Current covers of AGU Journals. For older covers, see the archives of each journal. High resolution images are available in the issue information PDF of each issue.
Examples of mud volcanoes that responded to the main earthquakes of the Central
Italy seismic sequence. (a) Satellite image and (b) lateral view show the S.M. in Paganico mud volcano after the
Mw 6.5 earthquake of 30 October.
(c) N-S trending fractures controlling the surface mud extrusion of the Valle Corvone mud volcano after the 30 October earthqua
ke. (d) Lateral view of the newly formed Contrada S. Salvatore mud volcano, which erupted the day after the 30 October earthquake. (e) N-S trending fracture along the so-called Case Tedeschi 2bis mud volcano, a newly formed seep south of the Monteleone di Fermo village. (f ) Stereoplot showing the trend of ground fractures controlling mud volcanism. An average value of N355°±5°E/90° is taken as input parameter for the normal stress
Schematic showing how tabular icebergs are constructed using Lagrangian elements. (a) Hierarchy of ice elements’ physical structure: (i) Previous iceberg models represent icebergs using non-interacting point-particle elements; (ii) In the new framework ice elements are given finite extent so that they are able to interact with the ocean across multiple grid cells, and can interact with other elements; (iii) These finite extent elements can be joined together by numerical bonds (magenta lines) to form larger structures such as tabular icebergs. (b) Areal photograph of a tabular iceberg with elements superimposed over it to illustrate how the Lagrangian elements can be used to model tabular icebergs. In this schematic, the ice elements (purple dots) are initialized in a staggered lattice covering the surface area of the iceberg. For purposes of mass aggregation, the ice elements are assumed to have hexagonal shape (red hexagons). For purposes of element interactions, the ice elements are assumed to be circular (black circles). Elements are initially bonded to adjacent elements using numerical bonds (magenta lines). These numerical bonds form equilateral triangles which give the shape rigidity. An ocean grid has been included (dashed cyan lines). The background photo is an areal photograph of iceberg PIIB (Area5 42 km2) taken in Baffin Bay in 2012. A red ship can be identified on the bottom of the photo for scale.
In Smart et al., image shows results of the updated classification algorithm at Shrimp Vent with the main area of sampling indicated by the dashed white circle. (a) 2D photomosaic of the Shrimp Vent area showing the distribution of bacterial mats and seafloor characteristics. (b) Gridded results of the SVM classification method showing seafloor (blue), bacteria (green) and active venting (yellow). (c)Classification algorithm results showing only areas of active venting in red indicating the spatial distribution of active venting.
The Ex-Alta 1 Cube-Satellite, to be launched in late 2016 as part of the ESA QB50 constellation mission, will demonstrate the potential
In Roesler et al., total condensate (precipitating rain and snow and nonprecipitating water and ice) and the vertical velocity at 12 h into the simulation for the (left) 1.5 TKE scheme and the (right) CLUBB scheme. The total condensate is shown in the rainbow color bar, and the vertical velocity is shown with the blue-to-red color bar.
Guimbar et al., investigated the eastern tropical fresh pool (EPFP) spatial and temporal dynamics. The maximal surface extension of the EPFP exhibits a very large interannual variability. Over the past decade, two extreme events occurred, clearly related to the El Niño-Southern Oscillation (ENSO) phases with associated anomalies of precipitation, surface currents, and trade wind in the central Pacific. In particular, changes of the atmospheric freshwater fluxes and ocean surface currents during winter 2014 seems to trigger the onset of an abnormal fresh event related to the strong El Niño 2014–2015, leading to these unprecedented maximum values of the EPFP maximum extent (October-November) in 2014 and 2015.
annual-mean precipitation response between 40N and 40S to increased CO
In Oostingh et al., image shows examples of volcanic alignment and geomorphology interpretations. (a) Satellite image of Mt Eccles and (b) interpreted alignment direction. (c) Satellite image of Lake Cartcarrong (maar) and (d) interpreted elongation of the maar structure with preferred orientation.
