An Evaluation of Tropical Cyclone Genesis Forecasts from Global Numerical Models

In 1991, Typhoon Nat over the western North Pacific made four directional reversals due to its interactions with two other tropical cyclones (TCs), Luke and Mireille. This paper analyzes the performance of three global and two regional models in predicting the movement of Nat to determine the extent to which each of the models was capable of correctly simulating such binary interactions. The global models include those of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the U.K. Meteorological Office (UKMO) and the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS). The regional models studied are the Typhoon Model (TYM) of the Japan Meteorological Agency and the One-Way Tropical Cyclone Model (OTCM) of the U.S. Navy. It was found that in general the global models made better predictions than the regional ones, especially when the large-scale flow was well defined. During the interaction periods, the UKMO model and the TYM were the best. The ECMWF model was also...

Daily inter-annual simulations of SST and MLD using atmospherically forced OGCMs: Model evaluation in comparison to buoy time series

The US global model lags the performance of two European competitors in predicting weather up to two weeks ahead.

This paper examines the sensitivity of sea surface temperature (SST) to water turbidity in the Black Sea using the eddy-resolving (∼3.2-km resolution) Hybrid Coordinate Ocean Model (HYCOM), which includes a nonslab K-profile parameterization (KPP) mixed layer model. The KPP model uses a diffusive attenuation coefficient of photosynthetically active radiation (kPAR) processed from a remotely sensed dataset to take water turbidity into account. Six model experiments (expt) are performed with no assimilation of any ocean data and wind/thermal forcing from two sources: 1) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA) and 2) Fleet Numerical Meteorology and Oceanography Center (FNMOC) Navy Operational Global Atmospheric Prediction System (NOGAPS). Forced with ECMWF, experiment 1 uses spatially and monthly varying kPAR values over the Black Sea, experiment 2 assumes all of the solar radiation is absorbed at the sea surface, and experiment 3 uses a constant kPAR value of 0.06 m−1, representing clear-water constant solar attenuation depth of 16.7 m. Experiments 4, 5, and 6 are twins of 1, 2, and 3 but forced with NOGAPS. The monthly averaged model SSTs resulting from all experiments are then compared with a fine-resolution (∼9 km) satellite-based monthly SST climatology (the Pathfinder climatology). Because of the high turbidity in the Black Sea, it is found that a clear-water constant attenuation depth (i.e., expts 3 and 6) results in SST bias as large as 3°C in comparison with standard simulations (expts 1 and 4) over most of the Black Sea in summer. In particular, when using the clear-water constant attenuation depth as opposed to using spatial and temporal kPAR, basin-averaged rms SST difference with respect to the Pathfinder SST climatology increases ∼46% (from 1.41°C in expt 1 to 2.06°C in expt 3) in the ECMWF forcing case. Similarly, basin-averaged rms SST difference increases ∼36% (from 1.39°C in expt 4 to 1.89°C in expt 6) in the NOGAPS forcing case. The standard HYCOM simulations (expts 1 and 4) have a very high basin-averaged skill score of 0.95, showing overall model success in predicting climatological SST, even with no assimilation of any SST data. In general, the use of spatially and temporally varying turbidity fields is necessary for the Black Sea OGCM studies because there is strong seasonal cycle and large spatial variation in the solar attenuation coefficient, and an additional simulation using a constant kPAR value of 0.19 m−1, the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) space–time mean for the Black Sea, did not yield as accurate SST results as experiments 1 and 4. Model–data comparisons also revealed that relatively large HYCOM SST errors close to the coastal boundaries can be attributed to the misrepresentation of land– sea mask in the ECMWF and NOGAPS products. With the relatively accurate mask used in NOGAPS, HYCOM demonstrated the ability to simulate accurate SSTs in shallow water over the broad northwest shelf in the Black Sea, a region of large errors using the inaccurate mask in ECMWF. A linear relationship is found between changes in SST and changes in heat flux below the mixed layer. Specifically, a change of ∼50 W m−2 in sub-mixed-layer heat flux results in a SST change of ∼3.0°C, a value that occurs when using clear-water constant attenuation depth rather than monthly varying kPAR in the model simulations, clearly demonstrating potential impact of penetrating solar radiation on SST simulations.

