A multimodel comparison of the performance of land surface parameterization schemes increases understanding of the land-atmosphere feedback mechanisms over West Africa.

Although the terms 'health' and 'healthy' are often applied to marine ecosystems and communicate information about holistic condition (e.g. as required by the Ecosystem Approach), their meaning is unclear. Ecosystems have been understood in various ways, from non-interacting populations of species to complex integrated systems. Health has been seen as a metaphor, an indicator that aggregates over system components, or a non-localized emergent system property. After a review, we define good ecosystem health as: 'the condition of a system that is self-maintaining, vigorous, resilient to externally imposed pressures, and able to sustain services to humans. It contains healthy organisms and populations, and adequate functional diversity and functional response diversity. All expected trophic levels are present and well interconnected, and there is good spatial connectivity amongst subsystems.' We equate this condition with good ecological or environmental status, e.g. as referred to by recent EU Directives. Resilience is central to health, but difficult to measure directly. Ecosystems under anthropogenic pressure are at risk of losing resilience, and thus of suffering regime shifts and loss of services. For monitoring whole ecosystems, we propose an approach based on 'trajectories in ecosystem state space', illustrated with time-series from the northwestern North Sea. Change is visualized as Euclidian distance from an arbitrary reference state. Variability about a trend in distance is used as a proxy for inverse resilience. We identify the need for institutional support for long time-series to underpin this approach, and for research to establish state space co-ordinates for systems in good health.

[1] The objective of this paper is to investigate if the assimilation of ocean color data into a complex marine ecosystem model can improve the hindcast of key biogeochemical variables in shelf seas. A localized Ensemble Kalman filter was used to make a yearlong assimilation of weekly satellite chlorophyll data into a three-dimensional ecosystem model of the western English Channel. The skill of assimilation was evaluated with respect to non assimilated in situ data using twelve time series of biogeochemical observations collected weekly at the monitoring station L4. It was found that the assimilation scheme reduced the root mean square error and increased the correlation with the spatial distributions of the assimilated chlorophyll data, with respect to the reference run. More significantly, the skill metrics for non assimilated variables indicate that the hindcast of the mean data values at L4 was improved; however improvements in the short term forecast were not discernable. On the basis of our application, we provide general recommendations for the successful application of ocean color assimilation to hindcast key biogeochemical variables in shelf seas.

This paper presents the first decadal reanalysis simulation of the biogeochemistry of the North West European shelf, along with a full evaluation of its skill, confidence, and value. An error-characterized satellite product for chlorophyll was assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The results showed that the reanalysis improved the model simulation of assimilated chlorophyll in 60% of the study region. Model validation metrics showed that the reanalysis had skill in matching a large data set of in situ observations for 10 ecosystem variables. Spearman rank correlations were significant and higher than 0.7 for physical-chemical variables (temperature, salinity, and oxygen), $0.6 for chlorophyll and nutrients (phosphate, nitrate, and silicate), and significant, though lower in value, for partial pressure of dissolved carbon dioxide ($0.4). The reanalysis captured the magnitude of pH and ammonia observations, but not their variability. The value of the reanalysis for assessing environmental status and variability has been exemplified in two case studies. The first shows that between 325,000 and 365,000 km 2 of shelf bottom waters were vulnerable to oxygen deficiency potentially threatening bottom fishes and benthos. The second application confirmed that the shelf is a net sink of atmospheric carbon dioxide, but the total amount of uptake varies between 36 and 46 Tg C yr 21 at a 90% confidence level. These results indicate that the reanalysis output data set can inform the management of the North West European shelf ecosystem, in relation to eutrophication, fishery, and variability of the carbon cycle.