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1. Spatiotemporal evolution of COVID-19 infection and detection within night light networks: comparative analysis of USA and China

   https://doi.org/10.1007/s41109-020-00345-4  

   Small, Christopher ; Sousa, Daniel ( February 2021 , Applied Network Science)

   The spatial distribution of population affects disease transmission, especially when shelter in place orders restrict mobility for a large fraction of the population. The spatial network structure of settlements therefore imposes a fundamental constraint on the spatial distribution of the population through which a communicable disease can spread. In this analysis we use the spatial network structure of lighted development as a proxy for the distribution of ambient population to compare the spatiotemporal evolution of COVID-19 confirmed cases in the USA and China. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band sensor on the NASA/NOAA Suomi satellite has been imaging night light at ~ 700 m resolution globally since 2012. Comparisons with sub-kilometer resolution census observations in different countries across different levels of development indicate that night light luminance scales with population density over ~ 3 orders of magnitude. However, VIIRS’ constant ~ 700 m resolution can provide a more detailed representation of population distribution in peri-urban and rural areas where aggregated census blocks lack comparable spatial detail. By varying the low luminance threshold of VIIRS-derived night light, we depict spatial networks of lighted development of varying degrees of connectivity within which populations are distributed. The resulting size distributions of spatial network components (connected clusters of nodes) vary with degree of connectivity, but maintain consistent scaling over a wide range (5 × to 10 × in area & number) of network sizes. At continental scales, spatial network rank-size distributions obtained from VIIRS night light brightness are well-described by power laws with exponents near −2 (slopes near −1) for a wide range of low luminance thresholds. The largest components (10⁴to 10⁵km²) represent spatially contiguous agglomerations of urban, suburban and periurban development, while the smallest components represent isolated rural settlements. Projecting county and city-level numbers of confirmed cases of COVID-19 for the USA and China (respectively) onto the corresponding spatial networks of lighted development allows the spatiotemporal evolution of the epidemic (infection and detection) to be quantified as propagation within networks of varying connectivity. Results for China show rapid nucleation and diffusion in January 2020 followed by rapid decreases in new cases in February. While most of the largest cities in China showed new confirmed cases approaching zero before the end of February, most of these cities also showed distinct second waves of cases in March or April. Whereas new cases in Wuhan did not approach zero until mid-March, as of December 2020 it has not yet experienced a second wave of cases. In contrast, the results for the USA show a wide range of trajectories, with an abrupt transition from slow increases in confirmed cases in a small number of network components in January and February, to rapid geographic dispersion to a larger number of components shortly before mobility reductions occurred in March. Results indicate that while most of the upper tail of the network had been exposed by the end of March, the lower tail of the component size distribution has only shown steep increases since mid-June.

    

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2. Modelling of the tsunami from the December 22, 2018 lateral collapse of Anak Krakatau volcano in the Sunda Straits, Indonesia

   https://doi.org/10.1038/s41598-019-48327-6  

   Grilli, Stephan T. ; Tappin, David R. ; Carey, Steven ; Watt, Sebastian F. L. ; Ward, Steve N. ; Grilli, Annette R. ; Engwell, Samantha L. ; Zhang, Cheng ; Kirby, James T. ; Schambach, Lauren ; et al ( August 2019 , Scientific Reports)

