Structure of the planetary boundary layer over southeast England: modeling and measurements

The Weather Research and Forecasting model was applied to analyze variations in the planetary boundary layer (PBL) structure over Southeast England including central and suburban London. The parameterizations and predictive skills of two nonlocal mixing PBL schemes, YSU and ACM2, and two local mixing PBL schemes, MYJ and MYNN2, were evaluated over a variety of stability conditions, with model predictions at a 3 km grid spacing. The PBL height predictions, which are critical for scaling turbulence and diffusion in meteorological and air quality models, show significant intra-scheme variance (> 20%), and the reasons are presented. ACM2 diagnoses the PBL height thermodynamically using the bulk Richardson number method, which leads to a good agreement with the lidar data for both unstable and stable conditions. The modeled vertical profiles in the PBL, such as wind speed, turbulent kinetic energy (TKE), and heat flux, exhibit large spreads across the PBL schemes. The TKE predicted by MYJ were found to be too small and show much less diurnal variation as compared with observations over London. MYNN2 produces better TKE predictions at low levels than MYJ, but its turbulent length scale increases with height in the upper part of the strongly convective PBL, where it should decrease. The local PBL schemes considerably underestimate the entrainment heat fluxes for convective cases. The nonlocal PBL schemes exhibit stronger mixing in the mean wind fields under convective conditions than the local PBL schemes and agree better with large-eddy simulation (LES) studies.

An optimal inverse method using Doppler lidar measurements to estimate the surface sensible heat flux

Inverse methods are widely used in various fields of atmospheric science. However, such methods are not commonly used within the boundary-layer community, where robust observations of surface fluxes are a particular concern. We present a new technique for deriving surface sensible heat fluxes from boundary-layer turbulence observations using an inverse method. Doppler lidar observations of vertical velocity variance are combined with two well-known mixed-layer scaling forward models for a convective boundary layer (CBL). The inverse method is validated using large-eddy simulations of a CBL with increasing wind speed. The majority of the estimated heat fluxes agree within error with the proscribed heat flux, across all wind speeds tested. The method is then applied to Doppler lidar data from the Chilbolton Observatory, UK. Heat fluxes are compared with those from a mast-mounted sonic anemometer. Errors in estimated heat fluxes are on average 18 %, an improvement on previous techniques. However, a significant negative bias is observed (on average −63%) that is more pronounced in the morning. Results are improved for the fully-developed CBL later in the day, which suggests that the bias is largely related to the choice of forward model, which is kept deliberately simple for this study. Overall, the inverse method provided reasonable flux estimates for the simple case of a CBL. Results shown here demonstrate that this method has promise in utilizing ground-based remote sensing to derive surface fluxes. Extension of the method is relatively straight-forward, and could include more complex forward models, or other measurements.

Secondary cyclogenesis along an occluded front leading to damaging wind gusts: windstorm Kyrill, January 2007

Windstorm Kyrill affected large parts of Europe in January 2007 and caused widespread havoc and loss of life. In this study the formation of a secondary cyclone, Kyill II, along the occluded front of the mature cyclone Kyrill and the occurrence of severe wind gusts as Kyrill II passed over Germany are investigated with the help of high-resolution regional climate model simulations. Kyrill underwent an explosive cyclogenesis south of Greenland as the storm crossed polewards of an intense upper-level jet stream. Later in its life cycle secondary cyclogenesis occurred just west of the British Isles. The formation of Kyrill II along the occluded front was associated (a) with frontolytic strain and (b) with strong diabatic heating in combination with a developing upper-level shortwave trough. Sensitivity studies with reduced latent heat release feature a similar development but a weaker secondary cyclone, revealing the importance of diabatic processes during the formation of Kyrill II. Kyrill II moved further towards Europe and its development was favored by a split jet structure aloft, which maintained the cyclone’s exceptionally deep core pressure (below 965 hPa) for at least 36 hours. The occurrence of hurricane force winds related to the strong cold front over North and Central Germany is analyzed using convection-permitting simulations. The lower troposphere exhibits conditional instability, a turbulent flow and evaporative cooling. Simulation at high spatio-temporal resolution suggests that the downward mixing of high momentum (the wind speed at 875 hPa widely exceeded 45 m s-1) accounts for widespread severe surface wind gusts, which is in agreement with observed widespread losses.

