Parameterizing turbulent exchange over sea ice: the ice station weddell results

A 4-month deployment on Ice Station Weddell (ISW) in the western Weddell Sea yielded over 2000 h of nearly continuous surface-level meteorological data, including eddy-covariance measurements of the turbulent surface fluxes of momentum, and sensible and latent heat. Those data lead to a new parameterization for the roughness length for wind speed, z₀, for snow-covered sea ice that combines three regimes: an aerodynamically smooth regime, a high-wind saltation regime, and an intermediate regime between these two extremes where the macroscale or `permanent' roughness of the snow and ice determines z₀. Roughness lengths for temperature, z_T, computed from this data set corroborate the theoretical model that Andreas published in 1987. Roughness lengths for humidity,z_Q, do not support this model as conclusively but are all, on average, within an order of magnitude of its predictions. Only rarely arez_Tand z_Q equal to z₀. These parameterizations have implications for models that treat the atmosphere-ice-ocean system.     

Kuskonook Creek, an example of a debris flow analysis

Two debris flows occurred on Kuskonook Creek in British Columbia, Canada, in August and September 2004. The initiation factors included a major forest fire in the catchment in 2003, in association with relatively small rainfall events and the accumulation of sediment in the creek channels since the last large debris flow event. Previous regional studies and morphometric comparisons with other similar catchments indicate that Kuskonook Creek has characteristics predisposed to debris flows, even without the affects of a forest fire. Based on the investigations and analyses, a magnitude/frequency relationship for future debris events on Kuskonook Creek was developed, and this information was used to carry out a partial risk assessment. It is suggested that for design purposes, a 1/50-year return period and the corresponding debris flow magnitude of 15,000 m³ would provide conservative protection to the users of the provincial highway at the mouth of the creek.     

Rock magnetic properties of recent soils from northeastern Bulgaria

In this paper, basic rock magnetic studies of Holocene loess-soil samples from northeastern Bulgaria are reported. The sites are related to the Danube river and located at different distances southwards, thus representing various pedogenic conditions. The study is primarily aimed at determining the main magnetic carrier(s) and their physical characteristics (grain-size distribution, magnetic enhancement, etc.). Oxyhydroxides, maghemite and titanomagnetites of various oxidation degrees are assumed to be the main ferromagnetic minerals present. Our results suggest that the uppermost part of recent soil profiles is rich in stable, near-single-domain (SD) particles, while the illuvial horizons are characterized by a gradual decrease in grain sizes, from highly viscous to a true superparamagnetic (SP) domain state. The properties of samples from carbonate-rich horizons of recent soils are basically controlled by detrital minerals, while those from sites with more intensive pedogenesis and especially grey forest soils are influenced by strongly magnetic minerals formed ' in situ '.     

Flux of particulate matter in the tidal marshes and subtidal shallows of the Rhode River estuary

There was a net influx of suspended particulate matter to the uppermost part of the Rhode River estuary during the several years of this study. Most of the influx was due to episodic discharges of suspended sediment from the watershed during heavy rains. In contrast, tidal exchange of particulate matter was not related to rainstorms. Sediment composition data and historical records indicate that marsh accretion accounts for only 13% of the sediment trapping although marshes occupy 60% of the study area. Influx of particulate matter to the marshes is directly related to the amount of time they are submerged during tidal cycles.     

Effects of watershed and estuarine characteristics on the abundance of submerged aquatic vegetation in Chesapeake Bay subestuaries

Watershed land use can affect submerged aquatic vegetation (SAV) by elevating nutrient and sediment loading to estuaries. We analyzed the effects of watershed use and estuarine characteristics on the spatial variation of SAV abundance among 101 shallow subestuaries of Chesapeake Bay during 1984–2003. Areas of these subestuaries range from 0.1 to 101 km², and their associated local watershed areas range from 6 to 1664 km². Watershed land cover ranges from 6% to 81% forest, 1% to 64% cropland, 2% to 38% grassland, and 0.3% to 89% developed land. Landscape analyses were applied to develop a number of subestuary metrics (such as subestuary area, mouth width, elongation ratio, fractal dimension of shoreline, and the ratio of local watershed area to subestuary area) and watershed metrics (such as watershed area). Using mapped data from aerial SAV surveys, we calculated SAV coverage for each subestuary in each year during 1984–2003 as a proportion of potential SAV habitat (the area < 2 m deep). The variation in SAV abundance among subestuaries was strongly linked with subestuary and watershed characteristics. A regression tree model indicated that 60% of the variance in SAV abundance could be explained by subestuary fractal dimension, mean tidal range, local watershed dominant land cover, watershed to subestuary area ratio, and mean wave height. Similar explanatory powers were found in wet and dry years, but different independent variables were used. Repeated measures ANOVA with multiple-mean comparison showed that SAV abundance declined with the dominant watershed land cover in the order: forested, mixed-undisturbed, or mixed-developed > mixed-agricultural > agricultural > developed. Change-point analyses indicated strong threshold responses of SAV abundance to point source total nitrogen and phosphorus inputs, the ratio of local watershed area to subestuary area, and septic system density in the local watershed.     

