The importance of moisture distribution for the growth and energetics of mid-latitude systems

A primitive equation model is used to study the sensitivity of baroclinic wave life cycles to the initial latitude-height distribution of humidity. Diabatic heating is parametrized only as a consequence of condensation in regions of large-scale ascent. Experiments are performed in which the initial relative humidity is a simple function of model level, and in some cases latitude bands are specified which are initially relatively dry. It is found that the presence of moisture can either increase or decrease the peak eddy kinetic energy of the developing wave, depending on the initial moisture distribution. A relative abundance of moisture at mid-latitudes tends to weaken the wave, while a relative abundance at low latitudes tends to strengthen it. This sensitivity exists because competing processes are at work. These processes are described in terms of energy box diagnostics. The most realistic case lies on the cusp of this sensitivity. Further physical parametrizations are then added, including surface fluxes and upright moist convection. These have the effect of increasing wave amplitude, but the sensitivity to initial conditions of relative humidity remains. Finally, 'control' and 'doubled CO2' life cycles are performed, with initial conditions taken from the time-mean zonal-mean output of equilibrium GCM experiments. The attenuation of the wave resulting from reduced baroclinicity is more pronounced than any effect due to changes in initial moisture.

Portmanteau model diagnostics and tests for nonlinearity: a comparative Monte Carlo study of two alternative methods

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes

Aluminium distribution in ZSM-5 revisited: the role of Al-Al interactions

We present a theoretical study of the distribution of Al atoms in zeolite ZSM-5 with Si/Al=47, where we focus on the role of Al-Al interactions rather than on the energetics of Al/Si substitutions at individual sites. Using interatomic potential methods, we evaluate the energies of the full set of symmetrically independent configurations of Al siting in a Si94Al2O192 cell. The equilibrium Al distribution is determined by the interplay of two factors: the energetics of the Al/Si substitution at an individual site, which tends to populate particular T sites (e.g. the T14 site), and the Al-Al interaction, which at this Si/Al maximises Al-Al distances in agreement with Dempsey’s rule. However, it is found that the interaction energy changes approximately as the inverse of the square of the distance between the two Al atoms, rather than the inverse of the distance expected if this were merely charge repulsion. Moreover, we find that the anisotropic nature of the framework density plays an important role in determining the magnitude of the interactions, which are not simply dependent on Al-Al distances.

PDFOS: PDF estimation based over-sampling for imbalanced two-class problems

This contribution proposes a novel probability density function (PDF) estimation based over-sampling (PDFOS) approach for two-class imbalanced classification problems. The classical Parzen-window kernel function is adopted to estimate the PDF of the positive class. Then according to the estimated PDF, synthetic instances are generated as the additional training data. The essential concept is to re-balance the class distribution of the original imbalanced data set under the principle that synthetic data sample follows the same statistical properties. Based on the over-sampled training data, the radial basis function (RBF) classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier’s structure and the parameters of RBF kernels are determined using a particle swarm optimisation algorithm based on the criterion of minimising the leave-one-out misclassification rate. The effectiveness of the proposed PDFOS approach is demonstrated by the empirical study on several imbalanced data sets.

The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Species distribution models for crop pollination: a modelling framework applied to Great Britain

Insect pollination benefits over three quarters of the world's major crops. There is growing concern that observed declines in pollinators may impact on production and revenues from animal pollinated crops. Knowing the distribution of pollinators is therefore crucial for estimating their availability to pollinate crops; however, in general, we have an incomplete knowledge of where these pollinators occur. We propose a method to predict geographical patterns of pollination service to crops, novel in two elements: the use of pollinator records rather than expert knowledge to predict pollinator occurrence, and the inclusion of the managed pollinator supply. We integrated a maximum entropy species distribution model (SDM) with an existing pollination service model (PSM) to derive the availability of pollinators for crop pollination. We used nation-wide records of wild and managed pollinators (honey bees) as well as agricultural data from Great Britain. We first calibrated the SDM on a representative sample of bee and hoverfly crop pollinator species, evaluating the effects of different settings on model performance and on its capacity to identify the most important predictors. The importance of the different predictors was better resolved by SDM derived from simpler functions, with consistent results for bees and hoverflies. We then used the species distributions from the calibrated model to predict pollination service of wild and managed pollinators, using field beans as a test case. The PSM allowed us to spatially characterize the contribution of wild and managed pollinators and also identify areas potentially vulnerable to low pollination service provision, which can help direct local scale interventions. This approach can be extended to investigate geographical mismatches between crop pollination demand and the availability of pollinators, resulting from environmental change or policy scenarios.

