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Brett T. Hoover

Abstract

The eastern Pacific tropical cyclone basin is typified by a low-level westerly jet with the main development region residing on its northern, cyclonic-shear side. The persistent meridional shear of the zonal flow associated with the jet allows for the possibility of barotropic conversion of energy from the mean state into the kinetic energy of vortices—possibly contributing to tropical cyclogenesis, but this is difficult to quantify by perturbing the model based on intuition since there is no guarantee that perturbations will favorably interact with the jet to facilitate cyclogenesis.

Here, sensitivity gradients of vortex intensity through cyclogenesis are calculated for a set of cases spanning from 2004 to 2010 and are interpreted dynamically to determine which cases have sensitivities describing structures that can grow barotropically from the low-level jet. The adjoint model is run with adiabatic physics linearized about a basic state that contains moist convection. Optimal perturbations derived from these sensitivities are inserted into the model to observe the impact. Roughly 34% of observed cases exhibited structures in sensitivity to zonal flow that strongly imply barotropic growth, while about 21% exhibited no such structures. The remainder (roughly 45%) exhibit some reliance on barotropic growth. Cases with sensitivities exhibiting strong barotropic growth structures are typified by low-level westerly jets with larger meridional shear. In these cases, optimal perturbations require less initial energy to increase vortex intensity by a specified amount, the energy is more strongly focused at jet level, and the localized energy growth rate of perturbations is most efficient.

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Brett T. Hoover and Michael C. Morgan

Abstract

Through the use of an adjoint model, the sensitivity of the steering of a simulated tropical cyclone (TC) to various aspects of a model forecast trajectory can be calculated. This calculation, providing a priori information about how small perturbations to the model state will impact the steering of the TC at some future time, provides a wealth of dynamical information about the importance of synoptic-scale features and associated processes to the steering of a modeled TC that is difficult or impossible to obtain by other means. Regions of strong sensitivity to cyclone steering are regions where, if errors in the model state exist, those errors would have the largest effect on TC steering at a specified time in the future. However, without a dynamical understanding of why the steering of a simulated TC is sensitive to changes in these regions, errors in the methodology of implementing an adjoint model for calculating these sensitivities may result in sensitivity gradients that do not represent sensitivity of TC steering at all, and without a strong dynamical interpretation of these sensitivities, these errors may escape notice.

An adjoint model is employed for several cases of simulated TCs in the west Pacific to determine the dynamical significance of regions for which sensitivity to TC steering is found to be particularly strong. It is found that the region of subsidence upstream of a passing midlatitude trough can play a crucial role in the development of perturbations that strongly impact a recurving TC. A dynamical interpretation of this relationship is described and tested.

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Brett T. Hoover and Chris S. Velden

Abstract

The adjoint-derived observation impact method is used as a diagnostic to derive the impact of assimilated observations on a metric representing the forecast intensity of a tropical cyclone (TC). Storm-centered composites of observation impact and the model background state are computed across 6-hourly analysis/forecast cycles to compute the composite observation impact throughout the life cycle of Hurricane Joaquin (2015) to evaluate the impact of in situ wind and temperature observations in the upper and lower troposphere, as well as the impact of brightness temperature and precipitable water observations, on intensity forecasts with forecast lengths from 12 to 48 h. The compositing across analysis/forecast cycles allows for the exploration of consistent relationships between the synoptic-scale state of the initial conditions and the impact of observations that are interpreted as flow-dependent interactions between model background bias and correction by assimilated observations on the TC intensity forecast. The track of Hurricane Matthew (2016), with an extended period of time near the coasts of Florida, Georgia, and the Carolinas, allows for a comparison of the impact of aircraft reconnaissance observations with the impact of nearby overland rawinsonde observations available within the same radius of the TC.

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Brett T. Hoover and Michael C. Morgan

Abstract

The steering of a tropical cyclone (TC) vortex is commonly understood as the advection of the TC vortex by an “environmental wind.” In past studies, the environmental steering wind vector has been defined by the horizontal and vertical averaging of the horizontal winds in a box centered on the TC. The components of this environmental steering have been proposed as response functions to derive adjoint-derived sensitivities of TC zonal and meridional steering. The appropriateness of these response functions in adjoint sensitivity studies of TC steering is tested using a two-dimensional barotropic model and its adjoint for a 24-h forecast. It is found that these response functions do not produce sensitivities to TC steering because perturbations to the model initial conditions that change the final-time location of the TC also change the response functions in ways that have nothing to do with the steering of the TC at model verification.

An alternate response function is proposed wherein the environmental steering vector is defined as the wind averaged over the response function box attributed to vorticity outside of that box. By redefining the response functions for the zonal and meridional steering as components of this environmental steering vector, the effect of small changes to the final-time location of the TC is removed, and the resultant sensitivity gradients can be shown to truly represent the sensitivity of TC steering to perturbations of the model forecast state.

