An investigation of the impact of time of generation on carbon savings from PV systems in Great Britain

PV only generates electricity during daylight hours and primarily generates over summer. In the UK, the carbon intensity of grid electricity is higher during the daytime and over winter. This work investigates whether the grid electricity displaced by PV is high or low carbon compared to the annual mean carbon intensity using carbon factors at higher temporal resolutions (half-hourly and daily). UK policy for carbon reporting requires savings to be calculated using the annual mean carbon intensity of grid electricity. This work offers an insight into whether this technique is appropriate. Using half hourly data on the generating plant supplying the grid from November 2008 to May 2010, carbon factors for grid electricity at half-hourly and daily resolution have been derived using technology specific generation emission factors. Applying these factors to generation data from PV systems installed on schools, it is possible to assess the variation in the carbon savings from displacing grid electricity with PV generation using carbon factors with different time resolutions. The data has been analyzed for a period of 363 to 370 days and so cannot account for inter-year variations in the relationship between PV generation and carbon intensity of the electricity grid. This analysis suggests that PV displaces more carbon intensive electricity using half-hourly carbon factors than using daily factors but less compared with annual ones. A similar methodology could provide useful insights on other variable renewable and demand-side technologies and in other countries where PV performance and grid behavior are different.

Is there a “case for property” all the time?

The “case for property” in the mixed-asset portfolio is a topic of continuing interest to practitioners and academics. Such an analysis typically is performed over a fixed period of time and the optimum allocation to property inferred from the weight assigned to property through the use of mean-variance analysis. It is well known, however, that the parameters used in the portfolio analysis problem are unstable through time. Thus, the weight proposed for property in one period is unlikely to be that found in another. Consequently, in order to assess the case for property more thoroughly, the impact of property in the mixed-asset portfolio is evaluated on a rolling basis over a long period of time. In this way we test whether the inclusion of property significantly improves the performance of an existing equity/bond portfolio all of the time. The main findings are that the inclusion of direct property into an existing equity/bond portfolio leads to increase or decreases in return, depending on the relative performance of property compared with the other asset classes. However, including property in the mixed-asset portfolio always leads to reductions in portfolio risk. Consequently, adding property into an equity/bond portfolio can lead to significant increases in risk-adjusted performance. Thus, if the decision to include direct property in the mixed-asset portfolio is based upon its diversification benefits the answer is yes, there is a “case for property” all the time!

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Probabilistic evaluation of time series models : a comparison of several approaches

Several methods are examined which allow to produce forecasts for time series in the form of probability assignments. The necessary concepts are presented, addressing questions such as how to assess the performance of a probabilistic forecast. A particular class of models, cluster weighted models (CWMs), is given particular attention. CWMs, originally proposed for deterministic forecasts, can be employed for probabilistic forecasting with little modification. Two examples are presented. The first involves estimating the state of (numerically simulated) dynamical systems from noise corrupted measurements, a problem also known as filtering. There is an optimal solution to this problem, called the optimal filter, to which the considered time series models are compared. (The optimal filter requires the dynamical equations to be known.) In the second example, we aim at forecasting the chaotic oscillations of an experimental bronze spring system. Both examples demonstrate that the considered time series models, and especially the CWMs, provide useful probabilistic information about the underlying dynamical relations. In particular, they provide more than just an approximation to the conditional mean.

The signature of ENSO in the Northern Hemisphere midlatitude seasonal mean flow and high-frequency intraseasonal variability

