Geosciences Barcelona - CSIC, Barcelona, Spain.
Department of Applied Physics - Meteorology, University of Barcelona, Barcelona, Spain.
Sci Rep. 2023 Feb 1;13(1):1853. doi: 10.1038/s41598-023-28902-8.
Data acquired by a dense seismic network deployed in the Cerdanya basin (Eastern Pyrenees) is used to track the temporal and spatial evolution of meteorological events such as rainfall episodes or thunderstorms. Comparing seismic and meteorological data, we show that for frequencies above 40 Hz, the dominant source of seismic noise is rainfall and hence the amplitude of the seismic data can be used as a proxy of rainfall. The interstation distance of 1.5 km provides an unprecedented spatial resolution of the evolution of rainfall episodes along the basin. Two specific episodes, one dominated by stratiform rain and the second one dominated by convective rain, are analyzed in detail, using high resolution disdrometer data from a meteorological site near one of the seismic instruments. Seismic amplitude variations follow a similar evolution to radar reflectivity values, but in some stratiform precipitation cases, it differs from the radar-derived precipitation estimates in this region of abrupt topography, where radar may suffer antenna beam blockage. Hence, we demonstrate the added value of seismic data to complement other sources of information such as rain-gauge or weather radar observations to describe the evolution of ground-level rainfall fields at high spatial and temporal resolution. The seismic power and the rainfall intensity have an exponential relationship and the periods with larger seismic power are coincident. The time intervals with rain drops diameters exceeding 3.5 mm do not result in increased seismic amplitudes, suggesting that there is a threshold value from which seismic data are no longer proportional to the size of the drops. Thunderstorms can be identified by the recording of the sonic waves generated by thunders, with. Single thunders detected to distances of a few tens of kilometers. As the propagation of these acoustic waves is expected to be strongly affected by parameters as air humidity, temperature variations or wind, the seismic data could provide an excellent tool to investigate atmospheric properties variations during thunderstorms.
利用在塞达尼亚盆地（东比利牛斯山）部署的密集地震网络获取的数据，可追踪降雨事件或雷暴等气象事件的时间和空间演变。通过比较地震和气象数据，我们表明，对于高于 40 Hz 的频率，地震噪声的主要来源是降雨，因此地震数据的振幅可用作降雨的代理。1.5 公里的台站间距提供了盆地沿线降雨事件演变的前所未有的空间分辨率。使用附近一个气象站的高分辨率雨滴谱仪数据，详细分析了两个特定的事件，一个主要由层状雨主导，另一个主要由对流雨主导。地震振幅变化与雷达反射率值的演变相似，但在某些层状降水情况下，与该地区雷达可能遭受天线波束阻塞的雷达衍生降水估计不同。因此，我们证明了地震数据的附加价值，可补充雨量计或天气雷达观测等其他信息来源，以描述高时空分辨率的地面降雨场的演变。地震功率和降雨强度呈指数关系，并且具有较大地震功率的时间段是一致的。雨滴直径超过 3.5 毫米的时间间隔不会导致地震振幅增加，这表明存在一个阈值，超过该阈值后，地震数据不再与雨滴的大小成正比。通过记录雷声产生的声波，可以识别雷暴，这些声波可以探测到几十公里外的单个雷暴。由于这些声波的传播预计会受到空气湿度、温度变化或风等参数的强烈影响，因此地震数据可以成为研究雷暴期间大气特性变化的极好工具。
