The Swedish National Seismic Network (SNSN) was modernized and rapidly expanded during the period 1998–2012. The network currently operates 68 permanent seismic stations, all with broadband instruments supplying real‐time continuous data at 100 samples per second. Continuous data from 10 stations are shared with the international community via Orfeus, and approximately 10 stations of their individual choice are shared with institutes in neighboring countries (Denmark, Finland, Norway, and Germany). The SNSN uses the South Iceland Lowland (SIL) system as the primary system for automatic detection and event definition. In addition, an in‐house system based on migration and stacking is used for automatic detection of small events, and implementations of SeisComP (SC) and Earthworm are used primarily for rapid detection of larger regional events. Global monitoring is performed with SC, using approximately 250 global stations, and we operate a continuous rapid risk assessment system serving Swedish crisis management authorities. Since the start of automatic processing in August 2000, the SNSN has recorded and interactively analyzed more than 171,000 seismic events, of which 10,700 were earthquakes with local magnitudes ranging from around −1 to 4.3. The microearthquake activity detected in the last 20 yr has significantly improved the identification and understanding of seismically active structures in Sweden.

中文翻译：

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现代瑞典国家地震台网：板内微地震观测两个十年

瑞典国家地震台网（SNSN）在1998-2012年期间进行了现代化改造并迅速扩展。该网络目前运营着68个永久地震台站，所有这些台站都配有宽带仪器，以每秒100个样本的速度提供实时连续数据。通过Orfeus与国际社会共享来自10个站点的连续数据，并与邻国（丹麦，芬兰，挪威和德国）的机构共享大约10个站点的个人选择。SNSN使用南冰岛低地（SIL）系统作为自动检测和事件定义的主要系统。此外，基于迁移和堆叠的内部系统用于自动检测小事件，而SeisComP（SC）和Earthworm的实现主要用于快速检测较大的区域事件。通过SC在全球大约250个站点进行全球监控，并且我们为瑞典危机管理机构提供连续不断的快速风险评估系统。自2000年8月开始自动处理以来，SNSN记录并交互分析了171,000多个地震事件，其中10,700是局部震级在-1到4.3之间的地震。在过去的20年中检测到的微地震活动大大改善了瑞典对地震活动结构的识别和了解。SNSN记录并互动分析了171,000多个地震事件，其中10,700是局部震级在-1到4.3之间的地震。在过去的20年中检测到的微地震活动大大改善了瑞典对地震活动结构的识别和了解。SNSN记录并互动分析了171,000多个地震事件，其中10,700是局部震级在-1到4.3之间的地震。在过去的20年中检测到的微地震活动大大改善了瑞典对地震活动结构的识别和了解。