iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient–phytoplankton–zooplankton–detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry–climate interactions.

Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

Simulated Bromoform emission and concentration using the ocean biogeochemistry model MPIOM/HAMOCC forced by 6-hourly NCEP data

Bromoform (CHBr3) is one important precursor of atmospheric reactive bromine species that are involved in ozone depletion in the troposphere and stratosphere. In the open ocean bromoform production is linked to phytoplankton that contains the enzyme bromoperoxidase. Coastal sources of bromoform are higher than open ocean sources. However, open ocean emissions are important because the transfer of tracers into higher altitude in the air, i.e. into the ozone layer, strongly depends on the location of emissions. For example, emissions in the tropics are more rapidly transported into the upper atmosphere than emissions from higher latitudes. Global spatio-temporal features of bromoform emissions are poorly constrained. Here, a global three-dimensional ocean biogeochemistry model (MPIOM-HAMOCC) is used to simulate bromoform cycling in the ocean and emissions into the atmosphere using recently published data of global atmospheric concentrations (Ziska et al., 2013) as upper boundary conditions. Our simulated surface concentrations of CHBr3 match the observations well. Simulated global annual emissions based on monthly mean model output are lower than previous estimates, including the estimate by Ziska et al. (2013), because the gas exchange reverses when less bromoform is produced in non-blooming seasons. This is the case for higher latitudes, i.e. the polar regions and northern North Atlantic. Further model experiments show that future model studies may need to distinguish different bromoform-producing phytoplankton species and reveal that the transport of CHBr3 from the coast considerably alters open ocean bromoform concentrations, in particular in the northern sub-polar and polar regions.

Simulated Methyl iodide emission and concentration using the ocean biogeochemistry model MPIOM/HAMOCC forced by OMIP data

Production pathways of the prominent volatile organic halogen compound methyl iodide (CH3I) are not fully understood. Based on observations, production of CH3I via photochemical degradation of organic material or via phytoplankton production has been proposed. Additional insights could not be gained from correlations between observed biological and environmental variables or from biogeochemical modeling to identify unambiguously the source of methyl iodide. In this study, we aim to address this question of source mechanisms with a three-dimensional global ocean general circulation model including biogeochemistry (MPIOM-HAMOCC (MPIOM - Max Planck Institute Ocean Model HAMOCC - HAMburg Ocean Carbon Cycle model)) by carrying out a series of sensitivity experiments. The simulated fields are compared with a newly available global data set. Simulated distribution patterns and emissions of CH3I differ largely for the two different production pathways. The evaluation of our model results with observations shows that, on the global scale, observed surface concentrations of CH3I can be best explained by the photochemical production pathway. Our results further emphasize that correlations between CH3I and abiotic or biotic factors do not necessarily provide meaningful insights concerning the source of origin. Overall, we find a net global annual CH3I air-sea flux that ranges between 70 and 260 Gg/yr. On the global scale, the ocean acts as a net source of methyl iodide for the atmosphere, though in some regions in boreal winter, fluxes are of the opposite direction (from the atmosphere to the ocean).

Quantifying the roles of ocean circulation and biogeochemistry in governing ocean carbon-13 and atmospheric carbon dioxide at the last glacial maximum

We use a state-of-the-art ocean general circulation and biogeochemistry model to examine the impact of changes in ocean circulation and biogeochemistry in governing the change in ocean carbon-13 and atmospheric CO2 at the last glacial maximum (LGM). We examine 5 different realisations of the ocean's overturning circulation produced by a fully coupled atmosphere-ocean model under LGM forcing and suggested changes in the atmospheric deposition of iron and phytoplankton physiology at the LGM. Measured changes in carbon-13 and carbon-14, as well as a qualitative reconstruction of the change in ocean carbon export are used to evaluate the results. Overall, we find that while a reduction in ocean ventilation at the LGM is necessary to reproduce carbon-13 and carbon-14 observations, this circulation results in a low net sink for atmospheric CO2. In contrast, while biogeochemical processes contribute little to carbon isotopes, we propose that most of the change in atmospheric CO2 was due to such factors. However, the lesser role for circulation means that when all plausible factors are accounted for, most of the necessary CO2 change remains to be explained. This presents a serious challenge to our understanding of the mechanisms behind changes in the global carbon cycle during the geologic past.

