scholarly journals Understanding the representativeness of FLUXNET for upscaling carbon flux from eddy covariance measurements

2016 ◽  
Author(s):  
Jitendra Kumar ◽  
Forrest M. Hoffman ◽  
William W. Hargrove ◽  
Nathan Collier
Keyword(s):  
Carbon Cycle ◽  
Eddy Covariance ◽  
Temporal Dynamics ◽  
Data Availability ◽  
Full Potential ◽  
Data Set ◽  
Ecosystem Properties ◽  
Eddy Covariance Measurements ◽  
Spatio Temporal

Abstract. Eddy covariance data from regional flux networks are direct in situ measurement of carbon, water, and energy fluxes and are of vital importance for understanding the spatio-temporal dynamics of the the global carbon cycle. FLUXNET links regional networks of eddy covariance sites across the globe to quantify the spatial and temporal variability of fluxes at regional to global scales and to detect emergent ecosystem properties. This study presents an assessment of the representativeness of FLUXNET based on the recently released FLUXNET2015 data set. We present a detailed high resolution analysis of the evolving representativeness of FLUXNET through time. Results provide quantitative insights into the extent that various biomes are sampled by the network of networks, the role of the spatial distribution of the sites on the network scale representativeness at any given time, and how that representativeness has changed through time due to changing operational status and data availability at sites in the network. To realize the full potential of FLUXNET observations for understanding emergent ecosystem properties at regional and global scales, we present an approach for upscaling eddy covariance measurements. Informed by the representativeness of observations at the flux sites in the network, the upscaled data reflects the spatio-temporal dynamics of the carbon cycle captured by the in situ measurements. This study presents a method for optimal use of the rich point measurements from FLUXNET to derive an understanding of upscaled carbon fluxes, which can be routinely updated as new data become available, and direct network expansion by identifying regions poorly sampled by the current network. Data from this study are available at http://dx.doi.org/10.15486/NGT/1279968

Mapping the aerodynamic roughness of the Greenland ice sheet surface using ICESat-2

2021 ◽  
Author(s):  
Maurice van Tiggelen ◽  
Paul C.J.P. Smeets ◽  
Carleen H. Reijmer ◽  
Bert Wouters ◽  
Jakob F. Steiner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Elevation ◽  
Spatiotemporal Variability ◽  
Atmospheric Models ◽  
Laser Altimeter ◽  
Eddy Covariance Measurements ◽  
Aerodynamic Roughness

<p>The roughness of a natural surface is an important parameter in atmospheric models, as it determines the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately, this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available.</p><p>In this study, we take advantage of the measurements of the ICESat-2 satellite laser altimeter. We use the geolocated photons product (ATL03) to retrieve a 1-m resolution surface elevation product over the K-transect (West Greenland ice sheet). In combination with a bulk drag partitioning model, the retrieved surface elevation is used to estimate the aerodynamic roughness length (z<sub>0m</sub>) of the surface.</p><p>We demonstrate the high precision of the retrieved ICESat-2 elevation using co-located UAV photogrammetry, and then evaluate the modelled aerodynamic roughness against multiple in situ eddy-covariance observations. The results point out the importance to use a bulk drag model over a more empirical formulation.</p><p>The currently available ATL03 geolocated photons are used to map the aerodynamic roughness along the K-transect (2018-2020). We find a considerable spatiotemporal variability in z<sub>0m</sub>, ranging between 10<sup>−4</sup> m for a smooth snow surface to more than 10<sup>−1</sup> m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.</p>

Hydrological functioning of irrigated maize crops in southwest France using Eddy Covariance measurements and a land surface model

2021 ◽  
Author(s):  
Oluwakemi Dare-Idowu ◽  
Lionel Jarlan ◽  
Aurore Brut ◽  
Valerie Le-Dantec ◽  
Vincent Rivalland ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Sap Flow ◽  
Heat Fluxes ◽  
Added Value ◽  
Surface Model ◽  
Data Set ◽  
Flow Measurements ◽  
Ground Heat Flux

