Waves to Weather (W2W)
Description:
This special collection comprises the results of the Collaborative Research Center “Waves to Weather” (W2W), which is funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) for a period of 4 years with possible extensions up to 12 years. The main topic of W2W is predictability and prediction of weather. The current scientific themes of W2W are "Upscale error growth", "Cloud-scale uncertainties", and "Predictability of local weather". It includes theoretical studies, numerical modeling, and process studies based in part on cutting edge statistical methods and visualization tools, NWP models and data collected during the field campaign NAWDEX.
The aim of W2W is to identify the limits of predictability of weather and to produce the best forecasts that are physically possible. The focus of W2W is on the most important causes of remaining uncertainties in weather prediction, which include:
- the quick upscale growth of forecast errors from insufficiently resolved or represented processes like convection or boundary layer mixing, which modify synoptic-scale waves,
- our limited understanding of processes in clouds, and
- the influence of local factors on weather that influence the predictability associated with larger-scale wave disturbances.
W2W addresses these three areas in a concerted effort involving contributions from the disciplines of atmospheric dynamics, cloud physics, statistics, inverse methods and visualization.
W2W uses, and further develops a broad range of tools, including numerical models with detailed treatment of cloud processes and aerosols, and ensemble forecasts with sophisticated statistical post-processing to describe uncertainty. Improved insight has already been gained through the development of new interactive visualization methods, that enable rapid exploration of forecast ensembles to identify the sources and evolution of uncertainty in meteorologically significant features, as well as through the unprecedented dataset collected during the international field campaign NAWDEX.
W2W currently consist of eighteen individual scientific projects located in Germany (Ludwig-Maximilians University of Munich, Karlsruhe Institute of Technology, Johannes Gutenberg University in Mainz, German Aerospace Center (DLR) Oberpfaffenhofen, and University of Heidelberg).
Collection organizers:
Audine Laurian and George C. Craig, Meteorological Institute, Ludwig-Maximilians University, Munich, Germany
Waves to Weather (W2W)
Abstract
Global model simulations together with a stochastic convection scheme are used to assess the intrinsic limit of predictability that originates from convection up to planetary scales. The stochastic convection scheme has been shown to introduce an appropriate amount of variability onto the model grid without the need to resolve the convection explicitly. This largely reduces computational costs and enables a set of 12 cases equally distributed over 1 year with five ensemble members for each case, generated by the stochastic convection scheme. As a metric, difference kinetic energy at 300 hPa over the midlatitudes, both north and south, is used. With this metric the intrinsic limit is estimated to be about 17 days when a threshold of 80% of the saturation level is applied. The error level at 3.5 days roughly compares to the initial-condition uncertainty of the current ECMWF data assimilation system, which suggests a potential improvement of 3.5 forecast days through perfecting the initial conditions. Error-growth experiments that use a deterministic convection scheme show smaller errors of about half the size at early forecast times and an estimate of intrinsic predictability that is about 10% longer, confirming the overconfidence of deterministic convection schemes.
Abstract
Global model simulations together with a stochastic convection scheme are used to assess the intrinsic limit of predictability that originates from convection up to planetary scales. The stochastic convection scheme has been shown to introduce an appropriate amount of variability onto the model grid without the need to resolve the convection explicitly. This largely reduces computational costs and enables a set of 12 cases equally distributed over 1 year with five ensemble members for each case, generated by the stochastic convection scheme. As a metric, difference kinetic energy at 300 hPa over the midlatitudes, both north and south, is used. With this metric the intrinsic limit is estimated to be about 17 days when a threshold of 80% of the saturation level is applied. The error level at 3.5 days roughly compares to the initial-condition uncertainty of the current ECMWF data assimilation system, which suggests a potential improvement of 3.5 forecast days through perfecting the initial conditions. Error-growth experiments that use a deterministic convection scheme show smaller errors of about half the size at early forecast times and an estimate of intrinsic predictability that is about 10% longer, confirming the overconfidence of deterministic convection schemes.
