1. Contrary to Popular Belief, Maine is not the Easternmost State in the United States

If you want to see the first sunlight in the United States, you have to head to Maine, right? Well, not quite. While Maine is certainly easy and convenient to get to, it’s doesn’t see the day’s first sunrise in the United States. For that, you paradoxically have to go west. So far west, in fact, that you actually go east.

So where is the United States’ first sunrise? Believe it or not, it’s actually in Alaska. And it’s not in the main part of Alaska, either. You have to venture to the westernmost parts of the Aleutian Islands. Because those islands stretch so far west, they actually stretch into the Eastern Hemisphere. Excluding territories, the Aleutian Islands are the only part of the United States located in the Eastern Hemisphere. That means you’ll see not just the first sunrise in the United States, but one of the first sunrises in the entire world.

And Alaska’s claims don’t stop there.

2. Alaska is the Easternmost, Westernmost, and Northernmost State in the United States

At the eastern end of Semisopochnoi Island in the Aleutians, you’ll find the easternmost point in the United States (179.777°E). Interestingly, Semisopochnoi Island is actually closer to Russia than the main part of Alaska. But it’s far from the closest point to Russia. That belongs to Little Diomede Island in the Bering Strait. Little Diomede sits just 2.5 miles (4 km) from Big Diomede, it’s Russian counterpart, despite a 21-hour time difference between the two islands.

Only 65 miles (105 km) to the southeast of Semisopochnoi Island, you’ll find the westernmost point in the United States in the Alaska Maritime National Wildlife Refuge (179.143°W). Consisting of several uninhabited islands, the refuge is one of the most remote outposts on America’s northern frontier. But you can go further. The furthest, westernmost, and remotest post in the Aleutian Islands is Attu Station. At 172°E, Attu Station sits just 475 miles (770 km) from Ust’-Kamchatsk (Усть-Камчатск) on the Russian mainland. That’s a stark difference from the 1,500 miles (2,400 km) you’d have to travel to return to Anchorage.

Thankfully, things are much less complicated if you look north and south. It’s pretty clear that Alaska is the northernmost state in the United States. The town of Utqiagvik, which was formerly called Barrow, is the northernmost town in the United States. At 71.18 °N, it’s also one of the northernmost towns in the world. Only Canada, Russia, Norway, and Greenland have population centers further north.

And for the southernmost state…

3. Key West is not the Southernmost Point in the United States

While it’s true that Key West is the southernmost point in the Lower 48, it’s not even close to being the southernmost point in the United States. For that, you’ll need to look six degrees of latitude further south and a long way west. At the southern tip of Hawaii Volcanoes National Park, you’ll find Ka Lae, the actual southernmost point in the United States.

Additionally, if you include territories, you can go a lot further south. The southernmost point in a US territory is located at the Rose Atoll in American Samoa. The tiny island covers just 0.21 square kilometers and reaches latitudes of 14.6°S.

4. Los Angeles County Has a Larger Population than 41 States

It’s hard to believe, but Los Angeles County does actually have a larger population than 41 states. With a population of 10.04 million as of 2019, LA County is by far the most populous county in the United States.

And what are those 9 states that have a larger population? Here they are, ranked by population.

5. You Can Get on a Plane in Anchorage, Alaska and Be Anywhere in the Northern Hemisphere in Less Than 10 Hours

Amazingly, Anchorage is the only city in the world that can lay claim to this fact, even if you include the equivalent in the Southern Hemisphere. So what makes Anchorage so special? First, it has a major international airport that processes most cargo and many passengers bound for the United States from east Asia.

Not only does Anchorage have a major international airport, but it’s also the closest major international airport to either pole. Anchorage’s proximity to the North Pole makes it very quick and easy to fly over the pole to reach the other side of the world.

Consider an “over-the-pole” flight from New York City to Tokyo or Beijing. At the very minimum, you’re looking at 13 to 14 hours of total flight time. That’s because half of that time is spent getting from New York up to the pole.

When you start in Anchorage, you’re already most of the way to the pole. As a result, a direct flight from Anchorage to Frankfurt, Germany covers basically the same distance as a flight from Boston to Los Angeles.

6. Maine is a Particular Geographic Oddity

The state of Maine is best-known for its rugged outdoors, diverse wildlife, and world-famous seafood. However, being wedged between New Hampshire, Québec, and New Brunswick means that it’s got its fair share of geographic oddities.