   On Dec. 22, 2018, at approximately 20:55–57 local time, Anak Krakatau volcano, located in the Sunda Straits of Indonesia, experienced a major lateral collapse during a period of eruptive activity that began in June. The collapse discharged volcaniclastic material into the 250 m deep caldera southwest of the volcano, which generated a tsunami with runups of up to 13 m on the adjacent coasts of Sumatra and Java. The tsunami caused at least 437 fatalities, the greatest number from a volcanically-induced tsunami since the catastrophic explosive eruption of Krakatau in 1883 and the sector collapse of Ritter Island in 1888. For the first time in over 100 years, the 2018 Anak Krakatau event provides an opportunity to study a major volcanically-generated tsunami that caused widespread loss of life and significant damage. Here, we present numerical simulations of the tsunami, with state-of the-art numerical models, based on a combined landslide-source and bathymetric dataset. We constrain the geometry and magnitude of the landslide source through analyses of pre- and post-event satellite images and aerial photography, which demonstrate that the primary landslide scar bisected the Anak Krakatau volcano, cutting behind the central vent and removing 50% of its subaerial extent. Estimated submarine collapse geometries result in a primary landslide volume range of 0.22–0.30 km³, which is used to initialize a tsunami generation and propagation model with two different landslide rheologies (granular and fluid). Observations of a single tsunami, with no subsequent waves, are consistent with our interpretation of landslide failure in a rapid, single phase of movement rather than a more piecemeal process, generating a tsunami which reached nearby coastlines within ~30 minutes. Both modelled rheologies successfully reproduce observed tsunami characteristics from post-event field survey results, tide gauge records, and eyewitness reports, suggesting our estimated landslide volume range is appropriate. This event highlights the significant hazard posed by relatively small-scale lateral volcanic collapses, which can occuren-masse, without any precursory signals, and are an efficient and unpredictable tsunami source. Our successful simulations demonstrate that current numerical models can accurately forecast tsunami hazards from these events. In cases such as Anak Krakatau’s, the absence of precursory warning signals together with the short travel time following tsunami initiation present a major challenge for mitigating tsunami coastal impact.

    

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3. Active ocean–continent transform margins: seismic investigation of the Cayman Trough-Swan Island ridge-transform intersection

   https://doi.org/10.1093/gji/ggac019  

   Peirce, C. ; Grevemeyer, I. ; Hayman, N. W. ; Van Avendonk, H. J. A. ( January 2022 , Geophysical Journal International)

   The southern boundary of the Cayman Trough in the Caribbean is marked by the Swan Islands transform fault (SITF), which also represents the ocean–continent transition of the Honduras continental margin. This is one of the few places globally where a transform continental margin is currently active. The CAYSEIS experiment acquired an ∼165-km-long seismic refraction and gravity profile (P01) running across this transform margin, and along the ridge-axis of the Mid-Cayman Spreading Centre (MCSC) to the north. This profile reveals not only the crustal structure of an actively evolving transform continental margin, that juxtaposes Mesozoic-age continental crust to the south against zero-age ultraslow spread oceanic crust to the north, but also the nature of the crust and uppermost mantle beneath the ridge-transform intersection (RTI). The traveltimes of arrivals recorded by ocean-bottom seismographs (OBSs) deployed along-profile have been inverse and forward modelled, in combination with gravity modelling, to reveal an ∼25-km-thick continental crust that has been continuously thinned over a distance of ∼65 km to ∼10 km adjacent to the SITF, where it is juxtaposed against ∼3–4-km-thick oceanic crust. This thinning is primarily accommodated within the lower crust. Since Moho reflections are only sparsely observed, and, even then, only by a few OBSs located on the continental margin, the 7.5 km s–1 velocity contour is used as a proxy to locate the crust–mantle boundary along-profile. Along the MCSC, the crust–mantle boundary appears to be a transition zone, at least at the seismic wavelengths used for CAYSEIS data acquisition. Although the traveltime inversion only directly constrains the upper crust at the SITF, gravity modelling suggests that it is underlain by a higher density (>3000 kg m–3) region spanning the width (∼15 km) of its bathymetric expression, that may reflect a broad region of metasomatism, mantle hydration or melt-depleted lithospheric mantle. At the MCSC ridge-axis to the north, the oceanic crust appears to be forming in zones, where each zone is defined by the volume of its magma supply. The ridge tip adjacent to the SITF is currently in a magma rich phase of accretion. However, there is no evidence for melt leakage into the transform zone. The width and crustal structure of the SITF suggests its motion is currently predominantly orthogonal to spreading. Comparison to CAYSEIS Profile P04, located to the west and running across-margin and through 10 Ma MCSC oceanic crust, suggests that, at about this time, motion along the SITF had a left-lateral transtensional component, that accounts for its apparently broad seabed appearance westwards.

