Abstract

Composite dropsonde profiles are analyzed for developing and nondeveloping tropical waves in an attempt to improve the understanding of tropical cyclogenesis. These tropical waves were sampled by 25 reconnaissance missions during the 2010 Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign. Comparisons are made between mean profiles of temperature, mixing ratio, relative humidity, radial and tangential winds, relative vorticity, and virtual convective available potential energy (CAPE) for genesis and nongenesis cases. Genesis soundings are further analyzed in temporal progression to investigate whether significant changes in the thermodynamic or wind fields occur during the transition from tropical wave to tropical cyclone.

Significant results include the development of positive temperature anomalies from 500 to 200 hPa 2 days prior to genesis in developing waves. This is not observed in the nongenesis mean. Progressive mesoscale moistening of the column is observed within 150 km of the center of circulation prior to genesis. The genesis composite is found to be significantly moister than the nongenesis composite at the middle levels, while comparatively drier at low levels, suggesting that dry air is more detrimental to genesis when located at the middle levels. Time-varying tangential wind profiles reveal an initial delay in intensification, followed by an increase in organization 24 h pregenesis. The vertical evolution of relative vorticity, in addition to a warm-over-cold thermal structure, is more consistent with a top-down than a bottom-up genesis mechanism. Last, CAPE values are much greater for nongenesis than genesis profiles, indicating that greater instability does not necessarily favor genesis.

Abstract

The predictability of selected variables associated with tropical cyclogenesis is examined using 10-day ECMWF ensemble forecasts for 21 events from the 2010 Atlantic hurricane season. Variables are associated with the strength of the pregenesis disturbance, quantified via circulation and thickness anomaly, and the favorability of the immediate environment via moisture and vertical wind shear.

For approximately half of the cases, the predicted strength of the genesis signal is directly related to the predicted favorability of the environment. For the remainder of the cases, predictability is more directly associated with the strength and location of the analyzed disturbance. Some commonalities among the majority of the sample are also observed. Forecast joint distributions demonstrate that 700-hPa relative humidity of less than 60% within 300 km of the circulation center is a limiting factor for genesis. Genesis is also predicted and found to occur in the presence of significant wind shear (~15 m s⁻¹), but almost exclusively when the core and environment of the wave are both very moist.

The ensemble also demonstrates the potential to predict error standard deviation of variables averaged within 300- and 1000-km radii about individual tropical waves. Forecasts with greater ensemble standard deviation tend to be, on average, associated with greater mean error, especially for forecasts of less than 7 days. However, model biases, particularly a dry core and weak circulation bias, become pronounced at longer lead times. Overall, these results demonstrate that both the environmental conditions favorable to genesis and the genesis events themselves may be predictable to a week or more.

Abstract

The interaction between a tropical cyclone (TC) and an upper-level trough is simulated in an idealized framework using Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) for Tropical Cyclones (COAMPS-TC) on a β plane. We explore the effect of the trough on the environment, structure, and intensity of the TC. In a simulation that does not have a trough, environmental inertial stability is dominated by Coriolis, and outflow remains preferentially directed equatorward throughout the simulation. In the presence of a trough, negative storm-relative tangential wind in the base of the trough reduces the inertial stability such that the outflow shifts from equatorward to poleward. This interaction results in a ~24-h period of enhanced upper-level divergence coincident with intensification of the TC. Sensitivity tests reveal that if the TC is too far from the trough, favorable interaction does not occur. If the TC is too close to the trough, the storm weakens because of enhanced vertical wind shear. Only when the relative distance between the TC and the trough is 0.2–0.3 times the wavelength of the trough in x and 0.8–1.2 times the amplitude of the trough in y does favorable interaction and TC intensification occur. However, stochastic effects make it difficult to isolate the intensity change associated directly with the trough interaction. Outflow is found to be predominantly ageostrophic at small radii and deflects to the right (in the Northern Hemisphere) since it is unbalanced. The outflow becomes predominantly geostrophic at larger radii but not before a rightward deflection has already occurred. This finding sheds light on why the outflow accelerates toward but generally never reaches the region of lowest inertial stability.

