BG8.3 | From Long-Term Flux Observation and Ecosystem Research Networks to Individual Applications - Benefits to Science and Society
From Long-Term Flux Observation and Ecosystem Research Networks to Individual Applications - Benefits to Science and Society
Convener: Andreas Ibrom | Co-conveners: Andrey Dara, Karolina SakowskaECSECS, George Burba, Marilyn Roland, Natalia Kowalska, Dario Papale
Orals
| Tue, 25 Apr, 14:00–18:00 (CEST)
 
Room N2
Posters on site
| Attendance Tue, 25 Apr, 10:45–12:30 (CEST)
 
Hall A
Orals |
Tue, 14:00
Tue, 10:45
This session is merged from the sessions "Long-Term Flux Observation and Ecosystem Research Networks - Benefits for Science and Society" and "Using Flux Measurement for Immediate Societal Benefits".

The first part of the session provides:

• A discussion platform to exchange the state-of-the-art and novel developments in such long-term research networks
• Helps recognize the multiple values of these networks for science and society
• And motivates interaction between users, networks organizers, and stations

Specific topics are :

1. Characteristics and challenges of long-term measurements in research networks: among others, e.g., adaptation to scientific progress, technology change, and scope changes, harmonization of new and legacy data, development, and implementation of methods and procedures, quality assessment and control, and network representativeness and site-specific attribution of change in ecosystems to drivers, i.e. intrinsic ecosystem dynamics, management, and environmental change.
2. Scientific results specific to the analysis of long-term data: among others, e.g,. temporal scales of change: climate change, trends and variability, role in synthesis studies
3. Synergy from collaboration with other scientific communities (e.g. collocation with other networks, campaign studies, scientific studies)
4. Sustainability and purposes to society – dialogue with stakeholders and users, participation

The second part focuses on using flux measurements for immediate societal benefits:

• Most of the ongoing GHG measurements are used for important discoveries achieved through process-level academic studies, and for long-term climate and ecosystem modeling. Most of the water measurements at the GHG flux sites are used for applications of computing and interpreting ecosystem-level GHG exchange.

• Such measurements use ultra-high-resolution methodology and state-of-the-art hardware vastly superior to typical monitoring-grade methods and equipment deployed outside academia for a wide range of non-academic decision-making applications, from gas leaks to drought or heat wave detections. However, despite providing exceptional ways to measure GHG emissions and ET, direct flux measurements are very rarely utilized outside academia.

This part of the session, organized through research-industry collaborations, presents new ideas and existing examples of how to better utilize direct flux measurements for immediate societal benefits.

Orals: Tue, 25 Apr | Room N2

Chairpersons: Marilyn Roland, Andreas Ibrom, Natalia Kowalska
14:00–14:05
Part 1: Long-Term Flux Observation and Ecosystem Research Networks - Benefits for Science and Society
14:05–14:25
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EGU23-9870
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solicited
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Highlight
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On-site presentation
Werner Leo Kutsch and the ICOS Research Infrastructure Team

To understand, predict and mitigate climate change, it is crucial to have long-term and standardised measurements of greenhouse gas concentrations in the atmosphere and their fluxes between atmosphere, land and oceans. The Integrated Carbon Observation System, is a distributed European Research Infrastructure which provides high-precision and highly standardised observations from more than 170 stations  from three domains: Atmosphere, Ecosystem and Ocean. ICOS covers currently 16 European countries.  All ICOS data is made available by the ICOS Carbon Portal, first in near-real time (within 24h when possible), and after further quality control as domain specific annual releases. The data flow follows the Findable, Accessible, Interoperable, Reusable (FAIR) principles.

ICOS data have shown the importance of sustainable long-term observations to understand inter-annual variations, trends and extreme events. They show climate and antropogenic feedback on the carbon cycle and ecosystem-specific responses to disturbances. ICOS data are very useful for good practise guidelines on maintaining or enhancing ecosystem carbon sinks and, thus, might also be an important tool for monitoring and verifying respective policies. Further societal impact is generated by using ICOS data for verification of fossil fuel emission reductions and guiding cities towards climate neutrality.

 

 

How to cite: Kutsch, W. L. and the ICOS Research Infrastructure Team: The Integrated Carbon Observation System (ICOS) - Standardised observations for science and societies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9870, https://doi.org/10.5194/egusphere-egu23-9870, 2023.

14:25–14:35
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EGU23-14987
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Virtual presentation
Mhairi Coyle, Ross Morrison, Rebekka Artz, Ailsa Johnson-Marshall, and James Cash and the UK GHG FluxNet

Peatlands occupy 12% of the UK territory and can store large amounts of carbon (C). However, drainage, peat extraction, and other management activities have turned these ecosystems into greenhouse gas (GHG) emitters. Currently, peatlands account for ~ 4% of the UK’s total annual GHG emissions. Eddy covariance is considered the best method to measure landscape scale GHG exchange (CO2, CH4, N2O), between the Earth’s surface and the atmosphere. Recently many flux towers have been installed on UK peatlands under different land-use and in different condition, with some undergoing restoration. In total there are currently 30 operating, with 9 in Scotland (SCO2FLUX managed by The James Hutton Institute, JHI) and 21 across England, Wales and Northern Ireland (managed by UKCEH), including the Auchencorth Moss ICOS site. As part of the projects, NERC-MOTHERSHIP and SRC-CENTREPEAT, these peatland sites are being harmonised into a network. The data is being analysed using standard protocols in order to generate a powerful dataset to examine the exchange of CO2 and CH4 over UK peatlands. Some of the topics being investigated are: the spatial and temporal variability of emissions for all peatland classifications; the main drivers and controlling mechanisms of GHG exchange, such as the effect of water table depth on gas exchange and restoration impacts (e.g. raising water levels in agricultural peatlands); the value and effectiveness of restoration techniques (e.g. the timeline of recovery in the transition from forest to bog); improving the modelling of peatlands in JULES and other land-surface models; ground-proofing data for Earth observation techniques; assessing the contribution of peatlands to achieving net zero; examining the impact of wildfire on restoration from forest to bog.

An overview of the network of sites and some highlights of the analysis to date will be presented.

 

How to cite: Coyle, M., Morrison, R., Artz, R., Johnson-Marshall, A., and Cash, J. and the UK GHG FluxNet: UK GHG Flux Network – Peatlands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14987, https://doi.org/10.5194/egusphere-egu23-14987, 2023.

14:35–14:45
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EGU23-13737
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On-site presentation
Bert Gielen, Maarten Op de Beeck, Giacomo Nicolini, Simone Sabbatini, Fana Michilsens, Carlo Trotta, Arne Iserbyt, and Dario Papale

The Integrated Carbon Observation System (ICOS) is a pan-European Research Infrastructure with the goal to monitor the greenhouse gas balance of Europe. The terrestrial component of the infrastructure consists of a network of more than 100 flux towers that continuously measure the exchange of greenhouse gases between the atmosphere and the ecosystem by using the eddy covariance technique. To interpret these fluxes a whole suite of other parameters that describe the state of the vegetation are measured. The Ecosystem Thematic Center (ETC) is coordinating the ecosystem network providing assistance with instruments and methods, testing and developing new measurement techniques and associated processing algorithms; also ensuring a high level of data standardization, uncertainty analysis and database services in coordination with the ICOS Carbon Portal. This presentation will give a brief overview of the vegetation-related parameters that are measured within the ecosystem network following standard methods and discuss some new methods that have been tested and introduced. For example a campaign with Terrestrial Laser Scanning was performed at a subset of forest stations to examine the potential to estimate above ground biomass from the gathered point clouds. More recently, below-canopy PAR measurements were introduced at the forest stations to estimate Plant Area Index (PAI) in addition to estimates from Digital Hemispherical Photography. This new method shows to be less sensitive to specific light conditions, less labor intensive and has the advantage of creating continuous time series which will be very valuable for validation of remote sensing products. First results of a cross comparison between both methods at several ICOS stations will be shown and discussed during the presentation.

