Lidars for Wind Tunnels - an IRPWind Joint Experiment Project

Measurement campaigns with continuous-wave Doppler Lidars (Light detection and ranging) developed at DTU Wind Energy in Denmark were performed in two very different wind tunnels. Firstly, a measurement campaign in a small icing wind tunnel chamber at VTT in Finland was performed with high frequency measurements for increasing the understanding of the effect of in-cloud icing conditions on Lidar signal dynamics. Secondly, a measurement campaign in the relatively large boundary-layer wind tunnel at NTNU in Norway was performed in the wake of a scaled test turbine in the same configuration as previously used in blind test comparisons for wind turbine wake modelers. These Lidar measurement activities constitute the Joint Experiment Project” L4WT - Lidars for Wind Tunnels, with applications to wakes and atmospheric icing in a prospective Nordic Network” with the aim of gaining and sharing knowledge about possibilities and limitations with lidar instrumentation in wind tunnels, which was funded by the IRPWind project within the community of the European Energy Research Alliance (EERA) Joint Programme on Wind Energy

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

• Leaf dark respiration (Rdark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits. • Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark. • Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8–28°C). By contrast, Rdark at a standard T (25°C, Rdark25) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark25 at a given photosynthetic capacity (Vcmax25) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark25 values at any given Vcmax25 or [N] were higher in herbs than in woody plants. • The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs)

Climate control of terrestrial carbon exchange across biomes and continents

Peer reviewe

Assessing Smoothing Effects of Wind Power around Trondheim via Koopman Mode Decomposition

To cope with a large-scale introduction of renewables into power systems, it is important to understand the reduction of variability in the aggregated generation or the so-called smoothing effect. Knowledge of the degree of smoothing is used for assessing the potential impact of intermittent generation on the power system operation. Here, smoothing effects of aggregated wind power are assessed around Trondheim, Norway, by applying a recently proposed smoothing index based on the so-called Koopman Mode Decomposition (KMD). The method is shown to effectively decompose complex time-series of wind power outputs into a finite number of modes, each of which oscillates with a single frequency for all locations (or hypothetical wind farms). It is shown that the method is able to reconstruct the original power outputs well by only a small number of modes that retain the variability of the original time-series, and is able to provide a relevant quantification of the smoothing effects for each individual frequency (or mode).publishedVersio

Chronic fatigue is highly prevalent in survivors of autologous stem cell transplantation and associated with IL-6, neuroticism, cardiorespiratory fitness, and obesity

acceptedVersion© 2018. This is the authors' accepted and refereed manuscript to the chapter. Locked until 27.3.2019 due to copyright restrictions. The final authenticated version is available online at: http://dx.doi.org/10.1038/s41409-018-0342-