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Brett T. Hoover, Chris S. Velden, and Sharanya J. Majumdar

Abstract

To efficiently and effectively prioritize resources, adaptive observations can be targeted by using some objective criteria to estimate the potential impact an initial condition perturbation (or analysis increment) in a specific region would have on the future forecast. Several objective targeting guidance techniques have been developed, including total-energy singular vectors (TESV), adjoint-derived sensitivity steering vectors (ADSSV), and the ensemble transform Kalman filter (ETKF), all of which were tested during the 2008 The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Office of Naval Research Tropical Cyclone Structure-2008 (TCS-08) field experiments. An intercomparison between these techniques is performed in order to find underlying physical mechanisms in the respective guidance products, based on four tropical cyclone (TC) cases from the T-PARC/TCS-08 field campaigns. It is found that the TESV energy norm and the ADSSV response function are largely indirect measures of the TC track divergence that can be produced by an initial condition perturbation, explaining the strong correlation between these products. The downstream targets routinely chosen by the ETKF guidance system are often not found in the TESV and ADSSV guidance products, and it is found that downstream perturbations can affect the steering of a TC through the development of a Rossby wave in the subtropics that modulates the strength of the nearby subtropical ridge. It is hypothesized that the ubiquitousness of these downstream targets in the ETKF is largely due to the existence of large uncertainties downstream of the TC that are not taken into consideration by either the TESV or ADSSV techniques.

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Melissa L. Breeden, Brett T. Hoover, Matthew Newman, and Daniel J. Vimont

Abstract

Atmospheric blocking is associated with sensible weather impacts such as anomalous precipitation and flooding, cold air outbreaks, and heat waves. Given the asymmetry in the persistence characteristics of anticyclones and cyclones, many studies have emphasized the role of nonlinearities in blocking onset and maintenance. However, previous studies have demonstrated that both linear and nonlinear dynamics can amplify blocks. In this paper the structure and evolution of North Pacific blocking on weekly time scales is investigated using two methods: statistical analysis not requiring linearity, and a linear inverse model (LIM) composed of tropical outgoing longwave radiation and extratropical streamfunction, which relies on purely linear (and linearly parameterized) dynamics. Both approaches produce a similar evolution of North Pacific blocking. Using the LIM, the optimal precursors to blocking are determined, which at a 14-day lead time include an upper-level east Pacific anticyclone and suppressed convection over the central tropical Pacific. The tropics and extratropics both contribute to the deterministic evolution of blocking, with the tropics acting on longer time scales but imposing a weaker response than that contributed by the extratropics. The tropical contribution was driven by La Niña–like conditions that produce a hemispheric anticyclonic anomaly, while the extratropical initial conditions produce an equivalent barotropic, wavelike pattern. The LIM’s ability to reproduce the observed blocking evolution suggests the predictable evolution of blocking on weekly time scales can be modeled in a linear framework, and that subseasonal forecasting of North Pacific blocking needs to consider both tropical and extratropical conditions.

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Brett T. Hoover, David A. Santek, Anne-Sophie Daloz, Yafang Zhong, Richard Dworak, Ralph A. Petersen, and Andrew Collard

Abstract

Automated aircraft observations of wind and temperature have demonstrated positive impact on numerical weather prediction since the mid-1980s. With the advent of the Water Vapor Sensing System (WVSS-II) humidity sensor, the expanding fleet of commercial aircraft with onboard automated sensors is also capable of delivering high quality moisture observations, providing vertical profiles of moisture as aircraft ascend out of and descend into airports across the continental United States. Observations from the WVSS-II have to date only been monitored within the Global Data Assimilation System (GDAS) without being assimilated. In this study, aircraft moisture observations from the WVSS-II are assimilated into the GDAS, and their impact is assessed in the Global Forecast System (GFS). A two-season study is performed, demonstrating a statistically significant positive impact on both the moisture forecast and the precipitation forecast at short range (12–36 h) during the warm season. No statistically significant impact is observed during the cold season.

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Matthew A. Lazzara, Richard Dworak, David A. Santek, Brett T. Hoover, Christopher S. Velden, and Jeffrey R. Key

Abstract

Atmospheric motion vectors (AMVs) are derived from satellite-observed motions of clouds and water vapor features. They provide crucial information in regions void of conventional observations and contribute to forecaster diagnostics of meteorological conditions, as well as numerical weather prediction. AMVs derived from geostationary (GEO) satellite observations over the middle latitudes and tropics have been utilized operationally since the 1980s; AMVs over the polar regions derived from low‐earth (polar)‐orbiting (LEO) satellites have been utilized since the early 2000s. There still exists a gap in AMV coverage between these two sources in the latitude band poleward of 60° and equatorward of 70° (both hemispheres). To address this AMV gap, the use of a novel approach to create image sequences that consist of composites derived from a combination of LEO and GEO observations that extend into the deep middle latitudes is explored. Experiments are performed to determine whether the satellite composite images can be employed to generate AMVs over the gap regions. The derived AMVs are validated over both the Southern Ocean/Antarctic and the Arctic gap regions over a multiyear period using rawinsonde wind observations. In addition, a two-season numerical model impact study using the Global Forecast System indicates that the assimilation of these AMVs can improve upon the control (operational) forecasts, particularly during lower-skill (dropout) events.

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