How to cite: Gielen, B., Op de Beeck, M., Nicolini, G., Sabbatini, S., Michilsens, F., Trotta, C., Iserbyt, A., and Papale, D.: Latest developments in the long-term monitoring of vegetation characteristics in the ICOS ecosystem network., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13737, https://doi.org/10.5194/egusphere-egu23-13737, 2023.

14:45–14:55
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EGU23-16343
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On-site presentation
Simone Sabbatini, Giacomo Nicolini, Bert Gielen, Maarten Op de Beeck, Fana Michilsens, Arne Iserbyt, Denis Loustau, Sébastien Lafont, Benjamin Loubet, Eleonora Canfora, Diego Polidori, Alessio Ribeca, and Dario Papale

ICOS (Integrated Carbon Observation System) is a Research Infrastructure aiming at getting a deeper understanding of the European Carbon balance by means of a network of monitoring stations, based on eddy covariance (EC) technique, spread out all over the European Continent, and continuously expanding. The Ecosystem Thematic Centre (ETC) coordinates the activities of ecosystem stations to ensure high-precision datasets and standardisation. The so-called Labelling procedure is made of two steps, conceived to guide the candidate stations to get the official ICOS label: the Step 1 is focused on the sensors’ setup and is structured as a discussion between the ETC and the station teams, while the Step 2 concerns the practical build-up of the station and the data evaluation. For stations with the stricter standards (so-called Class 1 and Class 2), some quality tests on the data are included: one on the EC data quality, two on the representativeness of the measured EC fluxes and one on the representativeness of the ancillary plots.

Currently 58 of 86 candidate stations completed the labelling procedure, of which 30 Class 1 and 2. The more common fixes agreed in Step 1 are changes in sonic orientation and height or location, to better deal with fetch and canopy inhomogeneities. In Step 2, apart from increasing the signal resolution and fixing some metadata, a further correction of the location/height of the sensors led to solving the remaining problems. Overall, two thirds of the stations passed the three EC tests at the first try (all the wetlands, 74% of the forests, 33% of the crops), pointing at the efficiency of the Step 1 evaluations, while the remaining ten didn’t pass one or more of the two other EC tests, testifying that some issues are only discoverable from proper data analysis. About one third of the stations didn’t pass the ancillary representativeness test, all of them over forests: the most common solution was to add or move one or more plots.

The results support the common knowledge that more complex ecosystems - not uniform canopy geometries, fast growing vegetation - are more likely to be affected by some data quality issue. This constitutes a crucial warning to researchers and technicians in the direction of properly considering the station characteristics when planning its setup and sampling design, as well as continuously checking the data produced, to ensure the production of high-precision datasets.

How to cite: Sabbatini, S., Nicolini, G., Gielen, B., Op de Beeck, M., Michilsens, F., Iserbyt, A., Loustau, D., Lafont, S., Loubet, B., Canfora, E., Polidori, D., Ribeca, A., and Papale, D.: High-precision datasets from monitoring stations based on eddy covariance measurements: what six years of quality evaluation process of ICOS ecosystem stations have to tell, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16343, https://doi.org/10.5194/egusphere-egu23-16343, 2023.

14:55–15:05
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EGU23-6139
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ECS
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On-site presentation
Anastasia Gorlenko and Andreas Ibrom

The storage change term is calculated to account for the CO2 accumulation in the air column underneath the eddy covariance system when calculating net surface exchange. The rigorous form requires continuous measurements in space and time. Historically, a standard approximation was to measure CO2 concentrations solely at one point, the eddy covariance system measurement height. Since the storage term can contribute significantly to annual fluxes, e.g., the Net Ecosystem Exchange of CO2, other methods have been investigated, such as the vertically distributed measurements within a profile system.

This work aims at providing a physically sound storage change calculation method for long-term atmospheric stations such as ICOS. Additionally, the extrapolation to historical time series brings the possibility to correct the storage term when only the one-point measurements were available.

We used one year of eddy covariance and profile system data collected in the Sorø temperate forest in Denmark and compared different methods to calculate the storage change. We compared the top tower measurements with the results from the vertical profile system. We also considered the temporal resolution by contrasting two methods to average the samples: subtracting the end and beginning concentrations as the first method and using the times series linear regression slope as the second. We highlighted the effects on annual budgets, surface fluxes, and the interactions with other turbulence-driven variables, namely the friction velocity and the standard deviation of vertical velocity fluctuations.

These results are thus relevant for high canopies and other landscapes investigated with tall towers, where the storage change is expected to impact the annual budgets considerably.

How to cite: Gorlenko, A. and Ibrom, A.: Improving the CO2 storage measurements in a tall temperate forest, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6139, https://doi.org/10.5194/egusphere-egu23-6139, 2023.

15:05–15:15
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EGU23-13520
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ECS
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On-site presentation
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Ladislav Šigut

Eddy covariance is one of the most precise and direct methods for measurement of fluxes of matter and energy at the ecosystem scale. It is instrumental in the development of our understanding of carbon and water cycles. It allows us to examine local conditions at the given site or provide global picture of the interaction of the terrestrial ecosystems with the overlaying atmosphere through data integration in modelling frameworks. The application of the method is multifaceted, and the data processing consists of multiple steps (i.e. raw data processing, quality control, gap-filling, flux partitioning, aggregation) that are dependent and result in a processing chain. Especially for new teams applying the method and not being connected to station networks, it might be a daunting process to set up the processing chain without available tooling. Fortunately, in this respect, a lot of publicly available software is already available, especially for raw data processing and gap-filling and flux partitioning. Although quality control is a required step before gap-filling, the tools simplifying the process and making it reproducible have not received equivalent attention yet. The purpose of the R package openeddy is to fill this gap and support independent researchers with a software infrastructure for eddy covariance data post-processing that improves the reproducibility of the results. A set of tutorials is prepared within this contribution that helps to exemplify different features of openeddy software (https://github.com/lsigut). These include:

  • loading and saving of general tabular data including the support of units placed below the header
  • remapping of variable names including aggregation across multiple variables
  • automated merging of multiple EddyPro full output files
  • scatter plot for the whole year of data with a treatment of outliers
  • automated extraction of quality control information from coded columns included in EddyPro full output files
  • general purpose functions for data filtering according to specified thresholds
  • despiking function for removing outliers in the time series showing both daily and yearly variability
  • functions to define the region of interest of the ecosystem station and perform footprint filtering based on 1D footprint output from EddyPro software
  • assisted manual data exclusion
  • combining multiple quality control filters with different properties into one quality control column
  • summarization of quality control results in a tabular form or as a figure
  • visualization of the time series of selected variable and auxiliary (meteorological) variables; the plots are optimized for viewing of half-hourly data in weekly and monthly intervals but any resolution is supported
  • time series aggregation into various defined intervals including unit conversions
  • barplots for plotting of aggregated results
  • evaluation of aggregated uncertainty of flux measurements
  • computation of Griebel et al. 2020 space-time equitable budgets with uncertainty estimation
  • computation of spatio-temporal sampling coverage

This work was supported by the Ministry of Education, Youth, and Sports of the Czech Republic within the National Infrastructure for Carbon Observations—CzeCOS (No. LM2018123) and SustES—Adaptation Strategies for Sustainable Ecosystem Services and Food Security under Adverse Environmental Conditions (CZ.02.1.01/0.0/0.0/16_019/0000797).

