Global Flood Alerting with an Ensemble of Models and Remotely Sensed Observations
- 1University of Alabama in Huntsville, Huntsville, AL, United States of America (mtglasscoe@gmail.com)
- 2Department of Energy, Washington DC, United States of America
- 3ImageCat, Inc., Long Beach, CA, United States of America
- 4Niyam IT, Kihei, HI, United States of America
- 5Indiana University, Bloomington, IN, United States of America
- 6Pacific Disaster Center, Kihei, HI, United States of America
Flooding is one of the most frequent and costliest extreme weather events. The Model of Models (MoM) generates integrated products using ensembled hydrologic models and flood outputs derived from Earth observations. MoM provides global flood early warning and near-real time flood severity estimation. MoM results are shared via the Pacific Disaster Center’s (PDC) DisasterAWARE® multi-hazard alerting platform to the global community. Currently, DisasterAWARE incorporates Model of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context of population and infrastructure that may become affected. Automated procedures categorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users along with other flood products that assess potential impacts.
How to cite: Glasscoe, M., Kar, B., Schumann, G., Mendoza, M., Bausch, D., Wang, J., and Hampe, G.: Global Flood Alerting with an Ensemble of Models and Remotely Sensed Observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20837, https://doi.org/10.5194/egusphere-egu24-20837, 2024.
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