• Maine is the closest US State to Africa. Quoddy Head, Maine sits just 3,154 miles from El Beddouzza, Morocco. For comparison, Florida is more than 4,000 miles from its nearest point on the African continent.
• If you take a road trip through the Lower 48, passing through each state only once, you always end in Maine. That’s because Maine is the only state in the continental United States that borders only one other state.
• More French is spoken in Maine than any state in the United States. When French explorers landed in eastern Canada back in the 1600’s, many of them settled in what is present-day Maine. Their descendants are still there today. It doesn’t hurt bordering two French-speaking Canadian provinces, either.
• Maine is the single largest producer of blueberries in the United States.
• Nobody knows how Maine got its name. All they know is that the name first appeared in writing in 1622.
• Despite the mystery behind its name, Maine was part of Massachusetts until 1819.
• Maine is larger than the other 5 New England States combined.
• If you visited one island per day, it would take you more than 9 years to visit every island in Maine
• At 3,478 miles, Maine’s coastline is longer than California’s (3,427 miles)
• Maine is home to the only desert in New England (40 acres outside Freeport). It formed 11,000 years ago, when a glacier deposited large amounts of sand on the site.
• Portland, Oregon is named after Portland, Maine. The Oregon city’s name was decided on a coin toss between Portland and Boston.

7. The United States is Home to the Shortest River in the World

The Roe River in Montana is only 200 feet long. That’s a stark contrast to the Missouri (2,341 miles) and Mississippi (2,202 miles), the United States’ two longest rivers.

8. Nebraska is the Only Triply Landlocked State in the United States

A triply landlocked state means that you have to pass through at least three other states (and/or Canadian Provinces) to reach the ocean. Nebraska is the only state in the United States that can make the claim of being triply landlocked. Don’t believe me? Have a look at some of its neighbors. Do note that in the table below, there may be more than one way to reach the ocean. The table lists the fewest states you need to pass through to reach the ocean.

9. Hawaii’s Mauna Kea is Taller Than Mt. Everest

The summit of Mauna Kea is only 13,796 feet above sea level, less than half the elevation of Everest’s summit (29,032 feet). However, Mauna Kea extends deep into the depths of the Pacific Ocean, while Everest is completely landlocked. The Pacific Ocean has a mean depth of over 14,000 feet, and the Hawaiian Trough reaches an average depth of over 18,000 feet.

As a result, when you account for the underwater part of Mauna Kea, it’s much taller than what you see on the Big Island in Hawaii. Mauna Kea is actually 32,808 feet tall, surpassing the height of Mt. Everest, despite the stark difference in elevation at each respective summits.

10. The Statue of Liberty Should Be in New Jersey, not New York

When you think of New York City, the Statue of Liberty is probably one of the first things that comes to mind. Lady Liberty is so quintessentially New York. But did you know that she should actually be in New Jersey, not New York?

When France gifted the Statue of Liberty to the United States in 1885, the US Geological Survey placed Liberty Island in New York’s 8th Congressional District. However, when you look at a map, you’ll see the Statue of Liberty is actually in New Jersey Waters. Regardless of what the state line says, the statue remains part of both the State and the City of New York.

Bonus: America’s Four Most Sprawling Cities Are All in Alaska

Alaska’s large size and small population means that its cities and towns have plenty of room to spread out. Indeed, Alaska has one of the lowest population densities in the United States. What surprises most people is that Alaska is home to the country’s four most sprawling cities.

From a strictly surface area to population ratio, the Alaskan Cities sprawl far more than Los Angeles, Phoenix, Houston, and every other major city in the Lower 48. For example, the City of Juneau is larger than Rhode Island and Delaware combined. And the winner, Yakutat, is larger than eight other states.

Bonus #2: You Can Get a Taste for Driving on the Left Side of the Road Without Leaving the United States. Just Head to the U.S. Virgin Islands.

It’s incredibly rare for a state or territory to drive on the opposite side of the road from its parent country. But the United States has one. The other country that boasts a few of them is the United Kingdom.

The US Virgin Islands is the only jurisdiction in the United States where you drive on the left. But unlike other locations that drive on the left, most cars in the USVI are imported from the mainland US, and still have the steering wheel on the left side of the car.

The United States purchased the Virgin Islands from Denmark in 1917. At the time, traffic in Denmark drove on the left. To keep the islands’ residents happy and prevent animosity towards the US, the federal government kept traffic in the Virgin Islands on the left side of the road.

While Denmark switched to driving on the right in 1967, along with much of the rest of Europe, the Virgin Islands never did. To this day, the US Virgin Islands continues to drive on the left. For what it’s worth, so do the British Virgin Islands.

Conclusion

Whether you’re trying to figure out how to drive on the left in the Virgin Islands or trying to catch the day’s first sunrise at its easternmost point in Alaska, the United States has plenty of geographic quirks and oddities to explore. But we’re just scratching the surface here. The US is a big country, and I could easily write another whole post or two about its weird geography. Have you been experienced any of the United States’ weird geography in your travels? Let us know in the comments below.

Top Photo: Afternoon Sun Illuminates a Beautiful Canyon Landscape
Canyonlands National Park, Utah – December, 2021

The post Weird Geography: 10 Bizarre and Unusual Facts About the United States appeared first on Matthew Gove Blog.

We’re going to look at the same four models as we did for Hurricanes Henri and Ida last summer. However, I just launched a complete redesign of this blog less than a week ago. That redesign will allow us to analyze the models in a way that’s much easier to compare, and hopefully much easier to understand. Let’s get started.