Meteorology, air quality, and health in London: the ClearfLo project

The ClearfLo project provides integrated measurements of the meteorology, composition and particulate loading of London's urban atmosphere to improve predictive capability for air quality. Air quality and heat are strong health drivers and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants such as ozone, nitrogen dioxide, and fine and coarse particulate matter in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the ClearfLo project's interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures. Within ClearfLo (www.clearflo.ac.uk), a large multi-institutional project funded by the UK Natural Environment Research Council (NERC), integrated measurements of meteorology, gaseous and particulate composition/loading within London's atmosphere were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, kerbside and rural locations were complemented with high-resolution numerical atmospheric simulations . Combining these (measurement/modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and summer Olympics 2012) focus upon the vertical structure and evolution of the urban boundary layer, chemical controls on nitrogen dioxide and ozone production, in particular the role of volatile organic compounds, and processes controlling the evolution, size, distribution and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP

Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Inter-comparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981-2010) to the future (2070-2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.

A study on the sensitivities of simulated aerosol optical properties to composition and size distribution using airborne measurements

We present a flexible framework to calculate the optical properties of atmospheric aerosols at a given relative humidity based on their composition and size distribution. The similarity of this framework to climate model parameterisations allows rapid and extensive sensitivity tests of the impact of uncertainties in data or of new measurements on climate relevant aerosol properties. The data collected by the FAAM BAe-146 aircraft during the EUCAARI-LONGREX and VOCALS-REx campaigns have been used in a closure study to analyse the agreement between calculated and measured aerosol optical properties for two very different aerosol types. The agreement achieved for the EUCAARI-LONGREX flights is within the measurement uncertainties for both scattering and absorption. However, there is poor agreement between the calculated and the measured scattering for the VOCALS-REx flights. The high concentration of sulphate, which is a scattering aerosol with no absorption in the visible spectrum, made the absorption measurements during VOCALS-REx unreliable, and thus no closure study was possible for the absorption. The calculated hygroscopic scattering growth factor overestimates the measured values during EUCAARI-LONGREX and VOCALS-REx by ∼30% and ∼20%, respectively. We have also tested the sensitivity of the calculated aerosol optical properties to the uncertainties in the refractive indices, the hygroscopic growth factors and the aerosol size distribution. The largest source of uncertainty in the calculated scattering is the aerosol size distribution (∼35%), followed by the assumed hygroscopic growth factor for organic aerosol (∼15%), while the predominant source of uncertainty in the calculated absorption is the refractive index of organic aerosol (28–60%), although we would expect the refractive index of black carbon to be important for aerosol with a higher black carbon fraction.

Aerosol microphysics simulations of the Mt.~Pinatubo eruption with the UM-UKCA composition-climate model

We use a stratosphere–troposphere composition–climate model with interactive sulfur chemistry and aerosol microphysics, to investigate the effect of the 1991 Mount Pinatubo eruption on stratospheric aerosol properties. Satellite measurements indicate that shortly after the eruption, between 14 and 23 Tg of SO2 (7 to 11.5 Tg of sulfur) was present in the tropical stratosphere. Best estimates of the peak global stratospheric aerosol burden are in the range 19 to 26 Tg, or 3.7 to 6.7 Tg of sulfur assuming a composition of between 59 and 77 % H2SO4. In light of this large uncertainty range, we performed two main simulations with 10 and 20 Tg of SO2 injected into the tropical lower stratosphere. Simulated stratospheric aerosol properties through the 1991 to 1995 period are compared against a range of available satellite and in situ measurements. Stratospheric aerosol optical depth (sAOD) and effective radius from both simulations show good qualitative agreement with the observations, with the timing of peak sAOD and decay timescale matching well with the observations in the tropics and mid-latitudes. However, injecting 20 Tg gives a factor of 2 too high stratospheric aerosol mass burden compared to the satellite data, with consequent strong high biases in simulated sAOD and surface area density, with the 10 Tg injection in much better agreement. Our model cannot explain the large fraction of the injected sulfur that the satellite-derived SO2 and aerosol burdens indicate was removed within the first few months after the eruption. We suggest that either there is an additional alternative loss pathway for the SO2 not included in our model (e.g. via accommodation into ash or ice in the volcanic cloud) or that a larger proportion of the injected sulfur was removed via cross-tropopause transport than in our simulations. We also critically evaluate the simulated evolution of the particle size distribution, comparing in detail to balloon-borne optical particle counter (OPC) measurements from Laramie, Wyoming, USA (41° N). Overall, the model captures remarkably well the complex variations in particle concentration profiles across the different OPC size channels. However, for the 19 to 27 km injection height-range used here, both runs have a modest high bias in the lowermost stratosphere for the finest particles (radii less than 250 nm), and the decay timescale is longer in the model for these particles, with a much later return to background conditions. Also, whereas the 10 Tg run compared best to the satellite measurements, a significant low bias is apparent in the coarser size channels in the volcanically perturbed lower stratosphere. Overall, our results suggest that, with appropriate calibration, aerosol microphysics models are capable of capturing the observed variation in particle size distribution in the stratosphere across both volcanically perturbed and quiescent conditions. Furthermore, additional sensitivity simulations suggest that predictions with the models are robust to uncertainties in sub-grid particle formation and nucleation rates in the stratosphere.

