240 resultados para Wind forecast


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It is widely thought that changes in both the surface buoyancy fluxes and wind stress drive variability in the Atlantic meridional overturning circulation (AMOC), but that they drive variability on different time scales. For example, wind forcing dominates short-term variability through its effects on Ekman currents and coastal upwelling, whereas buoyancy forcing is important for longer time scales (multiannual and decadal). However, the role of the wind forcing on multiannual to decadal time scales is less clear. Here the authors present an analysis of simulations with the Nucleus for European Modelling of the Ocean (NEMO) ocean model with the aim of explaining the important drivers of the zonal density gradient at 26°N, which is directly related to the AMOC. In the experiments, only one of either the wind stress or the buoyancy forcing is allowed to vary in time, whereas the other remains at its seasonally varying climatology. On subannual time scales, variations in the density gradient, and in the AMOC minus Ekman, are driven largely by local wind-forced coastal upwelling at both the western and eastern boundaries. On decadal time scales, buoyancy forcing related to the North Atlantic Oscillation dominates variability in the AMOC. Interestingly, however, it is found that wind forcing also plays a role at longer time scales, primarily impacting the interannual variability through the excitation of Rossby waves in the central Atlantic, which propagate westward to interact with the western boundary, but also by modulating the decadal time-scale response to buoyancy forcing.

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Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens. There is little evidence of a link between individuals’ ex post forecast accuracy and their ex ante subjective assessments.

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Observations of atmospheric conditions and processes in citiesare fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality and climate models, and providing key information for city end-users (e.g. decision-makers, stakeholders, public). In this paper, Shanghai's urban integrated meteorological observation network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being: multi- purpose (e.g. forecast, research, service), multi-function (high impact weather, city climate, special end-users), multi-scale (e.g. macro/meso-, urban-, neighborhood, street canyon), multi-variable (e.g. thermal, dynamic, chemical, bio-meteorological, ecological), and multi- platform (e.g. radar, wind profiler, ground-based, satellite based, in-situ observation/ sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments; to identify data gaps based on science and user driven requirements; and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

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A statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy-seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO-CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near-surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long-term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods. For the present climate, SDD is able to simulate realistic PDFs of 10-m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD-simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD-simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI-ESM) decadal prediction system. Long-term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI-OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

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Spatially dense observations of gust speeds are necessary for various applications, but their availability is limited in space and time. This work presents an approach to help to overcome this problem. The main objective is the generation of synthetic wind gust velocities. With this aim, theoretical wind and gust distributions are estimated from 10 yr of hourly observations collected at 123 synoptic weather stations provided by the German Weather Service. As pre-processing, an exposure correction is applied on measurements of the mean wind velocity to reduce the influence of local urban and topographic effects. The wind gust model is built as a transfer function between distribution parameters of wind and gust velocities. The aim of this procedure is to estimate the parameters of gusts at stations where only wind speed data is available. These parameters can be used to generate synthetic gusts, which can improve the accuracy of return periods at test sites with a lack of observations. The second objective is to determine return periods much longer than the nominal length of the original time series by considering extreme value statistics. Estimates for both local maximum return periods and average return periods for single historical events are provided. The comparison of maximum and average return periods shows that even storms with short average return periods may lead to local wind gusts with return periods of several decades. Despite uncertainties caused by the short length of the observational records, the method leads to consistent results, enabling a wide range of possible applications.

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Wind energy potential in Iberia is assessed for recent–past (1961–2000) and future (2041–2070) climates. For recent–past, a COSMO-CLM simulation driven by ERA-40 is used. COSMO-CLM simulations driven by ECHAM5 following the A1B scenario are used for future projections. A 2 MW rated power wind turbine is selected. Mean potentials, inter-annual variability and irregularity are discussed on annual/seasonal scales and on a grid resolution of 20 km. For detailed regional assessments eight target sites are considered. For recent–past conditions, the highest daily mean potentials are found in winter over northern and eastern Iberia, particularly on high-elevation or coastal regions. In northwestern Iberia, daily potentials frequently reach maximum wind energy output (50 MWh day−1), particularly in winter. Southern Andalucía reveals high potentials throughout the year, whereas the Ebro valley and central-western coast show high potentials in summer. The irregularity in annual potentials is moderate (<15% of mean output), but exacerbated in winter (40%). Climate change projections show significant decreases over most of Iberia (<2 MWh day−1). The strong enhancement of autumn potentials in Southern Andalucía is noteworthy (>2 MWh day−1). The northward displacement of North Atlantic westerly winds (autumn–spring) and the strengthening of easterly flows (summer) are key drivers of future projections.

