Tea Thum | Finnish Meteorological Institute (original) (raw)

Papers by Tea Thum

<p>Urban areas are a large source of carbon dioxide (CO&amp... more <p>Urban areas are a large source of carbon dioxide (CO<sub>2</sub>) to the atmosphere. Cities are seeking solutions to reduce the CO<sub>2</sub> emissions and to achieve carbon neutrality. Thus, there is a growing interest in maximizing the carbon sinks of urban vegetation and soil. Current knowledge on the carbon sinks is mainly based on data from non-urban environments. In the cities, environmental controls of carbon flows are different compared to the surroundings: temperatures are higher and water cycles altered compared to non-urban areas, green areas are managed (e.g. mowed and irrigated), and trees typically have very limited space for their roots but less competition at the canopy-level. In order to reduce uncertainties particularly in observation based urban carbon emission estimation, biogenic fluxes and their behaviour need to be correctly described/presented.</p><p>In the CarboCity project (Urban green space solutions in carbon neutral cities; 2019–2023), we aim to achieve a thorough understanding of atmosphere-plant-soil carbon dynamics in urban areas, and to find the best practices for designing the green areas to maximise their carbon sinks and stocks. In Helsinki, Finland, we have three sites in the footprint area of the SMEAR III ICOS station (SMEAR – <em>Station for Measuring Earth surface-Atmosphere Relations</em>; ICOS – <em>Integrated Carbon Observation System</em>): a botanical garden, a small urban forest, and a street site. The measurements were started in 2020, and include photosynthesis and fluorescence of trees (<em>Tilia cordata</em> Mill., <em>T. × europaea</em> L., <em>Betula pendula</em> Roth) and soil respiration, together with several supporting measurements (e.g. air and soil temperature, relative humidity, soil water content, sap flow, LAI). Ecosystem-level CO<sub>2</sub> exchange over the whole area of all three sites is measured at the SMEAR III ICOS station. Since late 2020, we are measuring also carbonyl sulphide exchange at the neighbourhood scale, which is used as a proxy for GPP. In addition to the measurements in Helsinki, we will use measured data from London, Minneapolis-Saint Paul, Beijing and São Paolo – cities that differ in the climate regions, vegetation types, and management styles of their green areas. Furthermore, the measurements will be used to parameterise land surface model SUEWS (<em>Surface Urban Energy and Water balance Scheme</em>), soil carbon model Yasso and dynamic land-surface models.</p>

<p>... more <p>Terrestrial vegetation growth is hypothesised to increase under elevated atmospheric CO<sub>2</sub>, a process known as the CO<sub>2</sub> fertilisation effect. However, the magnitude of this effect and its long-term sustainability remains uncertain. One of the main limitations to the CO2  fertilisation effect is nutrient limitation to plant growth, in particular nitrogen (N) in temperate and boreal ecosystems. Recent studies have suggested that decreases in observed foliar N content (N%) and δ<sup>15</sup>N indicate widespread nitrogen limitation with increasing CO<sub>2</sub>  concentrations. However, the factors driving these two variables, and especially the foliar δ<sup>15</sup>N values, are complex and can be caused by a number of processes. On one hand, if the observed trends reflect nutrient limitation, this limitation can be caused by either CO<sub>2</sub> or warming driven growth. On the other hand, it is possible that nutrient limitation does not occur to its full extent due to plant plastic responses to alleviate nutrient limitation, causing a decrease in N%, but changes in the anthropogenic N deposition 15N signal cause the observed δ<sup>15</sup>N trend. In reality, it is likely that all these factors contribute to the observed trends. To understand ecosystem dynamics it is important to disentangle the processes behind these signals which is very difficult based on observational datasets only.</p><p>We use a novel land surface model to explore the causes behind the observed trends in foliar N% and δ<sup>15</sup>N. The QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) model  has the unique capacity to track ecologically relevant isotopic composition, including <sup>15</sup>N in plant and soil pools. The model also includes a realistic representation of plant plastic acclimation processes, specifically a representation of nitrogen allocation to and inside the canopy in response to nitrogen availability, so implicitly to changes in CO<sub>2 </sub> concentrations. We test the different hypotheses above behind the observed changes in N% and δ<sup>15</sup>N separately and quantify the contribution of each of the factors towards the observed trend. We then test the different hypotheses against existing observations of N% and…

