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TIMED/GUVI limb measurements and first‐principles simulations from the Thermosphere Ionosphere Electrodynamics Global Circulation Model (TIEGCM) are used to investigate thermospheric atomic oxygen (O) and molecular nitrogen (N2) responses in the middle thermosphere on a constant pressure surface (∼160 km) to the November 20 and 21, 2003 superstorm. The consistency between GUVI observations and TIEGCM simulated composition changes allows us to utilize TIEGCM outputs to investigate the storm‐time behaviors of O and N2 systematically. Diagnostic analysis shows that horizontal and vertical advection are the two main processes that determine the storm‐induced perturbations in the middle thermosphere. Molecular diffusion has a relatively smaller magnitude than the two advection processes, acting to compensate for the changes caused by the transport partly. Contributions from chemistry and eddy diffusion are negligible. During the storm initial and main phases, composition variations at high latitudes are determined by both horizontal and vertical advection. At middle‐low latitudes, horizontal advection is the main driver for the composition changes where O mass mixing ratio Ψo decreases (N2 mass mixing ratio ΨN2 increases); whereas horizontal and vertical advection combined to dominate the changes in the regions where Ψo increases (ΨN2 decreases). Over the entire storm period, horizontal advection plays a significant role in transporting high‐latitude composition perturbations globally. Our results also demonstrate that storm‐time temperature changes are not the direct cause of the composition perturbations on constant pressure surfaces. Key Points: Horizontal and vertical advection are the two main processes driving O and N2 changes in the middle thermosphere during the superstormMolecular diffusion is relatively weak in the middle thermosphere, acting to compensate for O and N2 changes caused by transport processesStorm‐time temperature changes are not the direct cause of the composition perturbations on constant pressure surfaces [ABSTRACT FROM AUTHOR]

Research shows that resilient communities are best achieved through active public participation, informed by local input. However, post-disaster strategies in the United States are typically federally led and top-down in nature. We present an exploratory case study of resilience planning in New York State in the aftermath of Superstorm Sandy, which is a combination of public participation and government supervision. We name this approach "managed-participation" because it emphasizes engaging the public in post-disaster planning, guided by a high degree of state-level leadership. We adapt a theoretical proposition of horizontal and vertical integration framework for an exploratory analysis of the case. We find that New York's approach contributes to both horizontal and vertical integration of impacted communities by enhancing active participation in resilience efforts, and taking advantage of the state government's position to connect local needs with federal funding. Furthermore, by utilizing expertise and funding support to guide and translate local knowledge, it produces potentially more viable resilience plans. [ABSTRACT FROM AUTHOR]

The diurnal variation of height‐distributed nitric oxide (NO) radiative emission during November 2004 superstorm is studied using TIMED‐SABER satellite observations over 55°N–55°S geographic latitude region. The NO volume emission rate (VER), both during day and nighttime, shows an equatorial movement with descending peak emission altitude as one moves toward the equator. The NO VER from altitude of 100 to 280 km is integrated in steps of 30 km above 160 km (and from 100 to 160 km), obtaining the NO infrared radiative flux (IRF). The response of NO IRF depends on the altitude and time of consideration. The NO IRF in the lower altitude (<190 km) shows higher enhancement and a slower recovery as compared to altitude above it. It is observed that NO IRF during day and night responds differently to the November 2004 superstorm. The zonally averaged daytime NO IRF is mainly highest during weaker main phase (10 November, Dst =−263 nT). The maximum zonally averaged nighttime NO IRF is observed during stronger main phase (8 November, Dst =−374 nT) for all altitudes. The maximum relative daytime (RDE) and nighttime enhancement (RNE), which represent the relative variation of NO IRF during storm periods as compared to quiet time value, also exhibit different variations during this storm period. The minimum RDE is observed to show an equatorial movement as one moves downward in altitude. The minimum RDE occurs at about 35°N–40°N for 250–280 km, which decreases toward the equator, and minimum RDE is found near the equator for 100–160 km. The minimum of RNE is observed over the equator for all altitudes. Key Points: The nitric oxide infrared radiative flux (NO IRF) responds differently to November 2004 geomagnetic storm during day and nighttimeMaximum variation in NO IRF is observed in the altitude below 190 kmNighttime NO IRF enhancement with respect to quiet time is higher compared to daytime enhancement [ABSTRACT FROM AUTHOR]

Much of the literature on the consequences of natural disasters has focused on their physical and psychological ramifications. Few researchers have considered how the impacts of a natural disaster can influence academic achievement. This study analyses data collected from nearly 300 students at a mid-sized, private university in the northeast United States to determine if the effects of Cyclone Sandy in 2012 are associated with measures of academic achievement. The findings reveal that experiencing headaches after the event resulted in a higher likelihood of students suffering a loss of academic motivation. In addition, experiencing headaches and a loss of academic motivation were correlated with a lower grade point average (GPA) during the semester in which Sandy made landfall. However, the more direct effects of the superstorm, including displacement and a loss of power, did not have a significant bearing on academic achievement. Lastly, the paper examines the implications for higher education policy and future research. [ABSTRACT FROM AUTHOR]

In support of projects for forecasting and mitigating the deleterious effects of extreme space weather storms, an examination is made of the intensities of magnetic superstorms recorded in the Dst index time series (1957–2016). Modified peak‐over‐threshold and solar cycle, block‐maximum samplings of the Dst time series are performed to obtain compilations of storm maximum −Dstm intensity values. Lognormal, upper limit lognormal, generalized Pareto, and generalized extreme‐value model distributions are fitted to the −Dstm data using a maximum‐likelihood algorithm. All four candidate models provide good representations of the data. Comparisons of the statistical significance and goodness of fits of the various models give no clear indication as to which model is best. The statistical models are used to extrapolate to extreme‐value intensities, such as would be expected (on average) to occur once per century. An upper limit lognormal fit to peak‐over‐threshold −Dstm data above a superstorm threshold of 283 nT gives a 100‐year extrapolated intensity of 542 nT and a 68% confidence interval (obtained by bootstrap resampling) of [466, 583] nT. A generalized extreme‐value distribution fit to solar cycle, block‐maximum −DstmBM data gives a nine‐solar cycle (approximately 100‐year) extrapolated intensity of 591 nT. The Dst data are found to be insufficient for providing usefully accurate estimates of a statistically theoretical upper limit for magnetic storm intensity. Secular change in storm intensities is noted, as is a need for improved estimates of pre‐1957 magnetic storm intensities. Plain Language Summary: Estimating the statistical likelihood of extreme‐value geomagnetic storm intensities depends on the selection of data and models. The data used here are discrete samples of a standard time series that measures geomagnetic disturbance. Different methods are examined for identifying data values that can serve as nonredundant representations of storm maximum intensity. Four different statistical models (two formal models and two physically motivated models) are examined as candidate descriptions of the data. Comparisons and contrasts are made of the goodness of model descriptions of the data. Extrapolations are made to estimate once‐per‐century storm intensities; an upper limit on storm intensity cannot be confidently established; slow secular change is noted in the occurrences of intense storms. General suggestions are made for improving inferences about the future occurrence of intense storms. Results inform projects concerned with forecasting and mitigating the deleterious effects of extreme space weather storms. Key Points: Estimates of 100‐year magnetic storm intensities are affected by limitations of the data and the statistical modelsA model fit to peak‐over‐threshold storm maximum data gives a 100‐year intensity and 68% confidence interval of 542 [466, 583] nTStorm maximum data are about as well fitted by lognormal models as they are by formal extreme‐value models [ABSTRACT FROM AUTHOR]