Carbon budget estimation of a subarctic catchment using adynamic ecosystem model at high spatial resolution

A large amount of organic carbon is stored in highlatitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an Arctic-enabled version of the process-based dynamic ecosystem model, LPJGUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment at 50m resolution. Integrating the observed carbon fluxes from aquatic systems with the modeled terrestrial carbon fluxes across the whole catchment, we estimate that the area is a carbon sink at present and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modeled sinks are very dependent on future atmospheric CO2 concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO2 increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO2 fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modeling subarctic ecosystem responses to climate change, such as aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances, and peatland expansion, our study provides one process-based approach to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes

Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution

Large amount of organic carbon is stored in high latitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an arctic-enabled version of the process-based dynamic ecosystem model, LPJ-GUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment comprising both mineral and peatland soils. The model is applied at 50 m resolution and is shown to be able to capture the seasonality and magnitudes of observed fluxes at this fine scale. The modelled magnitudes of CO₂ uptake generally follow the descending sequence: birch forest, non-permafrost Eriophorum, Sphagnum and then tundra heath during the observation periods. The catchment-level carbon fluxes from aquatic systems are dominated by CO₂ emissions from streams. Integrated across the whole catchment, we estimate that the area is a carbon sink at present, and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modelled sinks are very dependent on future atmospheric CO₂ concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO₂ increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO₂ fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, integrating comprehensive and diverse fluxes including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modelling subarctic ecosystem responses to climate change including aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances and peatland expansion, our application provides a mechanism to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes.This discussion paper has been under review for the journal Biogeosciences (BG). Please refer to the corresponding final paper in BG. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The final revised paper is available at: http://hdl.handle.net/1957/5694

Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution

A large amount of organic carbon is stored in high-latitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an Arctic-enabled version of the process-based dynamic ecosystem model, LPJ-GUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment at 50 m resolution. Integrating the observed carbon fluxes from aquatic systems with the modeled terrestrial carbon fluxes across the whole catchment, we estimate that the area is a carbon sink at present and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modeled sinks are very dependent on future atmospheric CO₂ concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO₂ increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO₂ fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modeling subarctic ecosystem responses to climate change, such as aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances, and peatland expansion, our study provides one process-based approach to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes.For a previous discussion paper please see: http://hdl.handle.net/1957/56948. This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net/home.html

The biophysical climate mitigation potential of boreal peatlands during the growing season

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.Peer reviewe

The fingerprint of the summer 2018 drought in Europe on ground-based atmospheric CO2 measurements

During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO2) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO2 cycles from 48 European stations were available for 2017 and 2018.The UK sites were funded by the UK Department of Business, Energy and Industrial Strategy (formerly the Department of Energy and Climate Change) through contracts TRN1028/06/2015 and TRN1537/06/2018. The stations at the ClimaDat Network in Spain have received funding from the ‘la Caixa’ Foundation, under agreement 2010-002624

Polskie uregulowania prawne dotyczące wyboru miejsca lokalizacji elektrowni jądrowej w zakresie zagrożeń geodynamicznych na tle wybranych regulacji międzynarodowych

The nuclear power plant site was determined following the formal analysis of the Polish economy and energy supply, with respect to societal reality. Beforehand, comprehensive studies were carried out covering essential geological factors and terrain circumstances. Every country undertakes sovereign decisions regarding nuclear power plants, based on legitimate regulations. In practice, guidance regarding general requirements, technical solutions and safety measures are derivative from experiences in other countries published by the International Atomic Energy Agency (IAEA) and the US Nuclear Regulatory Commission. The paper presents interrelations between the international guidelines and the Polish legal instructions

Mapping the reduction in gross primary productivity in subarctic birch forests due to insect outbreaks

It is projected that forest disturbances, such as insect outbreaks, will have an increasingly negative impact on forests with a warmer climate. These disturbance events can have a substantial impact on forests' ability to absorb atmospheric CO2, and may even turn forests from carbon sinks into carbon sources; hence, it is important to develop methods both to monitor forest disturbances and to quantify the impact of these disturbance events on the carbon balance. In this study we present a method to monitor insect-induced defoliation in a subarctic birch forest in northern Sweden, and to quantify the impact of these outbreaks on gross primary productivity (GPP). Since frequent cloud cover in the study area requires data with high temporal resolution and limits the use of finer spatial resolution sensors such as Landsat, defoliation was mapped with remote sensing data from the MODIS sensor with 250 m  ×  250 m spatial resolution. The impact on GPP was estimated with a light use efficiency (LUE) model that was calibrated with GPP data obtained from eddy covariance (EC) measurements from 5 years with undisturbed birch forest and 1 year with insect-induced defoliation. Two methods were applied to estimate the impact on GPP: (1) applying a GPP reduction factor derived from EC measured GPP to estimate GPP loss, and (2) running a LUE model for both undisturbed and defoliated forest and deriving the differences in modelled GPP. In the study area of 100 km2 the results suggested a substantial setback to the carbon uptake: an average decrease in regional GPP over the three outbreak years (2004, 2012, and 2013) was estimated to 15 ± 5 Gg C yr−1, compared to the mean regional GPP of 40 ± 12 Gg C yr−1 for the 5 years without defoliation, i.e. 38 %. In the most severe outbreak year (2012), 76 % of the birch forests were defoliated, and annual regional GPP was merely 50 % of GPP for years without disturbances. The study has generated valuable data on GPP reduction, and demonstrates a potential for mapping insect disturbance impact over extended areas

