New global gridded nutrient and oxygen datasets:
Basic properties and trend-detection application
Raw ocean observation data are quite difficult to use for analyzing interannual to decadal variability, because data distributions are random spatially and temporally and because background spatial and seasonal variations are generally larger than the signals to be sought. Therefore, easy-to-use gridded datasets produced from observations are important research basis. In particular, rapidly increasing use of biogeochemical models for simulating the past change and future projections implies growing demand for gridded data of biogeochemical parameters.
The gridded data can be produced from a pure observation and also from a combination of the data and model via data assimilations. The quality of the resultant data may be better for the latter, but when the data are used for a model-data comparison the former may be more desirable.
We have produced the first gridded nutrient (phosphate in particular) dataset over the globe on a monthly, 1x1 degree grid from the surf
ace to 1,000 m depth at selected standard depths since 1950. We also produced similar gridded dissolved oxygen dataset. Of course, regions that have enough available gridded data are limited, but the dataset can be used to examine interannual to decadal variability in some areas in the North Pacific and the North Atlantic. The density of available grid is the highest around Japan, reflecting continuous observations by Japanese. In this region, decreasing trend of phosphate is found to the south of Japan throughout the last 50 years. This decreasing trend is surprisingly well reproduced by a biogeochemical numerical model of Prof. Curtis Deutsch.
The observed trend can be caused by the global warming, but the spatial pattern of the trend cannot be explained by the enhanced surface stratification, which is a basic hypothesis for the nutrient reduction due to the global warming. Rather, the pattern suggests that the changes of gyre circulation and/or water mass formation play
important roles. This suggests that to know the regional biogeochemical impacts of the global warming, understanding of changes of physical environment is necessary.