Tag: hurricane

In 2022, Xavier University of Louisiana (XULA) launched their journey to future-proofing with the cloud. Modernizing the university’s technology was a top priority to help improve the security of the university, improve business continuity, and solve the unique challenges of the university’s location. Working together with AWS and AWS Partners Strata Information Group and VMware, XULA migrated over 90 percent of its critical systems to the cloud, boosted its cybersecurity posture, and reduced IT costs.

While the 2023 hurricane season kicks off June 1, the reality is that AWS is working to help organizations and communities respond to hurricanes long before a storm forms. Throughout the year, AWS Disaster Response develops and tests new innovations that utilize cloud technology to enable more efficient disaster response capabilities for our customers and relief organizations.

On September 28, 2022, Hurricane Ian made landfall in Southwest Florida. At the request of standby organizations Help.NGO and Information Technology Disaster Resource Center (ITDRC), the AWS Disaster Preparedness and Response team assisted with response operations across a variety of functions in the aftermath of Hurricane Ian.

The Water Institute of the Gulf runs its storm surge and wave analysis models on Amazon Web Services (AWS)—a task that sometimes requires large bursts of compute power. These models are critical in forecasting hurricane storm surge event (like Hurricane Laura in August 2020), evaluating flood risk for the Louisiana and other coastal states, helping governments prepare for future conditions, and managing the coast proactively.

Better estimates of hurricane wind speeds can lead to better decisions around evacuations and general hurricane response planning, saving both lives and property. Hurricane windspeed estimates are currently made using the manual Dvorak technique. The National Hurricane Center releases them every three to six hours. Artificial intelligence (AI) experts with the IMPACT team at NASA’s Marshall Space Flight Center and Development Seed created the Deep Learning-Based Hurricane Intensity Estimator to automate this process.