Profiling tropospheric CO_2 using Aura TES and TCCON instruments

Monitoring the global distribution and long-term variations of CO_2 sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO_2 concentrations from ground-based near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO_2 column amount. Estimates of tropospheric CO_2 that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO_2 estimates into the GEOS-Chem model. We find that quantifying lower tropospheric CO_2 by subtracting free tropospheric CO_2 estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of −5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO_2 estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO_2 with the precision and accuracy needed to quantify lower tropospheric CO_2 variability

Resolution of Ultramicroscopy and Field of View Analysis

In a recent publication we described a microscopical technique called Ultramicroscopy, combined with a histological procedure that makes biological samples transparent. With this combination we can gather three-dimensional image data of large biological samples. Here we present the theoretical analysis of the z-resolution. By analyzing the cross-section of the illuminating sheet of light we derive resolution values according to the Rayleigh-criterion. Next we investigate the resolution adjacent to the focal point of the illumination beam, analyze throughout what extend the illumination beam is of acceptable sharpness and investigate the resolution improvements caused by the objective lens. Finally we conclude with a useful rule for the sampling rates. These findings are of practical importance for researchers working with Ultramicroscopy to decide on adequate sampling rates. They are also necessary to modify deconvolution techniques to gain further image improvements

Whitepaper: Understanding land-atmosphere interactions through tower-based flux and continuous atmospheric boundary layer measurements

Executive summary ● Target audience: AmeriFlux community, AmeriFlux Science Steering Committee & Department of Energy (DOE) program managers [ARM/ASR (atmosphere), TES (surface), and SBR (subsurface)] ● Problem statement: The atmospheric boundary layer mediates the exchange of energy and matter between the land surface and the free troposphere integrating a range of physical, chemical, and biological processes. However, continuous atmospheric boundary layer observations at AmeriFlux sites are still scarce. How can adding measurements of the atmospheric boundary layer enhance the scientific value of the AmeriFlux network? ● Research opportunities: We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics at flux tower sites, (2) to support regionalscale modeling and upscaling of surface fluxes to continental scales, (3) to validate land-atmosphere coupling in Earth system models, and (4) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements. ● Recommended actions: Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites would allow the Earth science community to address new emerging research questions, to better interpret ongoing flux tower measurements, and would present novel opportunities for collaboration between AmeriFlux scientists and atmospheric and remote sensing scientists. We therefore recommend that (1) a set of instrumentation for continuous atmospheric boundary layer observations be added to a subset of AmeriFlux sites spanning a range of ecosystem types and climate zones, that (2) funding agencies (e.g., Department of Energy, NASA) solicit research on land-atmosphere processes where the benefits of fully integrated atmospheric boundary layer observations can add value to key scientific questions, and that (3) the AmeriFlux Management Project acquires loaner instrumentation for atmospheric boundary layer observations for use in experiments and short-term duration campaigns

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

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

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

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

Application du traitement numérique du signal a la scintigraphie clinique

Les traceurs radioactifs sont utilisés en Médecine aussi bien pour l'étude morphologique de certains organes peu accessibles aux méthodes d'investigation classiques, que pour des explorations dynamiques. On distingue deux types de détecteurs : les détecteurs mobiles ou "scanners" se déplacent en regard de l'organe examiné ; les détecteurs stationnaires prennent en compte l'ensemble des émissions en provenance de l'organe pendant toute la durée de l'examen. Malheureusement, dans les deux cas, l'image obtenue n'est qu'une représentation imparfaite de l'organe examiné. Nous présentons ici les résultats d'une technique de déconvolution positive, appliquée à des signaux unidimensionnels. Nous discutons les problèmes posés par le traitement bidimensionnel dans le cas où le bruit intervenant dans la mesure est Poissonien

Imagerie spatiofrequentielle acoustique de sources mobiles et representations conjointes : DECONVOLUTION des images

L'imagerie distribue l'intensité acoustique reçue par une antenne en fonction de la fréquence et de l'angle. Pour des véhicules à vitesse quelconque la représentation des ondes reçues est relativiste. Elle décrit les signaux en tenant compte des différences de marche et des effets DOPPLER différentiels sur chacun des capteurs. L'imagerie spatiofréquentielle, obtenue par transformée de FOURIER bidimensionnelle de l'interférogramme, dépend de diverses approximations : vitesse faible, champ lointain, semilointain,... Le caractère complexe de cette grandeur permet cependant de la relier à certaines représentations conjointes. Le terme réèl d'imagerie devient prépondérant sous certaines conditions pratiques d'observation. Divers exemples illustrent les effets ci-dessus et mettent en évidence les conditions d'application de la DECONVOLUTION positive. Cette technique utilisant le seul caractère positif de l'image permet d'améliorer la résolution angulaire par un facteur dépendant du rapport signal sur bruit. Ce facteur est de l'ordre de 2 dans les applications envisagées