[1] Arctic amplification (AA) – the observed enhanced warming in high northern latitudes relative to the northern hemisphere – is evident in lower-tropospheric temperatures and in 1000-to-500 hPa thicknesses. Daily fields of 500 hPa heights from the National Centers for Environmental Prediction Reanalysis are analyzed over N. America and the N. Atlantic to assess changes in north-south (Rossby) wave characteristics associated with AA and the relaxation of poleward thickness gradients. Two effects are identified that each contribute to a slower eastward progression of Rossby waves in the upper-level flow: 1) weakened zonal winds, and 2) increased wave amplitude. These effects are particularly evident in autumn and winter consistent with sea-ice loss, but are also apparent in summer, possibly related to earlier snow melt on high-latitude land. Slower progression of upper-level waves would cause associated weather patterns in mid-latitudes to be more persistent, which may lead to an increased probability of extreme weather events that result from prolonged conditions, such as drought, flooding, cold spells, and heat waves.

About heat waves

This study investigates the exchange of momentum between the atmosphere and ocean using data collected from four oceanic field experiments. Direct covariance estimates of momentum fluxes were collected in all four experiments and wind profiles were collected during three of them. The objective of the investigation is to improve parameterizations of the surface roughness and drag coefficient used to estimate the surface stress from bulk formulas. Specifically, the Coupled Ocean–Atmosphere Response Experiment (COARE) 3.0 bulk flux algorithm is refined to create COARE 3.5. Oversea measurements of dimensionless shear are used to investigate the stability function under stable and convective conditions. The behavior of surface roughness is then investigated over a wider range of wind speeds (up to 25 m s−1) and wave conditions than have been available from previous oversea field studies. The wind speed dependence of the Charnock coefficient α in the COARE algorithm is modified to , where m = 0.017 m−1 ...

/pdf/on-the-exchange-of-momentum-over-the-open-ocean-7tlbt5ly0x.pdf

On the exchange of momentum over the open ocean

Harvested by advanced technical systems honed over decades of research and development, wind energy has become a mainstream energy resource. However, continued innovation is needed to realize the potential of wind to serve the global demand for clean energy. Here, we outline three interdependent, cross-disciplinary grand challenges underpinning this research endeavor. The first is the need for a deeper understanding of the physics of atmospheric flow in the critical zone of plant operation. The second involves science and engineering of the largest dynamic, rotating machines in the world. The third encompasses optimization and control of fleets of wind plants working synergistically within the electricity grid. Addressing these challenges could enable wind power to provide as much as half of our global electricity needs and perhaps beyond.

/pdf/grand-challenges-in-the-science-of-wind-energy-29n51h8bdh.pdf

Grand challenges in the science of wind energy

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

/pdf/wind-power-forecasting-state-of-the-art-2009-385q4gx5c2.pdf

Wind power forecasting : state-of-the-art 2009.

Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

/pdf/sar-based-wind-resource-statistics-in-the-baltic-sea-4tnpmk2rac.pdf

SAR-Based Wind Resource Statistics in the Baltic Sea

Wind power forecasting is essential for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that may oc ...

Wind Power Forecasting Error Distributions : An International Comparison

Operational since 2004, the National Centre for Wind Turbines at Hovsore, Den- mark has become a reference research site for wind-power meteorology. In this study, we review the site, its instrumentation, observations, and main research programs. The programs comprise activities on, inter alia, remote sensing, where measurements from lidars have been compared extensively with those from traditional instrumentation on masts. In addition, with regard to wind-power meteorology, wind-resource methodologies for wind climate extrapo- lationhavebeenevaluatedandimproved.Further,specialattentionhasbeengiventoresearch on boundary-layer flow, where parametrizations of the length scale and wind profile have been developed and evaluated. Atmospheric turbulence studies are continuously conducted at Hovsore, where spectral tensor models have been evaluated and extended to account for atmosphericstability,andexperimentsusingmicroscaleandmesoscalenumericalmodelling.