The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil car... more The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil carbon is a substantial carbon storage with a large potential to impact the atmospheric carbon dioxide (CO 2) burden. Atmospheric CO 2 observations integrate all processes affecting C exchange between the surface and the atmosphere. Therefore they provide a benchmark for carbon cycle models. We evaluated two distinct soil carbon models (CBALANCE and YASSO) that were implemented to a global land surface model (JSBACH) against atmospheric CO 2 observations. We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO 2. We then compared these results with surface observations from Global Atmosphere Watch (GAW) stations as well as with column XCO 2 retrievals from the GOSAT satellite. The seasonal cycles of atmospheric CO 2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0 • N-45 • N) with only 1 % bias in the seasonal cycle amplitude (SCA), whereas YASSO was underestimating the SCA in this region by 32 %. YASSO gave more realistic seasonal cycle amplitudes of CO 2 at northern boreal sites (north of 45 • N) with underestimation of 15 % compared to 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO 2 even though it overestimated soil carbon stocks by 225 % (compared to underestimation of 36 % by YASSO) and its predictions of the global distribution of soil carbon stocks was unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies of these two soil carbon models. In the tropical region the YASSO model showed earlier increase in season of the heterotophic respiration since it is driven by precipitation instead of soil moisture as CBALANCE. In the temperate and boreal region the role of temperature is more dominant. There the heterotophic respiration from the YASSO model had larger annual variability, driven by air temperature, compared to the CBALANCE which is driven by soil 1

S1 Details on JSBACH simulations Simulations were conducted on Mistral (the High Performance Comp... more S1 Details on JSBACH simulations Simulations were conducted on Mistral (the High Performance Computing system of the German Climate Computing Center (DKRZ)), using revision 8522 of cosmos − landveg_rc − echam6.3_F OM − alloc, a svn branch of cosmos-landveg, the former JSBACH development branch of the department "The Land in the Earth System" of the Max Planck Institute for Meteorology.

Geoscientific Model Development

The article processing charges for this open-access publication were covered by the Max Planck So... more The article processing charges for this open-access publication were covered by the Max Planck Society. Review statement. This paper was edited by Philippe Peylin and reviewed by three anonymous referees.

This Supplementary Material includes a detailed model description with equations. Section 1 summa... more This Supplementary Material includes a detailed model description with equations. Section 1 summarises the general structure and vertical discretisation of vegetation and soil, and introduces general parameters (Tab 1). Section 2 describes the canopy processes, such as photosynthesis and stomatal coupling, with parameters in Tab. 2. Section 3 introduces vegetation growth, turnover and dynamics and the corresponding parameters are in Tab. 3. The soil biochemistry is described in Section 4, and its parameters are in Tab. 4. Section 5 describes the implementation of the isotope code, with parameters in Tab. 5. Section 6 describes the radiation scheme, surface energy balance and soil hydrology, with parameters described in Tab. 6. The PFT-specific parameters are listed in Tab. 7. 1 General model structure and discretisation Each gridcell of the model is subdivided into nested tiles, each of which is occupied by one specific vegetation-type, representing a plant functional type (PFT). The number of tiles per gridcell is flexible, making it is easy to implement more/different PFTs in the future. In the model, vegetation is represented by an average individual composed of a range of structural pools (leaves, sapwood, heartwood, coarse roots, fine roots, and fruit), a fast overturning, respiring non-structural pool (labile), as well as a seasonal, non-respiring, and non-structural storage pool (reserve). Tree vegetation types are furthermore characterised by their height (m), diameter (m), and stand density (m −2). Soil biogeochemistry is represented using five organic pools: metabolic (met), structural (str) and and woody (wl) litter, as well as fast (f) and slow (s) overturning soil organic matter. Each of these pools contains carbon (C), nitrogen (N) and phosphorus (P), as well as 13 C, 14 C, and 15 N. The unit of the pools is mol X m −2 for vegetation and mol X m −3 for soil biogeochemical pools, where X represents any of these elements. In addition, the model represents the following soil biogeochemical pools (NH 4 , NO 3 , NO y , N 2 O, N 2 , and PO 4), with equivalent units. The model operates on a half-hourly timescale (denoted as dt). Vegetation processes are assumed to respond to these instantaneous conditions and associated fluxes with a process-specific lag time (τ process mavg , see Tab. 1), representing a form of

New Phytologist

Vegetation nutrient limitation is essential for understanding ecosystem responses to global chang... more Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criterion based on whole-plant growth, and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO 2 Enrichment and N fertilisation experimental sites. We show that a model based solely on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N content with increased N availability. However, an optimal model which maximises total plant growth can correctly reproduce the observed patterns. The optimality model we present here is a whole-plant approach which reproduces biologically realistic changes in leaf N and can thereby improve ecosystem-level predictions under transient conditions.

Vegetation nutrient limitation is essential for understanding ecosystem responses to global chang... more Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criteria based on whole-plant growth and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO2 Enrichment (FACE) and N fertilisation experimental sites. We show a model solely based on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N c...

Geoscientific Model Development

We calibrated the JSBACH model with six different stomatal conductance formulations using measure... more We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball-Berry, and the Friend and Kiang stomatal conductance models. We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.

Geoscientific Model Development Discussions

The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen and p... more The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen and phosphorus, and strongly depend on the availability of water and energy. These interactions shape future terrestrial biosphere responses to global change. Many process-based models of the terrestrial biosphere have been gradually extended from considering carbon-water interactions to also including nitrogen, and later, phosphorus dynamics. This evolutionary model development has hindered full integration of these biogeochemical cycles and the feedbacks amongst them. Here we present a new terrestrial ecosystem model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system), which is formulated around a consistent representation of element cycling in terrestrial ecosystems. This new model includes i) a representation of plant growth which separates source (e.g. photosynthesis) and sink (growth rate of individual tissues, constrained by nutrients, temperature, and water availability) processes; ii) the acclimation of many ecophysiological processes to meteorological conditions and/or nutrient availabilities; iii) an explicit representation of vertical soil processes to separate litter and soil organic matter dynamics; iv) a range of new diagnostics (leaf chlorophyll content; 13 C, 14 C, and 15 N isotope tracers) to allow for a more in-depth model evaluation. We present the model structure and provide an assessment of its performance against a range of observations from global-scale ecosystem monitoring networks. We demonstrate that the framework is capable of consistently simulating ecosystem dynamics across a large gradient in climate and soil conditions, as well as across different plant functional types. To aid this understanding we provide an assessment of the model's sensitivity to its parameterisation and the associated uncertainty.

Geoscientific Model Development Discussions

We calibrated the JSBACH model with six different stomatal conductance formulations using measure... more We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the Boreal zone. The parameter posterior distributions were generated by adaptive population importance sampler and the optimal values by a simple stochastic optimisation algorithm. The observations used to constrain the model are evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. We were able to improve the coefficient of determination and the model bias with all stomatal conductance formulations. There was no clear candidate for the best stomatal conductance model, although certain versions produced better estimates depending on the examined variable (ET, GPP) and the used metric. We were also able to significantly enhance the model behaviour during a drought event in a Finnish Scots pine forest site. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity. This modification enabled the model to correctly time and replicate the springtime increase in GPP (and ET) for conifers throughout the measurements sites used in this study.

Environmental Science and Technology, Nov 1, 2005

The first measurements of nitrous oxide (N20) emissions from a landfill by the eddy covariance me... more The first measurements of nitrous oxide (N20) emissions from a landfill by the eddy covariance method are reported. These measurements were compared to enclosure emission measurements conducted at the same site. The average emissions from the municipal landfill of the Helsinki Metropolitan Area were 2.7 mg N m(-2) h(-1) and 6.0 mg N m(-2) h(-1) measured bythe eddy covariance and the enclosure methods, respectively. The N20 emissions from the landfill are about 1 order of magnitude higher than the highest emissions reported from Northern European agricultural soils, and 2 orders of magnitude higher than the highest emissions reported from boreal forest soils. Due to the small area of landfills as compared to other land-use classes, the total N20 emissions from landfills are estimated to be of minor importance for the total emissions from Finland. Expressed as a greenhouse warming potential (GWP100), the N2O emissions make up about 3% of the total GWP100 emission of the landfill. The emissions measured by the two systems were generally of similar magnitude, with enclosure measurements showing a high small-scale spatial variation.

