| Chlorophyll is an important indicator to eutrophication, which is also a key point for thecoastal ecosystem study, marine environmental evaluation, natural resource development,and the disaster prevention and alleviation. In addition, to discuss carbon exchangecalculation between air-sea interfaces using chlorophyll data, is of significant importanceto research on global-carbon cycle, global warming, and sea-level rising.In recent years, the chlorophyll distribution and its variation related to physical andchemical environmental factors (such as temperature, illumination, nutrients, winds, oceancirculation and tidal currents) has become an important subject in marine-ecologicalstudies. Furthermore, remote sensing has been one of the best methods in the marineobservation and monitoring, as it can provide data with wide range, long term, highfrequency and low cost. Those long-term synchronous data is one of the most reliable datasources for studies on temporal-spatial variation of chlorophyll distribution and multi-scalephysical-biological interactions. However, due to the aerosol and other reasons, large areaof remote-sensing chlorophyll data are often missing, which hinders its development, andalso becomes a hot topic in this field. Therefore, to retrieve the long-term synchronous data,the re-constructure and re-analysis of remote-sensing data is called for. This can extend theapplication of remote-sensing data, and improve its utilization efficiency. In this study,combining the advantages of the DINEOF method and the optimal interpolation (OI), analgorithm (DINEOF-OI) with multi-variables and second-order-correction has beendeveloped to study the variable chlorophyll distribution in multi scales including weather-process scales in the East China Sea (ECS). This paper introduces how to locate theinfluencing weights of observed data on re-constructed data in temporal and spatial series.Based on the algorithm developed in this paper, the recent decadal chlorophyll data in theECS has been re-constructed and analysed. The relative error between the re-constructedresults (SST, chlorophyll) and observations is under18%, which also shows a good agreement on spatial patterns. It indicates the re-constructed database can describe theprimary characteristics of chlorophyll distribution in the ECS in multi-scale processes.Furthermore, through coupling a numerical simulation, this study reveals the mechanismsof those multi-scale variations. It builds the foundation for future studies on therelationships between chlorophyll and physical factors in the ECS.This paper presents the seasonal and inter-annual variations and future trends of thechlorophyll-a concentration in the ECS; explores its relationship to the sea surfacetemperature (SST) and sea surface wind; discusses the impacts of high-frequency climateprocesses (ENSO etc.) on the phytoplankton (chlorophyll); it has been found that theresponse to the extreme wind process is different at different regions and differenttemporal-spatial scales. The conclusions of this study are given below:1）During the lastten years (from2003to2012), the chlorophyll concentration in the ECS has been increasedwith an average rate of0.012mg/m3.2）In the ECS, the sea surface temperature is themajor controlling factor of the chlorophyll concentration. Seasonally, chlorophyll and SSThave a high negative correlation in open sea area, but a low positive correlation in coastalregions.3）It shows little correlation between sea surface wind and chlorophyll in aseasonal scale, in which strong positive correlation occurs in the ECS open area and thewestern coastal region of the Yellow Sea.4）Based on the statistics of11cyclones passedthe ECS, the chlorophyll concentration increased by1.46mg/m3in average after thecyclone with a3-8day delay; while the SST decreased by1.91. The increasing rate ofchlorophyll concentration is closely related to the cyclone impact factor (calculated by theproduct of the cyclone lasting time T and its wind scale L), with a correlation coefficient of0.83.5）Using an eco-dynamic numerical model to simulate an extreme wind event (windspeed over12m/s) in the Bohai Sea, the result shows the event will generate a highchlorophyll concentration on the surface. The chlorophyll concentration will keepincreasing and reach its peak on the4th day; then it will gradually drop to the average level.The entire process will last for more than15days. In average, a typical strong winter windwill increase the chlorophyll concentration by20%in the Bohai Sea. |
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