The Bistatic Radar as an Effective Tool for Detecting and Monitoring the Presence of Phytoplankton on the Ocean Surface

Author:

Rodriguez-Alvarez NereidaORCID,Oudrhiri Kamal

Abstract

A massive dust storm formed over the Sahara Desert in June 2020. The African dust cloud, which traveled over the tropical Atlantic’s main development region for hurricanes, resulted in the highest aerosol optical thickness (AOT) for the past two decades. Dust particles contained in dust clouds are at some point deposited on the ocean surface, impacting the ocean biogeochemistry through the supply of nutrients. Although there are remote sensing systems that can map the AOT, the locations of the aerosol particles deposited on the ocean surface remain unknown quantities with remote sensing measurements. In addition, the supplied nutrients are not static and are displaced by ocean currents. Nutrients trigger the phytoplankton (algae) blooms, which form a film on the ocean surface and affect the ocean surface tension. The change in ocean surface tension causes a local decrease of ocean surface roughness over the areas covered with phytoplankton. Bistatic radar data from the CYclone Global Navigation Satellite System (CYGNSS) mission can detect changes in the ocean surface roughness, expressed as an increase in reflectivity when the surface becomes smoother. Therefore, decreased ocean surface roughness correlated with a recent dust storm represents a key indicator of the presence of phytoplankton. In this paper, we present for the first time the capability of bistatic radar measurements to provide an effective tool to map information of areas covered with phytoplankton, establishing bistatic radar as the most reliable remote sensing tool for detecting phytoplankton blooms and monitoring their presence across the ocean surface. We present the analysis of low ocean roughness signatures in the bistatic radar measurements from the CYGNSS mission observed in the Gulf of Mexico after the Sahara’s dust storm circulation from Africa to the American continent from May to July 2020. CYGNSS data offer an unprecedented spatial and temporal coverage that allows for the analysis of those signatures at time scales of 1-day, robust to the presence of clouds and dust clouds. The described capability benefits the improvement of models, promoting a better constraint of the supply of dust into the ocean surface and a better understanding of the excess of nutrients that triggers the phytoplankton blooms. This new bistatic radar application enhances our understanding on the role of dust storms on ocean biogeochemistry and the global carbon cycle.

Funder

Jet Propulsion Laboratory

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Cross-domain Radar Emitter Recognition Method with Few-shot Learning;2023 4th International Symposium on Computer Engineering and Intelligent Communications (ISCEIC);2023-08-18

2. Detecting Algal Bloom Using Cygnss and ERA-5 Data;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16

3. A Controlled Ground-Based Experiment to Assess the Capabilities of GNSS-R for Marine Litter Detection in a Flume;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16

4. Improving Spaceborne GNSS-R Algal Bloom Detection with Meteorological Data;Remote Sensing;2023-06-15

5. Latest Advances in the Global Navigation Satellite System—Reflectometry (GNSS-R) Field;Remote Sensing;2023-04-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3