How to cite: Šigut, L.: Post-process eddy covariance data with ease using R package openeddy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13520, https://doi.org/10.5194/egusphere-egu23-13520, 2023.

15:15–15:25
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EGU23-3301
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On-site presentation
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Holger Lange, Jaana Bäck, Georg Jocher, Natascha Kljun, Anne Klosterhalfen, Alexander Knohl, Natalia Kowalska, Adam Kristensson, Corinna Rebmann, Teresa Saura-Yera, and Alberto Vilagrosa

Utilizing forest ecosystems to mitigate climate change effects and to preserve biodiversity requires detailed insights into the feedbacks between forest type, climatic and soil conditions, and in particular forest management history and practice. Analysis of long-term observations at the site level, remote sensing proxies and understanding relevant biogeochemical and biophysical processes are key to achieving these insights. In the recently started EU H2020 project “CLimate Mitigation and Bioeconomy pathways for sustainable FORESTry” (CLIMB-FOREST), we address these issues based on intensely monitored sites with flux measurements (ICOS, Fluxnet), other ecosystem research and observation networks (eLTER, National Forest Inventories), remotely sensed observations and process understanding. This presentation outlines the activities of CLIMB-FOREST regarding (1) carbon stocks and fluxes according to stand age, species distribution, management and disturbance history; (2) biophysical effects of forest structure; (3) effects and importance of short-lived climate forcers (e.g. BVOCs) and (4) management and extreme event (drought, fire) impact on SOC and N dynamics. We also outline how the gained knowledge informs scenario runs of the Vegetation and Earth System Model RCA-GUESS in the project.

How to cite: Lange, H., Bäck, J., Jocher, G., Kljun, N., Klosterhalfen, A., Knohl, A., Kowalska, N., Kristensson, A., Rebmann, C., Saura-Yera, T., and Vilagrosa, A.: Usage of long-term forest research networks to advance understanding of ecosystem services – CLIMB-FOREST, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3301, https://doi.org/10.5194/egusphere-egu23-3301, 2023.

15:25–15:45
Coffee break
Chairpersons: George Burba, Susanne Wiesner, Karolina Sakowska
Part 2: Using Flux Measurement for Immediate Societal Benefits
16:15–16:20
16:20–16:40
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EGU23-9699
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solicited
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Highlight
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On-site presentation
Kosana Suvočarev, Margot Flynn, Jarin Tasnim Anika, Emma Ware, Olmo Guerrero Medina, Chitra Chopra, Ian McDonald, Henry Perry, Luis Francisco Daniel Bustamente, Rex Dave Pyles, and Kyaw Tha Paw U

The State of California is moving towards sustainable groundwater management and carbon neutrality goals. We aim to answer questions of importance to sustainable agricultural practices, in particular how to: (1) decrease unnecessary water losses from evapotranspiration (ET), (2) increase carbon sequestration, and (3) enhance overall water use efficiency. While implementing our cooperative extension program in Biometeorology, we deployed eddy covariance systems on flux towers placed on numerous farms to directly measure net water and carbon exchange between different agricultural crops and the atmosphere. Currently, we are simultaneously running up to twenty of these flux towers on any day of the year to address the seasonality of carbon and water cycling with innovative agricultural practices. Some of the most urgent questions posed by local communities, commodity boards, state agencies, NGOs and private corporations are mainly related to water use by different agricultural landscapes, but carbon fluxes are increasingly gaining attention as well. In order to explore these questions, our network of towers spans the entire Central Valley from northern California rice fields (that are increasingly being fallowed for water transfers), to the southern part of the state where transferred water is being used for perennial crops. Although some data and measurements are reported on the ET of California crops, the ever-changing adaptation practices in agricultural management are challenging previously established parameters (e.g. crop coefficients) used in irrigation management. For better spatial resolution, we often use semi-direct ET measurements, derived from residuals of observed surface energy budgets. In addition, alternative low-cost measurements, such as the surface renewal method, are actively being evaluated and we are refining different approaches for their independent use. 

This talk will mostly focus on ET measurements and the simultaneous quantification of water budgets of entire agricultural fields. We are designing several of our experiments to encompass a full water budget of the targeted fields. This provides a backup estimate of ET as well as an opportunity to couple soil moisture profiles, runoff, irrigation, and precipitation dynamics to eddy covariance flux tower measurements, and eventually help with the ET partitioning. This information is increasingly being sought by modelers and remote sensing scientists to calibrate their ET estimates as we work together on addressing emerging challenges in California agriculture and could potentially be used to understand the physiological response of crops to changes in plant water status and how this response could affect crop quality and productivity. Evaluation of alternative methods and models will include cross-comparisons of existing techniques with more advanced methods under development, including ACASA. We are especially excited to broaden our extension and farm education to small growers and communities that have been historically overlooked by cooperative extension and funding agencies.

How to cite: Suvočarev, K., Flynn, M., Anika, J. T., Ware, E., Guerrero Medina, O., Chopra, C., McDonald, I., Perry, H., Daniel Bustamente, L. F., Pyles, R. D., and Paw U, K. T.: Using Direct Evapotranspiration Measurements for Comminity-Engaged Education and Extension, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9699, https://doi.org/10.5194/egusphere-egu23-9699, 2023.

16:40–16:50
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EGU23-3603
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Virtual presentation
Ruwin Pandithage and Johan Jaques

Direct measurements of Evapotranspiration (ET) in combination with measured or modelled ETp, provide a direct insight into a plant- and location specific water balance and eventual subsequent drought stress that crop has been experiencing. Using further input from measured ETp and/or ETo, completed with the output of numerical weather prediction models for ETp and precipitation quantities (either deterministic- or ensemble prediction system values), a reference crop irrigation forecasts can be generated for the next days. Applying additionally crop specific water needs to the input variables, a crop- and phenological stage- specific forecast for irrigation can be issued for that particular location.

How to cite: Pandithage, R. and Jaques, J.: Direct Measurements of Evapotranspiration can help steer irrigation forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3603, https://doi.org/10.5194/egusphere-egu23-3603, 2023.

16:50–17:00
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EGU23-2427
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Highlight
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On-site presentation
Gerardo Fratini, Bill Miller, Katie Gerot, Johnathan McCoy, Ryan Walbridge, Alex Frodyma, Isaac Fuhrman, Andrew Parr, Derek Trutna, Liukang Xu, and George Burba

Growing food demand and declining water availability are among key global concerns in the modern society. These two opposing trends manifest uniquely at different scales, from the farm field to the global food distribution, and require innovative composite solutions in terms of policy, education, science and technology.

To solve the complex interactions of financial, social, and scientific issues, solutions to water use for crops require resource management based upon socioeconomic and scientific understanding. These important goals are achieved through a number of crucial regulatory, social and technical means. The latter include water inventories, water loss and water use measurements, as well as development of the techniques for water use reduction, optimization and prediction, and require direct measurements of water transport in real time, with high temporal resolution.

Cutting-edge technologies to assess water use at leaf to ecosystem scales have been actively developed in the academia for the past 40 years. One example of such technologies is a next-generation fully-automated evapotranspiration station network, to effectively and efficiently handle the “big data” on water use coming from a grid of measurement stations providing high spatial and temporal coverage of water usage on multiple scales, ranging from a single watershed to a region, state, or a continent.

In this presentation, we will focus on the main features and specifications of the very latest technology and the explanation of the latest scientific assessment methods available for direct, field-scale, unattended, and automated measurements of evapotranspiration. 

How to cite: Fratini, G., Miller, B., Gerot, K., McCoy, J., Walbridge, R., Frodyma, A., Fuhrman, I., Parr, A., Trutna, D., Xu, L., and Burba, G.: Direct Evapotranspiration Measurements for the Immediate Societal benefits, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2427, https://doi.org/10.5194/egusphere-egu23-2427, 2023.

