Global modelling of soil carbonyl sulfide exchange

Abstract. Carbonyl sulfide (COS) is an atmospheric trace gas of interest for C cycle research because COS uptake by continental vegetation is strongly related to terrestrial gross primary productivity (GPP), the largest and most uncertain flux in atmospheric CO2 budgets. However, to use atmospheric COS budgets as an additional tracer of GPP, an accurate quantification of COS exchange by soils is also needed. At present, the atmospheric COS budget is unbalanced globally, with total COS flux estimates from oxic and anoxic soils that vary between −409 and −104 GgS yr−1. This uncertainty hampers the use of atmospheric COS concentrations to constrain GPP estimates through atmospheric transport inversions. In this study we implemented a mechanistic soil COS model in the ORCHIDEE land surface model to simulate COS fluxes in oxic and anoxic soils. Evaluation of the model against flux measurements at 7 sites yields a mean root mean square deviation of 1.6 pmol m−2 s−1, instead of 2 pmol m−2 s−1 when using a previous empirical approach that links soil COS uptake to soil heterotrophic respiration. The new model predicts that, globally and over the 2009–2016 period, oxic soils act as a net uptake of −126 GgS yr−1, and anoxic soils are a source of +96 GgS yr−1, leading to a global net soil sink of only −30 GgS yr−1, i.e., much smaller than previous estimates. The small magnitude of the soil fluxes suggests that the error in the COS budget is dominated by the much larger fluxes from plants, oceans, and industrial activities. The predicted spatial distribution of soil COS fluxes, with large emissions in the tropics from oxic (up to 68.2 pmol COS m−2 s−1) and anoxic (up to 36.8 pmol COS m−2 s−1) soils, marginally improves the latitudinal gradient of atmospheric COS concentrations, after transport by the LMDZ atmospheric transport model. The impact of different soil COS flux representations on the latitudinal gradient of the atmospheric COS concentrations is strongest in the northern hemisphere. We also implemented spatio-temporal variations of near-ground atmospheric COS concentrations in the modelling of biospheric COS fluxes, which helped reduce the imbalance of the atmospheric COS budget by lowering COS uptake by soils and vegetation globally (−10 % for soil, and −8 % for vegetation with a revised mean estimate of −576 GgS y−r1 over 2009–2016). Sensitivity analyses highlighted the different parameters to which each soil COS flux model is the most responsive, selected in a parameter optimization framework. Having both vegetation and soil COS fluxes modelled within ORCHIDEE opens the way for using observed ecosystem COS fluxes and larger scale atmospheric COS mixing ratios to improve the simulated GPP, through data assimilation techniques.

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A description of the COS budget inferred by inverse modelling

10.5194/egusphere-egu21-15957 ◽

2021 ◽

Author(s):

Marine Remaud ◽

Camille Abadie ◽

Sauveur Belviso ◽

Antoine Berchet ◽

Frédéric Chevallier ◽

...

Keyword(s):

Land Surface ◽

Transport Model ◽

Atmospheric Transport ◽

Land Surface Model ◽

Diffusion Path ◽

Global Scale ◽

Striking Similarity ◽

Surface Model ◽

Terrestrial Vegetation ◽

The Tropics

Carbonyle Sulphide, a trace gas exhibiting a striking similarity with CO2 in the biochemical diffusion path of leaves, has been recognized to be a promising surrogate of CO2 for estimating carbon storage in the terrestrial vegetation. Based on the similarity between COS and CO2, an empirical linear model relating both gas concentrations provides constraints on the estimation of the Gross Primary Productivity (GPP), the amount of carbon dioxide that is absorbed by ecosystems. However, large uncertainties on the other components of its atmospheric budget prevent us from directly relating the atmospheric COS measurements to the the GPP at global scale. The largest uncertainty arises from the closure of its atmospheric budget, with a source component missing. We explore here the benefit of assimilating both COS and CO2 measurements into the LMDz atmospheric transport model to gain insight on the COS budget. We develop an analytic inverse system which optimized the biospheric fluxes within the 14 Plant functional Type (PFTs) as defined in the ORCHIDEE land surface model. The vegetation uptake of COS is parameterized as a linear function of GPP and of the leaf relative uptake (LRU), which is the ratio of COS to CO2 deposition velocities in plants. A possible scenario leads to a global biospheric sink between 800-900 GgS/y, with a higher GPP in the high latitudes and higher total oceanic emissions between 400 and 600 GgS/y over the tropics. The COS inter-hemispheric gradient is in better agreement with HIPPO independent aircraft measurements. The comparison against NOAA COS airborne profiles and Solar Induced Fluorescence shed light on a too strong GPP in spring in ORCHIDEE in northern America,&#160; leaving room for improvements. We also show that uncertainty in the location of hot spots in the prior anthropogenic inventory limits the use of atmospheric COS measurements in inverse modeling.

