Variability of the Deepwater Horizon Surface Oil Spill Extent and Its Relationship to Varying Ocean Currents and Extreme Weather Conditions

Satellite observations and their derived products played a key role during the Deepwater Horizon oil spill monitoring efforts in the Gulf of Mexico in April–July 2010. These observations were sometimes the only source of synoptic information available to monitor and analyse several critical parameters on a daily basis. These products also complemented in situ observations and provided data to assimilate into or validate model. The ocean surface dynamics in the Gulf of Mexico are dominated by strong seasonal cycles in surface temperature and mixing due to convective and storm energy, and by major currents that include the Loop Current and its associated rings. Shelf processes are also strongly influenced by seasonal river discharge, winds, and storms. Satellite observations were used to determine that the Loop Current exhibited a very northern excursion (to approximately 28∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document}N) during the month of May, placing the core of this current and of the ring that it later shed at approximately 150 km south of the oil spill site. Knowledge gained about the Gulf of Mexico since the 1980s using a wide range of satellite observations helped understand the timing and process of separation of an anticyclonic ring from the Loop Current during this time. The surface extent of the oil spill varied largely based upon several factors, such as the rate of oil flowing from the well, clean up and recovery efforts, and biological, chemical, and physical processes. Satellite observations from active and passive radars, as well as from visible and infrared sensors were used to determine the surface extent of the oil spill. Results indicate that the maximum and total cumulative areal extent were approximately 45 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document} 103\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document} km2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document} and 130 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document} 103\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document} km2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document}, respectively. The largest increase of surface oil occurred between April 22 and May 22, at an average rate of 1.3 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document} 103\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document} km2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document} per day. The largest decrease in the extent of surface oil started on June 26, at an average rate of 4.4 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document} 103\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document} km2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document} per day. Surface oil areas larger than approximately 40 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document} 103\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document} km2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document} occurred during several periods between late May and the end of June. The southernmost surface oil extent reached approximately 85∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document}W 27∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document}N during the beginning of June. Results obtained indicate that surface currents may have partly controlled the southern and eastern extent of the surface oil during May and June, while intense southeast winds associated with Hurricane Alex caused a reduction of the surface oil extent at the end of June and beginning of July, as oil was driven onshore and mixed underwater. Given the suite of factors determining the variability of the oil spill extent at ocean surface, work presented here shows the importance of data analyses to compare against assessments made to evaluate numerical models

N2 Fixation in Feather Mosses is a Sensitive Indicator of N Deposition in Boreal Forests

Nitrogen (N) fixation in the feather moss-cyanobacteria association represents a major N source in boreal forests which experience low levels of N deposition; however, little is known about the effects of anthropogenic N inputs on the rate of fixation of atmospheric N-2 in mosses and the succeeding effects on soil nutrient concentrations and microbial community composition. We collected soil samples and moss shoots of Pleurozium schreberi at six distances along busy and remote roads in northern Sweden to assess the influence of road-derived N inputs on N-2 fixation in moss, soil nutrient concentrations and microbial communities. Soil nutrients were similar between busy and remote roads; N-2 fixation was higher in mosses along the remote roads than along the busy roads and increased with increasing distance from busy roads up to rates of N-2 fixation similar to remote roads. Throughfall N was higher in sites adjacent to the busy roads but showed no distance effect. Soil microbial phospholipid fatty acid (PLFA) composition exhibited a weak pattern regarding road type. Concentrations of bacterial and total PLFAs decreased with increasing distance from busy roads, whereas fungal PLFAs showed no distance effect. Our results show that N-2 fixation in feather mosses is highly affected by N deposition, here derived from roads in northern Sweden. Moreover, as other measured factors showed only weak differences between the road types, atmospheric N-2 fixation in feather mosses represents a highly sensitive indicator for increased N loads to natural systems