/pdf/ten-years-of-boundary-layer-and-wind-power-meteorology-at-tbz1hqcuuv.pdf

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

[1] On the basis of an extensive data set from the air-sea interaction station Ostergarnsholm in the Baltic Sea, the dependence of drag on the ocean of wave state parameters has been studied for near-neutral conditions. For developing sea, the drag depends on wave age, u*/cp (u* friction velocity and cp the phase speed of the dominant waves), in agreement with recent findings over the World Ocean, strongly supporting that the Ostergarnsholm station can be relied upon to give results representative of open ocean conditions. For such conditions, it is demonstrated that the logarithmic wind law is indeed valid. For mixed sea/swell the logarithmic wind law is not valid and the drag coefficient, CD depends on two parameters representing the wave state: u*/cp and E1/E2, where E1 is the energy of the relatively long waves (having a phase velocity larger than the wind speed at 10 m) and E2, the short wave energy. Thus, plotting CD as a function of u*/cp gives a clear ordering of the data in parallel, sloping bands according to the value of E1/E2. Thus, whereas very young and slow waves affect the atmospheric flow similar to rigid roughness elements, with the occurrence of longer waves, an entirely different mechanism gains successively more importance and dynamical coupling with the atmospheric turbulence occurs. It may be speculated that the often observed kink in the wind profile represents the upper bound of a wave-boundary-layer, which is thus an order of magnitude deeper than predicted and observed during growing sea conditions.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2002JC001526

Effect of sea state on the momentum exchange over the sea during neutral conditions

Extensive mean meteorological data and high frequency sonic anemometer data from two sites in Denmark, one coastal onshore and one offshore, have been used to study the full-scale spectrum of boundary-layer winds, over frequencies f from about $$1\,\hbox {yr}^{-1}$$
 to 10 Hz. 10-min cup anemometer data are used to estimate the spectrum from about $$1\,\hbox {yr}^{-1}$$
 to $$0.05\,\hbox {min}^{-1}$$
 ; in addition, using 20-Hz sonic anemometer data, an ensemble of 1-day spectra covering the range $$1\,\hbox {day}^{-1}$$
 to 10 Hz has been calculated. The overlapping region in these two measured spectra is in good agreement. Classical topics regarding the various spectral ranges, including the spectral gap, are revisited. Following the seasonal peak at $$1\,\hbox {yr}^{-1}$$
 , the frequency spectrum fS(f) increases with $$f^{+1}$$
 and gradually reaches a peak at about $$0.2\,\hbox {day}^{-1}$$
 . From this peak to about $$1\,\hbox {hr}^{-1}$$
 , the spectrum fS(f) decreases with frequency with a $$-2$$
 slope, followed by a $$-2/3$$
 slope, which can be described by $$fS(f)=a_1f^{-2/3}+a_2f^{-2}$$
 , ending in the frequency range for which the debate on the spectral gap is ongoing. It is shown here that the spectral gap exists and can be modelled. The linear composition of the horizontal wind variation from the mesoscale and microscale gives the observed spectrum in the gap range, leading to a suggestion that mesoscale and microscale processes are uncorrelated. Depending on the relative strength of the two processes, the gap may be deep or shallow, visible or invisible. Generally, the depth of the gap decreases with height. In the low frequency region of the gap, the mesoscale spectrum shows a two-dimensional isotropic nature; in the high frequency region, the classical three-dimensional boundary-layer turbulence is evident. We also provide the cospectrum of the horizontal and vertical components, and the power spectra of the three velocity components over a wide range from $$1\,\hbox {day}^{-1}$$
 to 10 Hz, which is useful in determining the necessary sample duration when measuring turbulence statistics in the boundary layer.

/pdf/full-scale-spectrum-of-boundary-layer-winds-d2u3tt2pfk.pdf

Xiaoli Guo Larsén

Papers

SAR-Based Wind Resource Statistics in the Baltic Sea

Wind Power Forecasting Error Distributions : An International Comparison

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Effect of sea state on the momentum exchange over the sea during neutral conditions

Full-Scale Spectrum of Boundary-Layer Winds