Abstract
Low-latitude rainfall variability on the daily to intraseasonal time scale is often related to tropical waves, including convectively coupled equatorial waves, the Madden–Julian oscillation (MJO), and tropical disturbances (TDs). Despite the importance of rainfall variability for vulnerable societies in tropical Africa, the relative influence of tropical waves for this region is largely unknown. This article presents the first systematic comparison of the impact of six wave types on precipitation over northern tropical Africa during the transition and full monsoon seasons, using two satellite products and a dense rain gauge network. Composites of rainfall anomalies in the different datasets show comparable modulation intensities in the West Sahel and at the Guinea Coast, varying from less than 2 to above 7 mm day−1 depending on the wave type. African easterly waves (AEWs) and Kelvin waves dominate the 3-hourly to daily time scale and explain 10%–30% locally. On longer time scales (7–20 days), only the MJO and equatorial Rossby (ER) waves remain as modulating factors and explain about up to one-third of rainfall variability. Eastward inertio-gravity waves and mixed Rossby–gravity (MRG) waves are comparatively unimportant. An analysis of wave superposition shows that low-frequency waves (MJO, ER) in their wet phase amplify the activity of high-frequency waves (TD, MRG) and suppress them in the dry phase. The results stress that more attention should be paid to tropical waves when forecasting rainfall over northern tropical Africa.
Abstract
Low-latitude rainfall variability on the daily to intraseasonal time scale is often related to tropical waves, including convectively coupled equatorial waves, the Madden–Julian oscillation (MJO), and tropical disturbances (TDs). Despite the importance of rainfall variability for vulnerable societies in tropical Africa, the relative influence of tropical waves for this region is largely unknown. This article presents the first systematic comparison of the impact of six wave types on precipitation over northern tropical Africa during the transition and full monsoon seasons, using two satellite products and a dense rain gauge network. Composites of rainfall anomalies in the different datasets show comparable modulation intensities in the West Sahel and at the Guinea Coast, varying from less than 2 to above 7 mm day−1 depending on the wave type. African easterly waves (AEWs) and Kelvin waves dominate the 3-hourly to daily time scale and explain 10%–30% locally. On longer time scales (7–20 days), only the MJO and equatorial Rossby (ER) waves remain as modulating factors and explain about up to one-third of rainfall variability. Eastward inertio-gravity waves and mixed Rossby–gravity (MRG) waves are comparatively unimportant. An analysis of wave superposition shows that low-frequency waves (MJO, ER) in their wet phase amplify the activity of high-frequency waves (TD, MRG) and suppress them in the dry phase. The results stress that more attention should be paid to tropical waves when forecasting rainfall over northern tropical Africa.
Abstract
Tropical cyclones that evolve from a nontropical origin and undergo tropical transition (TT) play a prominent role in cyclogenesis in the North Atlantic Ocean. They pose a special challenge for predictions, as they often emerge at the end of a multiscale cascade of atmospheric processes. Here we use operational European Centre for Medium-Range Weather Forecasts ensemble predictions to investigate the TT of North Atlantic Hurricane Chris (2012), whose formation was preceded by the merger of two potential vorticity (PV) maxima, eventually resulting in the cyclone-inducing PV streamer. The principal goal is to elucidate the dynamic and thermodynamic processes governing the predictability of Chris’s cyclogenesis and subsequent TT. Dynamic time warping is applied to identify ensemble tracks that are similar to the analysis track. This technique permits small temporal and spatial shifts in the development. The formation of the pre-Chris cyclone is predicted by those members that also predict the merging of the two PV maxima. The PV streamer’s shape and its position relative to the pre-Chris cyclone determine whether the cyclone follows the TT pathway. The transitioning cyclones are located inside a favorable region of high equivalent potential temperatures that result from a warm seclusion underneath the cyclonic roll-up of the PV streamer. A systematic investigation of consecutive ensemble forecasts indicates that sudden changes in ensemble statistics of cyclone metrics are linked to specific events. The present case exemplifies how a novel combination of Eulerian and cyclone-relative ensemble forecast analysis tools allow inference of physical causes of abrupt changes in predictability.