Ocean models need over-ocean atmospheric forcing. However, such forcing is not necessarily provided near the land–sea boundary because 1) the atmospheric model grid used for forcing is frequently much coarser than the ocean model grid, and 2) some of the atmospheric model grid over the ocean includes land values near coastal regions. This paper presents a creeping sea-fill methodology to reduce the improper representation of scalar atmospheric forcing variables near coastal regions, a problem that compromises the usefulness of the fields for ocean model simulations and other offshore applications. For demonstration, atmospheric forcing variables from archived coarse-resolution gridded products—the 1.125° × 1.125° 15-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15) and 1.0° × 1.0° Navy Operational Global Atmospheric Prediction System (NOGAPS)—are used here. A fine-resolution [1/25° × 1/25° cos(lat)], (longitude × latitude) (∼3.2 km) eddy-resolving Black Sea Hybrid Coordinate Ocean Model (HYCOM) is then forced with/without sea-filled atmospheric variables from these gridded products to simulate monthly mean climatological sea surface temperature (SST). Using only over-ocean values from atmospheric forcing fields in the ocean model simulations significantly reduces the climatological mean SST bias (by ∼1°–3°C) and rms SST difference over the seasonal cycle (by ∼2°–3°C) in coastal regions. Performance of the creeping sea-fill methodology is also directly evaluated using measurements of wind speed at 10 m above the surface from the SeaWinds scatterometer on the NASA Quick Scatterometer (QuikSCAT) satellite. Comparisons of original monthly mean wind speeds from operational ECMWF and NOGAPS products with those from QuikSCAT give basin-averaged rms differences of 1.6 and 1.4 m s−1, respectively, during 2000–03. Similar comparisons performed with sea-filled monthly mean wind speeds result in a much lower rms difference (0.7 m s−1 for both products) during the same time period, clearly confirming the accuracy of the methodology even on interannual time scales. Most of the unrealistically low wind speeds from ECMWF and NOGAPS near coastal boundaries are appropriately corrected with the use of the creeping sea fill. Wind speed errors for ECWMF and NOGAPS (mean bias of ≥ 2.5 m s−1 with respect to QuikSCAT during 2000–03) are substantially eliminated (e.g., almost no bias) near most of the land–sea boundaries. Finally, ocean, atmosphere, and coupled atmospheric–oceanic modelers need to be aware that the creeping sea fill is a promising methodology in significantly reducing the land contamination resulting from an improper land–sea mask existing in gridded coarse-resolution atmospheric products (e.g., ECMWF).

Prior studies by the authors have documented the verification statistics of disturbance-based tropical cyclone (TC) genesis forecasts over the North Atlantic (AL) and eastern North Pacific (EP) basins, which led to the development of real-time probabilistic TC genesis guidance based on multiple logistic regression [the TC Logistic Guidance for Genesis (TCLOGG)]. This study provides a substantial update to that prior work by analyzing a more recent period (2017–22) with one additional model [Navy Global Environmental Model (NAVGEM)], expanding the forecast period temporally to 7 days, and expanding the study domain spatially to include all basins [except the central North Pacific (CP) basin, where the sample size of TC genesis events was too small to generate meaningful statistics]. TC genesis forecasts from five global models are verified against the NHC’s and JTWC’s best tracks. Verification statistics exhibit nontrivial interannual and model-to-model variability rendering it unfeasible to attempt to define repeatable performance rankings among the models. Nevertheless, results indicate that the ECMWF model exhibits the largest mean success ratio (SR) overall, while the UKMO and GFS models exhibit the greatest probability of detection (POD). All models exhibit a clear trade-off between SR and POD, yielding mean critical success index values < 0.35 for any individual model and basin. The ECMWF and UKMO models exhibit the greatest critical success index (CSI) values globally. This study provides additional evidence that some best track TC genesis events can be detected at least 1 week in advance, but maximum lead times are inconsistent. The resulting dataset of verified forecasts will serve as an updated training dataset for enhanced and updated TCLOGG products.

