It is often assumed that future coastal cliff retreat rates will accelerate as global sea level rises, but few studies have investigated how SLR (sea level rise) might change cliff-front wave dynamics. Using a new simple numerical model, this study simulates the number and type (breaking, broken, or unbroken) of cliff-front waves under future SLR scenarios. Previous research shows breaking waves deliver more energy to cliffs than broken waves, and unbroken waves generate minimal impact. Here, we investigated six cliff-platform profiles from three regions (USA, New Zealand, and UK) with varied tidal ranges and wave climates. Model inputs included 2013–2100 hindcast/forecast incident wave height and tidal water level, and three future SLR scenarios. Results show the number of both cliff-front breaking and broken waves generally increase for a high-elevation (relative to tide) cliff-platform junction. In contrast, breaking/broken wave occurrence decrease by 38–92% for a near-horizontal shore platform with a low-elevation cliff-platform junction under a high SRL scenario, leading to high (96–97%) unbroken wave occurrence. Overall, results suggest the response of cliff-front waves to future SLR is complex and depends on shore platform geometries and SLR scenarios, indicating that future cliff retreat rates may not homogeneously accelerate under SLR.

We present high spatial resolution (2.3"x1.9" or 43 pc x 36 pc at D = 3.9 Mpc) 100 GHz millimeter-wave continuum emission observations with the Nobeyama Millimeter Array toward an expanding molecular superbubble in the central region of M82. The 100 GHz continuum image, which is dominated by free-free emission, revealed that the four strongest peaks are concentrated at the inner edge of the superbubble along the galactic disk. The production rates of Lyman continuum photons calculated from 100 GHz continuum flux at these peaks are an order of magnitude higher than those from the most massive star forming regions in our Galaxy. At these regions, high velocity ionized gas (traced by H41a and [Ne II]) can be seen, and H2O and OH masers are also concentrated. The center of the superbubble, on the other hand, is weak in molecular and free-free emissions and strong in diffuse hard X-ray emission. These observations suggest that a strong starburst produced energetic explosions and resultant plasma and superbubble expansions, and induced the present starburst regions traced by our 100 GHz continuum observations at the inner edge of the molecular superbubble. These results, therefore, provide the first clear evidence of self-induced starburst in external galaxies. Starburst at the center of the superbubble, on the other hand, begins to cease because of a lack of molecular gas. This kind of intense starburst seems to have occurred several times within 10^6-10^7 years in the central region of M82.

Holocene marine terraces occur globally and record information about the timing and magnitude of past coseismic events. Staircased terraces develop through repetitive coseismic uplift of shore platforms, but are also subject to destruction from subsequent wave erosion and rock weathering. In this study we calibrate a rock coast evolution model using terrace field data from Mahia Peninsula, New Zealand, and use it to investigate how relative sea level (RSL) change influences Holocene terrace development. Analyses of 10,002 simulations reveal time periods of extremely rapid terrace creation and destruction as a result of shore platform development processes that are modulated both by episodic and gradual RSL change scenarios. Subtle differences in these scenarios give rise to completely different terrace sequences, even if coseismic event timing is held constant. Improved interpretation of Holocene terrace sequences require higher resolution paleo RSL data and chronological data on shore platform development.

We present the Suzaku results on a new candidate of a supernova remnant (SNR) in the Sagittarius C region. We detected diffuse X-rays of an elliptical shape (G359.41$-$0.12) and a chimney-like structure (the Chimney), both of which were fitted with a thin thermal the model of $k_{\rm B}T$$\sim$ 1 keV temperature. The absorption columns are same between these two structures, indicating that both are located at the same distance in the same line of sight. The narrow band image and one-dimensional profile of S xv K$\alpha$ at 2.45 keV show that the Chimney is emanating from G359.41$-$0.12. Therefore, these two sources are physically connected with each other. The sum of the thermal energies of the Chimney and G359.41$-$0.12 is estimated to be 1.4 $\times$ 10$^{50}$erg, typical for a galactic SNR. G359.41$-$0.12 is likely to be a new SNR candidate and the Chimney is an associated outflow.

Cobbles (64–256 mm) are found on beaches throughout the world, influence beach morphology, and can provide shoreline stability. Detailed, frequent, and spatially large-scale quantitative cobble observations at beaches are vital toward a better understanding of sand-cobble beach systems. This study used a truck-mounted mobile terrestrial LiDAR system and a raster-based classification approach to map cobbles automatically. Rasters of LiDAR intensity, intensity deviation, topographic roughness, and slope were utilized for cobble classification. Four machine learning techniques including maximum likelihood, decision tree, support vector machine, and k-nearest neighbors were tested on five raster resolutions ranging from 5–50 cm. The cobble mapping capability varied depending on pixel size, classification technique, surface cobble density, and beach setting. The best performer was a maximum likelihood classification using 20 cm raster resolution. Compared to manual mapping at 15 control sites (size ranging from a few to several hundred square meters), automated mapping errors were <12% (best fit line). This method mapped the spatial location of dense cobble regions more accurately compared to sparse and moderate density cobble areas. The method was applied to a ~40 km section of coast in southern California, and successfully generated temporal and spatial cobble distributions consistent with previous observations.