Abstract

Dropsonde data collected during the NASA Hurricane and Severe Storm Sentinel (HS3) field campaign from 16 research missions spanning 6 tropical cyclones (TCs) are investigated, with an emphasis on TC outflow and the warm core. The Global Hawk (GH) AV-6 aircraft provided a unique opportunity to investigate the outflow characteristics due to a combination of 18+-h flight durations and the ability to release dropsondes from high altitudes above 100 hPa. Intensifying TCs are found to be associated with stronger upper-level divergence and radial outflow relative to nonintensifying TCs in the sample, regardless of current intensity. A layer of 2–4 m s⁻¹ inflow 20–50 hPa deep is also observed 50–100 hPa above the maximum outflow layer, which appears to be associated with lower-stratospheric descent above the eye. The potential temperature of the outflow is found to be more strongly correlated with the equivalent potential temperature of the boundary layer inflow than to the present storm intensity, consistent with the outflow temperature having a stronger relationship with potential intensity than actual intensity. Finally, the outflow originates from a region of low inertial stability that extends above the cyclone from 300 to 150 hPa and from 50- to 200-km radius.

The unique nature of this dataset allows the height and structure of the warm core also to be investigated. The magnitude of the warm core was found to be positively correlated with TC intensity, while the height of the warm core was weakly positively correlated with intensity. Finally, neither the height nor magnitude of the warm core exhibits any meaningful relationship with intensity change.

Abstract

Several metrics are employed to evaluate predictive skill and attempt to quantify predictability using the ECMWF Ensemble Prediction System during the 2010 Atlantic hurricane season, with an emphasis on large-scale variables relevant to tropical cyclogenesis. These metrics include the following: 1) growth and saturation of error, 2) errors versus climatology, 3) predicted forecast error standard deviation, and 4) predictive power. Overall, variables that are more directly related to large-scale, slowly varying phenomena are found to be much more predictable than variables that are inherently related to small-scale convective processes, regardless of the metric. For example, 850–200-hPa wind shear and 200-hPa velocity potential are found to be predictable beyond one week, while 200-hPa divergence and 850-hPa relative vorticity are only predictable to about one day. Similarly, area-averaged quantities such as circulation are much more predictable than nonaveraged quantities such as vorticity. Significant day-to-day and month-to-month variability of predictability for a given metric also exists, likely due to the flow regime. For wind shear, more amplified flow regimes are associated with lower predictive power (and thereby lower predictability) than less amplified regimes. Relative humidity is found to be less predictable in the early and late season when there exists greater uncertainty of the timing and location of dry air. Last, the ensemble demonstrates the potential to predict error standard deviation of variables averaged in 10° × 10° boxes, in that forecasts with greater ensemble standard deviation are on average associated with greater mean error. However, the ensemble tends to be underdispersive.

Abstract

The response of Weather Research and Forecasting (WRF) model predictions of two tropical cyclones to perturbations in the initial conditions is investigated. Local perturbations to the vorticity field in the synoptic environment are created in features considered subjectively to be of importance to the track forecast. The rebalanced analysis is then integrated forward and compared with an unperturbed “control” simulation possessing similar errors to those in the corresponding operational model forecasts. In the first case, Typhoon Sinlaku (2008), the premature recurvature in the control simulation is found to be corrected by a variety of initial perturbations; in particular, the weakening of an upper-level low directly to its north, and the weakening of a remote short-wave trough in the midlatitude storm track. It is suggested that one or both of the short waves may have been initialized too strongly. In the second case, the forecasts for Hurricane Ike (2008) initialized 4 days prior to its landfall in Texas were not sensitive to most remote perturbations. The primary corrections to the track of Ike arose from a weakening of a midlevel ridge directly to its north, and the strengthening of a short-wave trough in the midlatitudes. For both storms, the targets selected by the ensemble transform Kalman filter (ETKF) were often, but not always, consistent with the most sensitive regions found in this study. Overall, the results can be used to retrospectively diagnose features in which the initial conditions require improvement, in order to improve forecasts of tropical cyclone track.

Abstract

Accurately simulating the Madden–Julian oscillation (MJO), which dominates intraseasonal (30–90 day) variability in the tropics, is critical to predicting tropical cyclones (TCs) and other phenomena at extended-range (2–3 week) time scales. MJO biases in intensity and propagation speed are a common problem in global coupled models. For example, the MJO in the Navy Earth System Prediction Capability (ESPC), a global coupled model, has been shown to be too strong and too fast, which has implications for the MJO–TC relationship in that model. The biases and extended-range prediction skill in the operational version of the Navy ESPC are compared to experiments applying different versions of analysis correction-based additive inflation (ACAI) to reduce model biases. ACAI is a method in which time-mean and stochastic perturbations based on analysis increments are added to the model tendencies with the goals of reducing systematic error and accounting for model uncertainty. Over the extended boreal summer (May–November), ACAI reduces the root-mean-squared error (RMSE) and improves the spread–skill relationship of the total tropical and MJO-filtered OLR and low-level zonal winds. While ACAI improves skill in the environmental fields of low-level absolute vorticity, potential intensity, and vertical wind shear, it degrades the skill in the relative humidity, which increases the positive bias in the genesis potential index (GPI) in the operational Navy ESPC. Northern Hemisphere integrated TC genesis biases are reduced (increased number of TCs) in the ACAI experiments, which is consistent with the positive GPI bias in the ACAI simulations.