Abstract
Tropical cyclones that evolve from a nontropical origin and undergo tropical transition (TT) play a prominent role in cyclogenesis in the North Atlantic Ocean. They pose a special challenge for predictions, as they often emerge at the end of a multiscale cascade of atmospheric processes. Here we use operational European Centre for Medium-Range Weather Forecasts ensemble predictions to investigate the TT of North Atlantic Hurricane Chris (2012), whose formation was preceded by the merger of two potential vorticity (PV) maxima, eventually resulting in the cyclone-inducing PV streamer. The principal goal is to elucidate the dynamic and thermodynamic processes governing the predictability of Chris’s cyclogenesis and subsequent TT. Dynamic time warping is applied to identify ensemble tracks that are similar to the analysis track. This technique permits small temporal and spatial shifts in the development. The formation of the pre-Chris cyclone is predicted by those members that also predict the merging of the two PV maxima. The PV streamer’s shape and its position relative to the pre-Chris cyclone determine whether the cyclone follows the TT pathway. The transitioning cyclones are located inside a favorable region of high equivalent potential temperatures that result from a warm seclusion underneath the cyclonic roll-up of the PV streamer. A systematic investigation of consecutive ensemble forecasts indicates that sudden changes in ensemble statistics of cyclone metrics are linked to specific events. The present case exemplifies how a novel combination of Eulerian and cyclone-relative ensemble forecast analysis tools allow inference of physical causes of abrupt changes in predictability.
Abstract
Research on the mesoscale kinetic energy spectrum over the past few decades has focused on finding a dynamical mechanism that gives rise to a universal spectral slope. Here we investigate the variability of the spectrum using 3 years of kilometer-resolution analyses from COSMO configured for Germany (COSMO-DE). It is shown that the mesoscale kinetic energy spectrum is highly variable in time but that a minimum in variability is found on scales around 100 km. The high variability found on the small-scale end of the spectrum (around 10 km) is positively correlated with the precipitation rate where convection is a strong source of variance. On the other hand, variability on the large-scale end (around 1000 km) is correlated with the potential vorticity, as expected for geostrophically balanced flows. Accordingly, precipitation at small scales is more highly correlated with divergent kinetic energy, and potential vorticity at large scales is more highly correlated with rotational kinetic energy. The presented findings suggest that the spectral slope and amplitude on the mesoscale range are governed by an ever-changing combination of the upscale and downscale impacts of these large- and small-scale dynamical processes rather than by a universal, intrinsically mesoscale dynamical mechanism.
Abstract
Research on the mesoscale kinetic energy spectrum over the past few decades has focused on finding a dynamical mechanism that gives rise to a universal spectral slope. Here we investigate the variability of the spectrum using 3 years of kilometer-resolution analyses from COSMO configured for Germany (COSMO-DE). It is shown that the mesoscale kinetic energy spectrum is highly variable in time but that a minimum in variability is found on scales around 100 km. The high variability found on the small-scale end of the spectrum (around 10 km) is positively correlated with the precipitation rate where convection is a strong source of variance. On the other hand, variability on the large-scale end (around 1000 km) is correlated with the potential vorticity, as expected for geostrophically balanced flows. Accordingly, precipitation at small scales is more highly correlated with divergent kinetic energy, and potential vorticity at large scales is more highly correlated with rotational kinetic energy. The presented findings suggest that the spectral slope and amplitude on the mesoscale range are governed by an ever-changing combination of the upscale and downscale impacts of these large- and small-scale dynamical processes rather than by a universal, intrinsically mesoscale dynamical mechanism.
Abstract
The extratropical transition (ET) of tropical cyclones (TCs) can significantly influence the evolution of the midlatitude flow. However, the interaction between recurving TCs and upstream upper-level troughs features a large and partly unexplained case-to-case variability. In this study, a synoptic, feature-based climatology of TC–trough interactions is constructed to discriminate recurving TCs that interact with decelerating and accelerating troughs. Upper-level troughs reducing their eastward propagation speed during the interaction with recurving TCs exhibit phase locking with lower-level temperature anomalies and are linked to pronounced downstream Rossby wave amplification. Conversely, accelerating troughs do not exhibit phase locking and are associated with a nonsignificant downstream impact. Irrotational outflow near the tropopause associated with latent heat release in regions of heavy precipitation near the transitioning storm can promote phase locking (via enhancement of trough deceleration) and further enhance the downstream impact (via advection of air with low potential vorticity in the direction of the waveguide). These different impacts affect the probability of atmospheric blocking at the end of the Pacific storm track, which is generally higher if a TC–trough interaction occurs in the western North Pacific. Blocking in the eastern North Pacific is up to 3 times more likely than climatology if an interaction between a TC and a decelerating trough occurs upstream, whereas no statistical deviation with respect to climatology is observed for accelerating troughs. The outlined results support the hypothesis that differences in phase locking can explain the observed variability in the downstream impact of ET.