Variability of the interplanetary medium at 1 A.U. over 24 years: 1963–1986

A survey is presented of hourly averages of observations of the interplanetary medium, made by satellites close to the Earth (i.e. at l a.u.) in the years 1963-1986. This survey therefore covers two complete solar cycles (numbers 20 and 21). The distributions and solar-cycle variations of IMF field strength, B, and its northward component (in GSM coordinates), B(z), and of the solar-wind density, n, speed, v, and dynamic pressure, P, are discussed. Because of their importance to the terrestrial magnetosphere/ionosphere, particular attention is given to B(z) and P. The solar-cycle variation in the magnitude and variability of B(z) previously reported for cycle 20, is also found for cycle 21. However, the solar-wind data show a number of differences between cycles 20 and 21. The average dynamic pressure is found to show a solar-cycle variation and a systematic increase over the period of the survey. The minimum of dynamic pressure at sunspot maximum is mainly due to reduced solar-wind densities in cycle 20, but lower solar-wind speed in cycle 21 is a more significant factor. The distribution of the duration of periods of stable polarity of the IMF B(z) component shows that the magnetosphere could achieve steady state for only a small fraction of the time and there is some evidence for a solar-cycle variation in this fraction. It is also found that the polarity changes in the IMF B(z) fall into two classes: one with an associated change in solar-wind dynamic pressure, the other without such a change. However, in only 20% of cases does the dynamic pressure change exceed 50%.

The importance of accurate wind resource assessment for evaluating the economic viability of small wind turbines

The techno-economic performance of a small wind turbine is very sensitive to the available wind resource. However, due to financial and practical constraints installers rely on low resolution wind speed databases to assess a potential site. This study investigates whether the two site assessment tools currently used in the UK, NOABL or the Energy Saving Trust wind speed estimator, are accurate enough to estimate the techno-economic performance of a small wind turbine. Both the tools tend to overestimate the wind speed, with a mean error of 23% and 18% for the NOABL and Energy Saving Trust tool respectively. A techno-economic assessment of 33 small wind turbines at each site has shown that these errors can have a significant impact on the estimated load factor of an installation. Consequently, site/turbine combinations which are not economically viable can be predicted to be viable. Furthermore, both models tend to underestimate the wind resource at relatively high wind speed sites, this can lead to missed opportunities as economically viable turbine/site combinations are predicted to be non-viable. These results show that a better understanding of the local wind resource is a required to make small wind turbines a viable technology in the UK.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

Projected changes in tropical cyclones over Vietnam and the South China Sea using a 25 km regional climate model perturbed physics ensemble

The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949-2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069-2098) TCs compared to a 1961-1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20-44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27-53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed > 35 m/s) was found to increase by 3-9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation.

Spatio-temporal variability of polynya dynamics and ice production in the Laptev Sea between the winters of 1979/80 and 2007/08

Polynyas in the Laptev Sea are examined with respect to recurrence and interannual wintertime ice production.We use a polynya classification method based on passive microwave satellite data to derive daily polynya area from long-term sea-ice concentrations. This provides insight into the spatial and temporal variability of open-water and thin-ice regions on the Laptev Sea Shelf. Using thermal infrared satellite data to derive an empirical thin-ice distribution within the thickness range from 0 to 20 cm, we calculate daily average surface heat loss and the resulting wintertime ice formation within the Laptev Sea polynyas between 1979 and 2008 using reanalysis data supplied by the National Centers for Environmental Prediction, USA, as atmospheric forcing. Results indicate that previous studies significantly overestimate the contribution of polynyas to the ice production in the Laptev Sea. Average wintertime ice production in polynyas amounts to approximately 55 km39 27% and is mostly determined by the polynya area, wind speed and associated large-scale circulation patterns. No trend in ice production could be detected in the period from 1979/80 to 2007/08.

The land-atmosphere water flux in the tropics

Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from X decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yr(-1), but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yr(-1)) is considered in discussion on the use of flux data to validate and interpolate models.