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Calibration of a multi-physics ensemble for greenhouse gas atmospheric transport model uncertainty estimation

10.5194/acp-2018-1117 ◽

2018 ◽

Author(s):

Liza I. Díaz-Isaac ◽

Thomas Lauvaux ◽

Marc Bocquet ◽

Kenneth J. Davis

Keyword(s):

Boundary Conditions ◽

Land Surface ◽

Transport Model ◽

Atmospheric Transport ◽

Wrf Model ◽

Meteorological Variables ◽

Multiple Model ◽

Optimal Ensemble ◽

Physics Ensemble ◽

The Impact

Abstract. Atmospheric inversions have been used to assess biosphere-atmosphere CO2 surface exchanges at various scales, but variability among inverse flux estimates remains significant, especially at continental scales. Atmospheric transport errors are one of the main contributors to this variability. To characterize transport errors and their spatio-temporal structures, we present an objective method to generate a calibrated ensemble adjusted with meteorological measurements collected across a region, here the US upper Midwest in midsummer. Using multiple model configurations of the Weather Research and Forecasting (WRF) model, we show that a reduced number of simulations (less than 10 members) reproduces the transport error characteristics of a 45-member ensemble while minimizing the size of the ensemble. The large ensemble of 45-members was constructed using different physics parameterization (i.e., land surface models (LSMs), planetary boundary layer (PBL) schemes, cumulus parameterizations and microphysics parameterizations) and meteorological initial/boundary conditions. All the different models were coupled to CO2 fluxes and lateral boundary conditions from CarbonTracker to simulate CO2 mole fractions. Meteorological variables critical to inverse flux estimates, PBL wind speed, PBL wind direction and PBL height, are used to calibrate our ensemble over the region. Two calibration techniques (i.e., simulated annealing and a genetic algorithm) are used for the selection of the optimal ensemble using the flatness of the rank histograms as the main criterion. We also choose model configurations that minimize the systematic errors (i.e. monthly biases) in the ensemble. We evaluate the impact of transport errors on atmospheric CO2 mole fraction to represent up to 40 % of the model-data mismatch (fraction of the total variance). We conclude that a carefully-chosen subset of the physics ensemble can represent the errors in the full ensemble, and that transport ensembles calibrated with relevant meteorological variables provide a promising path forward for improving the treatment of transport errors in atmospheric inverse flux estimates.

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Reconciling the carbon balance of northern Scandinavia through the integration of observations and modelling

10.5194/egusphere-egu21-1816 ◽

2021 ◽

Author(s):

Anusha Sathyanadh ◽

Guillaume Monteil ◽

Marko Scholze ◽

Anne Klosterhalfen ◽

Hjalmar Laudon ◽

...

Keyword(s):

Transport Model ◽

Atmospheric Transport ◽

Observation System ◽

Northern Sweden ◽

C Cycle ◽

Flux Measurements ◽

Vegetation Models ◽

The Impact ◽

Atmospheric Transport Model

The boreal biome is an important component of the global carbon (C) cycle. However, current estimates of its sink-source strength at regional scales and its responses to climate change rely primarily on models and thus remain uncertain. We investigated the C balance over a north Scandinavian boreal region by integrating observations of land-atmosphere fluxes and atmospheric CO2 concentrations at landscape to regional scales. We also placed a special focus to understand the impact of 2018 drought on the region. Flux estimates can be obtained through various techniques such as in-situ flux measurements, eddy covariance (EC) observations, vegetation modelling and inverse modelling of CO2 observations. These techniques are however typically relevant at very different spatial scales ranging from plot scale to country-scale, which makes it difficult to compare them. The -Svartberget site (SVB), an established ICOS (Integrated Carbon Observation System) station in Northern Sweden offers a unique range of observations, from in-situ flux measurements to EC fluxes and tall-tower concentration measurements. Here we used several vegetation models and an atmospheric transport model to connect the different scales for the period 2016-2018. The land-atmosphere carbon fluxes are from four different vegetation models (VPRM, LPJ-GUESS, ORCHIDEE and SiBCASA) and are used in the LUMIA/FLEXPART atmospheric transport model (Lund University Modular Inversion Algorithm) to generate estimates of atmospheric CO2 concentration. We found that the northern Sweden region remained as a C sink for the study period with models differed in sink strength. It was also noticed that the site SVB can be taken as a representative for the northern Sweden region. All models indicate similar but small reductions in the net CO2 uptake for the drought year 2018 in northern Sweden except LPJ-GUESS that reveal limitations which call for further model improvement. Our work highlights the interest of using combined ecosystem,-atmosphere ICOS sites such as SVB in the Scandinavian region and shows that it is a promising way forward to monitor CO2 fluxes at the regional scale.

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Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-5695-2019 ◽

2019 ◽

Vol 19 (8) ◽

pp. 5695-5718 ◽

Cited By ~ 2

Author(s):

Liza I. Díaz-Isaac ◽

Thomas Lauvaux ◽

Marc Bocquet ◽

Kenneth J. Davis

Keyword(s):

Boundary Conditions ◽

Land Surface ◽

Transport Model ◽

Atmospheric Transport ◽

Optimization Techniques ◽

Meteorological Variables ◽

Multiple Model ◽

Optimal Ensemble ◽

Physics Ensemble ◽

The Impact

Abstract. Atmospheric inversions have been used to assess biosphere–atmosphere CO2 surface exchanges at various scales, but variability among inverse flux estimates remains significant, especially at continental scales. Atmospheric transport errors are one of the main contributors to this variability. To characterize transport errors and their spatiotemporal structures, we present an objective method to generate a calibrated ensemble adjusted with meteorological measurements collected across a region, here the upper US Midwest in midsummer. Using multiple model configurations of the Weather Research and Forecasting (WRF) model, we show that a reduced number of simulations (less than 10 members) reproduces the transport error characteristics of a 45-member ensemble while minimizing the size of the ensemble. The large ensemble of 45 members was constructed using different physics parameterization (i.e., land surface models (LSMs), planetary boundary layer (PBL) schemes, cumulus parameterizations and microphysics parameterizations) and meteorological initial/boundary conditions. All the different models were coupled to CO2 fluxes and lateral boundary conditions from CarbonTracker to simulate CO2 mole fractions. Observed meteorological variables critical to inverse flux estimates, PBL wind speed, PBL wind direction and PBL height are used to calibrate our ensemble over the region. Two optimization techniques (i.e., simulated annealing and a genetic algorithm) are used for the selection of the optimal ensemble using the flatness of the rank histograms as the main criterion. We also choose model configurations that minimize the systematic errors (i.e., monthly biases) in the ensemble. We evaluate the impact of transport errors on atmospheric CO2 mole fraction to represent up to 40 % of the model–data mismatch (fraction of the total variance). We conclude that a carefully chosen subset of the physics ensemble can represent the uncertainties in the full ensemble, and that transport ensembles calibrated with relevant meteorological variables provide a promising path forward for improving the treatment of transport uncertainties in atmospheric inverse flux estimates.

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The impact of MM5 and WRF meteorology over complex terrain on CHIMERE model calculations

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-2319-2009 ◽

2009 ◽

Vol 9 (1) ◽

pp. 2319-2380 ◽

Cited By ~ 6

Author(s):

A. de Meij ◽

A. Gzella ◽

P. Thunis ◽

C. Cuvelier ◽

B. Bessagnet ◽

...