17:00–17:10
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EGU23-9419
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Highlight
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On-site presentation
Bradley Matthews, Enrichetta Fasano, Kathiravan Meeran, Andreas Luther, Simon Leitner, Hans Sanden, Francesco Vuolo, Helmut Schume, Andrea Watzinger, and Jia Chen

The substantial urban contribution to global anthropogenic greenhouse gas (GHG) budgets underlines the importance of improved GHG emissions monitoring in cities. Reducing urban emissions of carbon dioxide (CO2) and methane (CH4) will be critical to mitigating climate change; yet, GHG budgets of individual cities as quantified by emission inventories can be very uncertain. This is due to a lack of appropriate activity data and emission factors for compiling city-scale inventories or uncertainties in spatial downscaling of regional/national emissions.

The Vienna Urban Carbon Laboratory is currently investigating how monitoring of CO2 and CH4 emissions in Austria’s capital city can be supported by a range of atmospheric measurement methods, including a tall-tower application of eddy covariance flux measurements. Cities can represent non-ideal conditions for eddy covariance due to the aerodynamically rough surface conditions and spatial heterogeneity in GHG sources (and sinks). Nonetheless, if biases/errors caused by these factors are acceptable, the method provides a potentially significant advantage in that net urban emissions can be directly inferred from the measured vertical turbulent fluxes. Since December 2017, CO2 fluxes at 144 m above the surface have been measured using an eddy covariance system deployed at the A1 Arsenal radio tower in Vienna’s city centre. The original rationale for the tall tower approach was to partially mitigate the aforementioned challenges of urban eddy covariance (e.g. to get above the deep urban roughness layer and measure in the surface layer) and to increase the area of the city sampled by the flux footprint. In May 2022, the observations at the tower were expanded to measure CH4 fluxes, as well as atmospheric mixing ratios of CO2 and its stable carbon isotope composition. Furthermore, between May and July 2022, a parallel measurement campaign with four ground-based, sun-viewing FTIR spectrometers (EM27/SUN) was conducted to measure horizontal gradients in total column CO2 and CH4 concentrations.

This conference contribution will present an analysis of the tall-tower eddy covariance measurements of CO2 and CH4 fluxes and discuss potential applications within the scope of operational emissions monitoring. In addition to discussing the encouraging agreement between eddy covariance measurements and local CO2 emission inventories for the years 2018 to 2020, the initial eddy flux-inventory comparison for CH4 will be presented. Moreover, planned analyses (and initial results, where available) on several relevant fronts will be briefly discussed:  comparison of the eddy fluxes with inverse modelled CO2 and CH4 fluxes using differential column concentration measurements; comparison of partitioned CO2 fluxes with source-sector emission estimates derived from local inventories and measurements of stable carbon isotope composition of atmopsheric CO2. Finally, trends in CO2 fluxes between 2018 and 2022 will be presented to highlight the potential early indicator function and immediate societal benefits  that urban eddy covariance can provide.

How to cite: Matthews, B., Fasano, E., Meeran, K., Luther, A., Leitner, S., Sanden, H., Vuolo, F., Schume, H., Watzinger, A., and Chen, J.: Using tall tower flux measurements for GHG emissions monitoring in cities: Emerging results and perspectives from the Vienna Urban Carbon Laboratory, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9419, https://doi.org/10.5194/egusphere-egu23-9419, 2023.

17:10–17:20
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EGU23-14771
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Highlight
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On-site presentation
Andrea Pitacco, Luca Tezza, Isabella Ghiglieno, and Nadia Vendrame

Vegetation plays an important role in the global carbon budget, absorbing from the atmosphere about 29% of CO2 anthropogenic emissions. Today, forest ecosystems are recognized as carbon sink, while agricultural lands are not taken into account. This is due to the rapid turnover of the carbon assimilated by crops. Indeed, their biomass is removed for food production and the residues and soil organic matter are rapidly degraded due to deep and frequent soil cultivation. However, woody crops like vineyards present biological, structural, and management peculiarities, such as perennial structure, abundant pruning debris, limited soil disturbance, and vegetation cover of the alleys, which could potentially lead to the sequestration of a significant amount of CO2. Recently, several initiatives started to exploit the sequestration potential of agriculture, to reach the targets of Paris agreement (“4 per mille”, Carbon Farming…), but means, rules, and realistic assessment of sequestration potential are still lacking, exposing these proposals to substantial criticism. Eddy covariance technique, as implemented in coordinate networks, can be a powerful tool to proof this important environmental role of agriculture.

In order to asses the carbon balance of woody crops on a multi-annual scale, in 2015 we deployed an eddy covariance station in a vineyard located in the Franciacorta area (Northern Italy). The analysis of five years of measurements (2017-2021) shows a consistent pattern over this period with the vineyard acting as carbon sink on annual basis. The net CO2 uptake varied among the years, due to different environmental conditions, but on average it was around 200 gC m-2 y-1. This amount, considerable for an agricultural ecosystem, can represents an important base to quantify the role of viticulture in the perspective of carbon farming initiatives. Even if it can be objected that this sink may be only temporary and the built-up can be substantially disrupted at the end of the vineyard life cycle, these results show that there is a concrete possibility of storing carbon in agricultural soils. Thus, vineyards seem to be good candidates for carbon farming. Proper practices can be defined to preserve this storage at best, greatly contributing to the global carbon budget and boost the role of agriculture in climate change mitigation initiatives.

How to cite: Pitacco, A., Tezza, L., Ghiglieno, I., and Vendrame, N.: Vineyard carbon balance: assessing the perspective for carbon farming through long-term eddy covariance measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14771, https://doi.org/10.5194/egusphere-egu23-14771, 2023.

17:20–17:30
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EGU23-2409
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Virtual presentation
Sparkle Malone and Ruth Varner and the Continental Methane Observatory

Understanding the biogenic sources and sinks of methane (CH4) is critical to both predicting and mitigating future climate change. Methane is 28-34 times more effective at trapping heat in the atmosphere compared to an equivalent mass of carbon dioxide over a 100-year time frame and accounts for ∼ 42 % of warming since the pre-industrial period. Biogenic sources are likely responsible for driving dramatic increases in atmospheric CH4 over the past decade, yet these are the least constrained and most uncertain fluxes in the global methane budget. A lack of long-term measurements across a variety of ecosystems has resulted in many unanswered questions about both the processes driving methane fluxes and how to scale these fluxes across space and over time. There is an urgent need to address these questions. With an atmospheric residence time of ~9 years, mitigating CH4 emissions has the potential to be an important global warming mitigation strategy. Here, we show how the current infrastructure to measure CH4 limits our ability to constrain the natural biogenic CH4 flux. Using dissimilarity, multidimensional scaling, and cluster analysis, the United States of America was divided into 10 clusters distributed across temperature and precipitation gradients. Through our analysis using climate, land cover, and location variables, we identified priority areas for research infrastructure to provide a more complete understanding of the CH4 flux potential of ecosystem types.

How to cite: Malone, S. and Varner, R. and the Continental Methane Observatory: Gaps in network infrastructure limit our understanding of biogenic methane emissions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2409, https://doi.org/10.5194/egusphere-egu23-2409, 2023.

17:30–17:40
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EGU23-3653
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Highlight
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On-site presentation
Oleg Demidov

The Agriculture, Forestry, and Other Land Use (AFOLU) sector accounts for almost a quarter of global emissions. With proper management, the land-use sector can serve as a powerful carbon sink through sustainable practices along agriculture and forestry supply chains and through nature-based solutions (NBS) for carbon removal. However, accounting for the exchange of CO2 due to biological processes (soils, crops, trees, livestock) in the land is difficult, which leads to uncertainty around the exact impact of carbon removal practices and projects.

