Determining the Sun's influence on Lateglacial and Holocene climates: a focus on climate response to centennial-scale solar forcing at 2800 cal. BP

The influence of solar variability on the climate of the Lateglacial and Holocene periods has been the subject of increasing discussion during the last decade. In the Mid-Holocene, several studies have identified cold/wet events that occur at ca 2800 cal. BP and a link with a reduction in solar activity, inferred from the C-14 record, has been postulated. We present results from a multi-proxy study of peat humification, plant macrofossils and testate amoebae from a raised bog at Glen West, northwest Ireland, that indicate that dry bog surface conditions were experienced in the north of Ireland at the time of the solar anomaly starting at 2800 cal. BP. With the aid of C-14 wiggle-matching and tephrochronology, an abrupt shift to wetter conditions is dated to ca 2700 cal. BP, coinciding with a C-14 maximum but clearly post-dating the 2800 cal. BP event identified elsewhere in Europe. We explore the significance of this apparent lag in the Irish record, considering the possible role of the ocean in generating spatial and temporal complexities in the climate patterns of the North Atlantic region. We conclude that these complexities are likely to give rise to time-transgressive climate responses around the North Atlantic that will only be recognised by more critical chronological approaches.

Time-Dependent Density Diagnostics of Solar Flare Plasmas Using SDO/EVE

Temporally resolved electron density measurements of solar flare plasmas are presented using data from the EUV Variability Experiment (EVE) on board the Solar Dynamics Observatory. The EVE spectral range contains emission lines formed between 104 and 107 K, including transitions from highly ionized iron (gsim10 MK). Using three density-sensitive Fe XXI ratios, peak electron densities of 1011.2-1012.1 cm–3 were found during four X-class flares. While previous measurements of densities at such high temperatures were made at only one point during a flaring event, EVE now allows the temporal evolution of these high-temperature densities to be determined at 10 s cadence. A comparison with GOES data revealed that the peak of the density time profiles for each line ratio correlated well with that of the emission measure time profile for each of the events studied.

Nanoflare Activity In the Solar Chromosphere

We use ground-based images of high spatial and temporal resolution to search for evidence of nanoflare activity in the solar chromosphere. Through close examination of more than 1 x 10(9) pixels in the immediate vicinity of an active region, we show that the distributions of observed intensity fluctuations have subtle asymmetries. A negative excess in the intensity fluctuations indicates that more pixels have fainter-than-average intensities compared with those that appear brighter than average. By employing Monte Carlo simulations, we reveal how the negative excess can be explained by a series of impulsive events, coupled with exponential decays, that are fractionally below the current resolving limits of low-noise equipment on high-resolution ground-based observatories. Importantly, our Monte Carlo simulations provide clear evidence that the intensity asymmetries cannot be explained by photon-counting statistics alone. A comparison to the coronal work of Terzo et al. suggests that nanoflare activity in the chromosphere is more readily occurring, with an impulsive event occurring every similar to 360 s in a 10,000 km(2) area of the chromosphere, some 50 times more events than a comparably sized region of the corona. As a result, nanoflare activity in the chromosphere is likely to play an important role in providing heat energy to this layer of the solar atmosphere.

The radiated energy budget of Chromospheric Plasma in a major solar flare deduced from multi-wavelength observations

This paper presents measurements of the energy radiated by the lower solar atmosphere, at optical, UV, and EUV wavelengths, during an X-class solar flare (SOL2011-02-15T01:56) in response to an injection of energy assumed to be in the form of nonthermal electrons. Hard X-ray observations from RHESSI were used to track the evolution of the parameters of the nonthermal electron distribution to reveal the total power contained in flare accelerated electrons. By integrating over the duration of the impulsive phase, the total energy contained in the nonthermal electrons was found to be >2 × 1031 erg. The response of the lower solar atmosphere was measured in the free–bound EUV continua of H i (Lyman), He i, and He ii, plus the emission lines of He ii at 304 Å and H i (Lyα) at 1216 Å by SDO/EVE, the UV continua at 1600 Å and 1700 Å by SDO/AIA, and the white light continuum at 4504 Å, 5550 Å, and 6684 Å, along with the Ca ii H line at 3968 Å using Hinode/SOT. The summed energy detected by these instruments amounted to ~3 × 1030 erg; about 15% of the total nonthermal energy. The Lyα line was found to dominate the measured radiative losses. Parameters of both the driving electron distribution and the resulting chromospheric response are presented in detail to encourage the numerical modeling of flare heating for this event, to determine the depth of the solar atmosphere at which these line and continuum processes originate, and the mechanism(s) responsible for their generation.

A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells

Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.