In Stets et al., Stets et al. investigated the effects of carbonate buffering and metabolism on carbon dioxide (CO2) and dissolved inorganic carbon (DIC) concentrations in river networks. Carbonate buffering is less prominent in low alkalinity (a.) as compared with high alkalinity (b.) watersheds. Carbonate buffering decreases the rate of CO2 exchange across the air-water interface by decreasing the CO2 gradient, thereby affecting both the CO2 and DIC pools. Increased buffering and lags in CO2 exchange cause excess dissolved inorganic carbon (ΔDIC) to be higher in the small streams of high alkalinity watersheds (c.) as inputs from groundwater and negative net ecosystem production in small streams equilibrate more slowly in the high alkalinity watersheds. CO2 excess (ΔCO2) is high in the smallest streams of low alkalinity watersheds (d.). Rapid exchange with the atmosphere depletes CO2 pools, causing ΔCO2 to be lower in mid-sized streams of low alkalinity watersheds. Differences in carbonate buffering create spatial differences in CO 2 and DIC dynamics at the landscape scale.
Mohr et al. estimated how much organic carbon was released, stored, and evacuated from disturbed temperate rainforest into the Patagonian fjords after the explosive eruption of the Chaitén volcano in Chilean Patagonia (A). By quantifying fluxes of large wood (B) and organic rich topsoils (C) from the headwaters to the delta fans (D), they showed for the first time that Patagonian rainforests may temporarily switch from regional carbon sinks to carbon sources. Their finding demonstrates that infrequent volcanic eruptions may be one previously overlooked disturbance for generating spiked terrestrial organic carbon inputs from small mountain rivers and potentially account for large fractions of terrestrial carbon burial rates in the fjords.
In Rutte et al., image shows (a–d) Panoramic views of the Muskol dome. Distortion increases toward the image edges. Figures 4a and 4b are along section A in Figure 8. Thrusts and north vergent, recumbent, isoclinal folds in Figure 4d are in left part of Figure 4c. (e–h) Fault scarps in colluvial and alluvial deposits and range front normal faults along the active Sarez-Karakul graben system.
Ceres has plenty of permanently shadowed regions (mapped in blue) at the present day when its obliquity is small. However, due to obliquity changes in the past, only few permanent shadows remain.
Cartogram set “Natural resources under stress”: visualizing current and future per-capita renewable groundwater resources as affected by CC and population growth. Distorter variables are indicated in curly brackets. The left column shows per-capita groundwater resources, in m3/(cap yr), under current conditions (1971–2000, population in 2010) by a global equal-area map (a), and by a gridded cartogram with population in 2010 as distorter (b), and per-capita groundwater resources under future conditions as affected by climate and population change (2070–2099, population in 2085), with population in 2085 as distorter (c). The right column shows percent change of per-capita groundwater resources between current and future conditions due to both climate and population change (d), and due to CC only (e). Cartograms (c), (d), and (e) use population in 2085 according to SSP 2 for computation of per-capita groundwater resources in 2085 as distorter, and the total land area is enlarged by 45% as compared to maps (a) and (b), proportional to the increase of world population from 6.9 to 9.9 billion. Groundwater resources as computed by WaterGAP driven by five bias-adjusted climate models, high emissions scenario RCP 8.5 (Portmann et al., 2013).
In Li et al., three-dimensional renderings of 3h forward trajectories from (a–c) 500m, (d–f) 1.5km, (g–i) 2.5km of the 21 May air mass case (Figures11a,11d, and11g), the 29 May supercell case (Figures11b,11e, and11h), and the 11 June MCS case (Figures11c,11f, and11i), and (j–l) backward trajectories from the LMD of the three cases. Each trajectory line consists of 18 arrows with each arrow representing 10min air trajectory. The color of the arrows represents the ending height of the trajectories. The horizontal resolution of the trajectory seeds is 5km for all three cases.
Sumatra tsunami amplitude map with travel time shown by contours in 30 min time intervals. Bagiya et al., explain ahead-of-tsunami ionospheric disturbances from tsunami-generated acoustic gravity waves.
Galewsky et al. reviews how the isotopic composition of water vapor is impacted by deep convection and how it behaves within
In Aiuppa et al., image sequence showing evolution of Villarrica volcano throughout December 2014 to March 2015.
In Czuba et al. image shows Lidar hillshade highlighting major features (river, bluff, and ravine, each with relevant attributes) incorporated into the model. Inset image shows a 64m bluff; note the canoe for scale. Location and extent is shown in Figure3by a small red box.
In Uhlemann et al. [DOI: 10.1002/2016JF003983], image shows change in GMC from baseline model (Figure 7). Red colors indicate a relative
In Lapierre et al., based on an analysis of 1080 lakes distributed across the continental U.S., the image shows that surface water CO2 responds to contrasting drivers related to aquatic primary production, respiration by microorganisms, or terrestrial loadings of carbon depending on the climate and landscape context where these lakes are found. These results show that controls on lake CO2