Abstract

In this article two subsynoptic-scale cyclones that developed between 3 and 10 October 1996 over the western-central Mediterranean, causing floods, strong winds, and severe damage, are analyzed. Surface observations reveal that the accumulated rainfall at Santuario di Polsi (southern Calabria, Italy) is more than 480 mm for the first event (cyclone 9610A). The second cyclone (9610B) was characterized by a storm track predominantly over the sea, thus causing less recorded precipitation, but stronger wind. Satellite imagery shows two intensely convective vortices with a scale of 200–400 km and a spiral structure, with the cyclone 9610B displaying a well-defined eyelike feature.

The corresponding National Centers for Environmental Prediction analyses, although limited by 1° resolution, confirm the cyclones’ positions and intensities, as they can be inferred from satellite imagery, SSM/I data, and observations, but display also the “signature” of two tropical cyclone–like vortices, including a perfect alignment between the cutoffs at all levels with the surface center, and a warm core. The wind speed cross sections in the meridional and zonal directions through the eyelike feature reveal a virtually motionless column of air. A comparison with the cross sections taken in the same analyses across a named tropical storm in the Atlantic show a strong analogy between the gridded representation of these events.

Other remarkable features include very strong horizontal shear in the midtroposphere, and simultaneous lack of vertical shear; increasing low-level vorticity at the expenses of upper-level vorticity; creation of a low-level vorticity maximum; and finally strong low-level convergence and upper-level divergence during the onset and development of each cyclone.

Abstract

This study demonstrates that Global Hawk unmanned aircraft system dropwindsondes and Atmospheric Infrared Sounder (AIRS) observations can be complementary in sampling a tropical cyclone (TC). The assimilation of both datasets in a regional ensemble data assimilation system shows that the cumulative impact of both datasets is greater than either one alone because of the presence of mutually independent information content. The experiment that assimilates both datasets has smaller position and intensity errors in the mean analysis than those with individual datasets. The improvements in track and intensity forecasts that result from combining both datasets also indicate synergistic benefits. Overall, superior track and intensity forecasts are evident. This study suggests that polar-orbiting satellite spatial coverage should be considered in operational reconnaissance mission planning in order to achieve further improvements in TC analyses and forecasts.

Abstract

In this study, a 72-h cloud-permitting numerical prediction of Hurricane Wilma (2005), covering its initial 18-h spinup, an 18-h rapid intensification (RI), and the subsequent 36-h weakening stage, is performed using the Weather Research Forecast Model (WRF) with the finest grid length of 1 km. The model prediction uses the initial and lateral boundary conditions, including the bogus vortex, that are identical to the Geophysical Fluid Dynamics Laboratory’s then-operational data, except for the time-independent sea surface temperature field. Results show that the WRF prediction compares favorably in many aspects to the best-track analysis, as well as satellite and reconnaissance flight-level observations. In particular, the model predicts an RI rate of more than 4 hPa h⁻¹ for an 18-h period, with the minimum central pressure of less than 889 hPa. Of significance is that the model captures a sequence of important inner-core structural variations associated with Wilma’s intensity changes, namely, from a partial eyewall open to the west prior to RI to a full eyewall at the onset of RI, rapid eyewall contraction during the initial spinup, the formation of double eyewalls with a wide moat area in between during the most intense stage, and the subsequent eyewall replacement leading to the weakening of Wilma. In addition, the model reproduces the boundary layer growth up to 750 hPa with an intense inversion layer above in the eye. Recognizing that a single case does not provide a rigorous test of the model predictability due to the stochastic nature of deep convection, results presented herein suggest that it is possible to improve forecasts of hurricane intensity and intensity changes, and especially RI, if the inner-core structural changes and storm size could be reasonably predicted in an operational setting using high-resolution cloud-permitting models with realistic initial conditions and model physical parameterizations.

Abstract

The summary assessment metric (SAM) method is applied to an array of primary assessment metrics (PAMs) for the deterministic forecasts of three leading numerical weather prediction (NWP) centers for the years 2015–17. The PAMs include anomaly correlation, RMSE, and absolute mean error (i.e., the absolute value of bias) for different forecast times, vertical levels, geographic domains, and variables. SAMs indicate that in terms of forecast skill ECMWF is better than NCEP, which is better than but approximately the same as UKMO. The use of SAMs allows a number of interesting features of the evolution of forecast skill to be observed. All three centers improve over the 3-yr period. NCEP short-term forecast skill substantially increases during the period. Quantitatively, the effect of the 11 May 2016 NCEP upgrade to the four-dimensional ensemble variational data assimilation (4DEnVar) system is a 7.37% increase in the probability of improved skill relative to a randomly chosen forecast metric from 2015 to 2017. This is the largest SAM impact during the study period. However, the observed impacts are within the context of slowly improving forecast skill for operational global NWP as compared to earlier years. Clearly, the systems lagging ECMWF can improve, and there is evidence from SAMs in addition to the 4DEnVar example that improvements in forecast and data assimilation systems are still leading to forecast skill improvements.

