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Abstract We use high temporal‐resolution mesoscale imagery from the Geostationary Operational Environmental Satellite‐R (GOES‐R) series to track the Lamb and gravity waves generated by the 15 January 2022 Hunga Tonga‐Hunga Ha'apai eruption. The 1‐min cadence of these limited area (∼1,000×1,000 km²) brightness temperatures ensures an order of magnitude better temporal sampling than full‐disk imagery available at 10‐min or 15‐min cadence. The wave patterns are visualized in brightness temperature image differences, which represent the time derivative of the full waveform with the level of temporal aliasing being determined by the imaging cadence. Consequently, the mesoscale data highlight short‐period variations, while the full‐disk data capture the long‐period wave packet envelope. The full temperature anomaly waveform, however, can be reconstructed reasonably well from the mesoscale waveform derivatives. The reconstructed temperature anomaly waveform essentially traces the surface pressure anomaly waveform. The 1‐min imagery reveals waves with ∼40–80 km wavelengths, which trail the primary Lamb pulse emitted at ∼04:29 UTC. Their estimated propagation speed is ∼315 ± 15 m s⁻¹, resulting in typical periods of 2.1–4.2 min. Weaker Lamb waves were also generated by the last major eruption at ∼08:40–08:45 UTC, which were, however, only identified in the near field but not in the far field. We also noted wind effects such as mean flow advection in the propagation of concentric gravity wave rings and observed gravity waves traveling near their theoretical maximum speed. 

Abstract Atmospheric predictability from subseasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds, and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model intercomparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations, and formulates recommendations on how to proceed from there. 

Abstract ObjectivesSeveral theories have been proposed to explain the impact of ecological conditions on differences in life history variables within and between species. Here we compare female life history parameters of one western lowland gorilla population(Gorilla gorilla gorilla) and two mountain gorilla populations(Gorilla beringei beringei). Materials and MethodsWe compared the age of natal dispersal, age of first birth, interbirth interval, and birth rates using long‐term demographic datasets from Mbeli Bai (western gorillas), Bwindi Impenetrable National Park and the Virunga Massif (mountain gorillas). ResultsThe Mbeli western gorillas had the latest age at first birth, longest interbirth interval, and slowest surviving birth rate compared to the Virunga mountain gorillas. Bwindi mountain gorillas were intermediate in their life history patterns. DiscussionThese patterns are consistent with differences in feeding ecology across sites. However, it is not possible to determine the evolutionary mechanisms responsible for these differences, whether a consequence of genetic adaptation to fluctuating food supplies (“ecological risk aversion hypothesis”) or phenotypic plasticity in response to the abundance of food (“energy balance hypothesis”). Our results do not seem consistent with the extrinsic mortality risks at each site, but current conditions for mountain gorillas are unlikely to match their evolutionary history. Not all traits fell along the expected fast‐slow continuum, which illustrates that they can vary independently from each other (“modularity model”). Thus, the life history traits of each gorilla population may reflect a complex interplay of multiple ecological influences that are operating through both genetic adaptations and phenotypic plasticity. 

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.