{"id":177747,"date":"2022-06-27T15:03:25","date_gmt":"2022-06-27T19:03:25","guid":{"rendered":"https:\/\/web.uri.edu\/gso\/?p=177747"},"modified":"2022-07-06T09:06:41","modified_gmt":"2022-07-06T13:06:41","slug":"knowing-whats-possible-sp22","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/gso\/publications\/aboard-gso\/knowing-whats-possible-sp22\/","title":{"rendered":"Knowing What’s Possible"},"content":{"rendered":"

Knowing What's Possible<\/h1>

A doctoral student is pioneering a model for simulating the fury of hurricanes.<\/p><\/div><\/div>

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By Alexander Castro<\/h4>\n

Predicting the future has never been precise. Sheep or bird entrails were the ancient Romans\u2019 preferred methods. Saint Augustine, who despised all things magical, cataloged water and the dead as other oracular mediums. Aeromancy, or divination by clouds and wind currents, was another arcane specialty.<\/p>\n

\n

And today\u2019s clairvoyants? They\u2019re arguably the scientists who have swapped superstitious logic for algorithmic finesse, like Mansur Ali Jisan, a Ph.D. candidate and research assistant at GSO. He\u2019s developed the Hurricane Boundary Layer (HBL) model, an improved way to forecast wind during a hurricane.<\/p>\n

\u201cThe basic idea,\u201d Jisan says, \u201cis when a hurricane makes landfall, when it transitions from the ocean toward the land, there\u2019s a change in structure and intensity\u2026When a storm is over water, there\u2019s less drag. When it makes landfall, it interacts with different types of land.\u201d
\nThose interactions make for surface friction, which the HBL model uses to simulate a hurricane\u2019s vortex. Using data from the National Hurricane Center about the storm\u2019s position, speed, and radius, the vortex structure can even be modified throughout the forecast\u2019s duration.<\/p>\n

\u201cPrevious teams have worked on hurricanes as they move over the ocean,\u201d says David Smith, GSO\u2019s associate dean. \u201cNow they\u2019re moving onto shore with Mansur. What he\u2019s really adding is that all the land is not the same.\u201d<\/p>\n

<\/div>
Our research is not just academic, where a few people read your papers and that\u2019s it.<\/blockquote>Prof. Isaac Ginis<\/cite><\/div><\/section>\n

Jisan offers the Miami area as an example: a hurricane will encounter high friction in the city, but nearby wetlands will offer less resistance. The HBL model accommodates these differences in surface and roughness, all of which affect a hurricane\u2019s primary form of destruction: flooding. \u201cWater is the main impact that a storm leaves,\u201d Jisan says. \u201cIf you don\u2019t have good wind in your storm-surge simulation, your water-level prediction could be underestimated or overestimated.\u201d<\/p>\n

Another advantage of the HBL model is its simplicity compared to numerical weather prediction (NWP). Numerical models are widely used but they require inputting all sorts of specialist physics. The HBL\u2019s biggest extravagance, meanwhile, is \u201cincorporating surface friction,\u201d Jisan explains. \u201c[This] makes our model quite simple.\u201d<\/p>\n

That doesn\u2019t mean less accurate. So far, tested against historical storms like hurricanes Florence (1918) and Michael (2018), Jisan says the model has generated \u201cquite reasonable comparisons\u201d against the observation data.<\/p>\n

Accuracy and usability are indeed the goal, as the HBL model has been designed to \u201cbe used by anyone,\u201d Jisan says. \u201cI really hope that once we publish this code in open source, that emergency managers can use this for decision making.\u201d<\/p>\n

Jisan got a real-life chance to validate his model as part of his work with the Hurricane Research Group at GSO, led by Isaac Ginis, who also serves as Jisan\u2019s doctoral advisor. Ginis\u2019 group is affiliated with the Coastal Resilience Center, a Department of Homeland Security-funded effort that focuses on mitigating coastal hazards.<\/p>\n

\u201cOur research is not just academic, where a few people read your papers and that\u2019s it,\u201d Ginis says. \u201cWe are not only developing this code, we\u2019re making it relevant to the decision makers.\u201d During Hurricane Henri in 2021, Ginis\u2019 hurricane crew made predictions for the storm, with Jisan handling the wind calculations, and sent their results to emergency management in Rhode Island. Ginis describes Jisan as a highly enthusiastic collaborator, one who\u2019s made \u201csignificant contributions\u201d to the Hurricane Research Group.<\/p>\n

\u201cNot many people venture to develop models,\u201d Ginis says.<\/p>\n

Maybe that\u2019s because modeling a hurricane involves writing code for enormous supercomputers. The myriad calculations that comprise simulations need a massive amount of energy to run. Spewing carbon emissions while fighting hurricanes is a patently contemporary paradox, and it\u2019s something Jisan has considered. The HBL model is scalable, meaning it \u201ccan be run using any number of [CPUs] depending on the demand of the simulation.\u201d<\/p>\n