Abstract

The 11-member Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclones (COAMPS-TC) ensemble has been developed by the Naval Research Laboratory (NRL) to produce probabilistic forecasts of tropical cyclone (TC) track, intensity and structure. All members run with a storm-following inner grid at convection-permitting 4-km horizontal resolution. The COAMPS-TC ensemble is constructed via a combination of perturbations to initial and boundary conditions, the initial vortex, and model physics to account for a variety of different sources of uncertainty that affect track and intensity forecasts. Unlike global model ensembles, which do a reasonable job capturing track uncertainty but not intensity, mesoscale ensembles such as the COAMPS-TC ensemble are necessary to provide a realistic intensity forecast spectrum. The initial and boundary condition perturbations are responsible for generating the majority of track spread at all lead times, as well as the intensity spread from 36 to 120 h. The vortex and physics perturbations are necessary to produce meaningful spread in the intensity prediction from 0 to 36 h. In a large sample of forecasts from 2014 to 2017, the ensemble-mean track and intensity forecast is superior to the unperturbed control forecast at all lead times, demonstrating a clear advantage to running an ensemble versus a deterministic forecast. The spread–skill relationship of the ensemble is also examined, and is found to be very well calibrated for track, but is underdispersive for intensity. Using a mixture of lateral boundary conditions derived from different global models is found to improve upon the spread–skill score for intensity, but it is hypothesized that additional physics perturbations will be necessary to achieve realistic ensemble spread.

Abstract

As tropical cyclone (TC) official and model track forecasts improve, cases still exist where model position errors and uncertainty are large. The goal of this study is to identify forecast track bifurcations in both the Coupled Ocean-Atmosphere Mesoscale Prediction System-Tropical Cyclone (COAMPS-TC) ensemble and the Global Ensemble Forecast System (GEFS), with subsequent analyses focusing on the comparison of the synoptic environments of the bifurcating cases between the ensembles.

Thirty-three bifurcating cases are identified in the COAMPS-TC ensemble, while thirty-eight are identified in the GEFS, over a time period spanning the 2020-2022 TC seasons in the Northern Hemisphere. For these bifurcating cases, early lead time position of an ensemble member relative to the ensemble mean shows little correlation to the 72 h member’s position relative to the ensemble mean. Rather, the TC’s 72 h forecast position relative to the ensemble mean shows high sensitivity to the tropospheric deep-layer steering flow at early lead times, particularly in the COAMPS-TC ensemble. For both ensembles, a region of weak flow is located near the TCs at the forecast initial time. Minor differences in the steering flow at early lead times induced by variations in the synoptic-scale environment cause the TC’s position relative to the col to vary across the ensembles members, resulting in a bifurcation. Differences in the results for the COAMPS-TC ensemble and GEFS are thought to be driven, in part, by the fact that the COAMPS-TC ensemble utilizes flow-independent initial-state perturbations, while the perturbations in the GEFS are flow-dependent.

Abstract

Given the prohibitive expense of running a global coupled high-resolution model for multiweek forecasts, we explore the feasibility of running a limited-area model forced by a global model on monthly time scales. Specifically, we seek to understand the constraints of the accuracy of lateral boundary conditions (LBCs) produced by NAVGEM on the skill of limited-area COAMPS forecasts. In this study, we analyze simulations of the successive MJO events of November 2011. In the NAVGEM simulations, the effect of ocean boundary conditions are examined, including fixed sea surface temperature (SST), observed SST, and coupled SST with HYCOM. With fixed SST, the second MJO fails to develop, highlighting the importance of the ocean response in the ability to model successive MJO events. Next, we examine the dependence of the regional COAMPS skill on the global model forecast performance. It is found that even when using the inferior but computationally inexpensive uncoupled NAVGEM for LBCs, coupled COAMPS can accurately predict the successive MJO events. A well-resolved atmospheric Rossby wave that slowly propagates westward in the COAMPS domain contributes to increased predictive skill. Ocean coupling and the ability of the model to sufficiently warm the ocean during the convectively suppressed phase also appears to be critical. Last, while COAMPS exhibits a significant moist bias, the sign and magnitude of the vertical and horizontal moisture flux appear to be consistent with reanalysis, a necessary attribute of any model to be used in multiweek MJO prediction.