Big Picture Overview

When I look at the “big picture” meteorological setup, I immediately see just how similar this setup is to the October, 2021 nor’easter. That storm slammed into southern New England on 26 October, packing wind gusts over 100 mph (160 km/h) and heavy rains. Trees and power lines were down all over the place, knocking out power for several days. At one point all of Massachusetts south and east of the I-95 corridor was 100% without power.

Likewise, the current storm is a rapidly strengthening, or “bombing” cyclone. To be classified as a bomb cyclone, a storm must undergo a 24 millibar pressure drop in 24 hours. Will that happen with this storm? It remains to be seen, but it’s quite likely.

On the upper air map, you’ll see a large, powerful trough digging south over the Carolinas. That trough will rapidly strengthen, undergoing bombogenesis as it pull north. Look at all the energy, shown in the orange and red colors, off the coast of Georgia and Florida.

What Causes Bombogenesis?

There’s one major feature on the above map that jumps out at me. See the corridor of strong winds that stretches from northern Mexico to the southern tip of Florida? That’s the subtropical jet, which serves two purposes here.

1. Funnels a nearly endless stream of rich tropical moisture from the Gulf of Mexico into the developing bomb cyclone.
2. Exerts a west-to-east force on the southern edge of the nor’easter, which accelerates the spin of the upper-level low.

Both influences will have significant impacts on rain and snowfall totals, as well as wind speeds. We’ll dive into those details shortly. Furthermore, even without the subtropical jet, the storm will track pretty much right over the Gulf Stream. The Gulf Stream alone provides more than enough fuel for the storm to rapidly strengthen and maintain itself.

Similarities to the October, 2021 Bomb Cyclone

So just how similar are the meteorological setups between this storm and the October nor’easter?

• Both storms are bomb cyclones
• They both formed off the coast of Georgia and the Carolinas
• There is an immense amount of tropical moisture to tap into from the Gulf Stream
• Steering currents are nearly identical

This Bomb Cyclone will not Impact New England like the October Storm Did

The greatest impact of the October storm was the widespread power outages. As a New England native, I’ve been through some monster storms over the years. I’ve never seen power outages and downed trees anywhere close to the magnitude we saw following the October nor’easter.

Thankfully, it’s extremely unlikely you’ll see anything remotely close to the magnitude of power outages in October. The biggest difference is that the leaves are no longer on the trees. As a result, the surface area of the trees is far less, meaning that it takes much greater winds to do the same amount of damage. Additionally, the most vulnerable limbs, branches, and trees came down in the October storm. This time around, trees and limbs won’t come down nearly as easily. Don’t get complacent, though. The risk of power outages is definitely there with this storm.

However, where you may dodge one bullet, there are others you’ll have to content with. The shift from fall into winter brings in much colder air. The precipitation in the October storm all fell as rain. This time around, you’ll be dealing with snow. And lots of it.

A Better Storm For Comparison

In fact, for a much similar storm, forget the October nor’easter. Instead, go back to exactly 7 years ago today – 27 January, 2015. That day, the first Blizzard of 2015 dumped over 3 feet of snow across southern New England. It kicked off an infamous snowmageddon winter, that plunged the region into a months-long deep freeze.

All right, enough history. Let’s dive into the models.

Model Comparison: Bomb Cyclone Track and Timing

Let’s look at the same models we did with our analysis of Hurricanes Henri and Ida last summer. If you’ve forgotten those models, here they are.

For tracking and timing, you want to focus on the position of the center of the surface low, denoted by the red “L” on the map. In addition, note the timestamp on the upper left corner of the map. Those timestamps are in Zulu time, or UTC. Eastern time is 5 hours behind UTC. Don’t worry about the wind barbs for now. We’ll look at those in much more detail shortly. Click on any image to view it in full size.

As you can see, the American, European, and Canadian models are in very close agreement with each other. They show the the low passing just offshore of Cape Cod and the Islands around 00Z on Sunday (7 PM EST Saturday). The UKMET shouldn’t be discounted, either. It’s timing agrees with the other three models. Steering currents over the Appalachians can easily push the storm further offshore. However, it’s unlikely that it will pass any closer to the coast than what the GFS, ECMWF, or GDPS indicate.

Model Comparison: Bomb Cyclone Intensity (Pressure)

All right, it’s time to answer the million dollar question: will this storm bomb? To do this, we’ll need to figure out when each model expects the storm to reach its peak intensity, or minimum pressure. Then, we’ll compare the pressure at its peak intensity to the pressure 24 hours earlier. Remember, in order for a storm to be considered a bomb cyclone, it must undergo a 24 millibar pressure drop in 24 hours. Here is when each model expects the storm to reach its peak intensity.

Now, all we need to do is compare it to the same plots 24 hours earlier.

So do the models expect the storm to bomb? Here are their official predictions.

Models are usually not this assertive, but that’s a pretty definitive yes. The storm will bomb. Cue Toots and the Maytals.

