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15 result(s) for "Quinting, Julian F."
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On the Impact of Tropical Cyclones on Rossby Wave Packets: A Climatological Perspective
Many studies have highlighted the importance of recurving tropical cyclones (TCs) in triggering Rossby waves. This study investigates the impact of western North Pacific (WNP), south Indian Ocean, and North Atlantic recurving TCs on the amplitude and frequency of synoptic-scale Rossby wave packets (RWPs) over a 30-yr period. The results indicate a significant increase of RWP frequency downstream of WNP and south Indian Ocean TCs. A statistically significant RWP amplitude anomaly downstream of these TCs suggests that RWPs, which are associated with TCs, are stronger than those that generally occur in midlatitudes. North Atlantic TCs do not seem to be associated with a statistically significant increase in RWP frequency and amplitude downstream. Processes that contribute to Rossby wave amplification are identified by creating composites for WNP TCs with and without downstream development. Potential vorticity, eddy kinetic energy, and quasigeostrophic forcing diagnostics highlight dynamical mechanisms that contribute to the synergistic interaction between the TC and the midlatitude flow. The existence of an upstream Rossby wave favors a downstream development. Diabatically enhanced upper-level divergent flow that can be attributed to the nonlinear interaction between the TC and the midlatitude flow impedes the eastward propagation of the upstream trough, amplifies the downstream ridge, and intensifies the jet. The amplified midlatitude flow provides upper-level forcing, which helps to maintain the predominantly diabatically driven divergent flow. Forecast uncertainties that are related to these complex TC–midlatitude flow interactions may spread into downstream regions. A climatological analysis of ensemble reforecast data emphasizes the importance of TC–midlatitude flow interactions and Rossby wave amplification on downstream predictability.
The Extratropical Transition of Tropical Cyclones. Part I: Cyclone Evolution and Direct Impacts
Extratropical transition (ET) is the process by which a tropical cyclone, upon encountering a baroclinic environment and reduced sea surface temperature at higher latitudes, transforms into an extratropical cyclone. This process is influenced by, and influences, phenomena from the tropics to the midlatitudes and from the meso- to the planetary scales to extents that vary between individual events. Motivated in part by recent high-impact and/or extensively observed events such as North Atlantic Hurricane Sandy in 2012 and western North Pacific Typhoon Sinlaku in 2008, this review details advances in understanding and predicting ET since the publication of an earlier review in 2003. Methods for diagnosing ET in reanalysis, observational, and model-forecast datasets are discussed. New climatologies for the eastern North Pacific and southwest Indian Oceans are presented alongside updates to western North Pacific and North Atlantic Ocean climatologies. Advances in understanding and, in some cases, modeling the direct impacts of ET-related wind, waves, and precipitation are noted. Improved understanding of structural evolution throughout the transformation stage of ET fostered in large part by novel aircraft observations collected in several recent ET events is highlighted. Predictive skill for operational and numerical model ET-related forecasts is discussed along with environmental factors influencing posttransition cyclone structure and evolution. Operational ET forecast and analysis practices and challenges are detailed. In particular, some challenges of effective hazard communication for the evolving threats posed by a tropical cyclone during and after transition are introduced. This review concludes with recommendations for future work to further improve understanding, forecasts, and hazard communication.