<p>This study aims to analyze the main components of the energy and hydric budgets of irrigated maize in southwestern France. To this objective, the ISBA-A-gs (<span>Interactions between Soil, Biosphere, and Atmosphere) </span>is run over six maize growing seasons. As a preliminary step, the ability of the ISBA-A-gs model to predict the different terms of the energy and water budgets is assessed thanks to a large database of <em>in situ</em> measurements by comparing the single budget version of the model with the new Multiple Energy Balance version solving an energy budget separately for the soil and the vegetation. The <em>in situ</em> data set acquired at the Lamasquere site (43.48<sup>o</sup> N, 1.249<sup>o</sup> E) includes half-hourly measurements of sensible (H) and latent heat fluxes (LE) estimated by an Eddy Covariance system. Measurements also include net radiation (Rn), ground heat flux (G), plant transpiration with sap flow sensors, meteorological variables, and 15-days measurements of vegetation characteristics. The seasonal dynamics of the turbulent fluxes were properly reproduced by both configurations of the model with an R² ranging from 0.66 to 0.89, and a root mean square error lower than 48 W m<sup>-2</sup>. Statistical metrics showed that H was better predicted by MEB with R² of 0.80 in comparison to ISBA-Ags (0.73). However, the difference between the RMSE of ISBA-Ags and MEB during the well-developed stage of the plants for both H and LE does not exceed 8 W m<sup>-2</sup>. This implies that MEB only has a significant added value over ISBA-Ags when the soil and the canopy are not fully coupled, and over a heterogeneous field. Furthermore, this study made a comparison between the sap flow measurements and the transpiration simulated by ISBA-A-gs and MEB. A good dynamics was reproduced by ISBA-A-gs and MEB, although, MEB (R²= 0.91) provided a slightly more realistic estimation of the vegetation transpiration. Consequently, this study investigated the dynamics of the water budget during the growing maize seasons. Results indicated that drainage is almost null on the site, while the observed values of cumulative evapotranspiration that was higher than the water inputs are related to a shallow ground table that provides supplement water to the crop. This work provides insight into the modeling of water and energy exchanges over maize crops and opens perspectives for better water management of the crop in the future.</p>

scholarly journals Deriving seasonal dynamics in ecosystem properties of semi-arid savanna grasslands from in situ-based hyperspectral reflectance

2015 ◽  
Vol 12 (15) ◽  
pp. 4621-4635 ◽  
Author(s):  
T. Tagesson ◽  
R. Fensholt ◽  
S. Huber ◽  
S. Horion ◽  
I. Guiro ◽  
...  
Keyword(s):  
Seasonal Dynamics ◽  
Near Infrared ◽  
Spectral Characteristics ◽  
Arid Ecosystems ◽  
Hyperspectral Reflectance ◽  
Data Set ◽  
Ecosystem Properties ◽  
Shortwave Infrared ◽  
Semi Arid

Abstract. This paper investigates how hyperspectral reflectance (between 350 and 1800 nm) can be used to infer ecosystem properties for a semi-arid savanna grassland in West Africa using a unique in situ-based multi-angular data set of hemispherical conical reflectance factor (HCRF) measurements. Relationships between seasonal dynamics in hyperspectral HCRF and ecosystem properties (biomass, gross primary productivity (GPP), light use efficiency (LUE), and fraction of photosynthetically active radiation absorbed by vegetation (FAPAR)) were analysed. HCRF data (ρ) were used to study the relationship between normalised difference spectral indices (NDSIs) and the measured ecosystem properties. Finally, the effects of variable sun sensor viewing geometry on different NDSI wavelength combinations were analysed. The wavelengths with the strongest correlation to seasonal dynamics in ecosystem properties were shortwave infrared (biomass), the peak absorption band for chlorophyll a and b (at 682 nm) (GPP), the oxygen A band at 761 nm used for estimating chlorophyll fluorescence (GPP and LUE), and blue wavelengths (ρ412) (FAPAR). The NDSI with the strongest correlation to (i) biomass combined red-edge HCRF (ρ705) with green HCRF (ρ587), (ii) GPP combined wavelengths at the peak of green reflection (ρ518, ρ556), (iii) LUE combined red (ρ688) with blue HCRF (ρ436), and (iv) FAPAR combined blue (ρ399) and near-infrared (ρ1295) wavelengths. NDSIs combining near infrared and shortwave infrared were strongly affected by solar zenith angles and sensor viewing geometry, as were many combinations of visible wavelengths. This study provides analyses based upon novel multi-angular hyperspectral data for validation of Earth-observation-based properties of semi-arid ecosystems, as well as insights for designing spectral characteristics of future sensors for ecosystem monitoring.

