Using EnKF Data Assimilation to Improve Predictions of Volcanic Ash Dispersion
Accurate forecasts of volcanic ash dispersion patterns as well as the ability to quantify cloud top heights and mass loading properties are critical in mitigating the risks associated with volcanic eruptions. Currently, physical dispersion models and satellite observations are the primary methods used to forecast and monitor volcanic ash clouds,
A Channel Selection Methodology For Enhancing Volcanic SO₂ Monitoring Using FY-3E/HIRAS-II Hyperspectral Data
The Hyperspectral Infrared Atmospheric Sounder Type II (HIRAS-II) aboard the Fengyun 3E (FY-3E) satellite provides valuable data on the vertical distribution of atmospheric states. However, effectively extracting quantitative atmospheric information from the observations is challenging due to the large number of hyperspectral sensor channels, interchannel correlations, associated observational errors, and
卫星红外数据火山热点识别算法研究进展
使用卫星红外数据识别火山热点可以实现安全且低成本的监测全球火山活动。本文综述了卫星红外数据在火山热点识别中的算法研究进展,特别强调了算法的分类和发展历史。这些算法主要基于火山活动时热点所在像元中红外通道亮温升高的原理,根据考虑火山及其周围地物的空间和时间特性来识别火山热异常,算法大致分为4种主要类型:空间特征算法、时间特征算法、综合特征算法和人工智能算法。从算法分类、特性、适用范围、局限性方面,厘清了当前国内外利用遥感的方式进行火山热点识别的现状,为理解和改进火山热点检测技术提供了全面的分类和评估,对火山热遥感前沿理论和技术发展具有重要意义。
Retrieval of Volcanic Ash Cloud Base Height Using Machine Learning Algorithms
There are distinct differences between radiation characteristics of volcanic ash and meteorological clouds, and conventional retrieval methods for cloud base height (CBH) of the latter are difficult to apply to volcanic ash without substantial parameterisation and model correction. Furthermore, existing CBH inversion methods have limitations, including the involvement of many