Wind Forecast

Whenever a nor’easter undergoes bombogenesis, one thing is assured: there will be wind. Lots of it. So just how much wind will there be? You probably remember the October bomb cyclone, which brought 100-plus mph (160 km/h) wind gusts to southeastern Massachusetts. Thankfully, I’ve got some good news for you: you won’t see winds like that with this storm.

Look North to Canada for the Best Indicators of Potential Wind Speeds

The fiercest nor’easters get their winds from the pressure gradient between the bombing low and a strong high pressure system over southern Québec. But have a look at this. The high over Québec is much further north and east than it traditionally is for the really bad storms. In fact, it’s not over Québec at all. It’s actually over Newfoundland and Labrador.

Because the high is further away, the pressure gradient won’t be as tight. As a result, wind speeds won’t be as high as they would have been had the high been closer. Don’t get me wrong, it’s still a tight pressure gradient, and you’ll still get plenty of wind. It just won’t be as bad as it could have been. Combined with the expectation that the center of the low will pass offshore instead of right over Cape Cod and the Islands, I expect winds to be less than the bomb cyclone that hit New England last October. Let’s look at the models.

When I look at the models’ wind predictions, I prefer to look at the sustained winds about 400 to 500 meters above the ground, at 925 mb. In coastal areas, models can sometimes underestimate wind speeds when they try to calculate how friction and terrain impact the wind as it comes off the ocean. The 925 mb (400-500 meter) predictions remove those possible anomalies, and also give you the maximum potential wind speeds.

How Much Wind to Expect in New England

In the wind forecasts above, I don’t see any plausible scenario where the ECMWF (European) model forecast verifies. You just simply aren’t going to get winds that strong that far inland. Using the other three models, it’s clear that the strongest winds will be contained to the immediate coastal areas.

Areas that are exposed to the north along the South Shore and the Cape and Islands will see the greatest impacts from the wind. You’ll find the strongest winds on the Cape and Islands. Right now, my best guess is that sustained winds will peak in the 40-50 knot range in exposed areas across the Cape and Islands. Hurricane-force gusts are certainly possible, but I don’t expect anything close to the 100 mph gusts that ripped through during the October storm.

Temperature and Wind Chill: How Cold will the Bomb Cyclone Get?

Despite the availability of rich, tropical moisture, the bomb cyclone will have a very well-established cold core by the time it reaches New England. Furthermore, all of New England and the Canadian Maritimes will be on the cold side of the storm as it passes by. As a result, you should expect bitterly cold wind chills during the bomb cyclone. The models are all in agreement.

Expected Temperatures

Expected Wind Chills

When looking at temperatures and wind chills, you really need to look at the coast vs inland. Even in extreme conditions, the ocean still helps regulate temperatures near the coast. That being said, with the exception of Martha’s Vineyard, Nantucket, and possibly parts of the outer Cape, wind chills will struggle to get out of the single digits. If you’re inland, you’ll see sub-zero wind chills for pretty much the duration of the event.

Precipitation Type

With strong northerly winds, sub-zero wind chills, and everywhere on the cold side of the system, it should not be a surprise that this will be a snow event. Parts of the outer Cape and the Islands may briefly see a little ice mix in during the warmest part of the storm early Saturday afternoon. Other than that, it will be all snow.

On the models, we’ll look at the maximum temperature in the vertical column of air during the warmest part of the storm. Blue and purple indicates that the entire column is below freezing. You will see snow in those areas. Areas in green may briefly see some ice or sleet mix in early Saturday afternoon before changing back to all snow. That’s a result of air on the warm side of the storm wrapping around the top of the low as it approaches.

The European and British models do not calculate the maximum vertical temperature, so we’ll only consider the American and Canadian models. As you can see, their two predictions are nearly identical.

Snowfall Totals Will Be Measured in Feet, Not Inches

Whenever you have a storm that has both bitterly cold temperatures and an ample fuel supply of rich, tropical moisture, you’re going to get massive snowfall totals. However, there is a bit of a silver lining. All four models are showing noticeably less snow totals than they were yesterday. Unfortunately, they are still showing around two to three feet maximum snowfall totals for this bomb cyclone.

Because the GFS and GDPS models use the Kuchera Ratio, which is the most accurate, to predict snowfall, we’ll give the heaviest weight to those models. However, for a number of reasons, nailing down exact snowfall totals for a precise location is extremely difficult in this scenario.

1. The low still hasn’t really formed yet, so we don’t have any actual data from it to feed into the models.
2. The snowfall gradients are tight. A small wobble in the storm track can make a big difference in the snow totals. For example, take any of the above predictions and shift the snowfall totals 40-50 miles east or west.
3. A westward shift in the storm’s track may mean some areas – particularly parts of the Cape and Islands – may see more ice, sleet, or mixed precipitation on Saturday afternoon, which would reduce snowfall totals. Again here, a small shift in the storm’s track can make a big difference. In this scenario, inland areas would also see greater snowfall totals.
4. An eastern shift in the storm’s track would shift the precipitation shield east, meaning the heaviest snow could fall offshore.