Abstract

Hurricane Joaquin (2015) was characterized by high track forecast uncertainty when it approached the Bahamas from 29 September 2015 to 1 October 2015, with 5-day track predictions ranging from landfall in the United States to east of Bermuda. The source of large track spread in Joaquin forecasts is investigated using an ensemble prediction system (EPS) based on the Hurricane Weather Research and Forecasting (HWRF) Model. For the first time, a high-resolution analysis of an HWRF-based EPS is performed to isolate the factors that control tropical cyclone (TC) track uncertainty. Differences in the synoptic-scale environment, the TC vortex structure, and the TC location are evaluated to understand the source of track forecast uncertainty associated with Joaquin, especially at later lead times when U.S. landfall was possible. EPS members that correctly propagated Joaquin into the central North Atlantic are compared with members that incorrectly predicted U.S. landfall. Joaquin track forecasts were highly dependent on the evolution of the environment, including weak atmospheric steering flow near the Bahamas and three synoptic-scale systems: a trough over North America, a ridge to the northeast of Joaquin, and an upper-tropospheric trough to the east of Joaquin. Differences in the steering flow were associated with perturbations of the synoptic-scale environment at the model initialization time. Ultimately, members that produced a more progressive midlatitude synoptic-scale pattern had reduced track errors. Joaquin track forecast uncertainty was not sensitive to the TC vortex structure or the initial TC position.

Abstract

This paper provides an account of the performance of an experimental version of the Hurricane Weather Research and Forecasting system (HWRFX) for 87 cases of Atlantic tropical cyclones during the 2005, 2007, and 2009 hurricane seasons. The HWRFX system was used to study the influence of model grid resolution, initial conditions, and physics. For each case, the model was run to produce 126 h of forecast with two versions of horizontal resolution, namely, (i) a parent domain at a resolution of about 27 km with a 9-km moving nest (27:9) and (ii) a parent domain at a resolution of 9 km with a 3-km moving nest (9:3). The former was selected to be consistent with the current operational resolution, while the latter is the first step in testing the impact of finer resolutions for future versions of the operational model. The two configurations were run with initial conditions for tropical cyclones obtained from the operational Geophysical Fluid Dynamics Laboratory (GFDL) and HWRF models. Sensitivity experiments were also conducted with the physical parameterization scheme. The study shows that the 9:3 HWRFX system using the GFDL initial conditions and a system of physics similar to the operational version (HWRF) provides the best results in terms of both track and intensity prediction. Use of the HWRF initial conditions in the HWRFX model provides reasonable skill, particularly when used in cases with initially strong storms (hurricane strength). However, initially weak storms (below hurricane strength) posed special challenges for the models. For the weaker storm cases, none of the predictions from the HWRFX runs or the operational GFDL forecasts provided any consistent improvement when compared to the operational Statistical Hurricane Intensity Prediction Scheme with an inland decay component (DSHIPS).

Abstract

The Hurricane Weather Research and Forecasting Model (HWRF) was operationally implemented with a 27-km outer domain and a 9-km moving nest in 2007 (H007) as a tropical cyclone forecast model for the North Atlantic and eastern Pacific hurricane basins. During the 2012 hurricane season, a modified version of HWRF (H212), which increased horizontal resolution by adding a third (3 km) nest within the 9-km nest, replaced H007. H212 thus became the first operational model running at convection-permitting resolution. In addition, there were modifications to the initialization, model physics, tracking algorithm, etc. This paper compares H212 hindcast forecasts for the 2010–11 Atlantic hurricane seasons with forecasts from H007 and H3GP, a triply nested research version of HWRF. H212 reduced track forecast errors for almost all forecast times versus H007 and H3GP. H3GP was superior for intensity forecasts, although H212 showed some improvement over H007. Stratifying the cases by initial vertical wind shear revealed that the main weakness for H212 intensity forecasts was for cases with initially high shear. In these cases, H212 over- and under-intensified storms that were initially stronger and weaker, respectively. These results suggest the primary deficiency negatively impacting H212 intensity forecasts, especially in cases of rapid intensification, was that physics calls were too infrequent for the 3-km inner mesh. Correcting this deficiency along with additional modifications in the 2013 operational version yielded improved track and intensity forecasts. These intensity forecasts were comparable to statistical–dynamical models, showing that dynamical models can contribute to a decrease in operational forecast errors.