Keyword(s):

Land Surface ◽

Transport Model ◽

Land Surface Model ◽

Heat Fluxes ◽

Surface Model ◽

Microphysics Scheme ◽

Model Calculations ◽

Po Valley ◽

The Difference ◽

The Impact

Abstract. The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models is similar, however some small differences are still noticeable. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PM10 concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) for the 5-layer soil temperature model, the calculated monthly mean PM10 concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMRE/WRF. The reason for this is that daytime NO2 concentrations are a higher than the observations and nighttime NO concentrations (titration effect) are underestimated.

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Better constraining the CO2 plant uptake at global scale: joint assimilation of COS and CO2 atmospheric measurements into a transport model.

10.5194/egusphere-egu2020-11474 ◽

2020 ◽

Author(s):

Marine Remaud ◽

Frédéric Chevallier ◽

Philippe Peylin ◽

Antoine Berchet ◽

Fabienne Maignan

Keyword(s):

Plant Uptake ◽

Land Surface ◽

Transport Model ◽

Atmospheric Transport ◽

Gross Primary Production ◽

Surface Fluxes ◽

Surface Model ◽

Atmospheric Measurements ◽

Inverse Systems ◽

Atmospheric Transport Model

Inverse systems that assimilate atmospheric carbon dioxide measurements (CO2) into a global atmospheric transport model, are commonly used together with anthropogenic emission inventories to infer net biospheric surface fluxes. However, when assimilating CO2 measurements only, the respiration fluxes cannot be disentangled from the gross primary production (GPP) fluxes, leaving few possibilities to interpret the inferred fluxes from a mechanistic point of view. Measurements of carbonyl sulfide (COS) may help to fill this gap: COS has similar diffusion pathway inside leaves&#160;as CO2 but is not re-emitted into the atmosphere by the plant respiration. We explore here the benefit of assimilating both COS and CO2 measurements into the LMDz atmospheric transport model to constrain GPP and respiration fluxes separately. To this end, we develop an analytic inverse system based on the 14 Plant functional Type (PFTs) as defined in the ORCHIDEE land surface model. The vegetation uptake of COS is parameterized as a linear function of GPP and of the leaf relative uptake (LRU), which is the ratio of COS to CO2 deposition velocities in plants. A new parameterization of the atmosphere soil exchanges is also included. We use the system to optimize GPP and respiration fluxes separately at the seasonal scale over the globe. The results lead to a balanced COS global budget and a seasonality of the COS fluxes in better agreement with observations. We find a large sensitivity of the partition between the ocean emissions and the COS plant uptake to the LRU parameterizations.

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The impact of MM5 and WRF meteorology over complex terrain on CHIMERE model calculations

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-6611-2009 ◽

2009 ◽

Vol 9 (17) ◽

pp. 6611-6632 ◽

Cited By ~ 41

Author(s):

A. de Meij ◽

A. Gzella ◽

C. Cuvelier ◽

P. Thunis ◽

B. Bessagnet ◽

...

Keyword(s):

Land Surface ◽

Transport Model ◽

Land Surface Model ◽

Heat Fluxes ◽

Surface Model ◽

Microphysics Scheme ◽

Model Calculations ◽

Temporal Correlations ◽

The Difference ◽

The Impact

Abstract. The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models in calculating surface parameters is similar, however differences are still observed. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PMv concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) in our WRF pre-processing for the 5-layer soil temperature model, calculated monthly mean PMv concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMERE/WRF. High temporal correlations are found between modeled and observed O3 concentrations.

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The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat

Atmosphere ◽

10.3390/atmos12040467 ◽

2021 ◽

Vol 12 (4) ◽

pp. 467

Author(s):

Rocío Baró ◽

Christian Maurer ◽

Jerome Brioude ◽

Delia Arnold ◽

Marcus Hirtl

Keyword(s):