Holocene coastal change at Luce Bay,South West Scotland

Coastal change during the Mid- to Late Holocene at Luce Bay, South West Scotland, is examined using morphological, stratigraphic and biostratigraphical techniques supported by radiocarbon dating. Deglaciation left extensive sediments, providing a source for depositional coastal landforms. Glacio-isostatic uplift resulted in the registration of evidence for former relative sea levels (RSLs), which support the pattern of Holocene RSL change for the northern Irish Sea as determined by shoreline-based Gaussian trend surface models. The rate of RSL rise was rapid from before ca. 8600 to ca. 7800 cal a bp , but then slowed, changing by <3 m over the next 3000 years, a pattern reflected in the convergence of shorelines predicted in the models. By ca. 4400 cal a bp RSL was falling towards present levels. As these changes were taking place, coastal barriers developed and dunes formed across them. In the West of the Bay, a lagoon forming to landward of the barriers and dunes acted as a sediment sink for dune sand. Changes in the coastal landscape influenced the occupation of the area by early human societies. This study illustrates the value of combining an understanding of process geomorphology, RSL and archaeology in studies of coastal change.     

Using structure‐from‐motion to create glacier DEMs and orthoimagery from historical terrestrial and oblique aerial imagery

Increased resolution and availability of remote sensing products, and advancements in small‐scale aerial drone systems, allows observations of glacial changes at unprecedented levels of detail. Software developments, such as structure‐from‐motion (SfM), now allow users an easy and efficient method to generate three‐dimensional (3D) models and orthoimages from aerial or terrestrial datasets. While these advancements show promise for current and future glacier monitoring, many regions still suffer a lack of observations from earlier time periods. We report on the use of SfM to extract spatial information from various historic imagery sources. We focus on three geographic regions, the European Alps, high Arctic Norway and the Nepal Himalayas. We used terrestrial field photographs from 1896, high oblique aerial photographs from 1936 and aerial handheld photographs from 1978 to generate digital elevation models (DEMs) and orthophotos of the Rhone glacier, Brøggerhalvøya and the lower Khumbu glacier, respectively. Our analysis shows that applying SfM to historic imagery can generate high quality models using only ground control points. Limited camera/orientation information was largely reproduced using self‐calibrated model data. Using these data, we calculated mean ground sampling distances across each site which demonstrates the high potential resolution of resulting models. Vertical errors for our models are ±5.4 m, ±5.2 m and ±3.3 m. Differencing shows similar patterns of thinning at lower Rhone (European Alps) and Brøggerhalvøya (Norway) glaciers, which have mean thinning rates of 0.31 m a^?1 (1896–2010) to 0.86 m a^?1 (1936–2010) respectively. On these clean ice glaciers thinning is highest in the terminus region and decreasing up‐glacier. In contrast to these glaciers, uneven topography, exposed ice‐cliffs and debris cover on the Khumbu glacier create a highly variable spatial distribution of thinning. The mean thinning rate for the Khumbu study area was found to be 0.54 ± 0.9 m a^?1 (1978–2015). Copyright © 2017 John Wiley & Sons, Ltd.     

Land Cover Changes on Ambergris Caye,Belize: A Case Study of Unregulated Tourism Development

Measuring land-use, land-cover change in biodiverse, tropical countries is critical for conservation management and sustainable planning because it provides quantifiable data regarding broad environmental changes. This project uses Landsat satellite imagery to document vegetation cover change on Ambergris Caye, Belize, from 2000 to 2017. The close proximity of the Belize Barrier Reef Reserve System has made Ambergris Caye the most popular tourist destination and economic hub in Belize. As a result, the region has undergone intense commercial and residential development coupled with rapid population growth over the past two decades. Understanding general trends in landscape dynamics is critical for the natural resource–based tourism industry of Belize to continue to thrive. Unsupervised classification methods and a per pixel postclassification comparison were used with Landsat imagery to estimate loss in vegetation cover and increases in urban and barren land. The results indicate a 10.85 percent decrease in vegetation and a 39 percent increase in urban and barren land during the seventeen-year study period with an annual forest loss rate of 0.67 percent per year using a compound interest rate formula. The results of this analysis represent a baseline study of vegetation change on Ambergris Caye to inform management and conservation efforts.     

Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI Active Region Patches (SHARP) product that facilitates cut-out magnetograms of solar active regions (AR) in the Sun in near-realtime (NRT), taken over a five-year interval (2012?–?2016). Our approach utilizes a set of thirteen predictors, which are not included in the SHARP metadata, extracted from line-of-sight and vector photospheric magnetograms. We exploit several machine learning (ML) and conventional statistics techniques to predict flares of peak magnitude \({>}\,\mbox{M1}\) and \({>}\,\mbox{C1}\) within a 24 h forecast window. The ML methods used are multi-layer perceptrons (MLP), support vector machines (SVM), and random forests (RF). We conclude that random forests could be the prediction technique of choice for our sample, with the second-best method being multi-layer perceptrons, subject to an entropy objective function. A Monte Carlo simulation showed that the best-performing method gives accuracy \(\mathrm{ACC}=0.93(0.00)\), true skill statistic \(\mathrm{TSS}=0.74(0.02)\), and Heidke skill score \(\mathrm{HSS}=0.49(0.01)\) for \({>}\,\mbox{M1}\) flare prediction with probability threshold 15% and \(\mathrm{ACC}=0.84(0.00)\), \(\mathrm{TSS}=0.60(0.01)\), and \(\mathrm{HSS}=0.59(0.01)\) for \({>}\,\mbox{C1}\) flare prediction with probability threshold 35%.