be used to constrain the random determination of the future state of a certain variable. The general equations used to estimate the variance of a generic variable are briefly discussed, and a simplified algorithm for a stochastic moist convection parameterization is proposed as a preliminary attempt. Results from the implementation of this stochastic convection scheme in the Navy Operational Global Atmospheric Prediction System (NOGAPS) ensemble are presented. It is shown that this method is able to generate substantial tropical perturbations that grow and “migrate” to the midlatitudes as forecast time progresses while moving from the small scales where the perturbations are forced to the larger synoptic scales. This stochastic convection method is able to produce substantial ensemble spread in the Tropics when compared with results from ensembles created from initial-condition perturbations. Although smaller, there is still a sizeable impact of the stochastic convection method in terms of ensemble spread in the extratropics. Preliminary simulations with initial-condition and stochastic convection perturbations together in the same ensemble system show a promising increase in ensemble spread and a decrease in the number of outliers in the Tropics.

Abstract 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.

Abstract 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.

The ancestor of unseasonal Typhoon Nanmadol (2004) over the western North Pacific is traced back to the Eastern Pacific (near 120°W) as an upper tropospheric, counter‐clockwise rotating mixed Rossby‐gravity (MRG) wave. The temporal and spatial evolution from an equatorial trapped MRG‐wave‐type disturbance to an off‐equatorial tropical depression is documented by utilizing NOGAPS (Navy's Operational Global Atmospheric Prediction System) analysis data. It is found that the MRG wave moved away from the equator after a dramatic reduction in its zonal dimension and downward development and amplification in the lower troposphere. These dramatic changes in MRG wave properties are attributed to the modulation of the easterly vertical shear, low‐level westerly‐easterly confluence in the large‐scale background flows, and convective coupling, as well as underlying high sea surface temperature (SST). The boundary layer convergence associated with asymmetric pressure field of the MRG wave is likely responsible for the transition from an equatorial MRG to an off‐equatorial tropical disturbance. This case study addresses the possibility that upper tropospheric MRG waves over the far eastern Pacific may provide “seeds” for tropical cyclogenesis over the western North Pacific.

Abstract Interannual and climatological variations of wind stress drag coefficient (CD) are examined over the global ocean from 1998 to 2004. Here CD is calculated using high temporal resolution (3- and 6-hourly) surface atmospheric variables from two datasets: 1) the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and 2) the Navy Operational Global Atmospheric Prediction System (NOGAPS). The stability-dependent CD algorithm applied to both datasets gives almost identical values over most of the global ocean, confirming the validity of results. Overall, major findings of this paper are as follows: 1) the CD value can change significantly (e.g., >50%) on 12-hourly time scales around the Kuroshio and Gulf Stream current systems; 2) there is strong seasonal variability in CD, but there is not much interannual change in the spatial variability for a given month; 3) a global mean CD ≈ 1.25 × 10−3 is found in all months, while CD ≥ 1.5 × 10−3 is prevalent over the North Pacific and North Atlantic Oceans and in southern high-latitude regions as well, and CD ≤ 1.0 × 10−3 is typical in the eastern equatorial Pacific cold tongue; and 4) including the effects of air–sea stability on CD generally causes an increase of >20% in comparison to the one calculated based on neutral conditions in the tropical regions. Finally, spatially and temporally varying CD fields are therefore needed for a variety of climate and air–sea interaction studies.

Abstract 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.

A global atmospheric forecast model that includes the middle atmosphere is used to investigate systematic model biases. As in many other global atmospheric models, Northern Hemispheric winter simulations from the vertically extended Navy Operational Global Atmospheric Prediction System reveal an unrealistic vertical tilt of the polar‐night jet associated with a temperature bias in the northern polar middle atmosphere. This bias has important implication for satellite data assimilation in that inaccurate model background field associated with the bias can cause a data assimilation system to reject useful observation data. Efforts are made to alleviate this bias using improved radiation and orographic gravity wave drag parameterizations, the latter of which can provide adequate amount of drag to greatly reduce the bias, but at the cost of overestimated surface polar pressure. To understand and fix this secondary bias, this study addresses the cause and effect of the bias in terms of the balance of model drag mechanisms between the middle and lower atmospheres as well as within the lower atmosphere. Disruption of these balances in the model is argued to lead to degradation of surface simulation by reasonable middle atmospheric gravity wave drag despite an improvement in the middle atmospheric circulation. An experimental treatment of limiting the parameterized gravity wave drag to the middle atmosphere, as similarly done with a spectral gravity wave drag parameterization, is shown to largely alleviate the bias. This study discusses results from a series of winter and multiyear simulations, schematically illustrates the drag balance in the model, and investigates conservation of atmospheric angular momentum.

Abstract 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.