The impact of pronounced positive and negative sea surface temperature (STT) anomalies in the tropical Pacific associated with the El Niño/Southern Oscillation (ENSO) phenomenon on the atmospheric circulation in the Northern Hemisphere extratropics during the boreal winter season is investigated. This includes both the impact on the seasonal mean flow and on the intraseasonal variability on synoptic time scales. Moreover, the interaction between the transient fluctuations on these times scales and the mean circulation is examined. Both data from an ensemble of five simulations with the ECHAM3 atmospheric general circulation model at a horizontal resolution of T42 each covering the period from 1979 through 1992 and operational analyses from ECMWF for the corresponding period are examined. In each of the simulations observed SSTs for the period of investigation are given as lower boundary forcing, but different atmospheric initial conditions are prescribed. The simulations with ECHAM3 reveal a distinct impact of the pronounced SST-anomalies in the tropical Pacific on the atmospheric circulation in the Northern Hemisphere extratropics during El Niño as well as during La Niña events. These changes in the atmospheric circulation, which are found to be highly significant in the Pacific/North American as well as in the Atlantic/European region, are consistent with the essential results obtained from the analyses. The pronounced SST-anomalies in the tropical Pacific lead to changes in the mean circulation, which are characterized by typical circulation patterns. These changes in the mean circulation are accompanied by marked variations of the activity of the transient fluctuations on synoptic time scales, that are changes in both the kinetic energy on these time scales and the atmospheric transports of momentum and heat accomplished by the short baroclinic waves. The synoptic disturbances, on the other hand, play also an important role in controlling the changes in the mean circulation associated with the ENSO phenomenon. They maintain these typical circulation patterns via barotropic, but counteract them via baroclinic processes. The hypothesis of an impact of the ENSO phenomenon in the Atlantic/European region can be supported. As the determining factor the intensification (reduction) of the Aleutian low and the simultaneous reduction (intensification) of the Icelandic low during El Niño and during La Niña events respectively, is identified. The changes in the intensity of the Aleutian low during the ENSO-events are accompanied by an alteration of the transport of momentum caused by the short baroclinic waves over the North American continent in such a way that the changes in the intensity of the Icelandic low during El Niño as well as during La Niña events are maintained.

Zonal-mean dynamics of extended recoveries from stratospheric sudden warmings

The recovery of the Arctic polar vortex following stratospheric sudden warmings is found to take upward of 3 months in a particular subset of cases, termed here polar-night jet oscillation (PJO) events. The anomalous zonal-mean circulation above the pole during this recovery is characterized by a persistently warm lower stratosphere, and above this a cold midstratosphere and anomalously high stratopause, which descends as the event unfolds. Composites of these events in the Canadian Middle Atmosphere Model show the persistence of the lower-stratospheric anomaly is a result of strongly suppressed wave driving and weak radiative cooling at these heights. The upper-stratospheric and lower-mesospheric anomalies are driven immediately following the warming by anomalous planetary-scale eddies, following which, anomalous parameterized nonorographic and orographic gravity waves play an important role. These details are found to be robust for PJO events (as opposed to sudden warmings in general) in that many details of individual PJO events match the composite mean. Azonal-mean quasigeostrophic model on the sphere is shown to reproduce the response to the thermal and mechanical forcings produced during a PJO event. The former is well approximated by Newtonian cooling. The response can thus be considered as a transient approach to the steady-state, downward control limit. In this context, the time scale of the lower-stratospheric anomaly is determined by the transient, radiative response to the extended absence of wave driving. The extent to which the dynamics of the wave-driven descent of the stratopause can be considered analogous to the descending phases of the quasi-biennial oscillation (QBO) is also discussed.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

On the 'downward control' of extratropical diabatic circulations by eddy-induced mean zonal forces

The situation considered is that of a zonally symmetric model of the middle atmosphere subject to a given quasi-steady zonal force F̄, conceived to be the result of irreversible angular momentum transfer due to the upward propagation and breaking of Rossby and gravity waves together with any other dissipative eddy effects that may be relevant. The model's diabatic heating is assumed to have the qualitative character of a relaxation toward some radiatively determined temperature field. To the extent that the force F̄ may be regarded as given, and the extratropical angular momentum distribution is realistic, the extratropical diabatic mass flow across a given isentropic surface may be regarded as controlled exclusively by the F̄ distribution above that surface (implying control by the eddy dissipation above that surface and not, for instance, by the frequency of tropopause folding below). This “downward control” principle expresses a critical part of the dynamical chain of cause and effect governing the average rate at which photochemical products like ozone become available for folding into, or otherwise descending into, the extratropical troposphere. The dynamical facts expressed by the principle are also relevant, for instance, to understanding the seasonal-mean rate of upwelling of water vapor to the summer mesopause, and the interhemispheric differences in stratospheric tracer transport. The robustness of the principle is examined when F̄ is time-dependent. For a global-scale, zonally symmetric diabatic circulation with a Brewer-Dobson-like horizontal structure given by the second zonally symmetric Hough mode, with Rossby height HR = 13 km in an isothermal atmosphere with density scale height H = 7 km, the vertical partitioning of the unsteady part of the mass circulation caused by fluctuations in F̄ confined to a shallow layer LF̄ is always at least 84% downward. It is 90% downward when the force fluctuates sinusoidally on twice the radiative relaxation timescale and 95% if five times slower. The time-dependent adjustment when F̄ is changed suddenly is elucidated, extending the work of Dickinson (1968), when the atmosphere is unbounded above and below. Above the forcing, the adjustment is characterized by decay of the meridional mass circulation cell at a rate proportional to the radiative relaxation rate τr−1 divided by {1 + (4H2/HR2)}. This decay is related to the boundedness of the angular momentum that can be taken up by the finite mass of air above LF̄ without causing an ever-increasing departure from thermal wind balance. Below the forcing, the meridional mass circulation cell penetrates downward at a speed τr−1 HR2/H. For the second Hough mode, the time for downward penetration through one density scale height is about 6 days if the radiative relaxation time is 20 days, the latter being representative of the lower stratosphere. At any given altitude, a steady state is approached. The effect of a rigid lower boundary on the time-dependent adjustment is also considered. If a frictional planetary boundary layer is present then a steady state is ultimately approached everywhere, with the mass circulation extending downward from LF̄ and closing via the boundary layer. Satellite observations of temperature and ozone are used in conjunction with a radiative transfer scheme to estimate the altitudes from which the lower stratospheric diabatic vertical velocity is controlled by the effective F̄ in the real atmosphere. The data appear to indicate that about 80% of the effective control is usually exerted from below 40 km but with significant exceptions up to 70 km (in the high latitude southern hemispheric winter). The implications for numerical modelling of chemical transport are noted.

The effect of non-uniform radiative damping on the zonal-mean dynamics of the extratropical middle atmosphere

The effect of spatial and temporal variations in the radiative damping rate on the response to an imposed forcing or diabatic heating is examined in a zonal-mean model of the middle atmosphere. Attention is restricted to the extratropics, where a linear approach is viable. It is found that regions with weak radiative damping rates are more sensitive in terms of temperature to the remote influence of the diabatic circulation. The delay in the response in such regions can mean that ‘downward’ control is not achieved on seasonal time-scales. A seasonal variation in the radiative damping rate modulates the evolution of the response and leaves a transient-like signature in the annual mean temperature field. Several idealized examples are considered, motivated by topical questions. It is found that wave drag outside the polar vortex can significantly affect the temperatures in its interior, so that high-latitude, high-altitude gravity-wave drag is not the only mechanism for warming the southern hemisphere polar vortex. Diabatic mass transport through the 100 hPa surface is found to lag the seasonal evolution of the wave drag that drives the transport, and thus cannot be considered to be in the downward control regime. On the other hand, the seasonal variation of the radiative damping rate is found to make only a weak contribution to the annual mean temperature increase that has been observed above the ozone hole. Copyright © 2002 Royal Meteorological Society.

CP-OQAM-OFDM based SC-FDMA: adjustable user bandwidth and space-time coding

The discrete Fourier transmission spread OFDM DFTS-OFDM) based single-carrier frequency division multiple access (SC-FDMA) has been widely adopted due to its lower peak-to-average power ratio (PAPR) of transmit signals compared with OFDM. However, the offset modulation, which has lower PAPR than general modulation, cannot be directly applied into the existing SC-FDMA. When pulse-shaping filters are employed to further reduce the envelope fluctuation of transmit signals of SC-FDMA, the spectral efficiency degrades as well. In order to overcome such limitations of conventional SC-FDMA, this paper for the first time investigated cyclic prefixed OQAMOFDM (CP-OQAM-OFDM) based SC-FDMA transmission with adjustable user bandwidth and space-time coding. Firstly, we propose CP-OQAM-OFDM transmission with unequally-spaced subbands. We then apply it to SC-FDMA transmission and propose a SC-FDMA scheme with the following features: a) the transmit signal of each user is offset modulated single-carrier with frequency-domain pulse-shaping; b) the bandwidth of each user is adjustable; c) the spectral efficiency does not decrease with increasing roll-off factors. To combat both inter-symbolinterference and multiple access interference in frequencyselective fading channels, a joint linear minimum mean square error frequency domain equalization using a prior information with low complexity is developed. Subsequently, we construct space-time codes for the proposed SC-FDMA. Simulation results confirm the powerfulness of the proposed CP-OQAM-OFDM scheme (i.e., effective yet with low complexity).

A 27 day persistence model of near-Earth solar wind conditions: a long lead-time forecast and a benchmark for dynamical models

Geomagnetic activity has long been known to exhibit approximately 27 day periodicity, resulting from solar wind structures repeating each solar rotation. Thus a very simple near-Earth solar wind forecast is 27 day persistence, wherein the near-Earth solar wind conditions today are assumed to be identical to those 27 days previously. Effective use of such a persistence model as a forecast tool, however, requires the performance and uncertainty to be fully characterized. The first half of this study determines which solar wind parameters can be reliably forecast by persistence and how the forecast skill varies with the solar cycle. The second half of the study shows how persistence can provide a useful benchmark for more sophisticated forecast schemes, namely physics-based numerical models. Point-by-point assessment methods, such as correlation and mean-square error, find persistence skill comparable to numerical models during solar minimum, despite the 27 day lead time of persistence forecasts, versus 2–5 days for numerical schemes. At solar maximum, however, the dynamic nature of the corona means 27 day persistence is no longer a good approximation and skill scores suggest persistence is out-performed by numerical models for almost all solar wind parameters. But point-by-point assessment techniques are not always a reliable indicator of usefulness as a forecast tool. An event-based assessment method, which focusses key solar wind structures, finds persistence to be the most valuable forecast throughout the solar cycle. This reiterates the fact that the means of assessing the “best” forecast model must be specifically tailored to its intended use.

Analysis and modeling of active occupancy of the residential sector in Spain: an indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

High-resolution (space, time) anthropogenic heat emissions: London 1970-2025

The anthropogenic heat emissions generated by human activities in London are analysed in detail for 2005–2008 and considered in context of long-term past and future trends (1970–2025). Emissions from buildings, road traffic and human metabolism are finely resolved in space (30 min) and time (200 × 200 m2). Software to compute and visualize the results is provided. The annual mean anthropogenic heat flux for Greater London is 10.9 W m−2 for 2005–2008, with the highest peaks in the central activities zone (CAZ) associated with extensive service industry activities. Towards the outskirts of the city, emissions from the domestic sector and road traffic dominate. Anthropogenic heat is mostly emitted as sensible heat, with a latent heat fraction of 7.3% and a heat-to-wastewater fraction of 12%; the implications related to the use of evaporative cooling towers are briefly addressed. Projections indicate a further increase of heat emissions within the CAZ in the next two decades related to further intensification of activities within this area.

Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

The 30-year TAMSAT African rainfall climatology and time-series (TARCAT) dataset

African societies are dependent on rainfall for agricultural and other water-dependent activities, yet rainfall is extremely variable in both space and time and reoccurring water shocks, such as drought, can have considerable social and economic impacts. To help improve our knowledge of the rainfall climate, we have constructed a 30-year (1983–2012), temporally consistent rainfall dataset for Africa known as TARCAT (TAMSAT African Rainfall Climatology And Time-series) using archived Meteosat thermal infra-red (TIR) imagery, calibrated against rain gauge records collated from numerous African agencies. TARCAT has been produced at 10-day (dekad) scale at a spatial resolution of 0.0375°. An intercomparison of TARCAT from 1983 to 2010 with six long-term precipitation datasets indicates that TARCAT replicates the spatial and seasonal rainfall patterns and interannual variability well, with correlation coefficients of 0.85 and 0.70 with the Climate Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) gridded-gauge analyses respectively in the interannual variability of the Africa-wide mean monthly rainfall. The design of the algorithm for drought monitoring leads to TARCAT underestimating the Africa-wide mean annual rainfall on average by −0.37 mm day−1 (21%) compared to other datasets. As the TARCAT rainfall estimates are historically calibrated across large climatically homogeneous regions, the data can provide users with robust estimates of climate related risk, even in regions where gauge records are inconsistent in time.