Technology and atmospheric mission platform - OPerations (TOP)

2020 ◽  
Author(s):  
Stefano Natali ◽  
Clemens Rendl ◽  
Gerhard Triebnig ◽  
Daniel Santillan ◽  
Marcus Hirtl ◽  
...  
Keyword(s):  
Web Application ◽  
Data Cube ◽  
Data Availability ◽  
Multidimensional Data ◽  
Full Potential ◽  
Time Model ◽  
Atmospheric Sciences ◽  
In Situ Data ◽  
European Environmental Agency

<p>The ongoing rise in missions to observe Earth from space, especially the various Copernicus’ Sentinel systems not only increases the volume of data daily, but also contributes to the variety of data, the velocity of data availability, and its veracity. In this scenario, Sentinel 5P has already changed the way in which chemical atmospheric components are monitored daily, providing data with global coverage and a very detailed spatial resolution.</p><p>The discipline of atmospheric sciences poses an additional difficulty in efficiently accessing and analysing all available data: the variety is high as the source of atmospheric data is threefold with data coming from EO systems, models as well as in-situ measurements. The heterogeneity and multidimensionality of the so-called data triangle (EO, model, and in-situ data) make an efficient exploitation of the full potential of the available information even more challenging.</p><p>Following the successful experience of the Technology and Atmospheric Mission Platform (TAMP), TOP (http://top-platform.eu/ ) implements the concept of operational Virtual Research Environment (VRE), allowing data users to access, visualize, process, and download heterogeneous, multidimensional data.</p><p>Based on the ADAM datacube technology (https://adamplatform.eu), TOP allows exploiting the following datasets: Sentinel 5P Level 2 products (NO<sub>2</sub> and O<sub>3</sub> tropospheric columns, SO<sub>2</sub>, CO, and CH<sub>4</sub> total columns, and aerosol index); Copernicus Atmosphere Monitoring Service (CAMS) global (surface PM<sub>10</sub>, total column NO<sub>2</sub>, SO<sub>2</sub>, and O<sub>3</sub>) and regional (surface PM<sub>10</sub>, NO<sub>2</sub>, SO<sub>2</sub> and O<sub>3</sub>) analysis and forecast fields; European Environmental Agency (EEA) measurements (CO, NO<sub>2</sub>, PM<sub>10</sub>, SO<sub>2</sub>).</p><p>Users can visualize and process all available data through a web application user interface (Data Analysis and Visualization Environment – DAVE), through a Jupyter notebook interface, and using the ADAM APIs and libraries to directly access available data.</p><p>TOP is deployed on the Mundi DIAS infrastructure (https://mundiwebservices.com/). This allows accessing always most recent satellite products (reprocessed, offline, near real time), model output (analyses and forecasts – up to 5 days) and station measurements (full archive, updated daily).</p><p>TOP is the first operational platform with the data triangle implemented. By creating an atmospheric multi-source data cube, it stimulates a multi-disciplinary scientific approach and significantly facilitates scientific professional life.</p>

scholarly journals The integrated water balance and soil data set of the Rollesbroich hydrological observatory

2016 ◽  
Author(s):  
Wei Qu ◽  
Heye R. Bogena ◽  
Johan A. Huisman ◽  
Marius Schmidt ◽  
Ralf Kunkel ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Temporal Dynamics ◽  
Meteorological Data ◽  
Temporal Variations ◽  
Hydrological Models ◽  
Data Set ◽  
Western Germany ◽  
Spatio Temporal

