Validating and improving the uncertainty assumptions for the assimilation of ocean‐colour‐derived chlorophyll a into a marine biogeochemistry model of the Northwest European Shelf Seas

Abstract

The correct specification of all sources of uncertainty is critical to the success of data assimilation (DA) in improving the realism and accuracy of forecasts and reanalyses. This work focuses on improving the uncertainty assumptions made during the assimilation of ocean-colour-derived chlorophyll a into an operational marine coupled physical-biogeochemical DA system, which produces daily biogeochemistry forecasts on the Northwest European Shelf Seas. Analysis of the observation-model misfits shows significant biases in chlorophyll a, which vary strongly with season. The behaviour of these misfits agrees well with previous studies and can be attributed to systematic errors within the coupled model. Diagnostic metrics, used frequently within numerical weather prediction, are applied to separate out the random component of the observation and model errors, allowing for the derivation of new error covariance matrices. These new error covariance matrices are then modified to account for the biases in the model that cannot be treated explicitly within the operational DA system. This has the effect of inflating both the error variances and the correlation length-scales. Experiments show that the new error covariances can result in significant improvements in the accuracy of the analysis and forecast. In particular, the new error covariance matrices reduce the bias in the spring phytoplankton bloom present when using the previous error covariances. Validation against independent glider observations in the North Sea also shows reductions in bias in chlorophyll a and oxygen that extend below the surface to the depth of the mixed layer. Accounting for the biases in the model in the error correlations can lead to much larger improvements than not accounting for them; however, there are also regions where large degradations are seen that may indicate model instabilities. This may be improved by estimating the bias separately for the different regions on the shelf.

Ecosystem connections in the shelf sea environment using complex networks

“…7 clearly match the well known geographic features of the area, e.g., German Bight, Southern Bight, Doggerbank, Norwegian Trench, or more broadly, English Channel and North Sea. Our complex network clustering provides also reasonably similar results to the expert-based partition of NWES applied in many works (Ostle et al, 2016;Legge et al, 2020;Fowler et al, 2022), with some extra fine details and some new regions included. shelf-open ocean exchange.…”

“…This has profound implications for including new types of biogeochemistry observations into the operational model of the NWES. The present version of the NWES operational system uses parametrized correlation lengthscales in its DA scheme (Waters et al, 2015;Skákala et al, 2018;Skakala et al, 2020;Skákala et al, 2021;Fowler et al, 2022) . Therefore, any new assimilated variables require prior knowledge of those lengthscales.…”

“…This is the case of the UK operational system for the NWES (e.g. (Edwards et al, 2012;Waters et al, 2015;Fowler et al, 2022)) run at the UK Met Office, using ERSEM as the biogeochemical model. Since future observational missions will provide new biogeochemical variables (such as nutrients, or pH) for assimilation (Skákala et al, 2021;Ford, 2021), it is of crucial importance to gain understanding of how transferable the correlation lengthscales are between the different biogeochemical variables.…”

Contrasted Trends in Chlorophyll‐a Satellite Products

“…These four products show very similar patterns as they are all partially based on the NASA R2018.0 and ESA reprocessing for their respective sensors, unlike Globcolour‐GSM which derives Schl thanks to a specific semi‐analytical ocean color model (Maritorena et al., 2002). Considering now the OC‐CCI product which is widely used in the ocean color community (e.g., Fowler et al., 2023; van Oostende et al., 2023), a decreasing trend can be observed in the northern and equatorial Pacific Ocean, along the Pacific Intertropical Convergence Zone (ITCZ), the tropical Indian and northern Atlantic Oceans (Figure 1b). However, a significant positive trend of Schl appears in the northern hemisphere for higher latitudes than 40°N and in the Southern Ocean generally south of the Subtropical Front (Graham & Boer, 2013), as well as in the south‐eastern Pacific.…”

Advancements in Detecting Spot Fungal Diseases on Date Palm Leaves: Development and Validation of Chlorophyll-Based Detection Models

“…Validation of these models involves comparing detection rates with ground-truth data obtained from laboratory analyses. Recent studies have shown that chlorophyll-based models offer a high detection accuracy, often in excess of 90% (Fowler et al, 2023).…”