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- Qiu, Chunjing, et al.
(författare)
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ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales
- 2018
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 11:2, s. 497-519
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Tidskriftsartikel (refereegranskat)abstract
- Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 Combining double low line 0.76; Nash-Sutcliffe modeling efficiency, MEF Combining double low line 0.76) and ecosystem respiration (ER, r2 Combining double low line 0.78, MEF Combining double low line 0.75), with lesser accuracy for latent heat fluxes (LE, r2 Combining double low line 0.42, MEF Combining double low line 0.14) and and net ecosystem CO2 exchange (NEE, r2 Combining double low line 0.38, MEF Combining double low line 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2<0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.
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| 2. |
- López-Ballesteros, Ana, et al.
(författare)
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Towards a feasible and representative pan-African research infrastructure network for GHG observations
- 2018
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- There is currently a lack of representative, systematic and harmonised greenhouse gas (GHG) observations covering the variety of natural and human-altered biomes that occur in Africa. This impedes the long-term assessment of the drivers of climate change, in addition to their impacts and feedback loops at the continental scale, but also limits our understanding of the contribution of the African continent to the global carbon (C) cycle. Given the current and projected transformation of socio-economic conditions in Africa (i.e. the increasing trend of urbanisation and population growth) and the adverse impacts of climate change, the development of a GHG research infrastructure (RI) is needed to support the design of suitable mitigation and adaptation strategies required to assure food, fuel, nutrition and economic security for the African population. This paper presents the initial results of the EU-African SEACRIFOG project, which aims to design a GHG observation RI for Africa. The first stages of this project included the identification and engagement of key stakeholders, the definition of the conceptual monitoring framework and an assessment of existing infrastructural capacity. Feedback from stakeholder sectors was obtained through three Stakeholder Consultation Workshops held in Kenya, Ghana and Zambia. Main concerns identified were data quality and accessibility, the need for capacity building and networking among the scientific community, and adaptation to climate change, which was confirmed to be a priority for Africa. This feedback in addition to input from experts in the atmospheric, terrestrial and oceanic thematic areas, facilitated the selection of a set of 'essential variables' that need to be measured in the future environmental RI. An inventory of 47 existing and planned networks across the continent allowed for an assessment of the current RIs needs and gaps in Africa. Overall, the development of a harmonised and standardised pan-African RI will serve to address the continent's primary societal and scientific challenges through a potential cross-domain synergy among existing and planned networks at regional, continental and global scales.
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