CGD's Dr. James Hurrell

Abstract

Using suites of atmospheric general circulation model (AGCM) simulations forced by global, regional, and idealized sea surface temperature (SST) variations Jim Hurrell and Adam Phillips, in collaboration with Martin Hoerling and Jon Eischeid of NOAA, found that multi-decadal variations and trends in SSTs have determined the spatial patterns, time history and seasonality of observed changes in African rainfall since 1950 (Hoerling et al. 2006). In particular, they diagnosed 80 separate 50-yr Global Ocean Global Atmosphere (GOGA) simulations from five different AGCMs. The multi-model ensemble mean realistically captured the observed seasonality and spatial structure of downward trends in African rainfall, not only over the Sahel during boreal summer, but across the continent following the seasonal migration of rainfall. As an example, the simulated and observed spatial patterns correlated at +0.6 over southern Africa during the February-April (FMA) rainy season and all ensemble members produced drying trends (Fig. 1). That the observed drying trend fell within the distribution function of the simulated trends indicates that it was likely a consequence of 20th Century SST variations. Moreover, no single 50-yr trend in unforced coupled ocean-atmosphere model simulations yielded a drying rate as large as observed (blue curve in Fig. 2), and nearly half of the GOGA rainfall trends fell outside the PDF from unforced coupled models, suggesting the responsible air-sea interactions were not arising from natural variations alone - a statement that must be tempered by the fact that the current generation of coupled models does not offer a completely accurate picture of natural low frequency variations.

The role of the Indian Ocean is particularly intriguing because its warming since 1950 is consistent with a greenhouse gas signal (e.g., Hurrell et al. 2004). The atmospheric response to a positive Indian Ocean SST anomaly having an equatorial maximum of +1°C (a pattern approximating the observed 1950-1999 Indian Ocean SST trend) was, therefore, examined. The response did include widespread drying over the southern African region during FMA, and it was strikingly similar to the 1950-1999 FMA trend pattern itself (Fig. 2). The Indian Ocean warming thus appears to have been a key source for a decline in the austral summer African monsoon, though its role in forcing drought over the Sahel remains unclear.

Figure caption: The 1950-1999 trends in observed (left), GOGA (middle), and Indian Ocean forced (right) FMA rainfall (mm). The observed trend (gray bar) and PDFs of 50-yr rainfall trends averaged over the indicated region are shown in far right panel. The red (black) curve is from 80 (60) individual members of the GOGA (Indian Ocean) runs. The blue curve is from 15 members of unforced coupled model simulations.

Support: CLIVAR Program of the NOAA Office of Global Programs. The National Center for Atmospheric Research is sponsored by the National Science Foundation.

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Hurrell, J. W., and C. Deser, 2007: North Atlantic climate variability: the role of the North Atlantic Oscillation. Journal of Marine Systems, in press.

Abstract

Marine ecosystems are undergoing rapid change at local and global scales. To understand these changes, including the relative roles of natural variability and anthropogenic effects, and to predict the future state of marine ecosystems requires quantitative understanding of the physics, biogeochemistry and ecology of oceanic systems at mechanistic levels. Central to this understanding is the role played by dominant patterns or "modes" of atmospheric and oceanic variability, which orchestrate coherent variations in climate over large regions with profound impacts on ecosystems. We review the spatial structure of extratropical climate variability over the Northern Hemisphere and, specifically, focus on modes of climate variability over the extratropical North Atlantic.

A leading pattern of weather and climate variability over the Northern Hemisphere is the North Atlantic Oscillation (NAO). The NAO refers to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one phase to another produce large changes in surface air temperature, winds, storminess and precipitation over the Atlantic as well as the adjacent continents. The NAO also affects the ocean through changes in heat content, gyre circulations, mixed layer depth (Fig. 1), salinity, high latitude deep water formation and sea ice cover. Thus, indices of the NAO have become widely used to document and understand how this mode of variability alters the structure and functioning of marine ecosystems.

There is no unique way, however, to define the NAO. Several approaches are discussed, including both linear (e.g., principal component analysis) and nonlinear (e.g., cluster analysis) techniques. The former, which have been most widely used, assume preferred atmospheric circulation states come in pairs, in which anomalies of opposite polarity have the same spatial structure. In contrast, nonlinear techniques search for recurrent patterns of a specific amplitude and sign. They reveal, for instance, spatial asymmetries between different phases of the NAO that are likely important for ecological studies.

It also follows that there is no universally accepted index to describe the temporal evolution of the NAO. Several of the most common measures are presented and compared. All reveal that there is no preferred time scale of variability for the NAO: large changes occur from one winter to the next and from one decade to the next. There is also a large amount of within-season variability in the patterns of atmospheric circulation of the North Atlantic, so that most winters cannot be characterized solely by a canonical NAO structure. A better understanding of how the NAO responds to external forcing, including sea surface temperature changes in the tropics, stratospheric influences, and increasing greenhouse gas concentrations, is crucial to the current debate on climate variability and change.

Figure caption: Difference in mean winter (December-March) ocean mixed layer depth (m) between years when an index of the NAO exceeds one standard deviation over 1955-2003. The contour increment is 6 m and positive (negative) differences are given by the solid (dashed) contours.

Support: NSF and NOAA.