Assessment of carbon exchange between large homogeneous forests (LHF) and the atmosphere largely relies on the FLUXNET approach in which long-term eddy-covariance measurements from flux towers above extensive forest canopy are used. This approach assumes spatial homogeneity with a large fetch and ignores many other factors (especially horizontal heterogeneity below the sensor level). Applying this same approach to heterogeneous woodlands (HW) is erroneous because previous studies have shown that the air exchange between the leaf canopy and the background air above is dramatically enhanced near the edges of forests for a distance up to tens of tree heights. As a consequence, the enhanced turbulence near the edges raises the exchange of CO2 there (Figure 1). HWs occur in the vast majority of productive low-lying agricultural land in the UK, Europe and and other parts of the world. Understanding wind statistics, especially the intermittency of turbulence inside such woodlands, is crucial to estimating CO2 uptake; In order to improve the assessment of CO2 exchange associated with HW, we must improve our understanding of the key player, turbulence, and its impact on CO2 transport for woodlands. The scientific questions are: (i) what are the 3D characteristics of wind and turbulence inside and above the tree canopy? (ii) Can we model in-canopy mixing processes in order to improve the knowledge that is currently lacking? (iii) Compared with LHFs of the same tree species, can we express the additional carbon uptake in terms of some metrics of HW geometry (e.g., edge length, area)? (iv) What impact will the outcome make to the estimates of global terrestrial carbon uptake?
This project aims to address the scientific questions listed above and to shed light on the impact of HW on the CO2 exchange with the atmosphere aloft. Particular focuses will be on the spatial variability of CO2 exchange across a HW and the enhancement of the exchange per unit area with reference to LHF. The project represents the following innovative aspects: (1) the first LES for turbulent flows inside a HW; (2) the first use of a FACE facility to assesss the mixing capability of woodlands.
Building on decades of experience with large-eddy simulation (LES), the project will use LES to reveal detailed in-canopy transport processes[4,5] that affect CO2 fluxes. To evaluate the model, turbulence data from 12 sonic anemometers inside and above the canopy of the BIFoR woodland and other data (met and CO2 concentrations) will be used. The BIFoR facility will also be used as a unique “field dispersion laboratory” where the CO2 amount required to maintain a concentration 150 ppmv above ambient over several patches is monitored precisely and can be used to infer the mixing capability of the woodland.
Once evaluated, the model will be run for CO2 exchange scenarios (respectively for HWs and LHF) by imposing various CO2 concentrations above the canopy, thus enabling an assessment of the CO2 exchange for HWs and LHF. We seek functions to describe the difference between HWs and LHF based on geometric and/or meteorologial parameters, and then assess the scaled-up estimates using land-cover maps and the new parameterisation for HWs. Such estimates will be of interest to a wide community of climate and plant scientists.
Training and Skills
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to the student's projects and themes.
Student will take a training course scheduled in 2018 for the WRF (Weather Research & Forecasting) model and its LES configuration. Training for in-house codes (inlet LES condition & postprocessing) will be conducted by a research fellow, Dr Zhong. Computing related training courses will be provided by IT Services of University of Birmingham, e.g. UNIX and parallel computation. The student will also receive training on meteorological modelling by supervisors and research fellows of the modelling group. The student will work closely with other BIFoR FACE doctoral researchers in a tightly-knit researcher community. Also available is the training in a wide range of field and laboratory analysis techniques, associated spatial geostatistical analysis and visualisation and data interpretation.
Conduct literature review
Post-graduate subject training according to needs (eg carbon cycle, forest structure and function);
CENTA generic skills training
Specialist modelling training (WRF-LES & other codes)
Define and set-up model configurations;
Design the strategy of model evaluation;
Conduct initial analysis of BIFoR FACE field data.
Publish literature review
Publish initial data analysis with default model runs
Advanced CENTA training
Complete model evaluation
Design strategy of scenario simulations
Analyse model output
Continue simulations and analysis
Write further journal paper(s)
Partners and collaboration (including CASE)
CASE: Currently none. We will seek CASE partners from the BIFoR network if the proposal goes forward to advert. Potential CASE partners include Forest Research (Alice Holt flux tower being a possible comparator LHF site) and Commonwealth Forestry Association (BIFoR’s partner).
Other Partners: Professor Natascha Kljun, Geography, Swansea University, who has the expertise in footprint modelling, vegetation-atmosphere carbon exchange and upscaling of greenhouse gas flux measurements, is likely a collaborator of the project.
Any further details of the project can be obtained from:
Dr Xiaoming Cai, School of Geography, Earth and Env. Sci., University of Birmingham, email@example.com
Prof Rob MacKenzie, School of Geography, Earth and Env. Sci., University of Birmingham, firstname.lastname@example.org