Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

Biogeochemical models, capturing the major feedbacks of the pelagic ecosystem of the world ocean, are today often embedded into Earth system models which are increasingly used for decision making regarding climate policies. These models contain poorly constrained parameters (e.g., maximum phytoplankton growth rate), which are typically adjusted until the model shows reasonable behavior. Systematic approaches determine these parameters by minimizing the misfit between the model and observational data. In most common model approaches, however, the underlying functions mimicking the biogeochemical processes are nonlinear and non-convex. Thus, systematic optimization algorithms are likely to get trapped in local minima and might lead to non-optimal results. To judge the quality of an obtained parameter estimate, we propose determining a preferably large lower bound for the global optimum that is relatively easy to obtain and that will help to assess the quality of an optimum, generated by an optimization algorithm. Due to the unavoidable noise component in all observations, such a lower bound is typically larger than zero. We suggest deriving such lower bounds based on typical properties of biogeochemical models (e.g., a limited number of extremes and a bounded time derivative). We illustrate the applicability of the method with two real-world examples. The first example uses real-world observations of the Baltic Sea in a box model setup. The second example considers a three-dimensional coupled ocean circulation model in combination with satellite chlorophyll a

Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing

Anthropogenic emissions of greenhouse gases such as CO2 and N2O impinge on the Earth system, which in turn modulates atmospheric greenhouse gas concentrations. The underlying feedback mechanisms are complex and, at times, counterintuitive. So-called Earth system models have recently matured to standard tools tailored to assess these feedback mechanisms in a warming world. Applications for these models range from being targeted at basic process understanding to the assessment of geo-engineering options. A problem endemic to all these applications is the need to estimate poorly known model parameters, specifically for the biogeochemical component, based on observational data (e.g., nutrient fields). In the present study, we illustrate with an Earth system model that through such an approach biases and other model deficiencies in the physical ocean circulation model component can reciprocally compensate for biases in the pelagic biogeochemical model component (and vice versa). We present two model configurations that share a remarkably similar steady state (based on ad hoc measures) when driven by historical boundary conditions, even though they feature substantially different configurations (parameter sets) of ocean mixing and biogeochemical cycling. When projected into the future the similarity between the model responses breaks. Metrics such as changes in total oceanic carbon content and suboxic volume diverge between the model configurations as the Earth warms. Our results reiterate that advancing the understanding of oceanic mixing processes will reduce the uncertainty of future projections of oceanic biogeochemical cycles. Related to the latter, we suggest that an advanced understanding of oceanic biogeochemical cycles can be used for advancements in ocean circulation modules.</p

Mapping manifestations of parametric uncertainty in projected pelagic oxygen concentrations back to contemporary local model fidelity

Pelagic biogeochemical models (BGCMs) have matured into generic components of Earth System Models. BGCMs mimic the effects of marine biota on oceanic nutrient, carbon and oxygen cycles. They rely on parameters that are adjusted to match observed conditions. Such parameters are key to determining the models’ responses to changing environmental conditions. However, many of these parameters are difficult to constrain and constitute a major source of uncertainty in BGCM projections. Here we use, for the first time, variance-based sensitivity analyses to map BGCM parameter uncertainties onto their respective local manifestation in model entities (such as oceanic oxygen concentrations) for both contemporary climate and climate projections. The mapping effectively relates local uncertainties of projections to the uncertainty of specific parameters. Further, it identifies contemporary benchmarking regions, where the uncertainties of specific parameters manifest themselves, thereby facilitating an effective parameter refinement and a reduction of the associated uncertainty. Our results demonstrate that the parameters that are linked to uncertainties in projections may differ from those parameters that facilitate model conformity with present-day observations. In summary, we present a practical approach to the general question of where present-day model fidelity may be indicative for reliable projections

Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem

Numerical Earth System Models are generic tools used to extrapolate present climate conditions into a warming future and to explore geoengineering options. Most of the current-generation models feature a simple pelagic biogeochemical model component that is embedded into a three-dimensional ocean general circulation model. The dynamics of these biogeochemical model components is essentially controlled by so-called model parameters most of which are poorly known. Here we explore the feasibility to estimate these parameters in a full-fledged three-dimensional Earth System Model by minimizing the misfit to noisy observations. The focus is on parameter identifiability. Based on earlier studies, we illustrate problems in determining a unique estimate of those parameters that prescribe the limiting effect of nutrient- and light-depleted conditions on carbon assimilation by autotrophic phytoplankton. Our results showcase that for typical models and evaluation metrics no meaningful “best” unique parameter set exists. We find very different parameter sets which are, on the one hand, equally consistent with our (synthetic) historical observations while, on the other hand, they propose strikingly differing projections into a warming climate

