Climate Change and Large Marine Ecosystems (LMEs)

The study of marine climate variability and its impact on marine populations has been one of the principal areas of research since the inception of the forerunners of the ERD in 1969, and this area of study continues to play a prominent role in the Division's research efforts.

Research on climate change and LMEs is aimed at assessing and forecasting the effects of environmental variability on oceanographic processes from global to local effects important to fish populations, protected species, and marine ecosystems, and to deliver scientific information for decision making. This is done through research that:

  • Determines large-scale environmental events that impact marine resources
  • Describes the mechanisms leading to regime shifts
  • Assesses the effects of climate change on environmental processes important to fish and protected species populations
  • Develops means to effectively forecast climatic environmental variations that influence marine resources
  • Develops ecosystem relevant data products & indices
  • Develops and test new ecological indicators of climate variability

This research track has been highly productive, with ERD scientists playing prominent roles in studies of large-scale atmosphere-ocean interactions, the nature and causes of climate related regime shifts, and the physical and biological impacts of El Niño events on the extra-tropics. Much of the recent climate work has involved collaborations within leading domestic and international programs including:

  • U.S. GLOBEC Northeast Pacific (NEP) program
  • NOAA/Cooperative Institute for Arctic Research
  • TOPP

Specific Research Areas

State-Space Models

ERD has introduced state-space models into the geophysical literature as a tool to better analyze the dynamics of observed time series. For a single series, the state-space model decomposes a series into:

  • Non-parametric trend
  • Non-stationary seasonal component
  • Stochastic cycles or AR terms
  • Observation error

The models can handle missing data in a consistent fashion, a common problem in ecosystem analysis. The models are true statistical models with a likelihood, which means parameters of the model can be tested for significance and models with different components can be as to which better explains the observed data.

State-space models have a multivariate analogue that improve upon Empirical Orthogonal Functions (EOFs):

  • The data are not assumed to be independent in time
  • The model includes observation error
  • Dynamics at different time-scales can be isolated
  • Statistical tests for structural breaks, outliers and other features are possible

Seasonal Variability

Trends in large-scale climate change can affect local dynamics on different scales, such as through changes in the seasonal dynamics in a local region. ERD has been a leader in implementing statistical methods that can correctly identify changes in the seasonal cycle that are separate from the long-term trend in the region. This has included:

  • That upwelling in the California Current System (CCS) has been increasing, even as the trend in SST has been increasing over the same period
  • Significant variation in seasonal thermal structure throughout the CCS
  • Seasonal variation in stratification in the CCS
  • Differential seasonal variability in the major pressure systems in the region

Long-term Variability in the Northeast Pacific (NEP)

  • Long-term changes in Upwelling in the CCS
  • Changes in the wind stress and related parameters in the West Wind Drift area and the effect on conditions in the CCS
  • Causes of regime shifts in the NEP
  • Long-term changes in the upper thermal structure in the CCS
  • Differential effects of El Ninos on the CCS
  • Long-term changes in mixed-layer depth, stratification and heat content in the CCS

Basin Scale Dynamics

  • Stationary and non-stationary dynamics in indices of ENSO dynamics
  • North Pacific SST dynamics, and dynamics by current system (CCS, Gulf of Alaska/Bering Sea, Kuroshio, Oyashio, Humboldt)

Inter-Basin Comparisons

  • Detection and relative timing/direction of abrupt changes in major indices in the North Atlantic and North Pacific basins
  • Changes in wavenumber dynamics affecting global teleconnections

Relevance to NOAA's Strategic Mission for Fiscal Years 2008-2012:

  • Understand climate variability and change to enhance society's ability to plan and respond
    • Climate variability and ecosystem predictions
    • Collaborative, science-based approaches to ecosystem management
    • Improved monitoring and forecasting of ecosystem conditions based on climate observations and models.
    • Improved understanding of climate change and climate predictability at decadal time scales, with impacts on marine ecosystems