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Many studies evaluating model boundary-layer schemes focus either on near-surface parameters or on short-term observational campaigns. This reflects the observational datasets that are widely available for use in model evaluation. In this paper we show how surface and long-term Doppler lidar observations, combined in a way to match model representation of the boundary layer as closely as possible, can be used to evaluate the skill of boundary-layer forecasts. We use a 2-year observational dataset from a rural site in the UK to evaluate a climatology of boundary layer type forecast by the UK Met Office Unified Model. In addition, we demonstrate the use of a binary skill score (Symmetric Extremal Dependence Index) to investigate the dependence of forecast skill on season, horizontal resolution and forecast leadtime. A clear diurnal and seasonal cycle can be seen in the climatology of both the model and observations, with the main discrepancies being the model overpredicting cumulus capped and decoupled stratocumulus capped boundary-layers and underpredicting well mixed boundary-layers. Using the SEDI skill score the model is most skillful at predicting the surface stability. The skill of the model in predicting cumulus capped and stratocumulus capped stable boundary layer forecasts is low but greater than a 24 hr persistence forecast. In contrast, the prediction of decoupled boundary-layers and boundary-layers with multiple cloud layers is lower than persistence. This process based evaluation approach has the potential to be applied to other boundary-layer parameterisation schemes with similar decision structures.

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With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

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Arctic sea ice thickness is thought to be an important predictor of Arctic sea ice extent. However, coupled seasonal forecast systems do not generally use sea ice thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the sea ice thickness initial state, have been run. These experiments show that accurate knowledge of the sea ice thickness field is crucially important for sea ice concentration and extent forecasts up to 8 months ahead, especially in summer. Perturbing sea ice thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate sea ice thickness into coupled forecast systems could significantly increase skill.

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We use combinations of geomagnetic indices, based on both variation range and hourly means, to derive the solar wind flow speed, the interplanetary magnetic field strength at 1 AU and the total open solar flux between 1895 and the present. We analyze the effects of the regression procedure and geomagnetic indices used by adopting four analysis methods. These give a mean interplanetary magnetic field strength increase of 45.1 ± 4.5% between 1903 and 1956, associated with a 14.4 ± 0.7% rise in the solar wind speed. We use averaging timescales of 1 and 2 days to allow for the difference between the magnetic fluxes threading the coronal source surface and the heliocentric sphere at 1 AU. The largest uncertainties originate from the choice of regression procedure: the average of all eight estimates of the rise in open solar flux is 73.0 ± 5.0%, but the best procedure, giving the narrowest and most symmetric distribution of fit residuals, yields 87.3 ± 3.9%.

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There are no direct observational methods for determining the total rate at which energy is extracted from the solar wind by the magnetosphere. In the absence of such a direct measurement, alternative means of estimating the energy available to drive the magnetospheric system have been developed using different ionospheric and magnetospheric indices as proxies for energy consumption and dissipation and thus the input. The so-called coupling functions are constructed from the parameters of the interplanetary medium, as either theoretical or empirical estimates of energy transfer, and the effectiveness of these coupling functions has been evaluated in terms of their correlation with the chosen index. A number of coupling functions have been studied in the past with various criteria governing event selection and timescale. The present paper contains an exhaustive survey of the correlation between geomagnetic activity and the near-Earth solar wind and two of the planetary indices at a wide variety of timescales. Various combinations of interplanetary parameters are evaluated with careful allowance for the effects of data gaps in the interplanetary data. We show that the theoretical coupling, P�, function first proposed by Vasyliunas et al. is superior at all timescales from 1-day to 1-year.

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Transport of pollution and heatout of streets into the boundary layer above is not currently understood and so fluxes cannot be quantified. Scalar concentration within the street is determined by the flux out of it and so quantifying fluxes for turbulent flow over a rough urban surface is essential. We have developed a naphthalene sublimation technique to measure transfer from a two-dimensional street canyon in a wind tunnel for the case of flow perpendicular to the street. The street was coated with naphthalene, which sublimes at room temperature, so that the vapour represented the scalar source. The transfer velocity wT relates the flux out of the canyon to the concentration within it and is shown to be linearly related to windspeed above the street. The dimensionless transfer coefficient wT/Uδ represents the ventilation efficiency of the canyon (here, wT is a transfer velocity,Uδ is the wind speed at the boundary-layer top). Observed values are between 1.5 and 2.7 ×10-3 and, for the case where H/W→0 (ratio of buildingheight to street width), values are in the same range as estimates of transfer from a flat plate, giving confidence that the technique yields accurate values for street canyon scalar transfer. wT/Uδ varies with aspect ratio (H/W), reaching a maximum in the wake interference regime (0.3 < H/W < 0.65). However, when upstream roughness is increased, the maximum in wT/Uδ reduces, suggesting that street ventilation is less sensitive to H/W when the flow is in equilibrium with the urban surface. The results suggest that using naphthalene sublimation with wind-tunnel models of urban surfaces can provide a direct measure of area-averaged scalar fluxes.

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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.

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During the substorm growth phase, magnetic reconnection extracts ~10^15 J from the solar wind through magnetic reconnection at the magnetopause, which is then stored in the magnetotail lobes. Plasma sheet pressure then increases to balance magnetic flux density increases in the lobes. We examine plasma sheet pressure, density and temperature during substorm growth phases using nine years of Cluster data (>316,000 data points). We show that plasma sheet pressure and temperature are higher during growth phases with higher solar wind driving whereas the density is approximately constant. We also show a weak correlation between plasma sheet temperature before onset and the minimum SuperMAG SML auroral index in the subsequent substorm. We discuss how energization of the plasma sheet before onset may result from thermodynamically adiabatic processes; how hotter plasma sheets may result in magnetotail instabilities and how this relates to the onset and size of the subsequent substorm expansion phase.