A Hierarchical Bayesian Approach for Bias Correction of NEXRAD Dual-Polarization Rainfall Estimates: Case Study on Hurricane Irma in Florida

Author(s):  
Yingzhao Ma ◽  
V. Chandrasekar
2016 ◽  
Vol 16 (6) ◽  
pp. 15 ◽  
Author(s):  
Hairong Gu ◽  
Woojae Kim ◽  
Fang Hou ◽  
Luis Andres Lesmes ◽  
Mark A. Pitt ◽  
...  

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 727
Author(s):  
Eric J. Ma ◽  
Arkadij Kummer

We present a case study applying hierarchical Bayesian estimation on high-throughput protein melting-point data measured across the tree of life. We show that the model is able to impute reasonable melting temperatures even in the face of unreasonably noisy data. Additionally, we demonstrate how to use the variance in melting-temperature posterior-distribution estimates to enable principled decision-making in common high-throughput measurement tasks, and contrast the decision-making workflow against simple maximum-likelihood curve-fitting. We conclude with a discussion of the relative merits of each workflow.


2014 ◽  
Vol 61 (1) ◽  
pp. 116-132 ◽  
Author(s):  
Xi Li ◽  
Kiwamu Ishikura ◽  
Chunying Wang ◽  
Jagadeesh Yeluripati ◽  
Ryusuke Hatano

Author(s):  
Alexander Kolpakov ◽  
Austin Marie Sipiora ◽  
Caley Johnson ◽  
Erin Nobler

This case study presents findings from an analysis of the emergency preparation and response for Hurricane Irma, the most recent hurricane impacting the Tampa Bay region. The Tampa Bay region, in particular, is considered one of the most vulnerable areas in the United States to hurricanes and severe tropical weather. A particular vulnerability stems from how all petroleum fuel comes to the area by marine transport through Port Tampa Bay, which can be (and has been in the past) impacted by hurricanes and tropical storms. The case study discussed in this paper covers previous fuel challenges, vulnerabilities, and lessons learned by key Tampa Bay public agency fleets during the past 10 years (mainly as a result of the most recent 2017 Hurricane Irma) to explore ways to improve the area’s resilience to natural disasters. Some of the strategies for fuel-supply resiliency include maintaining emergency fuel supply, prioritizing fuel use, strategically placing the assets around the region to help with recovery, investing in backup generators (including generators powered by alternative fuels), planning for redundancies in fuel supply networks, developing more efficient communication procedures between public fleets, hurricane preparedness-planning, and upgrading street drainage systems to reduce the threat of local flooding.


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