Current methods for measuring CO2 emissions and sequestration in the land have gaps. Direct measurements (e.g. soil sampling) are too costly and labor intensive. Industry calculators provide averaged data, which masks local variation and individual effort. Remote-sensing solutions focus on detecting the change of select practices but still use standardized formulas to estimate the carbon impact.

These factors limit the ability of companies to track and incentivize the sustainable practices of their suppliers, mislead climate action, and slow down the transition to Net Zero.

In this talk, Dr. Oleg Demidov will discuss the CarbonSpace technology, which provides unique, remotely generated carbon footprint data and insights for global supply chains and NBS projects. The technology core uses machine learning algorithms trained on multispectral satellite imagery and GHG flux data from globally distributed eddy covariance ground stations. This approach requires no on-site operations and provides net ecosystem exchange (NEE) estimates at a resolution of 30 meters. NEE is a parameter that represents carbon stock change in several carbon pools: aboveground biomass, belowground biomass, soils, and dead organic matter. NEE can be positive or negative, meaning total emissions or sequestration. 

Dr. Demidov will cover several case studies demonstrating the proven value of CarbonSpace data. In North Dakota, CarbonSpace showed the impact of varied management practices on carbon sequestration in croplands, and, in Ireland, CarbonSpace provided a new set of data that improved the accuracy of a dairy product LCA. Additionally, Dr. Demidov will discuss progress and challenges with certification and market acceptance for the CarbonSpace technology. 

Join this discussion to learn how CarbonSpace’s disruptive approach enables corporations and NBS project developers to evaluate their carbon removal efforts and guide further climate strategy based on quality, accurate data.

How to cite: Demidov, O.: AI combined with Flux Data and Remote sensing generates insightful carbon footprint data for the land-use sector, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3653, https://doi.org/10.5194/egusphere-egu23-3653, 2023.

17:40–17:50
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EGU23-10860
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Highlight
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Virtual presentation
Stefan Metzger, George Burba, Ankur Desai, Kyle Hemes, Deepak Jaiswal, John Stephen Kayode, Isaya Kisekka, Jitendra Kumar, Bhaskar Mitra, Andrew Mwape, Sreenath Paleri, Rajasheker Reddy Pullanagari, Benjamin Runkle, and Susanne Schödel

A combination of technological, nature-based and demand-side solutions are envisioned to avert the most drastic consequences of climate change, connected via a greenhouse gas (GHG) economy and government policies (e.g., net-zero incentives, compensations etc.). Measurement, Reporting and Verification (MRV) of GHGs reduced or removed from the atmosphere are central to ensuring that revenue streams develop in proportion to true climate benefits with equitable rewards for small and large originators.

However, current MRV limitations (e.g., cost, robustness, interoperability, scalability, multi-year latency, etc.) curtail our ability to approach climate solutions in a well-informed and consistent manner. This challenge can be addressed by creating an MRV benchmark that is directly and frequently measured, uniformly derived, universally applicable to the technological and nature-based solutions, and traceable in near-real time and space. In order to narrow the knowledge-action gap the social and natural sciences both recognize this need for continuous information on local GHG emission and sequestration akin to weather intelligence.

Technology transfer of the latest, most direct GHG quantification methods from academic climate science to the climate solution marketplace provides a promising avenue for creating such a benchmark: Next-generation information reconstruction (https://tinyurl.com/flux-tower-mapping) applied to existing local-to-global networks of direct GHG flux measurements can achieve unmatched statistical power, interpretability and process insight. This integration will generate an orders-of-magnitude improved stream of directly-measured emission and sequestration rates for robustly anchoring project-scale GHG mitigation and wall-to-wall remote sensing and models. The resulting benchmark directly represents a financial commodity: the physical emission and sequestration of GHGs. Thus, they can be used to manage GHGs in day-to-day practices and to assess the value of financial derivatives such as GHG certificates based on discipline-specific protocols, while accounting for reliability, storage duration and other factors.

This approach will result in decameter-resolution maps of GHG emission and sequestration per unit of time, locked in a secure vessel such as a blockchain to prevent tampering, deleting, or modifying. Access via mobile Apps and APIs will enable public awareness and confidence, climate solution research, GHG certificate intercomparisons, development of regulatory and financial products, tools, climate-smart technologies, practices and commercial services, and national as well as local policies. Paths to monetization include licensing to credit originators, offset buyers and marketplaces, through connecting pixel-scale GHG exchange to regulatory practice for a range of GHG certificate protocols, industries, stakeholders and management practices. With this conceptual outline, we invite all types of stakeholders to join Carbon Dew: the Community of Practice that aims to anchor equitable climate solutions worldwide in direct measurements of GHG sequestration and emission (https://tinyurl.com/join-carbon-dew).

How to cite: Metzger, S., Burba, G., Desai, A., Hemes, K., Jaiswal, D., Kayode, J. S., Kisekka, I., Kumar, J., Mitra, B., Mwape, A., Paleri, S., Pullanagari, R. R., Runkle, B., and Schödel, S.: Carbon Dew: Direct Greenhouse Gas Exchange Measurements Anchor Equitable Climate Solutions Worldwide, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10860, https://doi.org/10.5194/egusphere-egu23-10860, 2023.

17:50–18:00

Posters on site: Tue, 25 Apr, 10:45–12:30 | Hall A

Chairpersons: Marilyn Roland, George Burba
A.321
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EGU23-13406
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ECS
Wafa Chebbi, Mathieu Jonard, and Caroline Vincke

Beech (Fagus sylvatica L.), is one of the most socio-economically valuable and widely distributed broadleaved trees in Europe. European beech favorable edaphic and climatic conditions are sufficient moisture in summer and mild temperatures in winter. This highly competitive species is also known to be drought-sensitive and thus may become more vulnerable to expected increasing number of heat waves and drought spells. A better understanding of beech response to soil drought is therefore crucial for forestry planning and forest management in a future warmer world. In this study, we investigate the water balance and radial growth dynamics of a beech stand in an ICOS site in Belgium (BE-Vielsalm), with a special focus on soil drought impacts, based on about three decades of observations (1996-2020). The continuous decreasing trend of beech radial growth (dendrochronological time series) coupled with recent crown defoliation raised concern about the vitality of this stand. On the basis of this site-specific data set, the calibration and the validation of the model HETEROFOR were performed in order to i) simulate the water balance and fluxes at the stand level; ii) track the occurrence and intensity of soil-induced transpiration deficit during the whole study period; iii) characterize the tree water uptake patterns according to soil depth for contrasted years (dry, intermediate and wet) and iv) evaluate the current and lag effects of spring and summer transpiration deficit on the observed annual radial growth of beech trees obtained from dendrochronological analysis. A good agreement between predicted and observed evapotranspiration and extractable water was obtained and showed the robustness of the model. The predicted transpiration deficit revealed an increasing trend, especially after 2010. We observed a negative effect of the spring transpiration deficit on tree radial growth during the current year as well as a carryover effect (i.e., a negative effect of the summer transpiration deficit of the previous year). This study will enrich the state of knowledge about the ongoing debate on the vulnerability of beech trees to drought in Europe.

Keywords: Fagus sylvatica, radial growth, soil water balance, forest evapotranspiration, drought, process-based modeling, eddy covariance.

How to cite: Chebbi, W., Jonard, M., and Vincke, C.: Increasing soil water deficit negatively impacts European beech radial growth: a case study combining long-term monitoring (1996-2020) and modeling approaches., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13406, https://doi.org/10.5194/egusphere-egu23-13406, 2023.