Atmospheric Chemistry and Physics, 2004

During the calendar years 1998-2002, 147 clear 8 nm diameter particle formation events have been ... more During the calendar years 1998-2002, 147 clear 8 nm diameter particle formation events have been identified at the SMEAR I station in Värriö, northern Finland. The events have been classified in detail according to the particle formation rate, growth rate, event starting time, different trace gas concentrations and pre-existing particle concentrations as well as various meteorological conditions. The frequency of particle formation and growth events was highest during the spring months between March and May, suggesting that increasing biological activity might produce the precursor gases for particle formation. The apparent 8 nm particle formation rates were around 0.1 /cm 3 s, and they were uncorrelated with growth rates that varied between 0.5 and 10 nm/h. The air masses with clearly elevated sulphur dioxide concentrations (above 1.6 ppb) came, as expected, from the direction of the Nikel and Monschegorsk smelters. Only 15 formation events can be explained by the pollution plume from these sources.

Biogeosciences Discussions, 2016

Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provid... more Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf level chlorophyll fluorescence measurements (ChlF) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based ...

Atmos Chem Phys, 2006

CO2 fluxes and concentrations were simulated in the planetary boundary layer above subarctic hill... more CO2 fluxes and concentrations were simulated in the planetary boundary layer above subarctic hilly terrain using a three dimensional model. The model solves the transport equations in the local scale and includes a vegetation sub-model. A WMO/GAW background concentration measurement site and an ecosystem flux measurement site are located inside the modeled region at a hilltop and above a mixed boreal forest, respectively. According to model results, the concentration measurement at the hill site was representative for continental background. However, this was not the case for the whole model domain. Concentration at few meters above active vegetation represented mainly local variation. Local variation became inseparable from the regional signal at about 60-100 m above ground. Flow over hills changed profiles of environmental variables and height of inversion layer, however CO2 profiles were more affected by upwind land use than topography. The hill site was above boundary layer during night and inside boundary layer during daytime. The CO2 input from model lateral boundaries dominated in both cases. Daily variation in the CO2 assimilation rate was clearly seen in the CO2 profiles. Concentration difference between the hill site and the forest site was about 5ppm during afternoon according to both model and measurements. The average modeled flux to the whole model region was about 40% of measured and modeled local flux at the forest site.

Egu General Assembly Conference Abstracts, May 1, 2014

The carbon cycle of the northern ecosystems is strongly influenced by the climatic variables. The... more The carbon cycle of the northern ecosystems is strongly influenced by the climatic variables. The changing climate may thus have noticeably impact on the carbon balances in the high-latitude regions. In this work we assessed the carbon balance of the Finnish ecosystems with a process-based biosphere model JSBACH that is a global model but can also be run at regional and site scales. We prepared the meteorological forcing for the model run by using a regional climate model REMO with new land cover data set based on European Corine Database. Our spatial resolution was 0.167 degrees and the time step for the simulation was one hour. We also made site level simulations at four eddy covariance measurement sites to evaluate the model performance. The sites included three forests and one agricultural site, all located in Finland and the forests were covering a wide north-south latitudinal gradient. Model performance was satisfactory, but the drought-induced drawdowns in the carbon fluxes were not replicated by the model. Surprisingly, the simulation results matched better the observations with the meteorological forcing taken from the REMO run than the simulation results run with the locally observed meteorology. The reason for this was the too early emergence of carbon fluxes when run with the site data, which was compensated by slightly colder spring temperatures of the regional run forcing. The two different forcings led to different directions on the annual carbon fluxes, i.e., sink or source, on some years. Additionally, we performed some tests to initialize the model with observed biomass and soil carbon pools to assess how the model that is usually run with steady state assumption performs. The modelled carbon balance for Finland was comparable to other estimations that were based, e.g., on forest inventory or inverse modeling. When subdividing Finland along the north-south direction, carbon fluxes in northern part of Finland had different characteristics in their behavior compared to other regions. This is partly related to different land cover types and partly to the environmental conditions: northern Finland had smallest fraction of forests and a higher percentage of deciduous forests than other regions. We studied the impact of climatic variables on the carbon fluxes during different seasons in the whole Finland and three sub-regions during years 2001-2010. We found that temperature was the most important controlling factor of the carbon fluxes, whereas the precipitation did not have a large role according to the modeling results. The warmer autumns led to increase in the respiration flux that influenced the whole annual carbon balance. Some grid points showed increasing trend in respiration, otherwise no trends in carbon fluxes were present during our study period.