Midday auroral breakup events and related energy and momentum transfer from the magnetosheath

Combined observations by meridian-scanning photometers, all-sky auroral TV camera and the EISCAT radar permitted a detailed analysis of the temporal and spatial development of the midday auroral breakup phenomenon and the related ionospheric ion flow pattern within the 71°–75° invariant latitude radar field of view. The radar data revealed dominating northward and westward ion drifts, of magnitudes close to the corresponding velocities of the discrete, transient auroral forms, during the two different events reported here, characterized by IMF |BY/BZ| < 1 and > 2, respectively (IMF BZ between −8 and −3 nT and BY > 0). The spatial scales of the discrete optical events were ∼50 km in latitude by ∼500 km in longitude, and their lifetimes were less than 10 min. Electric potential enhancements with peak values in the 30–50 kV range are inferred along the discrete arc in the IMF |BY/BZ| < 1 case from the optical data and across the latitudinal extent of the radar field of view in the |BY/BZ| > 2 case. Joule heat dissipation rates in the maximum phase of the discrete structures of ∼ 100 ergs cm−2 s−1 (0.1 W m−2) are estimated from the photometer intensities and the ion drift data. These observations combined with the additional characteristics of the events, documented here and in several recent studies (i.e., their quasi-periodic nature, their motion pattern relative to the persistent cusp or cleft auroral arc, the strong relationship with the interplanetary magnetic field and the associated ion drift/E field events and ground magnetic signatures), are considered to be strong evidence in favour of a transient, intermittent reconnection process at the dayside magnetopause and associated energy and momentum transfer to the ionosphere in the polar cusp and cleft regions. The filamentary spatial structure and the spectral characteristics of the optical signature indicate associated localized ˜1-kV potential drops between the magnetopause and the ionosphere during the most intense auroral events. The duration of the events compares well with the predicted characteristic times of momentum transfer to the ionosphere associated with the flux transfer event-related current tubes. It is suggested that, after this 2–10 min interval, the sheath particles can no longer reach the ionosphere down the open flux tube, due to the subsequent super-Alfvénic flow along the magnetopause, conductivities are lower and much less momentum is extracted from the solar wind by the ionosphere. The recurrence time (3–15 min) and the local time distribution (∼0900–1500 MLT) of the dayside auroral breakup events, combined with the above information, indicate the important roles of transient magnetopause reconnection and the polar cusp and cleft regions in the transfer of momentum and energy between the solar wind and the magnetosphere.

The cleft ion fountain: a two-dimensional kinetic model

The transport of ionospheric ions from a source in the polar cleft ionosphere through the polar magnetosphere is investigated using a two-dimensional, kinetic, trajectory-based code. The transport model includes the effects of gravitation, longitudinal magnetic gradient force, convection electric fields, and parallel electric fields. Individual ion trajectories as well as distribution functions and resulting bulk parameters of density, parallel average energy, and parallel flux for a presumed cleft ionosphere source distribution are presented for various conditions to illustrate parametrically the dependences on source energies, convection electric field strengths, ion masses, and parallel electric field strengths. The essential features of the model are consistent with the concept of a cleft-based ion fountain supplying ionospheric ions to the polar magnetosphere, and the resulting plasma distributions and parameters are in general agreement with recent low-energy ion measurements from the DE 1 satellite.

Application of two-dimensional wavelet transform in near-shore X-band radar images

Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields, and spatial wave information could be obtained from the radar images. Two-dimensional Fourier Transform (2-D FT) is the common algorithm to derive the spectra of radar images. However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms. When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain. In this article, we introduce two-dimensional Wavelet Transform (2-D WT) to capture the non-homogeneity of wave fields from nearshore radar images. The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves. Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West (SSW) to West South West (WSW). To verify the results of 2-D WT, wave shoaling in radar images is calculated based on dispersion relation. The theoretical calculation results agree with the results of 2-D WT on the whole. The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.