Abstract

As part of the Atlantic Zone Monitoring Program two different methods were applied to merge three Level-3 AVHRR SST products into a homogenized blend covering the time period from 1982 to present over the Northwest Atlantic, providing a regionally-tuned climatological base on which to assess whether current observations are below, near or above normal. Weekly and monthly SST composites were constructed by averaging daily anomalies within each time period and adding the result to the climatological mean for the period. This approach reduces biases introduced from missing data during a strong warming/cooling seasonal period. Since AVHRR SST data have many spatial and temporal gaps, a common difficulty is establishing how much data are sufficient to yield useful estimations of temperature anomalies. A statistical Monte Carlo method showed that monthly and weekly regional averages composed respectively of as little as 7% and 10% of possible data still yield useful results. A test case shows the increased usefulness of the blend for State of the Ocean reporting. Application of the data set confirmed the use of coastal air temperature as a useful proxy for SST allowing hindcasting past changes or forecasting future changes associated with global warming over Eastern Canadian waters.

摘要

作为大西洋区监测计划的一部分，应用两种不同的方法将三种 3 级 AVHRR SST 产品合并成一个均质混合物，涵盖了从 1982 年到目前在西北大西洋的时间段，提供了一个区域调整的气候基础，用于评估当前观测值是否低于、接近或高于正常值。通过平均每个时间段内的每日异常并将结果添加到该时期的气候平均值来构建每周和每月的 SST 复合材料。这种方法减少了在强烈的变暖/变冷季节期间缺失数据引入的偏差。由于 AVHRR SST 数据有许多空间和时间差距，一个常见的困难是确定多少数据足以产生有用的温度异常估计。统计蒙特卡罗方法表明，分别由 7% 和 10% 的可能数据组成的每月和每周区域平均值仍然会产生有用的结果。一个测试案例显示了混合对海洋状况报告的更多用处。数据集的应用证实了使用沿海气温作为 SST 的有用代理，允许后报过去的变化或预测与加拿大东部水域全球变暖相关的未来变化。