How Much Snow Should You Expect?

We can give equal weight to all four models to determine where the heaviest snow will fall. Given my experience both with the models and with these types of bomb cyclones, I think the heaviest snow will set up in southeastern New England, along and east of the Interstate 95 corridor. Rhode Island will take a pretty good wallop, but will ultimately be spared the worst of the snowfall. Total accumulations will drop rapidly once you get west of I-95.

For the largest snow totals, I think 20 to 24 inches across Bristol and Plymouth Counties in Massachusetts is your safest bet at this point. That swath will likely spread across western Barnstable County (Cape Cod) and up into the far southern suburbs of Boston as well. 28 to 32 inches in a few isolated spots is certainly not out of the question, either, but I am not expecting widespread totals above 2 feet.

Summary

I know there’s a lot of information in this post, so let’s put it into a nice, clean table to summarize everything.

Conclusion

Like many other bomb cyclones, this is certainly a storm that you’re certainly going to want to take seriously. However, New England has certainly gone through far worse in the past. Make sure you stock up on what you’ll need for a few days, and then hunker down at home and enjoy it. The storm is fast moving, so it’ll be in and out in only about 24 hours. Then it’s just a matter of digging out, cleaning up, and getting back to your normal routine.

If you have any questions about anything related to this storm, please let me know in the comments below or reach out to me directly.

The post Wicked Bomb Cyclone Set to Pound New England with Fierce Winds and Heavy Snow appeared first on Matthew Gove Blog.

Which is exactly why New York City was the perfect and unusually satisfying destination to kick off our post-COVID travel. Seemingly the antithesis of my standard adventures deep in the remote back country, New York became the piece that fit perfectly into this often warped and twisted post-COVID puzzle. Having grown up in Massachusetts as a die-hard Red Sox fan, going to New York always felt like walking into enemy territory. Only this time it didn’t. People seemed very welcoming, much like what I experienced when I would travel to Mexico prior to the COVID-19 pandemic. Twisted and warped, indeed. At least we still got the quintessential New York experience of sitting in traffic and paying the ridiculous tolls to cross the George Washington Bridge.

Our destination in New York was the Cosmic Nature: Infinity exhibit at the New York Botanical Garden in The Bronx. After nearly two years of living through the pandemic, Infinity turned out to be an impeccable theme for our first post-COVID travel adventure.

Travel in a Post-COVID World

I’ll be honest with you. I had no idea what to expect in my first “real” post-COVID adventure. It’s been no secret how unpleasant so many of my previous encounters with the public throughout the pandemic. From the death threats I got in Arizona to derogatory slurs being hurled at me in Texas to the intimidating stares in just about every other state, I was pretty skeptical heading into New York City. The pandemic had seemed to bring out the absolute worst in everybody.

Despite their reputation, New Yorkers could not have been more friendly, welcoming, and respectful. Lines were orderly. Nobody was making a fuss over COVID-19 restrictions. What an incredible contrast from what I had to deal with in Arizona throughout the pandemic! Did it make any sense to me? No. Was I happy and relieved to see it? Without a doubt.

How has the COVID-19 Pandemic Changed Travel?

It has and it hasn’t. While many people expect a 9/11-style division between pre-COVID and post-COVID travel, I didn’t see it as quite that harsh. At least not right now. Flying out of Logan Airport in Boston less than 6 months after the 9/11 attacks was nothing like pre-9/11 travel. The endless lines, the extremely tight security, and the bomb-sniffing dogs didn’t feel real. Don’t forget that two out of the four hijacked planes in the 9/11 attacks originated in Boston, so we were grateful for the extra security at the time. But over time, we learned to accept that there was no going back to a pre-9/11 world.

While there will definitely be a pre and post-COVID distinction, I found a lot of normalcy visiting the Botanical Gardens in New York. Walking around looking at the exhibit felt eerily like pre-COVID times. You still have to wear a mask going into buildings, and there are signs everywhere to remind you that the pandemic is not yet over. But all the social distancing placards and blocked off areas were all gone. Those are so 2020, I guess.

New York City’s COVID-19 Vaccine Mandate

Nearly all of the post-COVID changes to your travel will be entering facilities. New York City requires you to show proof of COVID-19 vaccination to enter just about every public facility. If you’re not vaccinated, you will be denied entry, as negative tests are not accepted. Acceptable proof of vaccination includes:

• The original physical copy of your vaccination card
• An electronic copy or photograph of your vaccination card
• A photocopy of your vaccination record

Because they featured both indoor and outdoor exhibits, the Botanical Gardens were the perfect place to get a glimpse into what post-COVID travel may look like. Staff members verified our vaccine cards at the main entrance, and once we were inside, we did not need to show them again. My aunt and I both got our shots in the US, while my uncle was vaccinated in Canada. We had no issues getting in.

Both staff and security at the entrance to each building reminded us to wear masks inside and closely monitored foot traffic to ensure that the building did not exceed capacity. Other than that, though, it felt oddly normal.

