A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology.

Shahzadi, K., Pinardi, N., Barth, A., Troupin, C., Lyubartsev, V., Simoncelli, S. (2021). A New Global Ocean Climatology. FRONTIERS IN ENVIRONMENTAL SCIENCE, 9, 1-14 [10.3389/fenvs.2021.711363].

A New Global Ocean Climatology

Shahzadi K.
Formal Analysis
;
Pinardi N.
Conceptualization
;
2021

Abstract

A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology.
2021
Shahzadi, K., Pinardi, N., Barth, A., Troupin, C., Lyubartsev, V., Simoncelli, S. (2021). A New Global Ocean Climatology. FRONTIERS IN ENVIRONMENTAL SCIENCE, 9, 1-14 [10.3389/fenvs.2021.711363].
Shahzadi, K.; Pinardi, N.; Barth, A.; Troupin, C.; Lyubartsev, V.; Simoncelli, S.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/871624
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