Bibliography - S. A. Henson

1. Beaulieu, C., S. A. Henson, Jorge Sarmiento, J. P. Dunne, Ryan R. Rykaczewski, and L. Bopp, 2013: Factors challenging our ability to detect long-term trends in ocean chlorophyll. Biogeosciences, Copernicus Publications, 10, doi:10.5194/bg-10-2711-2013 2711-2724
   [ Abstract ]

   Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Seaviewing Wide Field-of-view Sensor (SeaWiFS), which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS) instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI) expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation) especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

2. Henson, S. A., Jorge Sarmiento, J. P. Dunne, L. Bopp, I. Lima, S. C. Doney, J. John, and C. Beaulieu, 2010: Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity. Biogeosciences, 7, doi:10.5194/bg-7-621-2010 621-640
   [ Abstract ]

   Global climate change is predicted to alter the ocean’s biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ∼40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (∼ 20−30 years). Analysis of modelled chlorophyll and primary production from 2001– 2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ∼2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decadeslong data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

3. Henson, S. A., J. P. Dunne, and Jorge Sarmiento, 2009: Decadal variability in North Atlantic phytoplankton blooms. Journal of Geophysical Research, 114(CO403), doi:10.1029/2008JC005139
   [ Abstract ]

   The interannual to decadal variability in the timing and magnitude of the North Atlantic phytoplankton bloom is examined using a combination of satellite data and output from an ocean biogeochemistry general circulation model. The timing of the bloom as estimated from satellite chlorophyll data is used as a novel metric for validating the model’s skill. Maps of bloom timing reveal that the subtropical bloom begins in winter and progresses northward starting in May in subpolar regions. A transition zone, which experiences substantial interannual variability in bloom timing, separates the two regions. Time series of the modeled decadal (1959–2004) variability in bloom timing show no long-term trend toward earlier or delayed blooms in any of the three regions considered here. However, the timing of the subpolar bloom does show distinct decadal-scale periodicity, which is found to be correlated with the North Atlantic Oscillation (NAO) index. The mechanism underpinning the relationship is identified as anomalous wind-driven mixing conditions associated with the NAO. In positive NAO phases, stronger westerly winds result in deeper mixed layers, delaying the start of the subpolar spring bloom by 2–3 weeks. The subpolar region also expands during positive phases, pushing the transition zone further south in the central North Atlantic. The magnitude of the bloom is found to be only weakly dependent on bloom timing, but is more strongly correlated with mixed layer depth. The extensive interannual variability in the timing of the bloom, particularly in the transition region, is expected to strongly impact the availability of food to higher trophic levels.

4. Henson, S. A., Jorge Sarmiento, and J. P. Dunne, 2009: Is global warming already changing ocean productivity? Biogeosciences Discuss, www.biogeosciences-discuss.net/6/10311/2009/, 6, 10311-10354
   [ Abstract ]

   Global warming is predicted to alter the ocean’s biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on the global distribution of ocean productivity comes from satellite 5 ocean colour data. Now that over ten years of SeaWiFS data have accumulated, can we begin to detect and attribute global warming trends in productivity? Here we compare recent trends in SeaWiFS data to longer-term records from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of real trends in the satellite data is confounded by the relatively short time series and large interannual 10 and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global warming. Instead, our analyses suggest that a time series of ~40 yr length is needed to distinguish a global warming trend from natural variability. Analysis of modelled chlorophyll and primary production from 2001–2100 15 suggests that, on average, the global warming trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

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