Infinity: The Crossroads of Art and Physics

The Cosmic Nature: Infinity exhibit at the Botanical Garden was easily one of the most fascinating art exhibits I’ve ever seen. Artist Yayoi Kusama presented a captivating crossroads between land and water, art and physics, and indoors and out to showcase her lifelong fascination with the natural world. Unfortunately, we were there on one of the last weekends the exhibit was open. If you ever get a chance to see Kusama’s work elsewhere, I highly recommend it. It’s well worth the journey.

The grounds of the New York Botanical Gardens are beautiful to begin with. However, it doesn’t take long before you see Kusama’s touch. What originally feels like walking onto the grounds of The Masters quickly transports you Japan. The combination of all the flowers in bloom and the near-peak fall colors made it truly magical.

Our first stop was at a large tent where the public could make their own infinity art. Each person was given a flower and had to place it somewhere in the tent that was not on the fan, not on the fire extinguisher, and not in your pocket. When you walk into the tent, it is simply sensory overload for your eyes.

The First Taste of Infinity in Our Post-COVID Travel

Next up was our first taste of infinity at the Infinite Pumpkins room. It takes a second going from the bright, sunny outdoors to a pitch dark room, but I think that was done intentionally. Once your eyes adjust, you find yourself in a small room with a cube that’s roughly 4 feet in all dimensions.

A light underneath the cube slowly turns on, illuminating paper lantern pumpkins covering the bottom of the cube. As the light reaches full brightness, you look into the cube, and like magic, the rows of pumpkins look like they go on forever, into infinity. You start walking around the cube, and find that every side you look into, you’re staring into infinity. Look down, and you’re staring into a bottomless pit full of pumpkins. Since I have a degree in physics, my interest was particularly piqued.

So how does she do it? If you’re familiar with Kusama’s work, you know that reflection is a common theme in her art. The sides of the Infinity Pumpkins cube were all two-way mirrors, which gives you a truly unique sense of infinity regardless of the angle you’re viewing it. Photography was banned in the room, so I unfortunately can’t show you any pictures. However, you can find pictures of similar exhibits with a quick Google search.

Your Narcissism For Sale at the Narcissus Garden

In Greek Mythology, Narcissus is the god who was well-known for his beauty. He rejected all romantic advances, and ultimately fell in love with his own reflection in a pool of water. He became so consumed by his obsession with himself he stared at his reflection for the rest of his life, drawing the ire and vengeance of the other gods. If you’ve ever wondered where the term “narcissism” comes from, that’s where.

As part of a protest against elitism in the 1960’s, Kusama stood among 1,500 mirrored orbs with a sign that read “Your Narcissism For Sale”. She sold the orbs for $2 each. Later in her career, she built the Narcissus Garden, letting the orbs float around a large pond surrounded by plants and nature. In addition to seeing your own reflection, the orbs reflect the trees, sky, and water, allowing you to be one with the landscape.

Discovering Teleportation Inside the Conservatory

The Enid Haupt Conservatory is one of the most striking buildings at the New York Botanical Gardens. Housing exotic plants from around the world, the majestic Palm Dome ties the building together. And if there’s one thing walking amongst so many exotic tropical plants gives you, it’s some serious wanderlust.

Due to COVID-19 restrictions, the loop through the conservatory was only one-way. You start in the tropical rainforest, where you’re instantly transported to the lush jungles of South America, Africa, Asia, and the Caribbean. You’ll see everything from common houseplants to the most exotic and rare flora. And if you listen closely, you can almost hear the exotic birds, monkeys, and jaguars that call the rainforest home.

Towards the end of the rainforest exhibit, the path starts to descend, like you’re sinking into the ground. The exhibit surrounds you with swampy aquatic plants. Then, all of a sudden you reach a flight of stairs. Go down the stairs into an underground metal tunnel that feels like it’s right out of Star Trek. Walk for a couple of minutes. You’ll go up a short flight of stairs and be dropped right into the middle of the desert. I turned to my aunt and said, “if we ever figure out teleportation, I’m pretty sure that’s what it’s gonna feel like.”

The desert exhibit is just as exotic. While it features many staples of the American Southwest, it will also transport you to more deserts such as the Kalahari, the Australian Outback, and Arabia. Seeing the native plants from the Kalahari mixed in with American staples such as the Saguaro and the Prickly Pear did catch me off guard a little. But it was really cool to see them together. You can’t do that in Arizona.

Chance Encounters are One Reason Why I Love to Travel

When the COVID-19 pandemic shut down travel in 2020, there was one thing I really missed from my adventures. Prior to the pandemic, I really enjoyed the short, chance encounters with interesting people when I would go down to Mexico. You can learn a lot about yourself and other cultures if you stop, listen to what they have to say, and learn from it. As I traveled more and more, I found myself having more of these interactions in unexpected places.

Not surprisingly, I had a really cool chance encounter in New York while waiting in line to see the Dancing Pumpkin exhibit. It’s hard to describe the Dancing Pumpkin other than it looks like a dancing polka-dotted octopus, so here’s a picture of it. You can get your picture taken in front of it and walk around underneath it.