Bio-physical interactions and feedbacks in a global climate model

This PhD thesis addresses the topic of large-scale interactions between climate and marine biogeochemistry. To this end, centennial simulations are performed under present and projected future climate conditions with a coupled ocean-atmosphere model containing a complex marine biogeochemistry model. The role of marine biogeochemistry in the climate system is first investigated. Phytoplankton solar radiation absorption in the upper ocean enhances sea surface temperatures and upper ocean stratification. The associated increase in ocean latent heat losses raises atmospheric temperatures and water vapor. Atmospheric circulation is modified at tropical and extratropical latitudes with impacts on precipitation, incoming solar radiation, and ocean circulation which cause upper-ocean heat content to decrease at tropical latitudes and to increase at middle latitudes. Marine biogeochemistry is tightly related to physical climate variability, which may vary in response to internal natural dynamics or to external forcing such as anthropogenic carbon emissions. Wind changes associated with the North Atlantic Oscillation (NAO), the dominant mode of climate variability in the North Atlantic, affect ocean properties by means of momentum, heat, and freshwater fluxes. Changes in upper ocean temperature and mixing impact the spatial structure and seasonality of North Atlantic phytoplankton through light and nutrient limitations. These changes affect the capability of the North Atlantic Ocean of absorbing atmospheric CO2 and of fixing it inside sinking particulate organic matter. Low-frequency NAO phases determine a delayed response of ocean circulation, temperature and salinity, which in turn affects stratification and marine biogeochemistry. In 20th and 21st century simulations natural wind fluctuations in the North Pacific, related to the two dominant modes of atmospheric variability, affect the spatial structure and the magnitude of the phytoplankton spring bloom through changes in upper-ocean temperature and mixing. The impacts of human-induced emissions in the 21st century are generally larger than natural climate fluctuations, with the phytoplankton spring bloom starting one month earlier than in the 20th century and with ~50% lower magnitude. This PhD thesis advances the knowledge of bio-physical interactions within the global climate, highlighting the intrinsic coupling between physical climate and biosphere, and providing a framework on which future studies of Earth System change can be built on.

Regulation of Phytoplankton Carbon to Chlorophyll Ratio By Light, Nutrients and Temperature in the Equatorial Pacific Ocean: A Basin-Scale Model

The complex effects of light, nutrients and temperature lead to a variable carbon to chlorophyll (C:Chl) ratio in phytoplankton cells. Using field data collected in the Equatorial Pacific, we derived a new dynamic model with a non-steady C:Chl ratio as a function of irradiance, nitrate, iron, and temperature. The dynamic model is implemented into a basin-scale ocean circulation-biogeochemistry model and tested in the Equatorial Pacific Ocean. The model reproduces well the general features of phytoplankton dynamics in this region. For instance, the simulated deep chlorophyll maximum (DCM) is much deeper in the western warm pool (similar to 100 m) than in the Eastern Equatorial Pacific (similar to 50 m). The model also shows the ability to reproduce chlorophyll, including not only the zonal, meridional and vertical variations, but also the interannual variability. This modeling study demonstrates that combination of nitrate and iron regulates the spatial and temporal variations in the phytoplankton C:Chl ratio in the Equatorial Pacific. Sensitivity simulations suggest that nitrate is mainly responsible for the high C:Chl ratio in the western warm pool while iron is responsible for the frontal features in the C:Chl ratio between the warm pool and the upwelling region. In addition, iron plays a dominant role in regulating the spatial and temporal variations of the C:Chl ratio in the Central and Eastern Equatorial Pacific. While temperature has a relatively small effect on the C:Chl ratio, light is primarily responsible for the vertical decrease of phytoplankton C:Chl ratio in the euphotic zone.

Developing performance measures of mangrove wetlands using simulation models of hydrology, nutrient biogeochemistry, and community dynamics

The goal of mangrove restoration projects should be to improve community structure and ecosystem function of degraded coastal landscapes. This requires the ability to forecast how mangrove structure and function will respond to prescribed changes in site conditions including hydrology, topography, and geophysical energies. There are global, regional, and local factors that can explain gradients of regulators (e.g., salinity, sulfides), resources (nutrients, light, water), and hydroperiod (frequency, duration of flooding) that collectively account for stressors that result in diverse patterns of mangrove properties across a variety of environmental settings. Simulation models of hydrology, nutrient biogeochemistry, and vegetation dynamics have been developed to forecast patterns in mangroves in the Florida Coastal Everglades. These models provide insight to mangrove response to specific restoration alternatives, testing causal mechanisms of system degradation. We propose that these models can also assist in selecting performance measures for monitoring programs that evaluate project effectiveness. This selection process in turn improves model development and calibration for forecasting mangrove response to restoration alternatives. Hydrologic performance measures include soil regulators, particularly soil salinity, surface topography of mangrove landscape, and hydroperiod, including both the frequency and duration of flooding. Estuarine performance measures should include salinity of the bay, tidal amplitude, and conditions of fresh water discharge (included in the salinity value). The most important performance measures from the mangrove biogeochemistry model should include soil resources (bulk density, total nitrogen, and phosphorus) and soil accretion. Mangrove ecology performance measures should include forest dimension analysis (transects and/or plots), sapling recruitment, leaf area index, and faunal relationships. Estuarine ecology performance measures should include the habitat function of mangroves, which can be evaluated with growth rate of key species, habitat suitability analysis, isotope abundance of indicator species, and bird census. The list of performance measures can be modified according to the model output that is used to define the scientific goals during the restoration planning process that reflect specific goals of the project.