Jisan\u2019s typical setup uses 256 processors to spit out a five-day forecast. That\u2019s still an improvement over NWP models Jisan has tested, one of which takes around three hours and 480 CPUs to produce a five day forecast. An HBL-based forecast, meanwhile, takes about an hour.<\/p>\n

All that power doesn\u2019t come cheap, but thanks to the Coastal Resilience funding, Jisan can achieve such gargantuan number crunching. That\u2019s one perk of living in the US:\u201cIt really allows you to do the research you want to do,\u201d Jisan says.<\/p>\n

For him, that research is generally grounded in practicality and social benefit: \u201cI always try to think of how [my research] is going to impact our society,\u201d Jisan says. \u201cHow will it make people more aware of climate change or sea-level rise?\u201d<\/p>\n

Thoughts Not Far from Home<\/h3>\n

His native Bangladesh is more than aware. The southeast asian country endures a \u00admarathon of intense weather yearly. Outside of the monsoon season\u2019s unending rain, Jisan says hurricanes aren\u2019t uncommon. Yes, the nation is geographically poised to be stormy, but rising seas and temperatures don\u2019t help.<\/p>\n

\u201cPeople are unequivocal that it\u2019s causing hazard already in their lives, especially people living near the coast,\u201d Jisan says. His career began in orbit of these very issues, as a civil engineer at the Institute of Water and Flood Management in Dhaka, the Bangladeshi capital.
\nAccording to 2021 stats from Germanwatch, a Berlin nonprofit, Bangladesh placed seventh in the Climate Risk Index, an aggregate ranking of adverse climate events from 2000-2019. Yet a 2021 study in the journal Energy Strategy Reviews notes that Bangladesh contributes only 0.56 percent of global CO2 emissions.<\/p>\n

That\u2019s one example of the interaction between climate change and social inequity. No wonder Jisan praises GSO\u2019s Justice, Equity, Diversity and Inclusion initiatives as \u201ca really essential part of having a good research environment.\u201d<\/p>\n

To that same end, he believes public outreach is crucial to the researcher\u2019s approach: \u201cYou make a connection with the public and see what they\u2019re thinking\u2026and whether the research I\u2019m doing is helping them. What are the things people are actually worried about? What\u2019s on their minds?\u201d<\/p>\n

Jisan had a lot on his mind after finishing his Ph.D. comprehensive exams, so he went in search of a relaxing hobby. First stop: Best Buy, where he bought a basic drone, the DJI Mini 2. Next stop: New Hampshire and the Adirondacks, where Jisan\u2019s drone snapped many vivid sceneries from above. Jisan\u2019s optimism is almost tangible in these photos: Sweeps of red foliage into bright green. Clusters of yellow. Ripples sculpted into water. A smoldering sunset or two. And locally, the bridges, lighthouses and wee lil\u2019 islands that populate Rhode Island\u2019s coastline and bays.<\/p>\n

\u201cI really like living in this area, right near the coast,\u201d Jisan says. He has a one-minute commute to GSO from his home, where he lives with wife Nadia and their pet bunny Oreo (who has an Instagram, naturally). Jisan even appreciates \u201cthe cold weather system\u201d of New England. Yes, he\u2019s a fan of the snow\u2014the scourge of many a grumpy Rhode Islander.<\/p>\n

But the occasional blizzard seems a fair tradeoff for Rhode Island\u2019s historical luck when it comes to avoiding the worst of hurricanes. Other coastal communities aren\u2019t so lucky, so there\u2019s plenty of incentive to craft more accurate models for extreme weather. After all, a prophecy that can\u2019t be acted upon isn\u2019t very useful.<\/p>\n","protected":false},"excerpt":{"rendered":"

By Alexander Castro Predicting the future has never been precise. Sheep or bird entrails were the ancient Romans\u2019 preferred methods. Saint Augustine, who despised all things magical, cataloged water and the dead as other oracular mediums. Aeromancy, or divination by clouds and wind currents, was another arcane specialty. And today\u2019s clairvoyants? They\u2019re arguably the scientists […]<\/p>\n","protected":false},"author":2120,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[7,2983],"tags":[],"class_list":["post-177747","post","type-post","status-publish","format-standard","hentry","category-aboard-gso","category-spring-2022"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/posts\/177747","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/users\/2120"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/comments?post=177747"}],"version-history":[{"count":5,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/posts\/177747\/revisions"}],"predecessor-version":[{"id":177755,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/posts\/177747\/revisions\/177755"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/media?parent=177747"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/categories?post=177747"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/gso\/wp-json\/wp\/v2\/tags?post=177747"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}