Mediterranean cyclones and windstorms in a changing climate

Changes in the frequency and intensity of cyclones and associated windstorms affecting the Medi-terranean region simulated under enhanced Greenhouse Gas forcing conditions are investigated. The analysis is based on 7 climate model integrations performed with two coupled global models (ECHAM5 MPIOM and INGV CMCC), comparing the end of the twentieth century and at least the first half of the twenty-first century. As one of the models has a considerably enhanced resolution of the atmosphere and the ocean, it is also investigated whether the climate change signals are influenced by the model resolution. While the higher resolved simulation is closer to reanalysis climatology, both in terms of cyclones and windstorm distributions, there is no evidence for an influence of the resolution on the sign of the climate change signal. All model simulations show a reduction in the total number of cyclones crossing the Mediterranean region under climate change conditions. Exceptions are Morocco and the Levant region, where the models predict an increase in the number of cyclones. The reduction is especially strong for intense cyclones in terms of their Laplacian of pressure. The influence of the simulated positive shift in the NAO Index on the cyclone decrease is restricted to the Western Mediterranean region, where it explains 10–50 % of the simulated trend, depending on the individual simulation. With respect to windstorms, decreases are simulated over most of the Mediterranean basin. This overall reduction is due to a decrease in the number of events associated with local cyclones, while the number of events associated with cyclones outside of the Mediterranean region slightly increases. These systems are, however, less intense in terms of their integrated severity over the Mediterranean area, as they mostly affect the fringes of the region. In spite of the general reduction in total numbers, several cyclones and windstorms of intensity unknown under current climate conditions are identified for the scenario simulations. For these events, no common trend exists in the individual simulations. Thus, they may rather be attributed to long-term (e.g. decadal) variability than to the Greenhouse Gas forcing. Nevertheless, the result indicates that high-impact weather systems will remain an important risk in the Mediterranean Basin

The Solar Orbiter Science Activity Plan: translating solar and heliospheric physics questions into action

Solar Orbiter is the first space mission observing the solar plasma both in situ and remotely, from a close distance, in and out of the ecliptic. The ultimate goal is to understand how the Sun produces and controls the heliosphere, filling the Solar System and driving the planetary environments. With six remote-sensing and four in-situ instrument suites, the coordination and planning of the operations are essential to address the following four top-level science questions: (1) What drives the solar wind and where does the coronal magnetic field originate?; (2) How do solar transients drive heliospheric variability?; (3) How do solar eruptions produce energetic particle radiation that fills the heliosphere?; (4) How does the solar dynamo work and drive connections between the Sun and the heliosphere? Maximising the mission’s science return requires considering the characteristics of each orbit, including the relative position of the spacecraft to Earth (affecting downlink rates), trajectory events (such as gravitational assist manoeuvres), and the phase of the solar activity cycle. Furthermore, since each orbit’s science telemetry will be downloaded over the course of the following orbit, science operations must be planned at mission level, rather than at the level of individual orbits. It is important to explore the way in which those science questions are translated into an actual plan of observations that fits into the mission, thus ensuring that no opportunities are missed. First, the overarching goals are broken down into specific, answerable questions along with the required observations and the so-called Science Activity Plan (SAP) is developed to achieve this. The SAP groups objectives that require similar observations into Solar Orbiter Observing Plans, resulting in a strategic, top-level view of the optimal opportunities for science observations during the mission lifetime. This allows for all four mission goals to be addressed. In this paper, we introduce Solar Orbiter’s SAP through a series of examples and the strategy being followed

Sea ice in the Baltic Sea &ndash; revisiting BASIS ice, a historical data set covering the period 1960/1961&ndash;1978/1979

The Baltic Sea is a seasonally ice-covered, marginal sea in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by sea ice, the local weather services have been monitoring sea ice conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for Baltic Sea Ice and Sea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project of the Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical ice models and provide easy-to-access unique historical reference material for sea ice in the Baltic Sea. In addition we provide statistics showcasing the data quality. The website http://www.baltic-ocean.org hosts the post-processed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science, PANGAEA (doi:10.1594/PANGAEA.832353)

Simulating natural carbon sequestration in the Southern Ocean: on uncertainties associated with eddy parameterizations and iron deposition

The Southern Ocean is a major sink for anthropogenic carbon. Yet, there is no quantitative consensus about how this sink will change when surface winds increase (as they are anticipated to do). Among the tools employed to quantify carbon uptake are global coupled ocean-circulation–biogeochemical models. Because of computational limitations these models still fail to resolve potentially important spatial scales. Instead, processes on these scales are parameterized. There is concern that deficiencies in these so-called eddy parameterizations might imprint incorrect sensitivities of projected oceanic carbon uptake. Here, we compare natural carbon uptake in the Southern Ocean simulated with contemporary eddy parameterizations. We find that very differing parameterizations yield surprisingly similar oceanic carbon in response to strengthening winds. In contrast, we find (in an additional simulation) that the carbon uptake does differ substantially when the supply of bioavailable iron is altered within its envelope of uncertainty. We conclude that a more comprehensive understanding of bioavailable iron dynamics will substantially reduce the uncertainty of model-based projections of oceanic carbon uptake