A Blast From the Film-Era Past

As we got towards the front of the line, there was a group of three young women in front of us. I had my DSLR camera around my neck, so one of them turned to me and asked if I could take their picture for them. They told me the secrets to using their camera, and then went to pose for their picture in front of the Dancing Pumpkin.

As they walked over, I couldn’t help but notice their camera didn’t have a screen on the back of it. A closer glance at the back and I saw a label that said “Insert Film Here”. I hadn’t used a film camera in at least 20 years, so I thought this was pretty cool. But it gets better. After they got into position, I gave them the countdown. 3-2-1, and then pushed the button. You could hear the gears of the camera pulling the film through as it captured the image. Then I felt pressure pushing up on the underside of the brim of my hat.

I pulled the camera away from my face and looked down to see the picture coming out of the top. It was a Polaroid camera. I have a very high level of respect for people that still use film cameras, so I made sure to tell them. We had a good laugh over it as I gave the camera back to them. This may be the COVID isolation talking, but that brief interaction really made my day.

The Grand Finale at the Infinity Room

The Infinity Room is what people come to the Kusama exhibits for. Using nothing more than light and mirrors, the Infinity Room immerses you in an environment that fosters an out of body experience while at the same time heightening and arousing your senses. Remember the Infinite Pumpkins exhibit we visited earlier? The Infinity Room is the same thing, except instead of putting paper pumpkins inside the cube, you put yourself. And the other big difference? You can take pictures inside the Infinity Room. You only get 45 seconds inside, so be ready with your camera to make the most of it.

If you’re wondering where the worlds of art and physics collide, it’s inside the Infinity Room. When you step in, you’re instantly hit with visual overload. Prisms all over the wall and ceiling light up the mirrored walls with what feels like infinite colors. A slight echo subconsciously enhances your hearing, too. Make sure to observe the room from different angles. The optics will give you a sense for the many, or dare I say infinite, different aspects of infinity. Then just like that, the door opens and your time is up.

Final Thoughts on Post-COVID Travel

It felt so good to finally be able to get out and go adventuring. I really believe that post-COVID travel will feel much more “normal” than many people think. I got a bit of that feeling on a day trip to Boston a couple months ago, and this trip to New York certainly reinforced it.

However, just like after 9/11, we must remember that new practices, policies, and protocols are in place to keep you safe. Those 5-hour waits to get through security at Logan Airport in early 2002 quietly faded away as we embraced the new post-9/11 normal. And the COVID-19 restriction will do the same. Since the onset of the pandemic, I felt safer in New York City than I did in Phoenix, Boston, and everywhere else I’ve been in between. This is just the beginning of our next chapter, and as the world fully reopens, I couldn’t be more excited for what future adventures hold in 2022 and beyond.

Stay Up-to-Date with Our Adventures

To follow along and stay up-to-date with our post-COVID travel adventures, please sign up for the Matt Gove Photo newsletter. In addition, you’ll also get exclusive deals to our store that we don’t offer anywhere else, as well as free travel guides and visual storytelling (photography/video) tutorials. It’s free, and always will be. Where will your first post-COVID adventure take you?

Want to See More Photos of Cosmic Nature: Infinity?

Can’t get enough of infinity here? Head over to the Matt Gove Photo website. You’ll find the complete photo album from the Cosmic Nature: Infinity exhibit there.

Top Photo: Kusama’s Tulip Sculptures Take Over a Pond at the Cosmic Nature: Infinity Exhibit
New York, New York – October, 2021

The post Travel Journal: Post-COVID Adventures Kick Off in New York City appeared first on Matthew Gove Blog.

As expected, the upper-level steering currents have pushed Henri back to the east. It looks like the GFS (American) model was right all along. Its consistency and history of being right with Henri is why have been saying over the past three days that Henri will track east of the center of the National Hurricane Center‘s cones.

I still expect Henri to make a left hand turn while it comes ashore, as an upper-level low tries to sling shot the hurricane into Ontario. However, as we discussed yesterday, it will quickly run into a road block from a strong high pressure over Québec, briefly stalling out before being ejected across Northern New England and up into the Canadian Maritimes.

Current Watches and Warnings

The watches and warnings for Henri remain unchanged since yesterday. Hurricane Warnings remain in effect from

• The Massachusetts/Rhode Island State Line to New Haven, CT
• Block Island
• Port Jefferson, NY to the west end of Fire Island, NY

Likewise, Tropical Storm Warnings remain in effect from

• Chatham, MA to the Massachusetts/Rhode Island State Line
• Martha’s Vineyard and Nantucket
• New Haven, CT to Port Jefferson, NY, including all of New York City
• The west end of Fire Island, NY to Point Pleasant, NJ

Storm Threats and the Timing of Each

With Henri’s imminent landfall in southern New England, we are going to shift a bit from discussing exactly where the eye will come ashore to the timing of the threats Henri will bring to the region.

