Chlorophyll-a Monthly Frequency for Extreme Anomalies

An additional sub-indicator will be provided to evaluate the intra-annual changes in chlorophyll-a concentration anomalies in each Exclusive Economic Zone (EEZ) using the NOAA VIIRS chlorophyll-a ratio anomaly product produced daily for the globe at 2 km spatial resolution. The daily global VIIRS chlorophyll-a concentrations are produced from the NOAA Multi-Sensor Level 1 to Level 2 (MSL12) processing of the VIIRS sensor on the Suomi SNPP satellite. [Wang et al., 2017; Wang et al.,2014] This anomaly product is defined as the daily chlorophyll-a concentration subtracted from a rolling 61-day mean baseline with a 15 day lag (based on Stumpf et al., 2003), then normalized to the rolling 61 day mean to create the proportional difference anomaly. The processing steps are outlined below. 1. Classify and count pixels as moderate, high or extreme anomalies. For each day in the reporting year, pixels in the global EEZ area (as defined in World EEZ v11) that are classified as: moderate (in the 90th percentile), high (in the 95th percentile) and extreme (in the 99th percentiles). The number of days a given pixel is classified as moderate, high, or extreme within each month is then calculated. The number of days in each month where the pixel has valid data is also counted. 2. Calculating the monthly statistics Because these anomalies are based on daily observations, data gaps are expected due to cloud cover, sun glint, high sensor zenith angle, high sun zenith angle, and other possible algorithm flags. To avoid bias due to non-valid data retrievals, the frequencies are normalized using the number of days in the month with valid observations, as follows: Relative frequency of classified pixel chlorophyll-a anomalies= αc / ε Where α = the number of days in the month with a classified (moderate, high or extreme anomaly) anomaly Where c indicates the anomaly classification (moderate, high, or extreme anomaly) Where ε = the number of days in the month with valid data Finally, the monthly mean of the relative frequencies for each class is calculated for each EEZ, resulting in 3 monthly values, one value in each of the 3 classes for each country. For more information see the Global Manual of Ocean Statistics Available on the UNEP Document Repository (pages 19-24).本数据集将提供一项附加子指标，用于评估每个专属经济区（Exclusive Economic Zone，EEZ）内叶绿素-a浓度异常的年内变化，所用数据为美国国家海洋和大气管理局（National Oceanic and Atmospheric Administration，NOAA）VIIRS叶绿素-a比值异常产品，该产品以2千米空间分辨率每日生成全球覆盖数据集。全球每日VIIRS叶绿素-a浓度数据，由搭载于Suomi SNPP卫星的VIIRS传感器，经NOAA多传感器一级到二级（Multi-Sensor Level 1 to Level 2，MSL12）处理流程生成[Wang等人，2017；Wang等人，2014]。该异常产品的定义为：以滞后15天的61天滑动平均基准减去当日叶绿素-a浓度，再将结果归一化至该61天滑动平均基准，以得到比例差值异常（该方法基于Stumpf等人，2003年的研究）。具体处理步骤如下：1. 异常像素分类与计数将像素划分为中度、重度或极端异常三类。对于报告年度内的每一天，将全球专属经济区（依据World EEZ v11标准划定）内的像素按以下标准分类：中度异常（处于90百分位）、重度异常（处于95百分位）、极端异常（处于99百分位）。随后统计每个像素在每个月内被归类为中度、重度或极端异常的天数，同时统计该月内该像素拥有有效数据的天数。2. 月度统计量计算由于此类异常基于每日观测数据，受云覆盖、太阳耀斑、传感器天顶角过大、太阳天顶角过大及其他算法标记限制等因素影响，数据缺失在所难免。为避免因无效数据反演带来的偏差，需利用当月有效观测天数对异常频率进行归一化处理，公式如下：分类像素叶绿素-a异常相对频率 = α_c / ε其中，α为当月被归类为（中度、重度或极端）异常的天数；c代表异常分类类型（中度、重度或极端异常）；ε为当月拥有有效数据的天数。最终，针对每个专属经济区计算每类异常相对频率的月度平均值，由此为每个国家生成3个月度数值，分别对应三类异常各一项。如需了解更多信息，请参阅联合国环境规划署（United Nations Environment Programme，UNEP）文件库中发布的《全球海洋统计手册》（第19-24页）。