Abstract
The extratropical transition (ET) of tropical cyclones (TCs) can significantly influence the evolution of the midlatitude flow. However, the interaction between recurving TCs and upstream upper-level troughs features a large and partly unexplained case-to-case variability. In this study, a synoptic, feature-based climatology of TC–trough interactions is constructed to discriminate recurving TCs that interact with decelerating and accelerating troughs. Upper-level troughs reducing their eastward propagation speed during the interaction with recurving TCs exhibit phase locking with lower-level temperature anomalies and are linked to pronounced downstream Rossby wave amplification. Conversely, accelerating troughs do not exhibit phase locking and are associated with a nonsignificant downstream impact. Irrotational outflow near the tropopause associated with latent heat release in regions of heavy precipitation near the transitioning storm can promote phase locking (via enhancement of trough deceleration) and further enhance the downstream impact (via advection of air with low potential vorticity in the direction of the waveguide). These different impacts affect the probability of atmospheric blocking at the end of the Pacific storm track, which is generally higher if a TC–trough interaction occurs in the western North Pacific. Blocking in the eastern North Pacific is up to 3 times more likely than climatology if an interaction between a TC and a decelerating trough occurs upstream, whereas no statistical deviation with respect to climatology is observed for accelerating troughs. The outlined results support the hypothesis that differences in phase locking can explain the observed variability in the downstream impact of ET.
Aerosol Effects on Clouds and Precipitation over Central Europe in Different Weather RegimesAbstract
The response of clouds to changes in the aerosol concentration is complex and may differ depending on the cloud type, the aerosol regime, and environmental conditions. In this study, a novel technique is used to systematically modify the environmental conditions in realistic convection-resolving simulations for cases with weak and strong large-scale forcing over central Europe with the Consortium for Small-Scale Modeling (COSMO) model. Besides control runs with quasi-operational settings, initial and boundary temperature profiles are modified with linear increasing temperature increments from 0 to 5 K between 3 and 12 km AGL to represent different amounts of convective available potential energy (CAPE) and relative humidity. The results show a systematic decrease of total precipitation with increasing cloud condensation nuclei (CCN) concentrations for the cases with strong synoptic forcing caused by a suppressed warm-rain process, whereas no systematic aerosol effect is simulated for weak synoptic forcing. The effect of increasing CCN tends to be stronger in the simulations with increased temperatures and lower CAPE. While the large-scale domain-averaged responses to increased CCN are weak, the precipitation forming over mountainous terrain reveals a stronger sensitivity for most of the analyzed cases. Our findings also demonstrate that the role of the warm-rain process is more important for strong than for weak synoptic forcing. The aerosol effect is largest for weakly forced conditions but more predictable for the strongly forced cases. However, more accurate environmental conditions are much more important than accurate aerosol assumptions, especially for weak large-scale forcing.
Abstract
The response of clouds to changes in the aerosol concentration is complex and may differ depending on the cloud type, the aerosol regime, and environmental conditions. In this study, a novel technique is used to systematically modify the environmental conditions in realistic convection-resolving simulations for cases with weak and strong large-scale forcing over central Europe with the Consortium for Small-Scale Modeling (COSMO) model. Besides control runs with quasi-operational settings, initial and boundary temperature profiles are modified with linear increasing temperature increments from 0 to 5 K between 3 and 12 km AGL to represent different amounts of convective available potential energy (CAPE) and relative humidity. The results show a systematic decrease of total precipitation with increasing cloud condensation nuclei (CCN) concentrations for the cases with strong synoptic forcing caused by a suppressed warm-rain process, whereas no systematic aerosol effect is simulated for weak synoptic forcing. The effect of increasing CCN tends to be stronger in the simulations with increased temperatures and lower CAPE. While the large-scale domain-averaged responses to increased CCN are weak, the precipitation forming over mountainous terrain reveals a stronger sensitivity for most of the analyzed cases. Our findings also demonstrate that the role of the warm-rain process is more important for strong than for weak synoptic forcing. The aerosol effect is largest for weakly forced conditions but more predictable for the strongly forced cases. However, more accurate environmental conditions are much more important than accurate aerosol assumptions, especially for weak large-scale forcing.
