Evaluating Operational AVHRR Sea Surface Temperature Data at the Coastline Using Benthic Temperature Loggers
Evaluating Operational AVHRR Sea Surface Temperature Data at the Coastline Using Benthic Temperature Loggers
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DOI：
10.3390/rs10060925
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发表时间：
2018-06-01
期刊：
影响因子：
5
通讯作者：
Yang, Mingxi
中科院分区：
文献类型：
--
作者：
Brewin, Robert J. W.;Smale, Dan A.;Yang, Mingxi
近岸海洋是地球上最具活力和生物生产力的区域之一，支持着广泛的生态系统服务。它也是最脆弱的地区之一，越来越多地受到人为压力的影响。在气候变化的背景下，监测近岸沿海沃茨的变化需要对关键的基本气候变量进行系统和持续的观测，其中之一是海面温度。由于温度影响沿海系统内的物理、化学和生物过程，准确监测对发现变化至关重要。SST是一种ECV，可以从卫星上系统地测量。然而，由于缺乏足够的现场数据，卫星SST在海岸线的准确性和精确度并不为人所知。在以前的研究中，我们试图解决这个问题，利用现场SST测量收集的一组冲浪者。在这里，我们利用了三年的时间序列（2014-2017年），使用部署在英国普利茅斯附近的潮下带岩礁站点的海带森林（约低于海图基准面3米）内的温度记录器（每30分钟记录一次）收集的原位水温测量值。我们将温度测量结果与该地区其他三个独立的原位SST数据集进行了比较，这三个数据集来自两个自治浮标，分别位于距离海岸线约7公里和约33公里的地方，以及来自海带站点附近两个海滩的一组冲浪者。这三个数据集显示出良好的一致性，与网站的空间分离一致的差异。现场SST测量收集的海带网站和两个自主浮标相匹配的业务高级甚高分辨率辐射计（AVHRR）EO SST通行证，所有在1小时内的现场数据。通过提取数据从最近的卫星像素的三个网站，我们观察到的AVHRR在检索SST在海岸线的性能显着减少，在海带网站的均方根差的两倍以上，在两个近海浮标观察。比较原位水温数据与周围的海带网站的像素显示，卫星数据的性能提高时，移动两到三个像素离岸，这种改善是更好地使用SST算法，在检索过程中独立对待每个像素。在这三个站点，我们与卫星和现场SST数据之间的差异与一套大气变量，从附近的大气观测站收集，和高时间分辨率的陆地表面温度（LST）数据集。我们发现，卫星和原位SST在海岸线（海带网站）之间的差异与LST和太阳天顶角有很好的相关性，这意味着污染的像素由土地是这些较大的差异在海岸线的主要原因，而不是大气校正的问题。这种污染可能直接来自像素内的土地，可能受到地理位置误差的影响，或者可能通过热邻近效应。我们的研究结果表明，使用海底温度记录器评估卫星SST数据在沿海地区的价值，并强调在海岸线的检索，可能会告知未来的改进业务产品的问题。
The nearshore coastal ocean is one of the most dynamic and biologically productive regions on our planet, supporting a wide range of ecosystem services. It is also one of the most vulnerable regions, increasingly exposed to anthropogenic pressure. In the context of climate change, monitoring changes in nearshore coastal waters requires systematic and sustained observations of key essential climate variables (ECV), one of which is sea surface temperature (SST). As temperature influences physical, chemical and biological processes within coastal systems, accurate monitoring is crucial for detecting change. SST is an ECV that can be measured systematically from satellites. Yet, owing to a lack of adequate in situ data, the accuracy and precision of satellite SST at the coastline are not well known. In a prior study, we attempted to address this by taking advantage of in situ SST measurements collected by a group of surfers. Here, we make use of a three year time-series (2014-2017) of in situ water temperature measurements collected using a temperature logger (recording every 30 min) deployed within a kelp forest (approximate to 3 m below chart datum) at a subtidal rocky reef site near Plymouth, UK. We compared the temperature measurements with three other independent in situ SST datasets in the region, from two autonomous buoys located approximate to 7 km and approximate to 33 km from the coastline, and from a group of surfers at two beaches near the kelp site. The three datasets showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected from the kelp site and the two autonomous buoys were matched with operational Advanced Very High Resolution Radiometer (AVHRR) EO SST passes, all within 1 h of the in situ data. By extracting data from the closest satellite pixel to the three sites, we observed a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square differences at the kelp site over twice that observed at the two offshore buoys. Comparing the in situ water temperature data with pixels surrounding the kelp site revealed the performance of the satellite data improves when moving two to three pixels offshore and that this improvement was better when using an SST algorithm that treats each pixel independently in the retrieval process. At the three sites, we related differences between satellite and in situ SST data with a suite of atmospheric variables, collected from a nearby atmospheric observatory, and a high temporal resolution land surface temperature (LST) dataset. We found that differences between satellite and in situ SST at the coastline (kelp site) were well correlated with LST and solar zenith angle; implying contamination of the pixel by land is the principal cause of these larger differences at the coastline, as opposed to issues with atmospheric correction. This contamination could be either from land directly within the pixel, potentially impacted by errors in geo-location, or possibly through thermal adjacency effects. Our results demonstrate the value of using benthic temperature loggers for evaluating satellite SST data in coastal regions, and highlight issues with retrievals at the coastline that may inform future improvements in operational products.