Collaborative Research: Rainfall estimation accuracy and classification from deep underwater sound measurements

合作研究：深层水下声音测量的降雨估计精度和分类

• 批准号: 0824927
• 负责人: Jeffrey Nystuen
• 金额: $ 13.9万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2013-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0824927&HistoricalAwards=false
• 关键词: Collaborative; Research; Rainfall; estimation; accuracy

The sound produced by rainfall underwater can be used to quantitatively measure rainfall at sea. The Ionian Sea Rainfall Experiment (ISREX) and the operational POSEIDON project are unique data sets that combine deep underwater acoustic measurements with high resolution radar and can be used to evaluate the performance of the acoustic measurement. Acoustic rainfall rate accuracy will be estimated using disdrometer-calibrated and gauge adjusted high-resolution X-band radar (XPOL) data from the Ionian Sea Rainfall Experiment (ISREX) and subsequently evaluated using operational PAL/ground-radar/buoy-anemometer (POSEIDON buoy and Hellenic Meteorological weather radar networks - Aegean and Ionian Seas) and archived PAL/rain gauge data (ITCZ - Pacific Ocean). The acoustic classification of rainfall will be evaluated in comparison with radar estimated fields of rainfall classification. A model incorporating the influence of the spatial and temporal scale storm structure on the acoustic signal will be developed and tested using ISREX and Poseidon data. Finally, the performance of acoustic data in retrieving raindrop size distributions (rainfall DSDs) will be evaluated through comparisons with dual-polarization radar DSD retrievals from ISREX and the operational radar measurements over the POSEIDON buoy in the north Aegean Sea. Understanding how to use passive ambient sound to monitor the marine environment is a fundamental tool that will contribute to our ability to monitor important climate processes globally. In particular, rainfall distribution is an important component of the global water cycle and has a strong acoustic signal on ocean surface constituting ~75% of global rainfall. Exploring the acoustic signal of rainfall is needed to use it for quantitative estimation of rain including presence, classification, accumulation and raindrop size distributions. Improving our ability to measure rain over the oceans is critical to describing global water cycle and understanding potential trends in climate change, and for validating estimates by global coverage satellite sensor. Monitoring and predicting climate change has huge broader impacts on human society. Utilizing the underwater acoustic signal from rain will allow rainfall climatology to be measured in many remote or severe weather regions (Atlantic and Pacific ITCZ, North Atlantic, etc.). Rainfall makes only one of the acoustic signals that are part of the marine ambient sound budget. Other physical processes that can be measured are wind and sea state (bubbles) conditions. A more complete understanding of the acoustic signal will allow all of these processes (rain, wind and bubbles) to be measured from sub-surface platforms allowing all weather, all season data collection. These include many new ocean instrumentation platforms including sub-surface moorings, cabled networks, drifters, profilers, gliders, etc. Passive acoustic monitoring for marine mammals, especially whales, is critical to ecological studies of these animals. Finally, the impact of human-generated sound on the marine environment is of growing concern. A collateral result of this work will be to better monitor the marine sound budget to provide fundamental baseline data to allow informed decisions regarding management of sound-producing human activities in the ocean.

水下降雨产生的声音可用于定量测量海上降雨。爱奥尼亚海降雨实验（ISREX）和实际的POSEIDON项目是将深水水声测量与高分辨率雷达相结合的独特数据集，可用于评估声学测量的性能。声波降雨率精度将使用来自爱奥尼亚海降雨实验（ISREX）的disdrometer校准和gauge调整的高分辨率x波段雷达（XPOL）数据进行估计，随后使用操作PAL/地面雷达/浮标风速计（POSEIDON浮标和希腊气象雷达网络-爱琴海和爱奥尼亚海）和存档PAL/雨量计数据（ITCZ -太平洋）进行评估。将对降雨的声学分类与雷达估计的降雨分类场进行比较。将利用ISREX和Poseidon数据开发和测试一个包含时空尺度风暴结构对声信号影响的模型。最后，通过与ISREX双极化雷达DSD数据和爱琴海北部POSEIDON浮标上的实际雷达测量数据进行比较，评估声学数据在反演雨滴大小分布（降雨DSDs）方面的性能。了解如何使用被动环境声来监测海洋环境是一个基本工具，它将有助于我们监测全球重要气候过程的能力。特别是，降雨分布是全球水循环的重要组成部分，在海洋表面具有很强的声信号，约占全球降雨量的75%。研究降雨的声信号是定量估计降雨的必要条件，包括降雨的存在、分类、积累和雨滴大小分布。提高我们测量海洋降雨的能力对于描述全球水循环和了解气候变化的潜在趋势，以及验证全球覆盖卫星传感器的估计至关重要。监测和预测气候变化对人类社会有着巨大而广泛的影响。利用雨水的水声信号将允许在许多偏远或恶劣天气地区（大西洋和太平洋ITCZ，北大西洋等）测量降雨气候学。降雨只产生海洋环境声预算中的一种声音信号。其他可以测量的物理过程是风和海况（气泡）条件。对声波信号的更全面了解将使所有这些过程（雨、风和气泡）能够从地下平台进行测量，从而实现所有天气、所有季节的数据收集。其中包括许多新的海洋仪器平台，包括水下系泊，电缆网络，漂流器，剖面仪，滑翔机等。被动声学监测海洋哺乳动物，特别是鲸鱼，对这些动物的生态研究至关重要。最后，人类产生的声音对海洋环境的影响日益受到关注。这项工作的附带结果将是更好地监测海洋声音预算，以提供基本基线数据，以便在管理海洋中产生声音的人类活动方面作出知情决定。