Twenty years of high-resolution sea surface temperature imagery around Australia: inter-annual and annual variability

The physical climate defines a significant portion of the habitats in which biological communities and species reside. It is important to quantify these environmental conditions, and how they have changed, as this will inform future efforts to study many natural systems. We present the results of a statistical summary of the variability in sea surface temperature (SST) time-series data for the waters surrounding Australia, from 1993 to 2013. We partition variation in the SST series into annual trends, inter-annual trends, and a number of components of random variation. We utilise satellite data and validate the statistical summary from these data to summaries of data from long-term monitoringstations and from the global drifter program. The spatially dense results show clear trends that associate with oceanographic features. Noteworthy oceanographic features include: average warming was greatest off southern West Australia and off eastern Tasmania where the warming was around 0.6 C per decade for a twenty year study period, and; insubstantial warming in areas dominated by the East Australian Current but this area did exhibit high levels of inter-annual variability (long-term trend increases and decreases but does not increase on average). The results of the analyses can be directly incorporated into (biogeographic) models that explain variation in biological data where both biological and environmental data are on a fine scale.

物理气候条件是塑造生物群落与物种栖息生境的核心组成部分。量化此类环境条件及其变化趋势，可为诸多自然系统的后续研究提供重要依据。本研究针对1993年至2013年澳大利亚周边海域的海表温度（sea surface temperature, SST）时序数据的变异性开展统计汇总，并展示相关分析结果。研究将SST序列的变异分解为年度趋势、年际趋势以及多类随机变异分量。本研究采用卫星数据开展分析，并将基于卫星数据得到的统计汇总结果，与长期监测站及全球漂流浮标计划（Global Drifter Program）的观测数据汇总结果进行验证比对。该空间分辨率较高的分析结果呈现出与海洋学特征显著相关的清晰趋势。值得关注的海洋学特征包括：在20年研究周期内，西澳大利亚南部近海与塔斯马尼亚东部近海的海表温度增温最为显著，增幅约为0.6℃/十年；而受东澳洋流主导的海域增温幅度极小，但该区域的年际变异性极强，仅存在长期的增减波动，整体并无平均增温趋势。本研究的分析结果可直接集成至生物地理（biogeographic）模型中，此类模型可针对精细尺度下的生物与环境数据，解释生物数据的变异规律。