<p>Urban areas are a large source of carbon dioxide (CO&amp... more <p>Urban areas are a large source of carbon dioxide (CO<sub>2</sub>) to the atmosphere. Cities are seeking solutions to reduce the CO<sub>2</sub> emissions and to achieve carbon neutrality. Thus, there is a growing interest in maximizing the carbon sinks of urban vegetation and soil. Current knowledge on the carbon sinks is mainly based on data from non-urban environments. In the cities, environmental controls of carbon flows are different compared to the surroundings: temperatures are higher and water cycles altered compared to non-urban areas, green areas are managed (e.g. mowed and irrigated), and trees typically have very limited space for their roots but less competition at the canopy-level. In order to reduce uncertainties particularly in observation based urban carbon emission estimation, biogenic fluxes and their behaviour need to be correctly described/presented.</p><p>In the CarboCity project (Urban green space solutions in carbon neutral cities; 2019–2023), we aim to achieve a thorough understanding of atmosphere-plant-soil carbon dynamics in urban areas, and to find the best practices for designing the green areas to maximise their carbon sinks and stocks. In Helsinki, Finland, we have three sites in the footprint area of the SMEAR III ICOS station (SMEAR – <em>Station for Measuring Earth surface-Atmosphere Relations</em>; ICOS – <em>Integrated Carbon Observation System</em>): a botanical garden, a small urban forest, and a street site. The measurements were started in 2020, and include photosynthesis and fluorescence of trees (<em>Tilia cordata</em> Mill., <em>T. × europaea</em> L., <em>Betula pendula</em> Roth) and soil respiration, together with several supporting measurements (e.g. air and soil temperature, relative humidity, soil water content, sap flow, LAI). Ecosystem-level CO<sub>2</sub> exchange over the whole area of all three sites is measured at the SMEAR III ICOS station. Since late 2020, we are measuring also carbonyl sulphide exchange at the neighbourhood scale, which is used as a proxy for GPP. In addition to the measurements in Helsinki, we will use measured data from London, Minneapolis-Saint Paul, Beijing and São Paolo – cities that differ in the climate regions, vegetation types, and management styles of their green areas. Furthermore, the measurements will be used to parameterise land surface model SUEWS (<em>Surface Urban Energy and Water balance Scheme</em>), soil carbon model Yasso and dynamic land-surface models.</p>

<p>... more <p>Terrestrial vegetation growth is hypothesised to increase under elevated atmospheric CO<sub>2</sub>, a process known as the CO<sub>2</sub> fertilisation effect. However, the magnitude of this effect and its long-term sustainability remains uncertain. One of the main limitations to the CO2  fertilisation effect is nutrient limitation to plant growth, in particular nitrogen (N) in temperate and boreal ecosystems. Recent studies have suggested that decreases in observed foliar N content (N%) and δ<sup>15</sup>N indicate widespread nitrogen limitation with increasing CO<sub>2</sub>  concentrations. However, the factors driving these two variables, and especially the foliar δ<sup>15</sup>N values, are complex and can be caused by a number of processes. On one hand, if the observed trends reflect nutrient limitation, this limitation can be caused by either CO<sub>2</sub> or warming driven growth. On the other hand, it is possible that nutrient limitation does not occur to its full extent due to plant plastic responses to alleviate nutrient limitation, causing a decrease in N%, but changes in the anthropogenic N deposition 15N signal cause the observed δ<sup>15</sup>N trend. In reality, it is likely that all these factors contribute to the observed trends. To understand ecosystem dynamics it is important to disentangle the processes behind these signals which is very difficult based on observational datasets only.</p><p>We use a novel land surface model to explore the causes behind the observed trends in foliar N% and δ<sup>15</sup>N. The QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) model  has the unique capacity to track ecologically relevant isotopic composition, including <sup>15</sup>N in plant and soil pools. The model also includes a realistic representation of plant plastic acclimation processes, specifically a representation of nitrogen allocation to and inside the canopy in response to nitrogen availability, so implicitly to changes in CO<sub>2 </sub> concentrations. We test the different hypotheses above behind the observed changes in N% and δ<sup>15</sup>N separately and quantify the contribution of each of the factors towards the observed trend. We then test the different hypotheses against existing observations of N% and…