A.322
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EGU23-13689
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ECS
Anne Klosterhalfen, Dietmar Fellert, Franziska Koebsch, Heinrich Kreilein, Christian Markwitz, Martina Mund, Marek Peksa, Frank Tiedemann, Edgar Tunsch, and Alexander Knohl

In this study, we present the 23-years long dataset (2000-2022) provided by the flux tower site (DE-Hai) in the National Park Hainich, Thuringia, in Central Germany. Next to eddy-covariance flux measurements comprehensive datasets of meteorological and environmental conditions (e.g., soil respiration, leaf area index) were obtained over the last two decades. These long-term datasets represent the land-atmosphere interactions and their feedback with average and several extreme meteorological conditions, and thus provide the opportunity to investigate the resilience of this old-growth deciduous forest against extreme events.

The diel, daily and annual cycles of net ecosystem CO2 exchange, latent and sensible heat fluxes are presented. Further ecosystem functions, such as Bowen ratio and water use efficiency, are analyzed. Footprint analysis revealed that the fluxes originated for > 95% from the mixed deciduous forest and that the main source region is located within 0.5-1 km around the tower. However, the source area differs slightly between day- and nighttime. The deciduous forest was a large and persistent net carbon sink, with an annual net ecosystem exchange between -339 and -670 g C m-2. Environmental drivers of the ecosystem flux exchange were identified based on statistical analysis. A large uncertainty was introduced to flux estimates due to the applied post-processing methods (e.g., gap-filling), and strong impacts of recent drought events were observed for the flux exchange during and after the events. Moreover, the interrelationship between tree growth estimates based on circumferences of individual trees and eddy-covariance fluxes on ecosystem-level were investigated. Discrepancies between the carbon sink estimates on tree- and ecosystem-level are discussed.

How to cite: Klosterhalfen, A., Fellert, D., Koebsch, F., Kreilein, H., Markwitz, C., Mund, M., Peksa, M., Tiedemann, F., Tunsch, E., and Knohl, A.: Analysis of a 23-years Long Eddy-covariance Fluxes Dataset from a Mixed Deciduous Forest in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13689, https://doi.org/10.5194/egusphere-egu23-13689, 2023.

A.323
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EGU23-11187
Gilberto Pastorello, Carlo Trotta, Alessio Ribeca, Keith Beattie, Sy-Toan Ngo, Housen Chu, You-Wei Cheah, Danielle Christianson, Giacomo Nicolini, Sigrid Dengel, Diego Polidori, Peter Isaac, Matthew Archer, Dominic Orchard, Deb Agarwal, Sebastien Biraud, Margaret Torn, and Dario Papale

Standardized processing of eddy covariance data is important for studies combining data from multiple sites, for validating remote sensing measurements as well as runs of ecosystem and climate models, and for applications relying on these flux data to create derived products like upscaled fluxes, among other examples. However, maintaining consistency within the software used for this processing while allowing for evolution of this code across research networks presents novel challenges in software development. The introduction of the ONEFlux (Open Network-Enabled Flux) eddy covariance data processing pipeline, originally developed within a collaboration of the AmeriFlux Management Project, the European Fluxes Database, and the ICOS Ecosystem Thematic Centre, supported the creation of consistently processed global eddy covariance data products. In particular, ONEFlux codes were used to generate the FLUXNET2015 dataset, which is widely adopted by thousands of eddy covariance data users in their work in research, ranging from soil microbiology to large scale drought effects, and also education, from basic plant biology all the way to global climate change. We are now more thoroughly instrumenting the code, and the code development process, to better address these challenges, efforts which we will describe in this presentation. In particular, we are seeking to improve software development practices to allow for more streamlined collaboration on expanding and contributing to the codebase. For instance, we are adopting planned release cycles for code updates, designing more detailed ways to incorporate and evaluate new modules, introducing data-centric testing and continuous integration, improving code performance, and adopting several other software engineering best practices more widely in the development workflows. The main goal of these changes is to lower the barriers for running ONEFlux by regional networks processing their data, while at the same time better supporting contributions from the community into the codebase. This will be critical to continue the current use of ONEFlux to generate updated versions of flux datasets by regional networks, the components of new global products.

How to cite: Pastorello, G., Trotta, C., Ribeca, A., Beattie, K., Ngo, S.-T., Chu, H., Cheah, Y.-W., Christianson, D., Nicolini, G., Dengel, S., Polidori, D., Isaac, P., Archer, M., Orchard, D., Agarwal, D., Biraud, S., Torn, M., and Papale, D.: Fostering collaboration through improved software development practices for the ONEFlux eddy covariance data processing pipeline, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11187, https://doi.org/10.5194/egusphere-egu23-11187, 2023.

A.325
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EGU23-16255
Giacomo Nicolini, Simone Sabbatini, Eleonora Canfora, Diego Polidori, Alessio Ribeca, Carlo Trotta, Domenico Vitale, Bert Gielen, Arne Iserbyt, Benjamin Loubet, Fana Michilsens, Maarten Op de Beeck, and Dario Papale

The eddy covariance is a micrometeorological technique which allows for the estimation of the net fluxes of gases and energy between the atmosphere and an ecosystem. To estimate the net balance, the required input data are high frequency measurements (e.g. 10 or 20 Hz) of wind speed and gas concentration or amount of energy, plus lower frequency measurements (e.g. 1s to 30min ) of some meteorological variables and gas concentration vertical gradients below the measuring point. From these measurements, through a set of processing algorithms and corrections, continuous time series of fluxes are obtained which can be used to, e.g.,  estimate the net ecosystem exchange, as input/validation for modelling purposes, or for eco-physiological analyses. Although the fundamental processing steps and corrections are well established, there is still a discrete margin of subjectivity in the choice of specific operations and corrections which leads to different results even starting from the same set of measured data. The ICOS Ecosystem infrastructure consists of a network of eddy covariance stations equipped with high-level standardized instrumentation, whose data are processed centrally by means of a fully standardized and documented processing pipeline. This allows to obtain robust and consistent datasets, along with sets of metadata (e.g. instruments characteristics and location) and ancillary variables (e.g. meteorological and biometric) that help their interpretation and ensure their traceability and reproducibility. The description of the full processing pipeline is the aim of this contribution. All the data and metadata produced by the ICOS Ecosystem Thematic Centre (ETC) are freely available through the ICOS Carbon Portal as well as the processing codes are available in the ICOS ETC GitHub repository.

How to cite: Nicolini, G., Sabbatini, S., Canfora, E., Polidori, D., Ribeca, A., Trotta, C., Vitale, D., Gielen, B., Iserbyt, A., Loubet, B., Michilsens, F., Op de Beeck, M., and Papale, D.: From raw data to standardized, fully corrected, quality ensured eddy covariance flux data: the ICOS Ecosystem processing pipeline, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16255, https://doi.org/10.5194/egusphere-egu23-16255, 2023.

A.326
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EGU23-16593
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ECS
Sundas Shaukat, Simone Sabbatini, Giacomo Nicolini, and Dario Papale and the ICOS-PIs

For monitoring GHGs and energy fluxes between ecosystems and the atmosphere, the Eddy covariance (EC) technique is a widely accepted approach. Its two dedicated instruments sonic anemometer and gas analyzers are available in the market with various designs and features. These many options, in addition to the diverse data processing methods that are routinely used, are potential sources of uncertainty that can impede site-to-site comparisons. The performances and specifications of the single sensor do not necessarily reflect uncertainty in the final measurements. As there are not any analogous measurements that could be used for validation, the Research Infrastructures (e.g., ICOS, NEON or Ameriflux) standardized the technique in its different steps, including sensor’s selection, instrumental setup, and data processing. However, no perfect sensor exists that can handle all possible environmental variables without probable concerns.