Toward a Systematic Evaluation of Warm Conveyor Belts in Numerical Weather Prediction and Climate Models. Part II: Verification of Operational Reforecasts
Warm conveyor belts (WCBs) associated with extratropical cyclones transport air from the lower troposphere into the tropopause region and contribute to upper-level ridge building and the formation of blocking anticyclones. Recent studies indicate that this constitutes an important source and magnifier of forecast uncertainty and errors in numerical weather prediction (NWP) models. However, a systematic evaluation of the representation of WCBs in NWP models has yet to be determined. Here, we employ the logistic regression models developed in Part I to identify the inflow, ascent, and outflow stages of WCBs in the European Centre for Medium-Range Weather Forecasts (ECMWF) subseasonal reforecasts for Northern Hemisphere winter in the period January 1997 to December 2017. We verify the representation of these WCB stages in terms of systematic occurrence frequency biases, forecast reliability, and forecast skill. Systematic WCB frequency biases emerge already at early lead times of around 3 days with an underestimation for the WCB outflow over the North Atlantic and eastern North Pacific of around 40% relative to climatology. Biases in the predictor variables of the logistic regression models can partially explain these biases in WCB inflow, ascent, or outflow. Despite an overconfidence in predicting high WCB probabilities, skillful WCB forecasts are on average possible up to a lead time of 8–10 days with more skill over the North Pacific compared to the North Atlantic region. Our results corroborate that the current limited forecast skill for the large-scale extratropical circulation on subseasonal time scales beyond 10 days might be tied to the representation of WCBs and associated upscale error growth.
EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models - Part 1: Development of deep learning model
Physical processes on the synoptic scale are important modulators of the large-scale extratropical circulation. In particular, rapidly ascending airstreams in extratropical cyclones, so-called warm conveyor belts (WCBs), modulate the upper-tropospheric Rossby wave pattern and are sources and magnifiers of forecast uncertainty. Thus, from a process-oriented perspective, numerical weather prediction (NWP) and climate models should adequately represent WCBs. The identification of WCBs usually involves Lagrangian air parcel trajectories that ascend from the lower to the upper troposphere within 2 d. This requires expensive computations and numerical data with high spatial and temporal resolution, which are often not available from standard output. This study introduces a novel framework that aims to predict the footprints of the WCB inflow, ascent, and outflow stages over the Northern Hemisphere from instantaneous gridded fields using convolutional neural networks (CNNs). With its comparably low computational costs and relying on standard model output alone, the new diagnostic enables the systematic investigation of WCBs in large data sets such as ensemble reforecast or climate model projections, which are mostly not suited for trajectory calculations. Building on the insights from a logistic regression approach of a previous study, the CNNs are trained using a combination of meteorological parameters as predictors and trajectory-based WCB footprints as predictands. Validation of the networks against the trajectory-based data set confirms that the CNN models reliably replicate the climatological frequency of WCBs as well as their footprints at instantaneous time steps. The CNN models significantly outperform previously developed logistic regression models. Including time-lagged information on the occurrence of WCB ascent as a predictor for the inflow and outflow stages further improves the models' skill considerably. A companion study demonstrates versatile applications of the CNNs in different data sets including the verification of WCBs in ensemble forecasts. Overall, the diagnostic demonstrates how deep learning methods may be used to investigate the representation of weather systems and their related processes in NWP and climate models in order to shed light on forecast uncertainty and systematic biases from a process-oriented perspective.
The Extratropical Transition of Tropical Cyclones. Part II: Interaction with the Midlatitude Flow, Downstream Impacts, and Implications for Predictability
The extratropical transition (ET) of tropical cyclones often has an important impact on the nature and predictability of the midlatitude flow. This review synthesizes the current understanding of the dynamical and physical processes that govern this impact and highlights the relationship of downstream development during ET to high-impact weather, with a focus on downstream regions. It updates a previous review from 2003 and identifies new and emerging challenges and future research needs. First, the mechanisms through which the transitioning cyclone impacts the midlatitude flow in its immediate vicinity are discussed. This “direct impact” manifests in the formation of a jet streak and the amplification of a ridge directly downstream of the cyclone. This initial flow modification triggers or amplifies a midlatitude Rossby wave packet, which disperses the impact of ET into downstream regions (downstream impact) and may contribute to the formation of high-impact weather. Details are provided concerning the impact of ET on forecast uncertainty in downstream regions and on the impact of observations on forecast skill. The sources and characteristics of the following key features and processes that may determine the manifestation of the impact of ET on the midlatitude flow are discussed: the upper-tropospheric divergent outflow, mainly associated with latent heat release in the troposphere below, and the phasing between the transitioning cyclone and the midlatitude wave pattern. Improving the representation of diabatic processes during ET in models and a climatological assessment of the ET’s impact on downstream high-impact weather are examples for future research directions.
EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models - Part 2: Model application to different datasets
Warm conveyor belts (WCBs) affect the atmospheric dynamics in midlatitudes and are highly relevant for total and extreme precipitation in many parts of the extratropics. Thus, these airstreams and their effect on midlatitude weather should be well represented in numerical weather prediction (NWP) and climate models. This study applies newly developed convolutional neural network (CNN) models which allow the identification of footprints of WCB inflow, ascent, and outflow from a limited number of predictor fields at comparably low spatiotemporal resolution. The goal of the study is to demonstrate the versatile applicability of the CNN models to different datasets and that their application yields qualitatively and quantitatively similar results as their trajectory-based counterpart, which is most frequently used to objectively identify WCBs. The trajectory-based approach requires data at higher spatiotemporal resolution, which are often not available, and is computationally more expensive. First, an application to reanalyses reveals that the well-known relationship between WCB ascent and extratropical cyclones as well as between WCB outflow and blocking anticyclones is also found for WCB footprints identified with the CNN models. Second, the application to Japanese 55-year reanalyses shows how the CNN models may be used to identify erroneous predictor fields that deteriorate the models' reliability. Third, a verification of WCBs in operational European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasts for three Northern Hemisphere winters reveals systematic biases over the North Atlantic with both the trajectory-based approach and the CNN models. The ensemble forecasts' skill tends to be lower when being evaluated with the trajectory approach due to the fine-scale structure of WCB footprints in comparison to the rather smooth CNN-based WCB footprints. A final example demonstrates the applicability of the CNN models to a convection-permitting simulation with the ICOsahedral Nonhydrostatic (ICON) NWP model. Our study illustrates that deep learning methods can be used efficiently to support process-oriented understanding of forecast error and model biases and opens numerous directions for future research.
The Future of Midlatitude Cyclones
Purpose of Review This review brings together recent research on the structure, characteristics, dynamics, and impacts of extratropical cyclones in the future. It draws on research using idealized models and complex climate simulations, to evaluate what is known and unknown about these future changes. Recent Findings There are interacting processes that contribute to the uncertainties in future extratropical cyclone changes, e.g., changes in the horizontal and vertical structure of the atmosphere and increasing moisture content due to rising temperatures. Summary While precipitation intensity will most likely increase, along with associated increased latent heating, it is unclear to what extent and for which particular climate conditions this will feedback to increase the intensity of the cyclones. Future research could focus on bridging the gap between idealized models and complex climate models, as well as better understanding of the regional impacts of future changes in extratropical cyclones.
What controls the formation of nocturnal low-level stratus clouds over southern West Africa during the monsoon season?
Nocturnal low-level stratus clouds (LLCs) are frequently observed in the atmospheric boundary layer (ABL) over southern West Africa (SWA) during the summer monsoon season. Considering the effect these clouds have on the surface energy and radiation budgets as well as on the diurnal cycle of the ABL, they are undoubtedly important for the regional climate. However, an adequate representation of LLCs in the state-of-the-art weather and climate models is still a challenge, which is largely due to the lack of high-quality observations in this region and gaps in understanding of underlying processes. In several recent studies, a unique and comprehensive data set collected in summer 2016 during the DACCIWA (Dynamics-aerosol-chemistry-cloud interactions in West Africa) ground-based field campaign was used for the first observational analyses of the parameters and physical processes relevant for the LLC formation over SWA. However, occasionally stratus-free nights occur during the monsoon season as well. Using observations and ERA5 reanalysis, we investigate differences in the boundary-layer conditions during 6 stratus-free and 20 stratus nights observed during the DACCIWA campaign. Our results suggest that the interplay between three major mechanisms is crucial for the formation of LLCs during the monsoon season: (i) the onset time and strength of the nocturnal low-level jet (NLLJ), (ii) horizontal cold-air advection, and (iii) background moisture level. Namely, weaker or later onset of NLLJ leads to a reduced contribution from horizontal cold-air advection. This in turn results in weaker cooling, and thus saturation is not reached. Such deviation in the dynamics of the NLLJ is related to the arrival of a cold air mass propagating northwards from the coast, called Gulf of Guinea maritime inflow. Additionally, stratus-free nights occur when the intrusions of dry air masses, originating from, for example, central or south Africa, reduce the background moisture over large parts of SWA. Backward-trajectory analysis suggests that another possible reason for clear nights is descending air, which originated from drier levels above the marine boundary layer.