FIRE INTENSITY AND SEVERITY IN BRAZILIAN CAMPOS GRASSLANDS

Brazilian Campos grasslands are rich in species and the maintenance of its diversity and physiognomy is dependent on disturbance (e.g. fire and grazing) Nevertheless, studies about fire intensity and severity are inexistent. The present paper describes fire parameters, using 14 experimental burn plots in southern Brazil (30 degrees 02` to 30 degrees 04`S, and 51 degrees 06` to 51 degrees 09`W. 311masl). Two sites under different fire histories were chosen: frequently burned and excluded since six years. Experimental burning was performed during summer (2006-2007), when most burning takes place in these grasslands. The following parameters were measured: air temperature and moisture, vegetation height, wind speed, fuel (fine, coarse), fuel moisture, fire temperatures (soil level and at 50cm), ash, residuals, flame freight, fire duration: burning efficiency and fire intensity were later calculated. Fuel load varied from 0.39 to 1.44kg.m(-2). and correlated positively with both fire temperature and fire intensity. Fire temperatures ranged 47 to 537.5 degrees C. being higher in the excluded site Fire intensity was low compared to grassland elsewhere (36 5-319.5kW.m(-1)), differing significantly between sties Fine fuel was the variable that best explained fire intensity. The results on fire intensity and severity in Campos grasslands can be considered a pilot study, since plots were very small. However the data provided can help other researchers to get permission for experimentation using larger plots The results provide support for further studies about the effects of fire on grassland vegetation and for studies involving fire models and fire risk prediction

The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Fire Hazard in Coconino County, Arizona

Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.

Impacto dos fatores climáticos nas vendas do varejo no Brasil. Uma abordagem com dados de painel com efeito fixo.

Os impactos das variações climáticas tem sido um tema amplamente pesquisado na macroeconomia mundial e também em setores como agricultura, energia e seguros. Já para o setor de varejo, uma busca nos principais periódicos brasileiros não retornou nenhum estudo específico. Em economias mais desenvolvidas produtos de seguros atrelados ao clima são amplamente negociados e através deste trabalho visamos também avaliar a possibilidade de desenvolvimento deste mercado no Brasil. O presente trabalho buscou avaliar os impactos das variações climáticas nas vendas do varejo durante período de aproximadamente 18 meses (564 dias) para 253 cidades brasileiras. As informações de variações climáticas (precipitação, temperatura, velocidade do vento, umidade relativa, insolação e pressão atmosférica) foram obtidas através do INMET (Instituto Nacional de Meteorologia) e cruzadas com as informações transacionais de até 206 mil clientes ativos de uma amostra não balanceada, oriundos de uma instituição financeira do ramo de cartões de crédito. Ambas as bases possuem periodicidade diária. A metodologia utilizada para o modelo econométrico foram os dados de painel com efeito fixo para avaliação de dados longitudinais através dos softwares de estatística / econometria EViews (software proprietário da IHS) e R (software livre). A hipótese nula testada foi de que o clima influencia nas decisões de compra dos clientes no curto prazo, hipótese esta provada pelas análises realizadas. Assumindo que o comportamento do consumidor do varejo não muda devido à seleção do meio de pagamento, ao chover as vendas do varejo em moeda local são impactadas negativamente. A explicação está na redução da quantidade total de transações e não o valor médio das transações. Ao excluir da base as cidades de São Paulo e Rio de Janeiro não houve alteração na significância e relevância dos resultados. Por outro lado, a chuva possui efeito de substituição entre as vendas online e offline. Quando analisado setores econômicos para observar se há comportamento diferenciado entre consumo e compras não observou-se alteração nos resultados. Ao incluirmos variáveis demográficas, concluímos que as mulheres e pessoas com maior faixa de idade apresentam maior histórico de compras. Ao avaliar o impacto da chuva em um determinado dia e seu impacto nos próximos 6 à 29 dias observamos que é significante para a quantidade de transações porém o impacto no volume de vendas não foi significante.

Análise de métodos de predição de conforto térmico de habitação em clima quente-úmido com condicionamento passivo

The assessment of building thermal performance is often carried out using HVAC energy consumption data, when available, or thermal comfort variables measurements, for free-running buildings. Both types of data can be determined by monitoring or computer simulation. The assessment based on thermal comfort variables is the most complex because it depends on the determination of the thermal comfort zone. For these reasons, this master thesis explores methods of building thermal performance assessment using variables of thermal comfort simulated by DesignBuilder software. The main objective is to contribute to the development of methods to support architectural decisions during the design process, and energy and sustainable rating systems. The research method consists on selecting thermal comfort methods, modeling them in electronic sheets with output charts developed to optimize the analyses, which are used to assess the simulation results of low cost house configurations. The house models consist in a base case, which are already built, and changes in thermal transmittance, absorptance, and shading. The simulation results are assessed using each thermal comfort method, to identify the sensitivity of them. The final results show the limitations of the methods, the importance of a method that considers thermal radiance and wind speed, and the contribution of the chart proposed