Abstract
Extratropical transition (ET) can cause high-impact weather in midlatitude regions and therefore constitutes an ongoing threat at the end of a tropical cyclone’s (TC) life cycle. Most of the ET events occur over the ocean, but some TCs recurve and undergo ET along coastal regions; however, the latter category is less investigated. Typhoon Sinlaku (2008), for example, underwent ET along the southern coast of Japan. It was one of the typhoons that occurred during the T-PARC field campaign, providing unprecedented high-resolution observational data. Sinlaku is therefore an excellent case to investigate the impact of a coastal region, and in particular orography, on the evolution of ET. Here, observations from T-PARC are employed to verify high-resolution simulations of Sinlaku. In addition, a sensitivity simulation is performed with the orography of Japan removed. The presence of orography causes blocking of low-level, cool midlatitude air north of Japan. Without this inflow of cool air, ET is delayed. Only once Sinlaku moves away from the orographic barrier does the cool, dry environmental air penetrate equatorward, and ET continues. On a local scale, evaporatively cooled air from below Sinlaku’s asymmetric precipitation field could be advected toward the cyclone center when orography was favorable for it. Changes in the vortex structure, as known from mature TCs interacting with orography, were only minor due to the high translation speed during ET. This study corroborates that orography can impact ET by modulating both the synoptic-scale environmental conditions and the mesoscale cyclone structure during ET.
Abstract
Extratropical transition (ET) can cause high-impact weather in midlatitude regions and therefore constitutes an ongoing threat at the end of a tropical cyclone’s (TC) life cycle. Most of the ET events occur over the ocean, but some TCs recurve and undergo ET along coastal regions; however, the latter category is less investigated. Typhoon Sinlaku (2008), for example, underwent ET along the southern coast of Japan. It was one of the typhoons that occurred during the T-PARC field campaign, providing unprecedented high-resolution observational data. Sinlaku is therefore an excellent case to investigate the impact of a coastal region, and in particular orography, on the evolution of ET. Here, observations from T-PARC are employed to verify high-resolution simulations of Sinlaku. In addition, a sensitivity simulation is performed with the orography of Japan removed. The presence of orography causes blocking of low-level, cool midlatitude air north of Japan. Without this inflow of cool air, ET is delayed. Only once Sinlaku moves away from the orographic barrier does the cool, dry environmental air penetrate equatorward, and ET continues. On a local scale, evaporatively cooled air from below Sinlaku’s asymmetric precipitation field could be advected toward the cyclone center when orography was favorable for it. Changes in the vortex structure, as known from mature TCs interacting with orography, were only minor due to the high translation speed during ET. This study corroborates that orography can impact ET by modulating both the synoptic-scale environmental conditions and the mesoscale cyclone structure during ET.
Abstract
Upper-tropospheric Rossby wave packets (RWPs) are important dynamical features, because they are often associated with weather systems and sometimes act as precursors to high-impact weather. The present work introduces a novel diagnostic to identify RWPs and to quantify their amplitude. It is based on the local finite-amplitude wave activity (LWA) of Huang and Nakamura, which is generalized to the primitive equations in isentropic coordinates. The new diagnostic is applied to a specific episode containing large-amplitude RWPs and compared with a more traditional diagnostic based on the envelope of the meridional wind. In this case, LWA provides a more coherent picture of the RWPs and their zonal propagation. This difference in performance is demonstrated more explicitly in the framework of an idealized barotropic model simulation, where LWA is able to follow an RWP into its fully nonlinear stage, including cutoff formation and wave breaking, while the envelope diagnostic yields reduced amplitudes in such situations.