This synthesis study is divided in to two sections. Primarily, effect of standardization is analysed using data from 15 sites covering different climate and ecosystems where two EC system run in parallel, one of them is standardized. The data are then processed both by the single station teams and centrally to evaluate differences due to setups and processing. Second part is reprocessing of long-term data from 9 sites, with the objective of understanding the effect of change in setups on a long timeseries, as well as to verify whether a standardized processing can aid harmonization of historical dataset gathered with old instruments with new dataset. Results pointed out that differences between the two systems and processing are site dependent and both setup and processing play role.

Effect of standardization in the EC setup has been quantified on average between 10 and 16 % in carbon flux, 11 and 19 % in LE flux and 5 and 7 % in H flux. Differences due to processing methods are in general smaller for the standardized setup (9 % in FC, 14 % in LE and 10 % in H) respect to the non-standardized setup (17 % for FC, 16 % for LE and 12 % for H). Reprocessing of long-term data by using ICOS standard processing scheme helped to reduce the effect of instrumental setup shift from nonstandard to ICOS more prominently in LE and H fluxes.

It is difficult to identify a single component that unites all the sites variations and differences because of the intricacy of the EC technique and its numerous steps (setup, calculation, and filtering). Although standardization does not guarantee the accuracy of the absolute numbers, it does help to decrease difference when modest changes (in time and among sites) must be recognized. Proper storage and organization of raw data and meta data is key for accurate data interpretation and future reanalysis.

 

How to cite: Shaukat, S., Sabbatini, S., Nicolini, G., and Papale, D. and the ICOS-PIs: Standardization of Eddy Covariance Measurements: Role of Setup, Calculation and Filtering in Parallel and Long-term datasets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16593, https://doi.org/10.5194/egusphere-egu23-16593, 2023.

A.327
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EGU23-12598
Domenico Vitale and Dario Papale

Variables sampled by eddy-covariance (EC) systems are not temporally aligned because, to avoid possible wind flow distortions, sensors are not perfectly co-located. If not properly treated, such a temporal mis-alignment constitutes a source of systematic error in the derived EC fluxes. 

In most of EC data processing pipelines, the time lag is detected by assessing the cross-covariance function between the vertical wind speed and the atmospheric concentration of the scalar of interest. In particular, the optimal time lag is detected in correspondence of the lag that maximizes (in absolute terms) the cross-covariance function between raw, high-frequency, time series. Such a procedure is effective when the cross-covariance function exhibits a distinct and pronounced peak, a condition occurring under second-order stationary conditions and when the signal-to-noise ratio is moderate/high. In other circumstances, the cross-covariance function can be characterized by multiple local minima or maxima of similar magnitude, making the detection of the optimal time lag problematic. This often occurs for trace gases or during dormant/senescence periods when  fluxes are of small magnitude.

This work introduces a new procedure being computationally efficient and completely data-driven where time lag is detected by assessing the statistical significance of the cross-correlation estimates between raw EC data subject to a preliminary (linear) transformation known as prewhitening. Prewhitening avoids the risk of nonsense (or spurious) correlations, making it more realistic and informative the assessment of the cross-correlation function, and then the detection of the optimal time lag.

The procedure consists of the following steps: i) removal of the serial correlation from at least one of the two series involved in the cross-correlation function using an autoregressive integrated moving average  (ARIMA) model; ii) filtering of the other time series using an ARIMA model with the same parameters estimated in the previous step; iii) evaluation of the cross-correlation function between the transformed variables (i.e. between the model residuals). 

The effectiveness of the procedure is evaluated for the detection of time lag affecting CO2, H2O, N2O and CH4 variables. Results indicate that applying the proposed approach and using sonic temperature instead of vertical wind speed greatly facilitates the detection of the optimal time lag, even in the case of low magnitude fluxes.

How to cite: Vitale, D. and Papale, D.: Time lag detection between raw eddy-covariance data by prewhitening and cross-correlation analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12598, https://doi.org/10.5194/egusphere-egu23-12598, 2023.

A.328
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EGU23-15755
Carlo Trotta, Nicolas Vuichard, Gilberto Pastorello, Ilenia Manco, Marco Mancini, Paola Mercogliano, and Dario Papale

Meteorological is an essential input for many terrestrial ecosystem models to simulate energy, water and carbon exchanges between the surface and the atmosphere. A significant improvement in the comprehension of the processes represented in the models is linked to the installation of the eddy covariance (EC) towers.In particular the EC carbon and energy data are utilized by the modelers to develop and parameterize the models and evaluate their  performances. 

Continuous, gap-free main in-situ meteorological time series are crucial for the EC fluxes processing (mainly gap-filling and partitioning) but are also used as input for simulations of many different models. Different approaches exist for filling the gaps present in the meteorological data collected at the EC sites. In the standard FLUXNET processing (ONEFlux) a downscaled approach is used (Vuichard and Papale 2015), which was originally based on the ERA-Interim dataset, and now uses ERA5.

Here we present the results of a modified method where the downscaling has been also compared across three different reanalysis datasets (ERA5 hourly data on single levels and ERA5-Land from Copernicus and a CMCC product at 2.2 km produced for the whole Italian territory). Our results show that the reanalysis product used has an impact on the performance of the overall gap-filling of data and we suggest the implementation of a new strategy in the standardized processing chains.

How to cite: Trotta, C., Vuichard, N., Pastorello, G., Manco, I., Mancini, M., Mercogliano, P., and Papale, D.: Use of global climate and weather reanalysis to fill meteorological time series gaps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15755, https://doi.org/10.5194/egusphere-egu23-15755, 2023.

A.329
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EGU23-927
George Burba

Continental-scale research infrastructures and flux networks (e.g., AmeriFlux, AsiaFlux, ChinaFlux, ICOS, NEON, OzFlux), as well as numerous smaller GHG flux networks, and individual sites, measure CO2, CH4, and other GHG exchange, as well as water vapor fluxes (evapotranspiration, ET) between ecosystem and atmosphere.

After four decades of academic use, the flux stations covered over 2100 stationary measurement locations, and numerous campaigns’ locations. Most measurements were used for process-level ecological and hydrological studies and long-term climate and ecosystem modeling.

Such measurements use ultra-high-resolution methodology and state-of-the-art hardware vastly superior to typical monitoring-grade methods and equipment deployed outside academia for a wide range of non-academic decision-making applications. However, despite providing exceptional ways to measure GHG emissions and ET, these are very rarely utilized outside academia.

The key reasons for such lack of utilization are:

  • The perceived complexity of the method - can be resolved via simple-language explanations and a detailed guide described in the presentation
  • The lack of data in the specific ecosystem or area and the associated expenses required to establish a new station - can be significantly reduced and often resolved by a peer-to-peer cross-sharing concept outlined in the presentation
  • The absence of a robust overall approach to using flux measurements for immediate societal benefits - can be resolved by adopting an approach currently used by automated weather stations (AWS) feeding and tuning remotes sensing products and resulting in weather modeling and forecasting (see Figure below)

The ultimate goal of this presentation is to ignite and provide a base for a discussion regarding the latest needs, ideas, and examples of the use of flux measurements for practical ‘everyday’ decision-making applications benefiting society. The new Community of Practice “Carbon Dew” is also introduced to address some of these pressing needs.

How to cite: Burba, G.: Direct Real-Time GHG and ET Measurements for Immediate Societal Benefits: Getting to an AWS-Like Approach with Simple Explanations and CarbonDew, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-927, https://doi.org/10.5194/egusphere-egu23-927, 2023.