Operational forecasting of tropical cyclone (TC) genesis has improved in recent years but still can be a challenge. Output from global numerical models continues to serve as a primary source of forecast guidance. Bulk verification statistics (e.g., critical success index) of TC genesis forecasts indicate that, overall, global models are increasingly able to predict TC genesis. However, as global model configurations are updated, TC genesis verification statistics will change. This study compares operational and retrospective forecasts from three configurations of NCEP’s Global Forecast System (GFS) to quantify the impact of model upgrades on TC genesis forecasts. First, bulk verification statistics from a homogeneous sample of model initialization cycles during the period 2013–14 are compared. Then, composites of select output fields are analyzed in an attempt to identify any key differences between hit and false alarm events. Bulk statistics indicate that TC genesis forecast performance decreased with the implementation of the 2015 version of the GFS, but then modestly recovered with the 2016 version of the model. In addition, the composite analysis suggests that false alarm forecasts in the 2015 version of the GFS may have been the result of inaccurately forecasting the location and/or strength of upper-level troughs poleward of the TC. There is also evidence of convective feedbacks occurring, such as ridging above the low-level circulation and upper-level convective outflow that were too strong, in this same set of false alarm forecasts. Overall, analyzing retrospective forecasts can assist forecasters in determining the strengths and weaknesses associated with a new configuration of a global model with respect to TC genesis.

A hybrid Lagrangian–Eulerian model for calculating the trajectories of near-surface drifters in the ocean is developed in this study. The model employs climatological, near-surface currents computed from a spline fit of all available drifter velocities observed in the Pacific Ocean between 1988 and 1996. It also incorporates contemporaneous wind fields calculated by either the U.S. Navy [the Navy Operational Global Atmospheric Prediction System (NOGAPS)] or the European Centre for Medium-Range Weather Forecasts (ECMWF). The model was applied to 30 drifters launched in the tropical Pacific Ocean in three clusters during 1990, 1993, and 1994. For 10-day-long trajectories the forecasts computed by the hybrid model are up to 164% closer to the observed trajectories compared to the trajectories obtained by advecting the drifters with the climatological currents only. The best-fitting trajectories are computed with ECMWF fields that have a temporal resolution of 6 h. The average improvement over all 30 drifters of the hybrid model trajectories relative to advection by the climatological currents is 21%, but in the open-ocean clusters (1990 and 1993) the improvement is 42% with ECMWF winds (34% with NOGAPS winds). This difference between the open-ocean and coastal clusters is due to the fact that the model does not presently include the effect of horizontal boundaries (coastlines). For zero initial velocities the trajectories generated by the hybrid model are significantly more accurate than advection by the mean currents on time scales of 5–15 days. For 3-day-long trajectories significant improvement is achieved if the drifter's initial velocity is known, in which case the model-generated trajectories are about 2 times closer to observations than persistence. The model's success in providing more accurate trajectories indicates that drifters' motion can deviate significantly from the climatological current and that the instantaneous winds are more relevant to their trajectories than the mean surface currents. It also demonstrates the importance of an accurate initial velocity, especially for short trajectories on the order of 1–3 days. A possible interpretation of these results is that winds affect drifter motion more than the water velocity since drifters do not obey continuity.

Evaluation of the effect of meteorological data resolution on Lagrangian particle dispersion simulations using the ETEX experiment

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 National Hurricane Center (NHC) has stated that guidance on tropical cyclone (TC) genesis is an operational forecast improvement need, particularly since numerical weather prediction models produce TC-like features and operationally required forecast lead times recently have increased. Using previously defined criteria for TC genesis in global models, this study bias corrects TC genesis forecasts from global models using multiple logistic regression. The derived regression equations provide 48- and 120-h probabilistic genesis forecasts for each TC genesis event that occurs in the Environment Canada Global Environmental Multiscale Model (CMC), the NCEP Global Forecast System (GFS), and the Met Office's global model (UKMET). Results show select global model output variables are good discriminators between successful and unsuccessful TC genesis forecasts. Independent verification of the regression-based probabilistic genesis forecasts during 2014 and 2015 are presented. Brier scores and reliability diagrams indicate that the forecasts generally are well calibrated and can be used as guidance for NHC’s Tropical Weather Outlook product. The regression-based TC genesis forecasts are available in real time online.

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...

