Factors challenging our ability to detect long-term trends in ocean chlorophyll
Factors challenging our ability to detect long-term trends in ocean chlorophyll
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DOI：
10.5194/bg-10-2711-2013
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发表时间：
2013-01-01
期刊：
影响因子：
4.9
通讯作者：
Bopp, L.
中科院分区：
文献类型：
--
作者：
Beaulieu, C.;Henson, S. A.;Bopp, L.
全球气候变化预计将影响海洋的生物生产力。关于当代海洋初级生产力全球分布的现有最全面的信息来自卫星数据。叶绿素a浓度的大空间斑块和年际至数十年的变化挑战了区分全球长期趋势的努力，因为卫星记录的持续时间和连续性有限。最长的海洋颜色卫星记录来自于2010年12月失败的海景宽视场传感器（SeaWiFS）。中分辨率成像光谱仪（MODIS）海洋颜色传感器已经超过了其最初计划的使用寿命。从目前的可见红外成像仪辐射计套件（VIIRS）仪器中成功检索高质量信号，或预计在2014年成功发射海洋和陆地颜色仪器（OLCI），将有望延长海洋颜色时间序列，并增加未来探测海洋生产力趋势的潜力。或者，海洋叶绿素a时间序列的潜在不连续性，由于仪器的变化而没有重叠和交叉校准的机会，将使趋势检测更具挑战性。在本文中，我们证明了在十年的SeaWiFS数据中，有几个区域具有统计上显著的趋势，但在全球范围内，趋势还不够大，无法与噪声区分开来。我们量化了红噪声（自相关）在这些观测时间序列中对趋势检测的挑战程度。我们进一步展示了时间序列中不同点的不连续性如何影响我们检测海洋叶绿素a趋势的能力。我们强调必须保持连续的、气候质量高的卫星数据记录，以用于气候变化探测和归因研究。
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 multi-decadal 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.