Spatio-Temporal Dynamics Of Phytoplankton Biomass From Ocean Color Remote Sensing And Cmip5 Model Suites
type: CreativeWork
description: Phytoplankton are the base of the marine food web, and, importantly, drive the biological carbon pump, the combination of photosynthesis, organic carbon sinking and subsurface decomposition of organic matter which effectively sequesters carbon away from the atmosphere. Our knowledge of phytoplankton activity is currently advancing fast through developments of multiple ocean-color remote sensing algorithms and via developments in ecological modules incorporated in climate models. While climate models are projecting relatively clear trends in ocean ecology over the next century, distinguishing between interannual variability and ocean biology trends from satellite observations is difficult. Short record length, satellite data continuity issues and strong interannual variability all impact quantified trends. Additionally, commonly observed chlorophyll-a is not strictly indicative of underlying phytoplankton biomass because of phytoplankton adaptation. This thesis investigates the trends, interannual variability and seasonality in new size-partitioned phytoplankton biomass products, with a focus on the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) mission period (1997-2010). In Chapter 2 we found phytoplankton biomass increases in the warm ocean regions over this period, opposing common expectations of decreases in warming oceans. Biomass increases are due to increased physical mixing of the watercolumn and are partially attributed to the large scale El Nino Southern Oscillation (ENSO) phenomenon. Recent studies have highlighted the emergence of different types of ENSO, with a shift towards more Central Pacific ENSO events. Chapter 3 uses statistical techniques (agglomerative hierarchical clustering (AHC), empirical orthogonal functional analysis (EOF)) on phytoplankton biomass to characterize ENSO “flavors” in the tropical Pacific. For the first time, we empirically derive biological indices for different ENSO types and show high correlations with existing climate in…
abstract: Phytoplankton are the base of the marine food web, and, importantly, drive the biological carbon pump, the combination of photosynthesis, organic carbon sinking and subsurface decomposition of organic matter which effectively sequesters carbon away from the atmosphere. Our knowledge of phytoplankton activity is currently advancing fast through developments of multiple ocean-color remote sensing algorithms and via developments in ecological modules incorporated in climate models. While climate models are projecting relatively clear trends in ocean ecology over the next century, distinguishing between interannual variability and ocean biology trends from satellite observations is difficult. Short record length, satellite data continuity issues and strong interannual variability all impact quantified trends. Additionally, commonly observed chlorophyll-a is not strictly indicative of underlying phytoplankton biomass because of phytoplankton adaptation. This thesis investigates the trends, interannual variability and seasonality in new size-partitioned phytoplankton biomass products, with a focus on the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) mission period (1997-2010). In Chapter 2 we found phytoplankton biomass increases in the warm ocean regions over this period, opposing common expectations of decreases in warming oceans. Biomass increases are due to increased physical mixing of the watercolumn and are partially attributed to the large scale El Nino Southern Oscillation (ENSO) phenomenon. Recent studies have highlighted the emergence of different types of ENSO, with a shift towards more Central Pacific ENSO events. Chapter 3 uses statistical techniques (agglomerative hierarchical clustering (AHC), empirical orthogonal functional analysis (EOF)) on phytoplankton biomass to characterize ENSO “flavors” in the tropical Pacific. For the first time, we empirically derive biological indices for different ENSO types and show high correlations with existing climate in…
author: Sharma, Priya
language: en
date published: 2018
date modified: 2026-07-24T03:45:49Z
provider: University of Pennsylvania
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Pennsylvania