内蒙古草原CH4 通量的DNDC 模型模拟

甲烷（CH4）是增温效应仅次于二氧化碳（CO2）的重要温室气体。内蒙古草原是欧亚温带草原的重要类型，具有典型的生态地域代表性。如何理解该区域CH4 交换的时空格局与环境控制、不同土地利用类型的源汇特征以及CH4 通量对气候变化的响应、对于我们进一步理解全球变化与陆地生态系统关系具有十分重要的意义。本研究以内蒙古草原锡林河流域为对象，首次在国内应用DNDC 生物地球化学模型模拟干草原和河漫滩湿地的CH4 通量，预测CH4 循环对未来气候变化的响应，并对该区域干草原的CH4 吸收进行了区域模拟估算。结果表明： 1.在模型中添加植被生长节律与土壤CH4 吸收的关系函数后，DNDC 模型能够准确地模拟锡林河流域干草原CH4 吸收的大小及其年变化。土壤温度、土壤水分和植被生长状况是影响干草原大气CH4 吸收的主要因素。 2.水位，土壤温度，质地和植被生长节律是控制河漫滩湿地CH4 通量的主要因子。根据有限水位测定值估算模拟周期内全部水位数据的方法能够应用于模拟水位相对比较稳定区域的未知时期水位。经过该修正的DNDC 模型能够较为准确的捕获锡林河流域河边湿地的CH4 排放通量的大小及年变化。 3.干草原和湿地年CH4 通量对温度变化敏感，而对降水量变化不敏感，其中湿地比干草原对温度变化的响应更加敏感。 4.温度升高可显著地促进干草原和湿地的日CH4 吸收和排放能力，其CH4 通量的增加均表现出明显的季节性差异。干草原日CH4 通量对降水量增加20% 的响应并不显著，而河漫滩湿地的响应虽显著，变幅却很小且增减程度不同。 5.与2005 年相比，2050 年干草原河漫滩湿地的CH4 吸收和排放量将分别增加10%和77%。锡林河流域CH4 通量对未来气候变化产生正反馈作用，并且湿地CH4 排放对未来气候变化的响应大于干草原CH4 吸收的响应。未来气候变化将增加锡林河流域CH4 源强度。 6. 锡林河流域干草原CH4 吸收量达2.42Gg C•yr-1。干草原CH4 吸收量的空间异质性较大，各栅格单元（0.01 ×0.01 度）的CH4 吸收量变化为0-404.6 kg C，其中大部分区域CH4 吸收量变化在150-250 kg C•yr-1 之间。草甸草原的大气CH4 吸收能力显著高于典型草原。干草原CH4 吸收率平均为2.59 kg C• ha-1 •yr-1。干草原CH4 吸收量的空间异质性是土壤有机质含量、土壤质地、土壤温度湿度，植被类型等因素共同作用的结果，与单一变量的关系并不明显。

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The ERSEM model is one of the most established ecosystem models for the lower trophic levels of the marine food-web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North-Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic part of the marine ecosystem, including the microbial food-web, the carbonate system and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case-studies of mesocosm type simulations, water column implementations and a brief example of a full-scale application for the North-West European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The European Regional Seas Ecosystem Model (ERSEM) is one of the most established ecosystem models for the lower trophic levels of the marine food web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic parts of the marine ecosystem, including the microbial food web, the carbonate system, and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case studies of mesocosm-type simulations, water column implementations, and a brief example of a full-scale application for the north-western European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling

In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.

Sensitivity of an Earth system climate model to idealized radiative forcing

We diagnose forcing and climate feedbacks in benchmark sensitivity experiments with the new Met Office Hadley Centre Earth system climate model HadGEM2-ES. To identify the impact of newly-included biogeophysical and chemical processes, results are compared to a parallel set of experiments performed with these processes switched off, and different couplings with the biogeochemistry. In abrupt carbon dioxide quadrupling experiments we find that the inclusion of these processes does not alter the global climate sensitivity of the model. However, when the change in carbon dioxide is uncoupled from the vegetation, or when the model is forced with a non-carbon dioxide forcing – an increase in solar constant – new feedbacks emerge that make the climate system less sensitive to external perturbations. We identify a strong negative dust-vegetation feedback on climate change that is small in standard carbon dioxide sensitivity experiments due to the physiological/fertilization effects of carbon dioxide on plants in this model.