Post-hoc derivation of SOHO Michelson doppler imager flat fields

<p><b>Context:</b> The SOHO satellite now offers a unique perspective on the Sun as it is the only space-based instrument that can provide large, high-resolution data sets over an entire 11-year solar cycle. This unique property enables detailed studies of long-term variations in the Sun. One significant problem when looking for such changes is determining what component of any variation is due to deterioration of the instrument and what is due to the Sun itself. One of the key parameters that changes over time is the apparent sensitivity of individual pixels in the CCD array. This can change considerably as a result of optics damage, radiation damage, and aging of the sensor itself. In addition to reducing the sensitivity of the telescope over time, this damage significantly changes the uniformity of the flat field of the instrument, a property that is very hard to recalibrate in space. For procedures such as feature tracking and intensity analysis, this can cause significant errors.</p> <p><b>Aims:</b> We present a method for deriving high-precision flat fields for high-resolution MDI continuum data, using analysis of existing continuum and magnetogram data sets.</p> <p><b>Methods:</b> A flat field is constructed using a large set (1000-4000 frames) of cospatial magnetogram and continuum data. The magnetogram data is used to identify and mask out magnetically active regions on the continuum data, allowing systematic biases to be avoided. This flat field can then be used to correct individual continuum images from a similar time.</p> <p><b>Results:</b> This method allows us to reduce the residual flat field error by around a factor 6-30, depending on the area considered, enough to significantly change the results from correlation-tracking analysis. One significant advantage of this method is that it can be done retrospectively using archived data, without requiring any special satellite operations.</p&gt

Balltracking: an highly efficient method for tracking flow fields

We present a method for tracking solar photospheric flows that is highly efficient, and demonstrate it using high resolution MDI continuum images. The method involves making a surface from the photospheric granulation data, and allowing many small floating tracers or balls to be moved around by the evolving granulation pattern. The results are tested against synthesised granulation with known flow fields and compared to the results produced by Local Correlation tracking (LCT). The results from this new method have similar accuracy to those produced by LCT. We also investigate the maximum spatial and temporal resolution of the velocity field that it is possible to extract, based on the statistical properties of the granulation data. We conclude that both methods produce results that are close to the maximum resolution possible from granulation data. The code runs very significantly faster than our similarly optimised LCT code, making real time applications on large data sets possible. The tracking method is not limited to photospheric flows, and will also work on any velocity field where there are visible moving features of known scale length

The evolution of electron overdensities in magnetic fields

When a neutral gas impinges on a stationary magnetized plasma an enhancement in the ionization rate occurs when the neutrals exceed a threshold velocity. This is commonly known as the critical ionization velocity effect. This process has two distinct timescales: an ion–neutral collision time and electron acceleration time. We investigate the energization of an ensemble of electrons by their self-electric field in an applied magnetic field. The evolution of the electrons is simulated under different magnetic field and density conditions. It is found that electrons can be accelerated to speeds capable of electron impact ionization for certain conditions. In the magnetically dominated case the energy distribution of the excited electrons shows that typically 1% of the electron population can exceed the initial electrostatic potential associated with the unbalanced ensemble of electrons

A Quantum Approach to Classical Statistical Mechanics

We present a new approach to study the thermodynamic properties of $d$-dimensional classical systems by reducing the problem to the computation of ground state properties of a $d$-dimensional quantum model. This classical-to-quantum mapping allows us to deal with standard optimization methods, such as simulated and quantum annealing, on an equal basis. Consequently, we extend the quantum annealing method to simulate classical systems at finite temperatures. Using the adiabatic theorem of quantum mechanics, we derive the rates to assure convergence to the optimal thermodynamic state. For simulated and quantum annealing, we obtain the asymptotic rates of $T(t) \approx (p N) /(k_B \log t)$ and $\gamma(t) \approx (Nt)^{-\bar{c}/N}$, for the temperature and magnetic field, respectively. Other annealing strategies, as well as their potential speed-up, are also discussed.Comment: 4 pages, no figure

Gas-plasma compressional wave coupling by momentum transfer

Pressure disturbances in a gas-plasma mixed fluid will result in a hybrid response, with magnetosonic plasma waves coupled to acoustic waves in the neutral gas. In the analytical and numerical treatment presented here, we demonstrate the evolution of the total fluid medium response under a variety of conditions, with the gas-plasma linkage achieved by additional coupling terms in the momentum equations of each species. The significance of this treatment lies in the consideration of density perturbations in such fluids: there is no 'pure' mode response, only a collective one in which elements of the characteristics of each component are present. For example, an initially isotropic gas sound wave can trigger an anisotropic magnetic response in the plasma, with the character of each being blended in the global evolution. Hence sound waves do not remain wholly isotropic, and magnetic responses are less constrained by pure magnetoplasma dynamics

Quantifying the value of ecosystem services: a case study of honeybee pollination in the UK

