Time-dependent Stochastic Modeling of Solar Active Region Energy

A time-dependent model for the energy of a flaring solar active region is presented based on a stochastic jump-transition model (Wheatland and Glukhov 1998; Wheatland 2008; Wheatland 2009). The magnetic free energy of the model active region varies in time due to a prescribed (deterministic) rate of energy input and prescribed (random) flare jumps downwards in energy. The model has been shown to reproduce observed flare statistics, for specific time-independent choices for the energy input and flare transition rates. However, many solar active regions exhibit time variation in flare productivity, as exemplified by NOAA active region AR 11029 (Wheatland 2010). In this case a time-dependent model is needed. Time variation is incorporated for two cases: 1. a step change in the rates of flare jumps; and 2. a step change in the rate of energy supply to the system. Analytic arguments are presented describing the qualitative behavior of the system in the two cases. In each case the system adjusts by shifting to a new stationary state over a relaxation time which is estimated analytically. The new model retains flare-like event statistics. In each case the frequency-energy distribution is a power law for flare energies less than a time-dependent rollover set by the largest energy the system is likely to attain at a given time. For Case 1, the model exhibits a double exponential waiting-time distribution, corresponding to flaring at a constant mean rate during two intervals (before and after the step change), if the average energy of the system is large. For Case 2 the waiting-time distribution is a simple exponential, again provided the average energy of the system is large. Monte Carlo simulations of Case~1 are presented which confirm the analytic estimates. The simulation results provide a qualitative model for observed flare statistics in active region AR 11029.Comment: 25 pages, 9 figure

Solar flare prediction using advanced feature extraction, machine learning and feature selection

YesNovel machine-learning and feature-selection algorithms have been developed to study: (i) the flare prediction capability of magnetic feature (MF) properties generated by the recently developed Solar Monitor Active Region Tracker (SMART); (ii) SMART's MF properties that are most significantly related to flare occurrence. Spatio-temporal association algorithms are developed to associate MFs with flares from April 1996 to December 2010 in order to differentiate flaring and non-flaring MFs and enable the application of machine learning and feature selection algorithms. A machine-learning algorithm is applied to the associated datasets to determine the flare prediction capability of all 21 SMART MF properties. The prediction performance is assessed using standard forecast verification measures and compared with the prediction measures of one of the industry's standard technologies for flare prediction that is also based on machine learning - Automated Solar Activity Prediction (ASAP). The comparison shows that the combination of SMART MFs with machine learning has the potential to achieve more accurate flare prediction than ASAP. Feature selection algorithms are then applied to determine the MF properties that are most related to flare occurrence. It is found that a reduced set of 6 MF properties can achieve a similar degree of prediction accuracy as the full set of 21 SMART MF properties

Acute health effects of the Tasman Spirit oil spill on residents of Karachi, Pakistan

BACKGROUND: On July 27 2003, a ship carrying crude oil run aground near Karachi and after two weeks released 37,000 tons of its cargo into the sea. Oil on the coastal areas and fumes in air raised health concerns among people. We assessed the immediate health impact of oil spill from the tanker Tasman Spirit on residents of the affected coastline in Karachi, Pakistan. METHODS: We conducted a study consisting of an exposed group including adults living in houses on the affected shoreline and two control groups (A and B) who lived at the distance of 2 km and 20 km away from the sea, respectively. We selected households through systematic sampling and interviewed an adult male and female in each household about symptoms relating to eyes, respiratory tract, skin and nervous system, smoking, allergies, beliefs about the effect on their health and anxiety about the health effects. We used logistic regression procedures to model each symptom as an outcome and the exposure status as an independent variable while adjusting for confounders. We also used linear regression procedure to assess the relationship exposure status with symptoms score; calculated by summation of all symptoms. RESULTS: Overall 400 subjects were interviewed (exposed, n = 216; group A, n = 83; and group B, n = 101). The exposed group reported a higher occurrence of one or more symptoms compared to either of the control groups (exposed, 96% vs. group A, 70%, group B 85%; P < 0.001). Mean summary symptom scores were higher among the exposed group (14.5) than control group A (4.5) and control group B (3.8, P < 0.001). Logistic regression models indicated that there were statistically significant, moderate-to-strong associations (Prevalence ORs (POR) ranging from 2.3 to 37.0) between the exposed group and the symptoms. There was a trend of decreasing symptom-specific PORs with increase in distance from the spill site. Multiple linear regression model revealed strong relationship of exposure status with the symptoms score (β = 8.24, 95% CI: 6.37 – 10.12). CONCLUSION: Results suggest that the occurrence of increased symptoms among the exposed group is more likely to be due to exposure to the crude oil spill

Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate

Traditional urban and transport infrastructure planning that emphasized motorized transport has fractured public space systems and worsened environmental quality, leading to a decrease in active travel. A novel multiscale simulation method for supporting an integrated transportation infrastructure and public space design is presented in this paper. This method couples a mesoscale agent-based traffic prediction model, traffic-related emission calculation, microclimate simulations, and human thermal comfort assessment. In addition, the effects of five urban design strategies on traffic pollution and pedestrian level microclimate are evaluated (i.e., a “two-fold” evaluation). A case study in Beijing, China, is presented utilizing the proposed urban modeling-design framework to support the assessment of a series of transport infrastructure and public space scenarios, including the Baseline scenario, a System-Internal Integration scenario, and two External Integration scenarios. The results indicate that the most effective way of achieving an environmentally- and pedestrian- friendly urban design is to concentrate on both the integration within the transport infrastructure and public space system and the mitigation of the system externalities (e.g., air pollution and heat exhaustion). It also demonstrates that the integrated blue-green approach is a promising way of improving local air quality, micro-climatic conditions, and human comfort

Soil quality regeneration by grass-clover leys in arable rotations compared to permanent grassland: Effects on wheat yield and resilience to drought and flooding

Intensive arable cropping depletes soil organic carbon and earthworms, leading to loss of macropores, and impaired hydrological functioning, constraining crop yields and exacerbating impacts of droughts and floods that are increasing with climate change. Grass and legume mixes traditionally grown in arable rotations (leys), are widely considered to regenerate soil functions, but there is surprisingly limited evidence of their effects on soil properties, resilience to rainfall extremes, and crop yields. Using topsoil monoliths taken from four intensively cropped arable fields, 19 month-old grass-clover ley strips in these fields, and from 3 adjacent permanent grasslands, effects on soil properties, and wheat yield in response to four-weeks of flood, drought, or ambient rain, during the stem elongation period were evaluated. Compared to arable soil, leys increased earthworm numbers, infiltration rates, macropore flow and saturated hydraulic conductivity, and reduced compaction (bulk density) resulting in improved wheat yields by 42–95 % under flood and ambient conditions. The leys showed incomplete recovery compared to permanent grassland soil, with modest gains in soil organic carbon, total nitrogen, water-holding capacity, and grain yield under drought, that were not significantly different (P > 0.05) to the arable controls. Overall, grass-clover leys regenerate earthworm populations and reverse structural degradation of intensively cultivated arable soil, facilitating adoption of no-tillage cropping to break out of the cycle of tillage-driven soil degradation. The substantial improvements in hydrological functioning by leys will help to deliver reduced flood and water pollution risks, potentially justifying payments for these ecosystem services, especially as over longer periods, leys increase soil carbon sequestration

Small Scale Wv-Feature Above France: Next Day Severe

Due to economic reasons world-wide can be seen that the human observers have to withdraw. Despite of the reduction of human synoptic observations today more data sources are available to the modern synopticians. Satellite information is one of the most important sources of the forecaster. And thereby satellite meteorology is a hot issue in the training departments of the national meteorological services

The knowledge of things unknown [electronic resource] : shewing the effects of the planets and other astronomical constellations : with the strange events that befal men, women, and children born under them /

Imperfect: t.p. lacking. Title and imprint information supplied from Wing and NUC pre-l956 imprints."The Husbandmans practice" (p. 78-121) and "The shepherds prognostication for the Weather (p.123-158) have special t.p.s.Reproduction of original in the Cambridge University Library.WingElectronic reproduction