Abstract
Abstract. In the framework of the INDESO (Infrastructure Development of Space Oceanography) project, an operational ocean forecasting system was developed to monitor the state of the Indonesian seas in terms of circulation, biogeochemistry and fisheries. This forecasting system combines a suite of numerical models connecting physical and biogeochemical variables to population dynamics of large marine predators (tunas). The physical–biogeochemical coupled component (the INDO12BIO configuration) covers a large region extending from the western Pacific Ocean to the eastern Indian Ocean at 1/12° horizontal resolution. The NEMO-OPA (Nucleus for European Model of the Ocean) physical ocean model and the PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies) biogeochemical model are running simultaneously ("online" coupling), at the same resolution. The operational global ocean forecasting system (1/4°) operated by Mercator Océan provides the physical forcing, while climatological open boundary conditions are prescribed for the biogeochemistry. This paper describes the skill assessment of the INDO12BIO configuration. Model skill is assessed by evaluating a reference hindcast simulation covering the last 8 years (2007–2014). Model results are compared to satellite, climatological and in situ observations. Diagnostics are performed on nutrients, oxygen, chlorophyll a, net primary production and mesozooplankton. The model reproduces large-scale distributions of nutrients, oxygen, chlorophyll a, net primary production and mesozooplankton biomasses. Modelled vertical distributions of nutrients and oxygen are comparable to in situ data sets although gradients are slightly smoothed. The model simulates realistic biogeochemical characteristics of North Pacific tropical waters entering in the archipelago. Hydrodynamic transformation of water masses across the Indonesian archipelago allows for conserving nitrate and oxygen vertical distribution close to observations, in the Banda Sea and at the exit of the archipelago. While the model overestimates the mean surface chlorophyll a, the seasonal cycle is in phase with satellite estimations, with higher chlorophyll a concentrations in the southern part of the archipelago during the SE monsoon and in the northern part during the NW monsoon. The time series of chlorophyll a anomalies suggests that meteorological and ocean physical processes that drive the interannual variability of biogeochemical properties in the Indonesian region are reproduced by the model.
Highlights
The “coral triangle” delineated by Malaysia, the Philippines, New Guinea, Solomon Islands, East Timor and Indonesia is recognised as a global hotspot of marine biodiversity (Allen and Werner, 2002; Mora et al, 2003; Green and Mous, 2004; Allen, 2008)
The simulation starts on 3 January 2007 from the global ocean forecasting system at 1/4◦ operated by Mercator Océan (PSY3 described in Lellouche et al, 2013) for temperature, salinity, currents and free surface at the same date
As mentioned before, Net primary production (NPP) estimates depend on the primary production model and on the ocean colour data used in the production models
Summary
The “coral triangle” delineated by Malaysia, the Philippines, New Guinea, Solomon Islands, East Timor and Indonesia is recognised as a global hotspot of marine biodiversity (Allen and Werner, 2002; Mora et al, 2003; Green and Mous, 2004; Allen, 2008). Surveys report an over 30 % reduction of mangroves in northern Java over the last 150 years and an increase of coral reef degradation from 10 to 50 % in the last 50 years (Bryant et al, 1998; Hopley and Suharsono, 2000; UNEP, 2009), leading to 80 % of the reefs being at risk in this region (Bryant et al, 1998) These changes damage coastal habitats, and propagate across the whole marine ecosystem from nutrients and the first levels of the food web up to higher trophic levels, along with concomitant changes in biogeochemical cycles.
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