The period since has seen substantial advancements, driven by the adoption of new sensor technologies, the establishment of key relationships with international organizations such as the National Oceanic and Atmospheric Administration (NOAA), Caribbean Meteorological Organization (CMO), and the UK Met Office. The fostering of these relationships has grown out of the recognition of the need for accurate and timely weather predictions due to the Caribbean's vulnerability to extreme weather impacts, particularly flooding and storm surge. Flooding and storm surge pose a persistent threat to the Cayman Islands, exacerbated by factors such as low-lying terrain and climate change, which has increased the intensity of heavy rainfall, tropical cyclones, and rising sea-level.
To address these challenges, the development and implementation of a "Smart Flood Early Warning Detection System" are proposed. This innovative system will integrate a weather sensor network to collect real-time data on rainfall, water levels, and other environmental factors specific to the Cayman Islands. By applying machine learning algorithms to these data, the system will identify patterns and predict potential flooding events. Additionally, the integration of geospatial artificial intelligence (GeoAI) will provide precise location-based analytics, seeking to enhance the accuracy and timeliness of flood warnings.
Similar to other small Caribbean Islands, mesoscale weather phenomena are not well identified or even missed by global numerical weather models. To overcome this challenge, exploration into high- resolution modelling using the Weather Research and Forecasting (WRF) model is currently ongoing. The higher resolution output is anticipated to further improve our ability to provide accurate and timely forecast. Regarding storm surge, the National Hurricane Center is supporting the development of storm surge modelling specific to the Cayman Islands. The work is anticipated to be completed towards the end of 2025 and will be an invaluable tool for preparatory activities, well in advance of a tropical cyclone’s approach.
When disasters strike, obtaining a comprehensive operational picture of the affected area is crucial, including understanding the extent of the damage, the potential for further harm, and the immediate needs of the impacted population. Disaster management information systems, increasingly centered around geospatial data, play an essential role in linking this information with the resources available to address these needs. These systems allow for the coordination of search and rescue teams, fire brigades, police, hospitals, and supply depots, ensuring an effective response that mitigates further damage and aids in recovery efforts. The integration of early warning systems, coupled with geospatial mapping, is vital for assessing disaster risks and implementing measures to prevent hazards from having severe impacts.
Further strengthening the country's disaster preparedness, an implementation plan for Phase II of the National Emergency Notification System (NENS) is being developed, including the integration of SMS, a mobile app, and email alerts; with the system currently having over 8,000 users. Plans for 2024 aim to expand the user base through revised marketing strategies, ensuring more residents are connected to the system. This modernization of the nation’s alert and warning infrastructure allows emergency officials to quickly disseminate lifesaving information, significantly enhancing the ability to protect life and property when time is of the essence.
The inclusion of advanced meteorological data is crucial for improving the NENS predictive capabilities. By utilizing real-time weather data, the system can better anticipate conditions leading to flooding, ultimately ensuring that communities in the Cayman Islands are better prepared for flood events. As equally important, is the communication of the hazards and risks within the Government as well as the general public. Early warnings allow for a more timely and effective response to pending severe weather, allowing for preparatory efforts to lessen severe weather impacts. The advancements in weather forecasting, strategic partnerships with organizations like NOAA, and regional collaboration through the Caribbean Meteorological Organization (CMO) have crystalized to further grow the capacity of the CINWS.
This includes regional collaboration through the CMO Caribbean WIS 2.0 node, which involved training, hands-on practice and the CINWS working with other NMHSs across the region so that the CINWS now exchanges weather observations in real-time nationally, regionally, and globally. The Cayman Islands has also been supported by the NOAA/NWS/NHC through the operational regional hurricane warning system, which included two week-long attachments for its meteorologists at the NHC. More recently, NOAA/NWS also supported training and capacity development through a 4-month training course for a CINWS meteorologist at the US Weather Prediction Center International Desk. Further, CMO Headquarters has facilitated the participation of the Cayman Island National Weather Service and Hazard Management Department in the NOAA storm surge forecasting training workshops held since 2022, with the 2024 workshop hosted by the Caribbean Institute of Meteorology and Hydrology (CIMH), the Technical Organ of the CMO.
These activities along with the modernization of emergency notification systems have been instrumental in advancing a more resilient and informed approach to managing the impacts of extreme weather. Ultimately, the Cayman Islands hydro-meteorological early warning system and services will be improved by implementing IoT initiatives and emerging technologies for island-wide monitoring and warning from integrating multiple data sources, low-latency telemetry and communication devices, and real-time data processing. This will enable the generation of more accurate and timely warnings of severe and extreme weather events and thus allow the country to contribute cogently to the global Early Warnings for All initiative.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner