868 resultados para Microsoft Office
Resumo:
The inclusion of the direct and indirect radiative effects of aerosols in high-resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three-dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing long-wave radiation over West Africa due to a better representation of dust. However, uncertainties in dust optical properties propagate to its direct effect and the subsequent model response. Inclusion of the indirect aerosol effects improves surface radiation biases at the North Slope of Alaska ARM site due to lower cloud amounts in high-latitude clean-air regions. This leads to improved temperature and height forecasts in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short-range forecasts. However, the indirect aerosol effect leads to a strengthening of the low-level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. Regional impacts on the African Easterly Jet (AEJ) are also presented with the large dust loading in the aerosol climatology enhancing of the heat low over West Africa and weakening the AEJ. This study highlights the importance of including a more realistic treatment of aerosol–cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes.
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A new coupled cloud physics–radiation parameterization of the bulk optical properties of ice clouds is presented. The parameterization is consistent with assumptions in the cloud physics scheme regarding particle size distributions (PSDs) and mass–dimensional relationships. The parameterization is based on a weighted ice crystal habit mixture model, and its bulk optical properties are parameterized as simple functions of wavelength and ice water content (IWC). This approach directly couples IWC to the bulk optical properties, negating the need for diagnosed variables, such as the ice crystal effective dimension. The parameterization is implemented into the Met Office Unified Model Global Atmosphere 5.0 (GA5) configuration. The GA5 configuration is used to simulate the annual 20-yr shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA), as well as the temperature structure of the atmosphere, under various microphysical assumptions. The coupled parameterization is directly compared against the current operational radiation parameterization, while maintaining the same cloud physics assumptions. In this experiment, the impacts of the two parameterizations on the SW and LW radiative effects at TOA are also investigated and compared against observations. The 20-yr simulations are compared against the latest observations of the atmospheric temperature and radiative fluxes at TOA. The comparisons demonstrate that the choice of PSD and the assumed ice crystal shape distribution are as important as each other. Moreover, the consistent radiation parameterization removes a long-standing tropical troposphere cold temperature bias but slightly warms the southern midlatitudes by about 0.5 K.
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We describe Global Atmosphere 3.0 (GA3.0): a configuration of the Met Office Unified Model (MetUM) developed for use across climate research and weather prediction activities. GA3.0 has been formulated by converging the development paths of the Met Office's weather and climate global atmospheric model components such that wherever possible, atmospheric processes are modelled or parametrized seamlessly across spatial resolutions and timescales. This unified development process will provide the Met Office and its collaborators with regular releases of a configuration that has been evaluated, and can hence be applied, over a variety of modelling régimes. We also describe Global Land 3.0 (GL3.0): a configuration of the JULES community land surface model developed for use with GA3.0.
Resumo:
It is widely accepted that there is a gap between design energy and real world operational energy consumption. The behaviour of occupants is often cited as an important factor influencing building energy performance. However, its consideration, both during design and operation, is overly simplistic, often assuming a direct link between attitudes and behaviour. Alternative models of decision making from psychology highlight a range of additional influential factors and emphasise that occupants do not always act in a rational manner. Developing a better understanding of occupant decision making could help inform office energy conservation campaigns as well as models of behaviour employed during the design process. This paper assesses the contribution of various behavioural constructs on small power consumption in offices. The method is based upon the Theory of Planned Behaviour (TPB) which assumes that intention is driven by three factors: attitude, subjective norms, and perceived behavioural control, but we also consider a fourth construct: habit measured through the Self- Report Habit Index (SRHI). A questionnaire was issued to 81 participants in two UK offices. Questionnaire results for each behavioural construct were correlated against each participant’s individual workstation electricity consumption. The intentional processes proposed by TPB could not account for the observed differences in occupants’ interactions with small power appliances. Instead, occupants were interacting with small power “automatically”, with habit accounting for 11% of the variation in workstation energy consumption. The implications for occupant behaviour models and employee engagement campaigns are discussed.
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As new buildings are constructed in response to changes in technology or user requirements, the value of the existing stock will decline in relative terms. This is termed economic depreciation and it may be influenced by the age and quality of buildings, amount and timing of expenditure, and wider market and economic conditions. This study tests why individual assets experience different depreciation rates, applying panel regression techniques to 375 UK office and industrial assets. Results suggest that rental value depreciation rates reduce as buildings get older, while a composite measure of age and quality provides more explanation of depreciation than age alone. Furthermore, economic and local real estate market conditions are significant in explaining how depreciation rates change over time.
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Met Office station data from 1980 to 2012 has been used to characterise the interannual variability of incident solar irradiance across the UK. The same data are used to evaluate four popular historical irradiance products to determine which are most suitable for use by the UK PV industry for site selection and system design. The study confirmed previous findings that interannual variability is typically 3–6% and weighted average probability of a particular percentage deviation from the mean at an average site in the UK was calculated. This weighted average showed that fewer than 2% of site-years could be expected to fall below 90% of the long-term site mean. The historical irradiance products were compared against Met Office station data from the input years of each product. This investigation has found that all products perform well. No products have a strong spatial trend. Meteonorm 7 is most conservative (MBE = −2.5%), CMSAF is most optimistic (MBE = +3.4%) and an average of all four products performs better than any one individual product (MBE = 0.3%)
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Weather and climate model simulations of the West African Monsoon (WAM) have generally poor representation of the rainfall distribution and monsoon circulation because key processes, such as clouds and convection, are poorly characterized. The vertical distribution of cloud and precipitation during the WAM are evaluated in Met Office Unified Model simulations against CloudSat observations. Simulations were run at 40-km and 12-km horizontal grid length using a convection parameterization scheme and at 12-km, 4-km, and 1.5-km grid length with the convection scheme effectively switched off, to study the impact of model resolution and convection parameterization scheme on the organisation of tropical convection. Radar reflectivity is forward-modelled from the model cloud fields using the CloudSat simulator to present a like-with-like comparison with the CloudSat radar observations. The representation of cloud and precipitation at 12-km horizontal grid length improves dramatically when the convection parameterization is switched off, primarily because of a reduction in daytime (moist) convection. Further improvement is obtained when reducing model grid length to 4 km or 1.5 km, especially in the representation of thin anvil and mid-level cloud, but three issues remain in all model configurations. Firstly, all simulations underestimate the fraction of anvils with cloud top height above 12 km, which can be attributed to too low ice water contents in the model compared to satellite retrievals. Secondly, the model consistently detrains mid-level cloud too close to the freezing level, compared to higher altitudes in CloudSat observations. Finally, there is too much low-level cloud cover in all simulations and this bias was not improved when adjusting the rainfall parameters in the microphysics scheme. To improve model simulations of the WAM, more detailed and in-situ observations of the dynamics and microphysics targeting these non-precipitating cloud types are required.
Resumo:
his article examines the impact of foreign real estate investment on U.S. office market capitalization rates. The geographic unit of analysis is MSA and the time period is 2001–2013. Drawing upon a database of commercial real estate transactions, the authors model the determinants of market capitalization rates with a particular focus on the significance of the proportion of market transactions involving foreign investors. Employing several econometric techniques to analyze the data, the results suggest statistically significant effects of foreign investment across 38 U.S. metro areas. It is estimated that, all else equal, a 100 basis point increase in foreign share of total investment in a U.S. metropolitan office market causes about an 8 basis point decrease in the market cap rate.
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The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.
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With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.
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We assess Indian summer monsoon seasonal forecasts in GloSea5-GC2, the Met Office fully coupled subseasonal to seasonal ensemble forecasting system. Using several metrics, GloSea5-GC2 shows similar skill to other state-of-the-art forecast systems. The prediction skill of the large-scale South Asian monsoon circulation is higher than that of Indian monsoon rainfall. Using multiple linear regression analysis we evaluate relationships between Indian monsoon rainfall and five possible drivers of monsoon interannual variability. Over the time period studied (1992-2011), the El Nino-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) are the most important of these drivers in both observations and GloSea5-GC2. Our analysis indicates that ENSO and its teleconnection with the Indian rainfall are well represented in GloSea5-GC2. However, the relationship between the IOD and Indian rainfall anomalies is too weak in GloSea5-GC2, which may be limiting the prediction skill of the local monsoon circulation and Indian rainfall. We show that this weak relationship likely results from a coupled mean state bias that limits the impact of anomalous wind forcing on SST variability, resulting in erroneous IOD SST anomalies. Known difficulties in representing convective precipitation over India may also play a role. Since Indian rainfall responds weakly to the IOD, it responds more consistently to ENSO than in observations. Our assessment identifies specific coupled biases that are likely limiting GloSea5-GC2 prediction skill, providing targets for model improvement.
Resumo:
Thermochromic windows are able to modulate their transmittance in both the visible and the near-infrared field as a function of their temperature. As a consequence, they allow to control the solar gains in summer, thus reducing the energy needs for space cooling. However, they may also yield a reduction in the daylight availability, which results in the energy consumption for indoor artificial lighting being increased. This paper investigates, by means of dynamic simulations, the application of thermochromic windows to an existing office building in terms of energy savings on an annual basis, while also focusing on the effects in terms of daylighting and thermal comfort. In particular, due attention is paid to daylight availability, described through illuminance maps and by the calculation of the daylight factor, which in several countries is subject thresholds. The study considers both a commercially available thermochromic pane and a series of theoretical thermochromic glazing. The expected performance is compared to static clear and reflective insulating glass units. The simulations are repeated in different climatic conditions, showing that the overall energy savings compared to clear glazing can range from around 5% for cold climates to around 20% in warm climates, while not compromising daylight availability. Moreover the role played by the transition temperature of the pane is examined, pointing out an optimal transition temperatures that is irrespective of the climatic conditions.
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This paper presents a study on reduction of energy consumption in buildings through behaviour change informed by wireless monitoring systems for energy, environmental conditions and people positions. A key part to the Wi-Be system is the ability to accurately attribute energy usage behaviour to individuals, so they can be targeted with specific feedback tailored to their preferences. The use of wireless technologies for indoor positioning was investigated to ascertain the difficulties in deployment and potential benefits. The research to date has demonstrated the effectiveness of highly disaggregated personal-level data for developing insights into people’s energy behaviour and identifying significant energy saving opportunities (up to 77% in specific areas). Behavioural research addressed social issues such as privacy, which could affect the deployment of the system. Radio-frequency research into less intrusive technologies indicates that received-signal-strength-indicator-based systems should be able to detect the presence of a human body, though further work would be needed in both social and engineering areas.
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Cool materials are characterized by having a high solar reflectance r – which is able to reduce heat gains during daytime - and a high thermal emissivity ε that enables them to dissipate the heat absorbed throughout the day during night. Despite the concept of cool roofs - i.e. the application of cool materials to roof surfaces - is well known in US since 1990s, many studies focused on their performance in both residential and commercial sectors under various climatic conditions for US countries, while only a few case studies are analyzed in EU countries. The present work aims at analyzing the thermal benefits due to their application to existing office buildings located in EU countries. Indeed, due to their weight in the existing buildings stock, as well as the very low rate of new buildings construction, the retrofit of office buildings is a topic of great concern worldwide. After an in-depth characterization of the existing buildings stock in the EU, the book gives an insight into roof energy balance due to different technological solutions, showing in which cases and to what extent cool roofs are preferable. A detailed description of the physical properties of cool materials and their availability on the market provides a solid background for the parametric analysis carried out by means of detailed numerical models that aims at evaluating cool roofs performance for various climates and office buildings configurations. With the help of dynamic simulations, the thermal behavior of representative office buildings of the existing EU buildings stock is assessed in terms of thermal comfort and energy needs for air conditioning. The results, which consider several variations of building features that may affect the resulting energy balance, show how cool roofs are an effective strategy for reducing overheating occurrences and thus improving thermal comfort in any climate. On the other hand, potential heating penalties due to a reduction in the incoming heat fluxes through the roof are taken into account, as well as the aging process of cool materials. Finally, an economic analysis of the best performing models shows the boundaries for their economic convenience.