The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil car... more The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil carbon is a substantial carbon storage with a large potential to impact the atmospheric carbon dioxide (CO 2) burden. Atmospheric CO 2 observations integrate all processes affecting C exchange between the surface and the atmosphere. Therefore they provide a benchmark for carbon cycle models. We evaluated two distinct soil carbon models (CBALANCE and YASSO) that were implemented to a global land surface model (JSBACH) against atmospheric CO 2 observations. We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO 2. We then compared these results with surface observations from Global Atmosphere Watch (GAW) stations as well as with column XCO 2 retrievals from the GOSAT satellite. The seasonal cycles of atmospheric CO 2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0 • N-45 • N) with only 1 % bias in the seasonal cycle amplitude (SCA), whereas YASSO was underestimating the SCA in this region by 32 %. YASSO gave more realistic seasonal cycle amplitudes of CO 2 at northern boreal sites (north of 45 • N) with underestimation of 15 % compared to 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO 2 even though it overestimated soil carbon stocks by 225 % (compared to underestimation of 36 % by YASSO) and its predictions of the global distribution of soil carbon stocks was unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies of these two soil carbon models. In the tropical region the YASSO model showed earlier increase in season of the heterotophic respiration since it is driven by precipitation instead of soil moisture as CBALANCE. In the temperate and boreal region the role of temperature is more dominant. There the heterotophic respiration from the YASSO model had larger annual variability, driven by air temperature, compared to the CBALANCE which is driven by soil 1

S1 Details on JSBACH simulations Simulations were conducted on Mistral (the High Performance Comp... more S1 Details on JSBACH simulations Simulations were conducted on Mistral (the High Performance Computing system of the German Climate Computing Center (DKRZ)), using revision 8522 of cosmos − landveg_rc − echam6.3_F OM − alloc, a svn branch of cosmos-landveg, the former JSBACH development branch of the department "The Land in the Earth System" of the Max Planck Institute for Meteorology.

Geoscientific Model Development

The article processing charges for this open-access publication were covered by the Max Planck So... more The article processing charges for this open-access publication were covered by the Max Planck Society. Review statement. This paper was edited by Philippe Peylin and reviewed by three anonymous referees.

This Supplementary Material includes a detailed model description with equations. Section 1 summa... more This Supplementary Material includes a detailed model description with equations. Section 1 summarises the general structure and vertical discretisation of vegetation and soil, and introduces general parameters (Tab 1). Section 2 describes the canopy processes, such as photosynthesis and stomatal coupling, with parameters in Tab. 2. Section 3 introduces vegetation growth, turnover and dynamics and the corresponding parameters are in Tab. 3. The soil biochemistry is described in Section 4, and its parameters are in Tab. 4. Section 5 describes the implementation of the isotope code, with parameters in Tab. 5. Section 6 describes the radiation scheme, surface energy balance and soil hydrology, with parameters described in Tab. 6. The PFT-specific parameters are listed in Tab. 7. 1 General model structure and discretisation Each gridcell of the model is subdivided into nested tiles, each of which is occupied by one specific vegetation-type, representing a plant functional type (PFT). The number of tiles per gridcell is flexible, making it is easy to implement more/different PFTs in the future. In the model, vegetation is represented by an average individual composed of a range of structural pools (leaves, sapwood, heartwood, coarse roots, fine roots, and fruit), a fast overturning, respiring non-structural pool (labile), as well as a seasonal, non-respiring, and non-structural storage pool (reserve). Tree vegetation types are furthermore characterised by their height (m), diameter (m), and stand density (m −2). Soil biogeochemistry is represented using five organic pools: metabolic (met), structural (str) and and woody (wl) litter, as well as fast (f) and slow (s) overturning soil organic matter. Each of these pools contains carbon (C), nitrogen (N) and phosphorus (P), as well as 13 C, 14 C, and 15 N. The unit of the pools is mol X m −2 for vegetation and mol X m −3 for soil biogeochemical pools, where X represents any of these elements. In addition, the model represents the following soil biogeochemical pools (NH 4 , NO 3 , NO y , N 2 O, N 2 , and PO 4), with equivalent units. The model operates on a half-hourly timescale (denoted as dt). Vegetation processes are assumed to respond to these instantaneous conditions and associated fluxes with a process-specific lag time (τ process mavg , see Tab. 1), representing a form of

New Phytologist

Vegetation nutrient limitation is essential for understanding ecosystem responses to global chang... more Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criterion based on whole-plant growth, and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO 2 Enrichment and N fertilisation experimental sites. We show that a model based solely on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N content with increased N availability. However, an optimal model which maximises total plant growth can correctly reproduce the observed patterns. The optimality model we present here is a whole-plant approach which reproduces biologically realistic changes in leaf N and can thereby improve ecosystem-level predictions under transient conditions.

