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Seasonal and Interannual Variability of Satellite‐Derived Photosynthetically Available Radiation Over the Tropical Oceans
Author(s) -
Tan J.,
Frouin R.
Publication year - 2019
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2019jc014942
Subject(s) - empirical orthogonal functions , climatology , equator , environmental science , seasonality , multivariate enso index , satellite , monsoon , el niño southern oscillation , la niña , atmospheric sciences , geography , latitude , geology , statistics , mathematics , geodesy , aerospace engineering , engineering
The seasonal and interannual variability of photosynthetically available radiation (PAR) over the tropical oceans is examined using satellite imagery acquired from 1997 to 2017. Spatial and temporal biases between monthly PAR estimates from different instruments are determined and corrected, resulting in a consistent time series over the 20‐year record. Uncertainty is evaluated in comparisons with in situ measurements at various sites. Empirical orthogonal function (EOF) analysis is performed with both seasonal and nonseasonal PAR signals, and linear trends are quantified. Seasonal cycles dominate PAR variability, with the first three seasonal EOF modes explaining 84.7% of the total variance. The seasonal patterns are related to solar position and monsoon. Canonical El Niño–Southern Oscillation (ENSO) and Modoki ENSO are related to the two leading nonseasonal EOF modes, with a correlation coefficient of 0.84 between the first mode and the multivariate ENSO index and of 0.48 between the second mode and the El Niño Modoki index. Trend analysis reveals that PAR tends to decrease by 0.2%/year in the central Pacific north of the equator and to increase by 0.2%/year in the central Pacific around 5°S. The tendency is also for PAR to increase west of Central and South America. These changes are consistent with patterns of cloud change evidenced in the satellite cloud record and predicted by global climate models. The long‐term satellite PAR data set, together with information of nutrient availability and temperature, enables further studies to elucidate the causes of phytoplankton variability in the tropical oceans.