Air Quality ◽

Nuclear Power ◽

Transport Model ◽

Atmospheric Transport ◽

Point Of View ◽

Plume Dispersion ◽

Exclusion Zone ◽

Fire Plume ◽

Mean Values ◽

The Impact

This paper demonstrates the environmental impacts of the wildfires occurring at the beginning of April 2020 in and around the highly contaminated Chernobyl Exclusion Zone (CEZ). Due to the critical fire location, concerns arose about secondary radioactive contamination potentially spreading over Europe. The impact of the fire was assessed through the evaluation of fire plume dispersion and re-suspension of the radionuclide Cs-137, whereas, to assess the smoke plume effect, a WRF-Chem simulation was performed and compared to Tropospheric Monitoring Instrument (TROPOMI) satellite columns. The results show agreement of the simulated black carbon and carbon monoxide plumes with the plumes as observed by TROPOMI, where pollutants were also transported to Belarus. From an air quality and health perspective, the wildfires caused extremely bad air quality over Kiev, where the WRF-Chem model simulated mean values of PM2.5 up to 300 µg/m3 (during the first fire outbreak) over CEZ. The re-suspension of Cs-137 was assessed by a Bayesian inverse modelling approach using FLEXPART as the atmospheric transport model and Ukraine observations, yielding a total release of 600 ± 200 GBq. The increase in both smoke and Cs-137 emissions was only well correlated on the 9 April, likely related to a shift of the focus area of the fires. From a radiological point of view even the highest Cs-137 values (average measured or modelled air concentrations and modelled deposition) at the measurement site closest to the Chernobyl Nuclear Power Plant, i.e., Kiev, posed no health risk.

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Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

Journal of Hydrometeorology ◽

10.1175/jhm554.1 ◽

2007 ◽

Vol 8 (1) ◽

pp. 68-87 ◽

Cited By ~ 71

Author(s):

Margaret A. LeMone ◽

Fei Chen ◽

Joseph G. Alfieri ◽

Mukul Tewari ◽

Bart Geerts ◽

...

Keyword(s):

Soil Moisture ◽

Latent Heat ◽

Land Surface ◽

Field Experiments ◽

Time Of Day ◽

Horizontal Distribution ◽

Heat Fluxes ◽

Surface Model ◽

Green Vegetation ◽

The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

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Modelling nitrogen transport across compartments over northern Europe

10.5194/egusphere-egu21-8166 ◽

2021 ◽

Author(s):

Stefan Hagemann ◽

Ute Daewel ◽

Volker Matthias ◽

Tobias Stacke

Keyword(s):

Baltic Sea ◽

Land Surface ◽

Climate Model ◽

Transport Model ◽

Atmospheric Transport ◽

Regional Climate ◽

Marine Ecosystem ◽

Coupled System ◽

Nutrient Concentrations ◽

Nutrient Loads

River discharge and the associated nutrient loads are important factors that influence the functioning of the marine ecosystem. Lateral inflows from land carrying fresh, nutrient-rich water determine coastal physical conditions and nutrient concentration and, hence, dominantly influence primary production in the system. Since this forms the basis of the trophic food web, riverine nutrient concentrations impact the variability of the whole coastal ecosystem. This process becomes even more relevant in systems like the Baltic Sea, which is almost decoupled from the open ocean and land-borne nutrients play a major role for ecosystem productivity on seasonal up to decadal time scales.&#160;In order to represent the effects of climate or land use change on nutrient availability, a coupled system approach is required to simulate the transport of nutrients across Earth system compartments. This comprises their transport within the atmosphere, the deposition and human application at the surface, the lateral transport over the land surface into the ocean and their dynamics and transformation in the marine ecosystem. In our study, we combine these processes in a modelling chain within the GCOAST (Geesthacht Coupled cOAstal model SysTem) framework for the northern European region. This modelling chain comprises:&#160;<ul><li>Simulation of emissions, atmospheric transport and deposition with the chemistry transport model CMAQ at 36 km grid resolution using atmospheric forcing from the coastDat3 data that have been generated with the regional climate model COSMO-CLM over Europe at 0.11&#176; resolution using ERA-Interim re-analyses as boundary conditions</li> <li>Simulation of inert processes at the land surface with the global hydrology model HydroPy (former MPI-HM), i.e. considering total nitrogen without any chemical reactions</li> <li>Riverine transport with the Hydrological Discharge (HD) model at 0.0833&#176; spatial resolution</li> <li>Simulation of the North Sea and Baltic Sea ecosystems with 3D coupled physical-biogeochemical NPZD-model ECOSMO II at about 10 km resolution</li> </ul>&#160;We will present first results and their validation from this exercise.&#160;

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