Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation

Viskari, Toni; Laine, Maisa; Kulmala, Liisa; Mäkelä, Jarmo; Fer, Istem; Liski, Jari

doi:10.5194/gmd-13-5959-2020

Cited by 25 publications

(26 citation statements)

References 58 publications

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“…Thus, data and related metadata should be made available freely and openly to the scientific community to ensure good governance of forest and forestry information. Repeated measurements as well as improved modelling tools are further required to allow assimilation of most recent data in the modelling exercises [ 60 ].…”

Section: Discussionmentioning

confidence: 99%

Two large-scale forest scenario modelling approaches for reporting CO2 removal: a comparison for the Romanian forests

Blujdea

Sikkema

Dutcă

et al. 2021

Carbon Balance Manage

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Background Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. Results The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m3 ha−1, while the carbon stock in tree biomass will reach 76.5 tC ha−1. The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. Conclusions This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use.

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Section: Discussionmentioning

confidence: 99%

Two large-scale forest scenario modelling approaches for reporting CO2 removal: a comparison for the Romanian forests

Blujdea

Sikkema

Dutcă

et al. 2021

Carbon Balance Manage

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“…Because an accurate and comprehensive site history for each specific plot is difficult (or even impossible) to obtain, the issue of proper model initialisation [71] still hinders accurate reconstruction of SOC. A potential way forward is to explore the possibility of using a data assimilation method [90] to improve SOC estimates. Another issue is the limitation of the soils sampling.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses

Sever

Barcza

Hidy

et al. 2021

Land

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Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia’s GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC30) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC30 with no overall bias, and showed good performance at the LU level with no significant (p < 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC30 and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting.

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“…Yasso15 (Viskari et al, 2020) is the most recent version of the soil carbon decomposition model Yasso (Tuomi et al, 2009;Liski et al, 2005), where the rate of decomposition depends on climatic conditions and chemical composition of the soil organic matter. The model can be run as an annual or monthly basis.…”

Section: Yassomentioning

confidence: 99%

“…In addition to the size of the SOC pool, soil carbon decomposition depends also on temperature and precipitation (Davidson and Janssens, 2006). Therefore, there exist multiple ecosystem soil decomposition models that are driven by climate, such as, Yasso15 (Viskari et al, 2020), CENTURY (Parton et al, 1988), Millennial (Abramoff et al, 2018) and ORCHIDEE-SOM (Camino-Serrano et al, 2018). Soil carbon models are developed especially for native ecosystems, such as forests, and for agricultural soils (Karhu et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Carbon sequestration potential of street tree plantings in Helsinki

Havu

Kulmala

Kolari

et al. 2021

Preprint

Self Cite

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Abstract. Cities have become increasingly interested in reducing their greenhouse gas emissions, and increasing carbon sequestration and storage in urban vegetation and soil as part of their climate mitigation actions. However, most of our knowledge on biogenic carbon cycle is based on data and models from forested ecosystems even though urban nature and microclimate are very different to those in natural or forested ecosystems. There is a need for modelling tools that can correctly consider temporal variations of urban carbon cycle and take the urban specific conditions into account. The main aims of this study are to examine the carbon sequestration potential of two commonly used street tree species (Tilia x vulgaris and Alnus glutinosa) and their soils by taking into account the complexity of urban conditions, and evaluate urban land surface model SUEWS and soil carbon model Yasso15 in simulating carbon sequestration of these street tree plantings at different temporal scales (diurnal, monthly and annual). SUEWS provides the urban microclimate, and photosynthesis and respiration of street trees whereas the soil carbon storage is estimated with Yasso. Both models were run for 2002–2016 and within this period the model performances were evaluated against transpiration estimated from sap flow, soil carbon content and soil moisture measurements from two street tree sites located in Helsinki, Finland. The models were able to capture the variability in urban carbon cycle due to changes in environmental conditions and tree species. SUEWS simulated the stomatal control and transpiration well (RMSE < 0.31 mm h−1) and was able to produce correct soil moisture in the street soil (nRMSE < 0.23). Yasso was able to simulate the strong decline in initial carbon content but later overestimated respiration and thus underestimated carbon stock slightly (MBE > −5.42 kg C m−2). Over the study period, soil respiration dominated the carbon exchange over carbon sequestration, due to the high initial carbon loss from the soil after the street construction. However, the street tree plantings turned into a modest sink of carbon from the atmosphere on annual scale as the tree and soil respiration approximately balanced photosynthesis. The compensation point when street trees plantings turned from annual source to sink was reached faster by Alnus trees after 12 years, while by Tilia trees after 14 years. Overall, the results indicate the importance of soil in urban carbon sequestration estimations.

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Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation

Cited by 25 publications

References 58 publications

Two large-scale forest scenario modelling approaches for reporting CO2 removal: a comparison for the Romanian forests

Two large-scale forest scenario modelling approaches for reporting CO2 removal: a comparison for the Romanian forests

Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses

Carbon sequestration potential of street tree plantings in Helsinki

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