There is concern that insect pollinators, such as honey bees, are currently declining in abundance, and are under serious threat from environmental changes such as habitat loss and climate change; the use of pesticides in intensive agriculture, and emerging diseases. This paper aims to evaluate how much public support there would be in preventing further decline to maintain the current number of bee colonies in the UK. The contingent valuation method (CVM) was used to obtain the willingness to pay (WTP) for a theoretical pollinator protection policy. Respondents were asked whether they would be WTP to support such a policy and how much would they pay? Results show that the mean WTP to support the bee protection policy was £1.37/week/household. Based on there being 24.9 million households in the UK, this is equivalent to £1.77 billion per year. This total value can show the importance of maintaining the overall pollination service to policy makers. We compare this total with estimates obtained using a simple market valuation of pollination for the UK

Communicating Carabids: Engaging farmers to encourage uptake of Integrated Pest Management.

BACKGROUND: Natural enemy pest control (NPC) is becoming more desirable as restrictions increase on pesticide use. Carabid beetles are proven agents of NPC, controlling pests and weeds in crop areas. Agro-ecological measures can be effective for boosting carabid abundance and associated NPC, however the benefits of specific interventions to production are seldom communicated to farmers. We explore pathways to improved NPC by engaging farmers and increasing knowledge about Farm Management Practices (FMPs) beneficial to carabids using engagement materials. We used a questionnaire to measure awareness, beliefs, and attitudes to carabids and analysed these within a framework of the Theory of Planned Behaviour (TPB), relative to a control group. RESULTS: We found awareness of carabid predation to be associated with beliefs of pest and weed control efficacy. Within the framework of TPB, we found that current implementation of FMPs was higher if farmers perceived them to be both important for carabids, and easy to implement. This was also true for future intention to implement, yet the perceived importance was influenced by engagement materials. Field margins/buffer strips and beetle banks (16% and 13% of responses) were the most favoured by farmers as interventions for carabids. CONCLUSION: The TPB is a valuable tool with which to examine internal elements of farmer behaviour. In this study self-selected participants were influenced by online engagement in a single intervention, proving this approach has the potential to change behaviour. Our results are evidence for the effectiveness of raising awareness of NPC to change attitudes and increase uptake of sustainable practices

Identifying and accounting for the Coriolis Effect in satellite NO2 observations and emission estimates

Recent developments in atmospheric remote sensing from satellites have made it possible to resolve daily emission plumes from industrial point sources, around the globe. Wind rotation aggregation coupled with statistical fitting is commonly used to extract emission estimates from these observations. These methods are used here to investigate how the Coriolis Effect influences the trajectory of observed emission plumes, and to assess the impact of this influence on satellite derived emission estimates. Of the 17 industrial sites investigated, nine showed the expected curvature for the hemisphere they reside in. Five showed no or negligible curvature, and two showed opposing or unusual curvature. The sites which showed conflicting curvature all reside in topographically diverse regions, where strong meso-gamma scale (2&ndash;20 km) turbulence dominates over larger synoptic circulation patterns. For high curvature cases the assumption that the wind-rotated plume aggregate is symmetrically distributed across the downwind axis breaks down, which impairs the quality of statistical fitting procedures. Using NOx emissions from Matimba power station as a test case, not compensating for Coriolis curvature resulted in an10 underestimation of &sim; 9 % on average for years 2018 to 2021. This study is the first formal observation of the Coriolis Effect and its influence on satellite observed emission plumes, and highlight both the variability of emission calculation methods and the need for a standardised scheme for this data to act as evidence for regulators.</p

Estimating mangrove canopy height and above-ground biomass in the Everglades National Park with airborne LiDAR and TanDEM-X data

Mangrove forests are important natural ecosystems due to their ability to capture and store large amounts of carbon. Forest structural parameters, such as canopy height and above-ground biomass (AGB), provide a good measure for monitoring temporal changes in carbon content. The protected coastal mangrove forest of the Everglades National Park (ENP) provides an ideal location for studying these processes, as harmful human activities are minimal. We estimated mangrove canopy height and AGB in the ENP using Airborne LiDAR/Laser (ALS) and TanDEM-X (TDX) datasets acquired between 2011 and 2013. Analysis of both datasets revealed that mangrove canopy height can reach up to ~25 m and AGB can reach up to ~250 Mg·ha-1. In general, mangroves ranging from 9 m to 12 m in stature dominate the forest canopy. The comparison of ALS and TDX canopy height observations yielded an R2 = 0.85 and Root Mean Square Error (RMSE) = 1.96 m. Compared to a previous study based on data acquired during 2000-2004, our analysis shows an increase in mangrove stature and AGB, suggesting that ENP mangrove forests are continuing to accumulate biomass. Our results suggest that ENP mangrove forests have managed to recover from natural disturbances, such as HurricaneWilma