Using A Modified Ensemble Kalman Filter Approach To Filter Pan-Arctic Eddy Covariance Flux Data

We present an application of the Ensemble Kalman Filter (EnKF) to assimilate eddy covariance data from several sites in the arctic and test a simple model of tundra carbon dioxide exchange. We modified the EnKF to allow adaptive noise estimation by providing a feedback from the model-data residuals (innovations) to the Monte-Carlo noise added to the ensemble of model simulations. Leaf area index (LAI) was allowed to vary as an estimated parameter within the EnKF; variation in LAI accounts for seasonal phenology, wind driven changes in the tower footprint, and, most importantly, for latent or unaccounted variables missing from the model. We then use the EnKF to assimilate the data into the PLIRTLE model of arctic ecosystem-atmosphere CO2 exchange (Shaver et al. 2007, J. Ecol. 95:802-817). Filtering the data with the modified EnKF improved estimates of CO2 exchange both by filtering out noise in the eddy covariance data and by compensating for biases associated with deficiencies in the model. Accounting for latent variables in the EnKF, but without the adaptive noise estimation, improved the filter performance slightly over the unmodified EnKF. Adding the adaptive noise estimation without accounting for latent variables resulted in very high levels of model noise, which allowed the filter to track the data virtually without flaw, but did not filter out obvious noise in the data stream. The best performance was achieved when both latent-variable accounting and adaptive noise estimation were added to the EnKF. Finally we used the modified EnKF to test the PLIRTLE model. We found the trends in the estimates of LAI were associated with seasonal phenology. However, the EnKF also produced a diel pattern in the LAI estimates for some sites that was clearly not random. This pattern is indicative of some unaccounted variable missing from the PLIRTLE model. We hypothesize that the mechanism missing in the PLIRTLE model, at least for one Alaskan site, may be stomatal closure driven by low atmospheric humidity

Carbon budget estimation of a subarctic catchment using adynamic ecosystem model at high spatial resolution

A large amount of organic carbon is stored in highlatitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an Arctic-enabled version of the process-based dynamic ecosystem model, LPJGUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment at 50m resolution. Integrating the observed carbon fluxes from aquatic systems with the modeled terrestrial carbon fluxes across the whole catchment, we estimate that the area is a carbon sink at present and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modeled sinks are very dependent on future atmospheric CO2 concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO2 increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO2 fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modeling subarctic ecosystem responses to climate change, such as aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances, and peatland expansion, our study provides one process-based approach to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes

Evaluation and optimization of ICOS atmosphere station data as part of the labeling process

The Integrated Carbon Observation System (ICOS) is a pan-European research infrastructure which provides harmonized and high-precision scientific data on the carbon cycle and the greenhouse gas budget. All stations have to undergo a rigorous assessment before being labeled, i.e., receiving approval to join the network. In this paper, we present the labeling process for the ICOS atmosphere network through the 23 stations that were labeled between November 2017 and November 2019. We describe the label-ing steps, as well as the quality controls, used to verify that the ICOS data (CO2, CH4, CO and meteorological measurements) attain the expected quality level defined within ICOS. To ensure the quality of the greenhouse gas data, three to four calibration gases and two target gases are measured: one target two to three times a day, the other gases twice a month. The data are verified on a weekly basis, and tests on the station sampling lines are performed twice a year. From these high-quality data, we conclude that regular calibrations of the CO2, CH4 and CO analyzers used here (twice a month) are important in particular for carbon monoxide (CO) due to the analyzer's variability and that reducing the number of calibration injections (from four to three) in a calibration sequence is possible, saving gas and extending the calibration gas lifespan. We also show that currently, the on-site water vapor correction test does not deliver quantitative results possibly due to environmental factors. Thus the use of a drying system is strongly recommended. Finally, the mandatory regular intake line tests are shown to be useful in detecting artifacts and leaks, as shown here via three different examples at the stations.Peer reviewe