Abstract
Upper-tropospheric Rossby wave packets (RWPs) are important dynamical features, because they are often associated with weather systems and sometimes act as precursors to high-impact weather. The present work introduces a novel diagnostic to identify RWPs and to quantify their amplitude. It is based on the local finite-amplitude wave activity (LWA) of Huang and Nakamura, which is generalized to the primitive equations in isentropic coordinates. The new diagnostic is applied to a specific episode containing large-amplitude RWPs and compared with a more traditional diagnostic based on the envelope of the meridional wind. In this case, LWA provides a more coherent picture of the RWPs and their zonal propagation. This difference in performance is demonstrated more explicitly in the framework of an idealized barotropic model simulation, where LWA is able to follow an RWP into its fully nonlinear stage, including cutoff formation and wave breaking, while the envelope diagnostic yields reduced amplitudes in such situations.
Abstract
Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the parameters of a predictive distribution are estimated from a training period. We propose a flexible alternative based on neural networks that can incorporate nonlinear relationships between arbitrary predictor variables and forecast distribution parameters that are automatically learned in a data-driven way rather than requiring prespecified link functions. In a case study of 2-m temperature forecasts at surface stations in Germany, the neural network approach significantly outperforms benchmark postprocessing methods while being computationally more affordable. Key components to this improvement are the use of auxiliary predictor variables and station-specific information with the help of embeddings. Furthermore, the trained neural network can be used to gain insight into the importance of meteorological variables, thereby challenging the notion of neural networks as uninterpretable black boxes. Our approach can easily be extended to other statistical postprocessing and forecasting problems. We anticipate that recent advances in deep learning combined with the ever-increasing amounts of model and observation data will transform the postprocessing of numerical weather forecasts in the coming decade.
Abstract
Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the parameters of a predictive distribution are estimated from a training period. We propose a flexible alternative based on neural networks that can incorporate nonlinear relationships between arbitrary predictor variables and forecast distribution parameters that are automatically learned in a data-driven way rather than requiring prespecified link functions. In a case study of 2-m temperature forecasts at surface stations in Germany, the neural network approach significantly outperforms benchmark postprocessing methods while being computationally more affordable. Key components to this improvement are the use of auxiliary predictor variables and station-specific information with the help of embeddings. Furthermore, the trained neural network can be used to gain insight into the importance of meteorological variables, thereby challenging the notion of neural networks as uninterpretable black boxes. Our approach can easily be extended to other statistical postprocessing and forecasting problems. We anticipate that recent advances in deep learning combined with the ever-increasing amounts of model and observation data will transform the postprocessing of numerical weather forecasts in the coming decade.
Abstract
The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft, each with a sophisticated set of remote sensing and in situ instruments, and coordinated with a suite of ground-based measurements. A total of 49 research flights were performed, including, for the first time, coordinated flights of the four aircraft: the German High Altitude and Long Range Research Aircraft (HALO), the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 September to 22 October 2016 with frequently occurring extratropical and tropical cyclones was ideal for investigating midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, as well as their dynamic interaction with the jet stream, subsequent development, and eventual downstream weather impact on Europe. Examples are presented to highlight the wealth of phenomena that were sampled, the comprehensive coverage, and the multifaceted nature of the measurements. This unique dataset forms the basis for future case studies and detailed evaluations of weather and climate predictions to improve our understanding of diabatic influences on Rossby waves and the downstream impacts of weather systems affecting Europe.
Abstract
The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft, each with a sophisticated set of remote sensing and in situ instruments, and coordinated with a suite of ground-based measurements. A total of 49 research flights were performed, including, for the first time, coordinated flights of the four aircraft: the German High Altitude and Long Range Research Aircraft (HALO), the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 September to 22 October 2016 with frequently occurring extratropical and tropical cyclones was ideal for investigating midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, as well as their dynamic interaction with the jet stream, subsequent development, and eventual downstream weather impact on Europe. Examples are presented to highlight the wealth of phenomena that were sampled, the comprehensive coverage, and the multifaceted nature of the measurements. This unique dataset forms the basis for future case studies and detailed evaluations of weather and climate predictions to improve our understanding of diabatic influences on Rossby waves and the downstream impacts of weather systems affecting Europe.