A.330
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EGU23-955
Frank Griessbaum, Gerardo Fratini, Katie Gerot, Johnathan McCoy, Bill Miller, Ryan Walbridge, Alex Frodyma, Isaac Fuhrman, Andrew Parr, Derek Trutna, and George Burba

Over the last 30 years, dozens of networks of eddy covariance flux stations have been introduced in different countries and continents around the world. Many of them, such as the ICOS network in Europe or the AmeriFlux network in the US, have a specific focus on greenhouse gas measurement focus, mainly CO2, but in all cases, the latent heat flux is concurrently measured as a required variable, thus actual evapotranspiration can be derived.

This important hydrologic parameter is needed both in rainfed and irrigated areas to monitor drought conditions, and soil water balance as well as to determine irrigation water amounts to be applied to crops and the timing of optimal fertilizer applications. Quasi-real-time measurements of actual evapotranspiration can be used by water managers, crop consultants, and producers in both rainfed and irrigated agriculture, reducing water and energy use and associated expenses, ultimately helping increase the efficiency of global food production while reducing its costs. So, the importance of providing freely available, scientific-grade data is imperative.

The cutting-edge technologies to assess water use on leaf-level to ecosystem-level scales has been actively developed in academia for past 40 years. One example of such technologies is a next-generation fully-automated evapotranspiration station network, to effectively and efficiently handle the “big data” on water use coming from a grid of measurement stations providing high spatial and temporal coverage of water usage on multiple scales, ranging from a single watershed to a region, state, or a continent.

This presentation aims to provide multiple examples, and validations against existing standards, of the latest technology, hardware, and scientific method behind the eddy covariance approach to direct, field-scale, unattended, and automated measurements of evapotranspiration.

How to cite: Griessbaum, F., Fratini, G., Gerot, K., McCoy, J., Miller, B., Walbridge, R., Frodyma, A., Fuhrman, I., Parr, A., Trutna, D., and Burba, G.: Prospects of Direct Evapotranspiration Measurements for the Immediate Societal benefits, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-955, https://doi.org/10.5194/egusphere-egu23-955, 2023.

A.331
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EGU23-12022
Tommaso Julitta, Andreas Burkart, Roberto Colombo, Edoardo Cremonese, Alexander Damm, Olivia Dondina, Tarek El-Madany, Frank Griessbaum, Bill Miller, George Burba, Fanny Kittler, Mirco Migliavacca, Uwe Rascher, Marilyn Roland, Micol Rossini, Christian Brümmer, Dirk Schuettemeyer, Jan Segers, Georg Wohlfahrt, and Dario Papale

Field spectroscopy is a powerful tool for understanding plant carbon uptake and for providing a link between local flux measurements and global satellite remote sensing. In fact, optical remote sensing techniques can capture valuable information on both phenology and physiology. Even if the concept is of interest for the scientific community, the integration of field spectroscopy techniques in flux networks is still challenging and largely unresolved. Further, mainly due to the lack of available instruments, obtained relationships between remote sensing measurements and gross primary productivity (GPP) are often site specific and so far poorly exploited.

JB devices (FloX and RoX) are field spectrometer systems acquiring in situ radiometric measurements with standardized routines. They have been installed over the last five years across several ecosystems (e.g. croplands, forests, grasslands), often at eddy covariance stations. Recently, an effort was made to standardize the data processing and to align it to flux networks. The development of an open source processing chain was made and the definition of all the metadata needed to correctly interpret the measurements, including devices specification and setup, is ongoing.

With this contribution, we aim to advance understanding on the relationship between optical proximal sensing information and GPP using a selection of eight diverse sites equipped with JB devices and belonging to flux networks (ICOS or FLUXNET). Selected sites represent different vegetation types, including broadleaf forest, needle leaf forests, croplands, and grasslands. The time series length varies from one season to 4 years, depending on the time the instrument was installed. From the hyperspectral data, a subset of vegetation indices (e.g. indices related to biomass, chlorophyll content, carotenoids, and sun induced chlorophyll fluorescence (SIF, NIRv), and was computed where available (i.e. only on six of the equipped FloX sites). The data output was qualitatively checked and aggregated to the same temporal resolution as for the flux data (30 mins). Several models were tested to investigate this relationship, exploited both on half-hourly interval and on daily aggregation. Overall, good results were found. In general, SIF and NIRv were found to be the best predictor for GPP at half-hourly scales (r2 =0.75 over croplands and broadleaf forests). When the analysis was computed on daily aggregation, the indices related to chlorophyll content showed the best agreement with GPP. Significant differences were found according to vegetation types, where needle leaf forests were giving the poorest results. Our analysis demonstrates the valuable information carried by field spectroscopy data in the context of understanding GPP dynamics, supporting the hypothesis that the link between optical sensing and fluxes can be better interpreted with a growing number of field spectrometer data available at flux sites.

How to cite: Julitta, T., Burkart, A., Colombo, R., Cremonese, E., Damm, A., Dondina, O., El-Madany, T., Griessbaum, F., Miller, B., Burba, G., Kittler, F., Migliavacca, M., Rascher, U., Roland, M., Rossini, M., Brümmer, C., Schuettemeyer, D., Segers, J., Wohlfahrt, G., and Papale, D.: Field Spectroscopy versus GPP. A test case using JB Devices at flux sites., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12022, https://doi.org/10.5194/egusphere-egu23-12022, 2023.

A.332
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EGU23-13653
Matthew Saunders, Emmanuel Salmon, Ingunn Skjelvan, Tommy Bornman, Jörg Klausen, Gregor Feig, Lutz Merbold, and Werner L. Kutsch

Climate change is having an accelerating global impact through the increased frequency, magnitude and duration of droughts, fires, floods and other extreme climatic events. The societal solutions to this crisis depend on the ability of policy makers, private enterprise, and society at large to access and utilise scientific research into climatic variables and carbon/ greenhouse gas dynamics across scientific domains. One of the most suitable approaches to make the scientific data available to support the needs of all parties is the development of standardised observations in sustainable research infrastructures (RIs), that can facilitate both basic and applied scientific analyses and produce the data products needed.

The Horizon Europe funded KADI project (Knowledge and climate services from an African observation and Data research Infrastructure) aims to provide the conceptual framework for the future implementation of a pan-African RI that delivers the science-based services to fully address the requirements of the Paris agreement and the UN Sustainable Development Goals. The project will have direct societal benefit through facilitating inter-disciplinary cooperation between African and European Partners and conceptualising the requirements for climate change observations in Africa.

The KADI project will work towards the development of a comprehensive design for a pan-African climate observation system using the climate services identified and required by key stakeholders as a guiding design principle, and further building on the knowledge compiled and gaps identified through the SEACRIFOG collaborative inventory tool, the OSCAR/Surface, OSCAR/Space and OSCAR/Requirements tools. The project will provide a broad information-based network that will connect scientists, data and knowledge users at local, national and global levels, to develop a community of practice in climate services. These networking and knowledge exchange activities will allow for the development of an RI design study and the identification of the key players who can implement the conceptual design as sustainable funding for long-term observations becomes available.

The key activities of the project will utilise a co-design approach to identify the required climate services by key stakeholders/end-users and will explore these further through a series of climate service pilot projects that will focus on the impacts of climate change on terrestrial ecosystems, coastal areas, urban developments and national GHG budgets as well as on lessons learnt from existing long-term observations. The outputs from this will further inform the strategic design of the long-term observational and data infrastructures required. A knowledge exchange platform will facilitate pan-African and European innovation and will provide the link between the science-based concept design and the policy cooperation required to develop a functional and collaborative RI that will provide long-term sustainable support for the integration of African climate-services into global observation systems.

How to cite: Saunders, M., Salmon, E., Skjelvan, I., Bornman, T., Klausen, J., Feig, G., Merbold, L., and Kutsch, W. L.: Designing a pan-African climate observation system to deliver societal benefit through climate action: The KADI project., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13653, https://doi.org/10.5194/egusphere-egu23-13653, 2023.