Vegetation nutrient limitation is essential for understanding ecosystem responses to global chang... more Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criteria based on whole-plant growth and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO2 Enrichment (FACE) and N fertilisation experimental sites. We show a model solely based on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N c...

Geoscientific Model Development

We calibrated the JSBACH model with six different stomatal conductance formulations using measure... more We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball-Berry, and the Friend and Kiang stomatal conductance models. We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.

Geoscientific Model Development Discussions

The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen and p... more The dynamics of terrestrial ecosystems are shaped by the coupled cycles of carbon, nitrogen and phosphorus, and strongly depend on the availability of water and energy. These interactions shape future terrestrial biosphere responses to global change. Many process-based models of the terrestrial biosphere have been gradually extended from considering carbon-water interactions to also including nitrogen, and later, phosphorus dynamics. This evolutionary model development has hindered full integration of these biogeochemical cycles and the feedbacks amongst them. Here we present a new terrestrial ecosystem model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system), which is formulated around a consistent representation of element cycling in terrestrial ecosystems. This new model includes i) a representation of plant growth which separates source (e.g. photosynthesis) and sink (growth rate of individual tissues, constrained by nutrients, temperature, and water availability) processes; ii) the acclimation of many ecophysiological processes to meteorological conditions and/or nutrient availabilities; iii) an explicit representation of vertical soil processes to separate litter and soil organic matter dynamics; iv) a range of new diagnostics (leaf chlorophyll content; 13 C, 14 C, and 15 N isotope tracers) to allow for a more in-depth model evaluation. We present the model structure and provide an assessment of its performance against a range of observations from global-scale ecosystem monitoring networks. We demonstrate that the framework is capable of consistently simulating ecosystem dynamics across a large gradient in climate and soil conditions, as well as across different plant functional types. To aid this understanding we provide an assessment of the model's sensitivity to its parameterisation and the associated uncertainty.

Geoscientific Model Development Discussions

We calibrated the JSBACH model with six different stomatal conductance formulations using measure... more We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the Boreal zone. The parameter posterior distributions were generated by adaptive population importance sampler and the optimal values by a simple stochastic optimisation algorithm. The observations used to constrain the model are evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. We were able to improve the coefficient of determination and the model bias with all stomatal conductance formulations. There was no clear candidate for the best stomatal conductance model, although certain versions produced better estimates depending on the examined variable (ET, GPP) and the used metric. We were also able to significantly enhance the model behaviour during a drought event in a Finnish Scots pine forest site. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity. This modification enabled the model to correctly time and replicate the springtime increase in GPP (and ET) for conifers throughout the measurements sites used in this study.

Environmental Science and Technology, Nov 1, 2005

The first measurements of nitrous oxide (N20) emissions from a landfill by the eddy covariance me... more The first measurements of nitrous oxide (N20) emissions from a landfill by the eddy covariance method are reported. These measurements were compared to enclosure emission measurements conducted at the same site. The average emissions from the municipal landfill of the Helsinki Metropolitan Area were 2.7 mg N m(-2) h(-1) and 6.0 mg N m(-2) h(-1) measured bythe eddy covariance and the enclosure methods, respectively. The N20 emissions from the landfill are about 1 order of magnitude higher than the highest emissions reported from Northern European agricultural soils, and 2 orders of magnitude higher than the highest emissions reported from boreal forest soils. Due to the small area of landfills as compared to other land-use classes, the total N20 emissions from landfills are estimated to be of minor importance for the total emissions from Finland. Expressed as a greenhouse warming potential (GWP100), the N2O emissions make up about 3% of the total GWP100 emission of the landfill. The emissions measured by the two systems were generally of similar magnitude, with enclosure measurements showing a high small-scale spatial variation.

Atmospheric Chemistry and Physics, 2004

During the calendar years 1998-2002, 147 clear 8 nm diameter particle formation events have been ... more During the calendar years 1998-2002, 147 clear 8 nm diameter particle formation events have been identified at the SMEAR I station in Värriö, northern Finland. The events have been classified in detail according to the particle formation rate, growth rate, event starting time, different trace gas concentrations and pre-existing particle concentrations as well as various meteorological conditions. The frequency of particle formation and growth events was highest during the spring months between March and May, suggesting that increasing biological activity might produce the precursor gases for particle formation. The apparent 8 nm particle formation rates were around 0.1 /cm 3 s, and they were uncorrelated with growth rates that varied between 0.5 and 10 nm/h. The air masses with clearly elevated sulphur dioxide concentrations (above 1.6 ppb) came, as expected, from the direction of the Nikel and Monschegorsk smelters. Only 15 formation events can be explained by the pollution plume from these sources.

Biogeosciences Discussions, 2016

Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provid... more Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf level chlorophyll fluorescence measurements (ChlF) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based ...

Atmos Chem Phys, 2006

CO2 fluxes and concentrations were simulated in the planetary boundary layer above subarctic hill... more CO2 fluxes and concentrations were simulated in the planetary boundary layer above subarctic hilly terrain using a three dimensional model. The model solves the transport equations in the local scale and includes a vegetation sub-model. A WMO/GAW background concentration measurement site and an ecosystem flux measurement site are located inside the modeled region at a hilltop and above a mixed boreal forest, respectively. According to model results, the concentration measurement at the hill site was representative for continental background. However, this was not the case for the whole model domain. Concentration at few meters above active vegetation represented mainly local variation. Local variation became inseparable from the regional signal at about 60-100 m above ground. Flow over hills changed profiles of environmental variables and height of inversion layer, however CO2 profiles were more affected by upwind land use than topography. The hill site was above boundary layer during night and inside boundary layer during daytime. The CO2 input from model lateral boundaries dominated in both cases. Daily variation in the CO2 assimilation rate was clearly seen in the CO2 profiles. Concentration difference between the hill site and the forest site was about 5ppm during afternoon according to both model and measurements. The average modeled flux to the whole model region was about 40% of measured and modeled local flux at the forest site.

Egu General Assembly Conference Abstracts, May 1, 2014

The carbon cycle of the northern ecosystems is strongly influenced by the climatic variables. The... more The carbon cycle of the northern ecosystems is strongly influenced by the climatic variables. The changing climate may thus have noticeably impact on the carbon balances in the high-latitude regions. In this work we assessed the carbon balance of the Finnish ecosystems with a process-based biosphere model JSBACH that is a global model but can also be run at regional and site scales. We prepared the meteorological forcing for the model run by using a regional climate model REMO with new land cover data set based on European Corine Database. Our spatial resolution was 0.167 degrees and the time step for the simulation was one hour. We also made site level simulations at four eddy covariance measurement sites to evaluate the model performance. The sites included three forests and one agricultural site, all located in Finland and the forests were covering a wide north-south latitudinal gradient. Model performance was satisfactory, but the drought-induced drawdowns in the carbon fluxes were not replicated by the model. Surprisingly, the simulation results matched better the observations with the meteorological forcing taken from the REMO run than the simulation results run with the locally observed meteorology. The reason for this was the too early emergence of carbon fluxes when run with the site data, which was compensated by slightly colder spring temperatures of the regional run forcing. The two different forcings led to different directions on the annual carbon fluxes, i.e., sink or source, on some years. Additionally, we performed some tests to initialize the model with observed biomass and soil carbon pools to assess how the model that is usually run with steady state assumption performs. The modelled carbon balance for Finland was comparable to other estimations that were based, e.g., on forest inventory or inverse modeling. When subdividing Finland along the north-south direction, carbon fluxes in northern part of Finland had different characteristics in their behavior compared to other regions. This is partly related to different land cover types and partly to the environmental conditions: northern Finland had smallest fraction of forests and a higher percentage of deciduous forests than other regions. We studied the impact of climatic variables on the carbon fluxes during different seasons in the whole Finland and three sub-regions during years 2001-2010. We found that temperature was the most important controlling factor of the carbon fluxes, whereas the precipitation did not have a large role according to the modeling results. The warmer autumns led to increase in the respiration flux that influenced the whole annual carbon balance. Some grid points showed increasing trend in respiration, otherwise no trends in carbon fluxes were present during our study period.