: LONG TERM GOALS: Investigate methods to advance our understanding of dynamical and physical processes in the atmosphere, particularly in the areas of data assimilation and physical processes. Use this information to enhance our ability to predict the atmosphere using global and mesoscale numerical models. OBJECTIVES: Investigate methods for producing the most effective data assimilation system for weather forecasting. Establish common radiation parameterizations in the numerical models at the Naval Research Laboratory (NRL). APPROACH: Leverage the university research community to develop and refine basic scientific principles that can be applied to the advanced development of numerical weather prediction systems. Incorporate these principles into NRL s global model, the Navy Operational Global Atmospheric Prediction System (NOGAPS) and NRL s mesoscale model, the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS).

Accurately forecasting tropical cyclone (TC) genesis is an important operational need, especially since the National Hurricane Center’s Tropical Weather Outlook product has been extended from 2 to 5 days. A previous study by the coauthors verified North Atlantic TC genesis forecasts from five global models out to 4 days during 2004–11. This study expands on the previous research by 1) verifying TC genesis forecasts over both the Atlantic and eastern North Pacific basins, 2) extending the forecast window to 5 days, and 3) updating the analysis period through 2014. Verification statistics are presented and compared between the two basins. Probability of detection and critical success indices generally are greater over the eastern North Pacific basin compared to the North Atlantic. There is a trade-off between models that exhibit a greater probability of detection and a greater false alarm ratio, and models that exhibit a smaller false alarm ratio and a smaller probability of detection. Results also reveal that the models preferentially miss TCs over the North Atlantic (eastern North Pacific) that have a relatively small radius of the outer closed isobar (radius of maximum wind) at the forecast genesis time. Overall, global models have become a more reliable source of TC genesis guidance during the past few years compared to the early years in the dataset.

This study describes atmospheric forcing parameters constructed from different global climatologies, applied to the Black Sea, and investigates the sensitivity of Hybrid Coordinate Ocean Model (HYCOM) simulations to these products. Significant discussion is devoted to construction of these parameters before using them in the eddy-resolving (≈3.2-km resolution) HYCOM simulations. The main goal is to answer how the model dynamics can be substantially affected by different atmospheric forcing products in the Black Sea. Eight wind forcing products are used: four obtained from observation-based climatologies, including one based on measurements from the SeaWinds scatterometer on the Quick Scatterometer (QuikSCAT) satellite, and the rest formed from operational model products. Thermal forcing parameters, including solar radiation, are formed from two operational models: the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Fleet Numerical Meteorology and Oceanography Center (FNMOC) Navy Operational Global Atmospheric Prediction System (NOGAPS). Climatologically forced Black Sea HYCOM simulations (without ocean data assimilation) are then performed to assess the accuracy and sensitivity of the model sea surface temperature (SST) and sea surface circulation to these wind and thermal forcing products. Results demonstrate that the model-simulated SST structure is quite sensitive to the wind and thermal forcing products, especially near coastal regions. Despite this sensitivity, several robust features are found in the model SST in comparison to a monthly 9.3-km-resolution satellite-based Pathfinder SST climatology. Annual mean HYCOM SST usually agreed to within ≈±0.2° of the climatology in the interior of the Black Sea for any of the wind and thermal forcing products used. The fine-resolution (0.25° × 0.25°) wind forcing from the scatterometer data along with thermal forcing from NOGAPS gave the best SST simulation with a basin-averaged rms difference value of 1.21°C, especially improving model results near coastal regions. Specifically, atmospherically forced model simulations with no assimilation of any ocean data suggest that the basin-averaged rms SST differences with respect to the Pathfinder SST climatology can vary from 1.21° to 2.15°C depending on the wind and thermal forcing product. The latter rms SST difference value is obtained when using wind forcing from the National Centers for Environmental Prediction (NCEP), a product that has a too-coarse grid resolution of 1.875° × 1.875° for a small ocean basin such as the Black Sea. This paper also highlights the importance of using high-frequency (hybrid) wind forcing as opposed to monthly mean wind forcing in the model simulations. Finally, there are large variations in the annual mean surface circulation simulated using the different wind sets, with general agreement between those forced by the model-based products (vector correlation is usually >0.7). Three of the observation-based climatologies generally yield unrealistic circulation features and currents that are too weak.