    

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4. Basal Accretion Along the South Central Chilean Margin and Its Relationship to Great Earthquakes

   https://doi.org/10.1029/2020JB019861  

   Bangs, N. L. ; Morgan, J. K. ; Tréhu, A. M. ; Contreras‐Reyes, E. ; Arnulf, A. F. ; Han, S. ; Olsen, K. M. ; Zhang, E. ( October 2020 , Journal of Geophysical Research: Solid Earth)

   The south central Chilean margin regularly produces many of the world's largest earthquakes and tsunami, including the 2010Mw8.8 Maule and 1960Mw9.5 Valdivia events. In 2017, we acquired seismic reflection data along ~1,000 km of the margin using the R/VLangseth's 15 km long receiver array and 108.2 l (6,600 in³) seismic source to image structures associated with these ruptures. We focus on the Valdivia segment with the largest coseismic slip (~40 m). The outer 40 km of the forearc is an accretionary wedge constructed primarily of stacked sedimentary packages with irregular lengths and thicknesses and little along‐strike continuity. Forearc structures indicate that the accretionary wedge grows primarily through basal accretion of the downgoing trench fill. The décollement propagates along a weak boundary near the top of the trench fill but occasionally branches downward into the underthrust sediment along bedding horizons, peeling off slices that are underplated to the forearc. The shallow décollement level and the rarity of underplating events allow most of the trench sediment to subduct. As a result, only ~30% of the incoming sediment has been accreted since the Early Pliocene. This implies that, on average, ~1 km of sediment must subduct beyond the outer forearc, an inference that is supported by our seismic images. We propose that the thickness and great downdip and along‐strike extent of the underthrust layer, which separates the megathrust from the underlying roughness of the igneous ocean crust, ensures a smooth broad zone of strong coupling that generates the world's largest earthquakes and tsunami.

    

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5. Spatiotemporal evolution of COVID-19 infection and detection within night light networks: comparative analysis of USA and China

   https://doi.org/10.1007/s41109‐020‐00345‐4  

   Small, Christopher ; Sousa, Daniel ( December 2021 , Applied Network Science)

   null (Ed.)

   Abstract The spatial distribution of population affects disease transmission, especially when shelter in place orders restrict mobility for a large fraction of the population. The spatial network structure of settlements therefore imposes a fundamental constraint on the spatial distribution of the population through which a communicable disease can spread. In this analysis we use the spatial network structure of lighted development as a proxy for the distribution of ambient population to compare the spatiotemporal evolution of COVID-19 confirmed cases in the USA and China. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band sensor on the NASA/NOAA Suomi satellite has been imaging night light at ~ 700 m resolution globally since 2012. Comparisons with sub-kilometer resolution census observations in different countries across different levels of development indicate that night light luminance scales with population density over ~ 3 orders of magnitude. However, VIIRS’ constant ~ 700 m resolution can provide a more detailed representation of population distribution in peri-urban and rural areas where aggregated census blocks lack comparable spatial detail. By varying the low luminance threshold of VIIRS-derived night light, we depict spatial networks of lighted development of varying degrees of connectivity within which populations are distributed. The resulting size distributions of spatial network components (connected clusters of nodes) vary with degree of connectivity, but maintain consistent scaling over a wide range (5 × to 10 × in area & number) of network sizes. At continental scales, spatial network rank-size distributions obtained from VIIRS night light brightness are well-described by power laws with exponents near −2 (slopes near −1) for a wide range of low luminance thresholds. The largest components (10 4 to 10 5 km 2 ) represent spatially contiguous agglomerations of urban, suburban and periurban development, while the smallest components represent isolated rural settlements. Projecting county and city-level numbers of confirmed cases of COVID-19 for the USA and China (respectively) onto the corresponding spatial networks of lighted development allows the spatiotemporal evolution of the epidemic (infection and detection) to be quantified as propagation within networks of varying connectivity. Results for China show rapid nucleation and diffusion in January 2020 followed by rapid decreases in new cases in February. While most of the largest cities in China showed new confirmed cases approaching zero before the end of February, most of these cities also showed distinct second waves of cases in March or April. Whereas new cases in Wuhan did not approach zero until mid-March, as of December 2020 it has not yet experienced a second wave of cases. In contrast, the results for the USA show a wide range of trajectories, with an abrupt transition from slow increases in confirmed cases in a small number of network components in January and February, to rapid geographic dispersion to a larger number of components shortly before mobility reductions occurred in March. Results indicate that while most of the upper tail of the network had been exposed by the end of March, the lower tail of the component size distribution has only shown steep increases since mid-June. 

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