Abstract. The Rollesbroich headwater catchment located in Western Germany is a densely instrumented hydrological observatory and part of the TERENO (Terrestrial Environmental Observatories) initiative. The measurements acquired in this observatory present a comprehensive dataset that contains key hydrological fluxes in addition to important hydrological states and properties. Meteorological data (i.e. precipitation, air temperature, air humidity, radiation components, and wind speed) are continuously recorded and actual evapotranspiration is measured using the eddy covariance technique. Runoff is measured at the catchment outlet with a gauging station. In addition, spatio-temporal variations in soil water content and temperature are measured at high resolution with a wireless sensor network (SoilNet). Soil physical properties were determined using standard laboratory procedures from samples taken at a large number of locations in the catchment. This comprehensive data set can be used to validate remote sensing retrievals and hydrological models; to improve the understanding of spatial temporal dynamics of soil water content; to optimize data assimilation and inverse techniques for hydrological models; and to develop upscaling and downscaling procedures of soil water content information. The complete data set is freely available online (http://www.tereno.net).

scholarly journals EUROSPEC: at the interface between remote sensing and ecosystem CO<sub>2</sub> flux measurements in Europe

2015 ◽  
Vol 12 (15) ◽  
pp. 13069-13121 ◽  
Author(s):  
A. Porcar-Castell ◽  
A. Mac Arthur ◽  
M. Rossini ◽  
L. Eklundh ◽  
J. Pacheco-Labrador ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
Temporal Dynamics ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Global Carbon Cycle ◽  
Spectral Measurements ◽  
Cost Action ◽  
Global Carbon

Abstract. Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem level, using the eddy covariance (EC) technique, to the landscape and global levels. In addition to traditional vegetation indices, the photochemical reflectance index (PRI) and the emission of solar-induced chlorophyll fluorescence (SIF), now measurable from space, provide a new range of opportunities to monitor the global carbon cycle using remote sensing. However, the scale mismatch between EC observations and the much coarser satellite-derived data complicates the integration of the two sources of data. The solution is to establish a network of in situ spectral measurements that can act as bridge between EC measurements and remote sensing data. In situ spectral measurements have been already conducted for many years at EC sites, but using variable instrumentation, setups, and measurement standards. In Europe in particular, in situ spectral measurements remain highly heterogeneous. The goal of EUROSPEC Cost Action ES0930 was to promote the development of common measuring protocols and new instruments towards establishing best practices and standardization of in situ spectral measurements. In this review we describe the background and main tradeoffs of in situ spectral measurements, review the main results of EUROSPEC Cost Action, and discuss the future challenges and opportunities of in situ spectral measurements for improved estimation of local and global carbon cycle.

scholarly journals How to Draw a Neighborhood? The Potential of Big Data, Regionalization, and Community Detection for Understanding the Heterogeneous Nature of Urban Neighborhoods.

2019 ◽  
Author(s):  
Ate Poorthuis
Keyword(s):  
Big Data ◽  
Social Life ◽  
Technical Problem ◽  
Data Availability ◽  
Data Sets ◽  
Temporal Scales ◽  
Data Set ◽  
Heterogeneous Nature ◽  
Spatio Temporal ◽  
Neighborhood Boundaries

How to draw neighborhood boundaries, or spatial regions in general, has been a long‐standing focus in Geography. This article examines this question from a methodological perspective, often referred to as regionalization, with an empirical study of neighborhoods in New York City. I argue that methodological advances, combined with the affordances of big data, enable a different, more nuanced approach to regionalization than has been possible in the past. Conventional data sets often dictate constraints in terms of data availability and spatio‐temporal granularity. However, big data is now available at much finer spatio‐temporal scales and covers a wider array of aspects of social life. The emergence of these data sets supports the notion that neighborhoods can be fuzzy and highly dependent on spatio‐temporal scales and socio‐economic variables. As such, these new data sets can help to bring quantitative analysis in line with social theory that has long emphasized the heterogeneous nature of neighborhoods. This article uses a data set of geotagged tweets to demonstrate how different “sets” of neighborhoods may exist at different spatio‐temporal scales and for different algorithms. Such varying neighborhood boundaries are not a technical problem in need of a solution but rather a reflection of the complexity of the underlying urban fabric.

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