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| SIFT (Short-Term Inundation Forecast for Tsunamis) | |
|---|---|
| Name | SIFT (Short-Term Inundation Forecast for Tsunamis) |
| Developer | Pacific Marine Environmental Laboratory |
| Released | 2008 |
| Latest release version | (varies) |
| Programming language | Fortran, C, Python |
| Operating system | Linux |
| Genre | Tsunami forecasting |
SIFT (Short-Term Inundation Forecast for Tsunamis) is a forecasting system designed to produce rapid inundation and waveform predictions following tsunami-generating earthquakes and landslides. It couples precomputed numerical models with real-time observations to produce scenario-constrained forecasts for coastal response, providing inputs to emergency managers, tidal observatories, and hazard mitigation programs. SIFT integrates modeling, assimilation, and dissemination components developed and maintained within a collaboration among oceanographic and geophysical institutions.
SIFT is a software suite that combines tsunami source inversion, numerical propagation, and high-resolution inundation modeling to provide short-term forecasts for threatened coastlines. The project links capabilities from the National Oceanic and Atmospheric Administration, National Weather Service, Pacific Marine Environmental Laboratory, and regional partners to support operational centers such as the National Tsunami Warning Center and the Pacific Tsunami Warning Center. The system ingests data from networks like the Deep-ocean Assessment and Reporting of Tsunamis and coastal tide gauges maintained by organizations including the National Data Buoy Center to produce forecasts used by agencies such as the Federal Emergency Management Agency and regional authorities in countries like Japan, Chile, and Indonesia.
Development began in the early 2000s as observational networks expanded after events that involved agencies such as United States Geological Survey and research institutions including Scripps Institution of Oceanography and University of Washington. High-profile tsunamis such as the 2004 Indian Ocean earthquake and tsunami and the 2011 Tōhoku earthquake and tsunami motivated accelerated work, integrating contributions from researchers at University of Hawaii at Manoa, University of California, San Diego, and international partners like Geoscience Australia. Funding and oversight have involved entities such as the Office of Naval Research and intergovernmental collaborations with the Intergovernmental Oceanographic Commission of UNESCO.
SIFT uses a hybrid approach: precomputed Green’s function ensembles or unit-source databases are paired with rapid inversion algorithms to estimate source parameters, then applied to nested numerical models for propagation and inundation. The inversion step draws on real-time observations from instruments like DART II buoys and coastal tide stations to constrain seismic source models produced by agencies such as the USGS National Earthquake Information Center. Forward modeling employs hydrodynamic solvers that have roots in research by groups at Plymouth Marine Laboratory and modeling frameworks similar to those used in the Community Earth System Model community, adapted for high-resolution coastal grids.
Primary inputs include tsunami waveform data from the Deep-ocean Assessment and Reporting of Tsunamis network, seismic parameters from the United States Geological Survey, bathymetry and topography datasets such as those produced by National Geophysical Data Center and General Bathymetric Chart of the Oceans, and tide records from agencies like the National Ocean Service. Processing pipelines integrate software libraries and toolkits contributed by institutions such as NOAA and research groups at Massachusetts Institute of Technology and California Institute of Technology for data quality control, baseline removal, and temporal alignment. The system also leverages high-resolution coastal elevation models provided by programs like the National Coastal Mapping Program to drive inundation computations.
SIFT generates multiple products: predicted offshore waveforms, arrival times, maximum amplitude maps, and high-resolution inundation maps for specific communities. Products are formatted for operational centers including the National Tsunami Warning Center and distributed through communication channels used by FEMA, regional disaster management agencies in countries such as New Zealand and Peru, and academic partners at institutions like University of Tokyo. Visualizations and data feeds are compatible with decision-support platforms used by agencies like the International Tsunami Information Center and international warning systems coordinated by the Intergovernmental Oceanographic Commission.
Validation draws on historical events including the 2006 Kuril Islands earthquake and tsunami, the 2010 Chile earthquake, and the 2011 Tōhoku earthquake and tsunami, comparing model outputs with observations from DART II buoys, tide gauges maintained by the Japan Meteorological Agency, and post-event field surveys conducted by teams from USGS and universities. Performance metrics include arrival-time error, amplitude bias, and inundation extent correctness; evaluations have been presented in venues such as meetings of the American Geophysical Union and publications involving collaborators at Woods Hole Oceanographic Institution and Instituto Geofísico del Perú.
SIFT is applied operationally for emergency notifications, evacuation planning, and post-event reconnaissance prioritization by agencies like FEMA and academic consortia including the International Tsunami Research Group. It supports scenario development for coastal resilience programs run by entities such as the World Bank and national ministries in Chile, Indonesia, and Philippines. Limitations arise from uncertainties in rapid source estimation, incomplete observational coverage of the DART II and tide-gauge networks, and computational constraints when producing high-resolution inundation forecasts for many segments simultaneously; these constraints have motivated integration with cloud computing resources and collaborations with supercomputing centers such as Oak Ridge National Laboratory and Lawrence Berkeley National Laboratory.
Category:Tsunami warning systems