Enhanced Tropospheric Wave Forcing of Two Anticyclones in the Prephase of the January 2009 Major Stratospheric Sudden Warming Event
Tropospheric forcing of planetary wavenumber 2 is examined in the prephase of the major stratospheric sudden warming event in January 2009 (MSSW 2009). Because of a huge increase in Eliassen–Palm fluxes induced mainly by wavenumber 2, easterly angular momentum is transported into the Arctic stratosphere, deposited, and then decelerates the polar night jet. In agreement with earlier studies, the results reveal that the strongest eddy heat fluxes, associated with wavenumber 2, occur at 100 hPa during the prephase of MSSW 2009 in ERA-Interim. In addition, moderate conditions of the cold phase of ENSO (La Niña) contribute to the eddy heat flux anomaly. It is shown that enhanced tropospheric wave forcing over Alaska and Scandinavia is caused by tropical processes in two ways. First, in a climatological sense, La Niña contributes to an enhanced anticyclonic flow over both regions. Second, the Madden–Julian oscillation (MJO) has an indirect influence on the Alaskan ridge by enhancing eddy activity over the North Pacific. This is manifested in an increase in cyclone frequency and associated warm conveyor belt outflow, which contribute to the maintenance and amplification of the Alaskan anticyclone. The Scandinavian ridge is maintained by wave trains emanating from the Alaskan ridge propagating eastward, including an enhanced transport of eddy kinetic energy. The MSSW 2009 is an extraordinary case of how a beneficial phasing of La Niña and MJO conditions together with multiscale interactions enhances tropospheric forcing for wavenumber 2–induced zonal mean eddy heat flux in the lower stratosphere.
Structural Characteristics of T-PARC Typhoon Sinlaku during Its Extratropical Transition
The structure and the environment of Typhoon Sinlaku (2008) were investigated during its life cycle in The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). On 20 September 2008, during the transformation stage of Sinlaku’s extratropical transition (ET), research aircraft equipped with dual-Doppler radar and dropsondes documented the structure of the convection surrounding Sinlaku and low-level frontogenetical processes. The observational data obtained were assimilated with the recently developed Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) software tool. The resulting analysis provides detailed insight into the ET system and allows specific features of the system to be identified, including deep convection, a stratiform precipitation region, warm- and cold-frontal structures, and a dry intrusion. The analysis offers valuable information about the interaction of the features identified within the transitioning tropical cyclone. The existence of dry midlatitude air above warm-moist tropical air led to strong potential instability. Quasigeostrophic diagnostics suggest that forced ascent during warm frontogenesis triggered the deep convective development in this potentially unstable environment. The deep convection itself produced a positive potential vorticity anomaly at midlevels that modified the environmental flow. A comparison of the operational ECMWF analysis and the observation-based SAMURAI analysis exhibits important differences. In particular, the ECMWF analysis does not capture the deep convection adequately. The nonexistence of the deep convection has considerable implications on the potential vorticity structure of the remnants of the typhoon at midlevels. An inaccurate representation of the thermodynamic structure of the dry intrusion has considerable implications on the frontogenesis and the quasigeostrophic forcing.