Wind

Because Henri is expected to weaken so rapidly as it starts interacting with the land in southern New England, most places along the south coast will likely see the strongest winds before the storm makes landfall. Even if you remove the effect of the land, Henri is over cool waters, and will be weakening as it approaches the coast.

This timing of the strongest winds is especially true for the eastern half of the storm, primarily from Narragansett Bay to Cape Cod and the Islands. Because Henri has been pushed back tot he east, those locations will likely see stronger winds than were predicted just yesterday. Wind gusts in excess of 50 knots are all but certain, except possibly for the outer portions of Cape Cod. The potential is there to see gusts to 70 knots, but it’s far from a guarantee.

The one exception is in the area immediately around the location that the eye of Henri makes landfall. The eye is expected to pass near Block Island and the far eastern tip of Long Island before coming ashore near the Connecticut/Rhode Island state line.

Storm Surge

Because winds are out of the south (onshore) in the eastern half of the storm, Rhode Island and southeast Massachusetts will bear the brunt of the storm surge. West of Henri’s eye, winds will be out of the north (offshore), with the exception of the north coast of Long Island. However, Long Island Sound is so small compared to the open Atlantic Ocean, storm surge effects on the north shore of Long Island will be less than points further east.

To determine which locations will see the greatest impact from the storm surge, you simply need to look at where the window for the strongest winds overlaps with the timing of high tide. You’ll find the lowest impacts where the strongest winds overlap with low tide, which occurs about 6 hours before and after each high tide. Also, don’t forget that locations closer to the eye tend to see greater impacts than locations on the edge of Henri.

What Does This Table Mean?

Thankfully, there is not one location that really jumps out at me as being much higher risk for storm surge. High tide in most spots in both Narragansett Bay and Buzzards Bay will fall at the beginning of that window of maximum winds, which will help limit the impact of the storm surge. Hyannis is far enough out in the outer part of Henri’s circulation that lower wind speeds will help offset the fact that high tide falls at the end of window of maximum winds. Finally, the Connecticut locations will see most likely see offshore winds. New London may see a brief period of onshore winds this morning, but they will quickly shift as Henri approaches. I would expect to see 3 to 5 foot storm surge in all of the above locations.

Inland Flooding

Based on model guidance and early radar returns, the majority of the rain is in the western Half of Henri. As a result, the highest risk for inland flooding will be in Connecticut, western Massachusetts, southeastern New York, and northern New Jersey. Depending on where Henri stalls out to make its turn to the east, southern Vermont could be at a higher risk for flooding as well. The rest of New England is by no means out of the woods, but is at much lower risk given the sharp gradient in forecast rainfall totals. Remember, if you see flooding, Turn Around, Don’t Drown!

Power Outages

Widespread power outages should be expected across most of Connecticut, Rhode Island, Massachusetts, and Long Island. Downed trees are the #1 cause of power outages in storms like this. New England has had a lot of rain in recent weeks. As a result, the soil is quite saturated, making it easier for Henri to uproot trees. If you see downed power lines, don’t go anywhere near them! Back away and call the electric company.

Be prepared to be without power for a while if you do lose it. We’re talking days here, not hours. But thankfully, barring any unforeseen catastrophes, it shouldn’t be weeks, either, despite some of the reports you may have heard on the news. Further north, it would not surprise me at all to see isolated power outages across parts of Vermont, New Hampshire, and southern Maine.

Conclusion

Hurricane Henri has arrived in southern New England. By now, you should be hunkered down and sheltering in place until the storm passes. Henri will likely be the most significant tropical cyclone to impact southern New England since Hurricane Bob in 1991.

Once Henri makes landfall, it will rapidly weaken. It is expected to be a tropical depression by 2 AM EDT Monday, and will be just a remnant low by midday. However, that should not be taken lightly. Just because the wind diminishes, it does not mean the threat for flooding has dissipated, too. In fact, it’s quite the opposite. Be smart, stay safe, and enjoy the ride.

The post Hurricane Henri in New England: Sunday Morning Outlook appeared first on Matthew Gove Blog.

Big Picture Overview

The primary steering currents that are driving Henri have strengthened since yesterday’s discussion. The low has set up over West Virginia and continues to dig to the south and east. Similarly, the high pressure has firmly established itself over Québec.

Because air moves from areas of high pressure to areas of low, the low pressure system over West Virginia will try to suck Henri into it. You can see the effect in the upper-level steering currents, which the green arrows mark in the plot above. As a result, that low has been responsible for the drastic westward shift in Henri’s forecast track over the past 48 hours or so.

Unfortunately, it’s not as simple as Henri getting sucked into the upper-level steering currents and getting flung up into Ontario. Remember that big ridge of high pressure over Québec? That acts like a roadblock, preventing Henri from moving north and northwest once it makes landfall in southern New England. Furthermore, as the low pressure expands to the south and east as it strengthens, it will actually push Henri back to the east as it tries to pull the hurricane into it.

So what’s the end result? As Henri gets pulled into the low, it will screech to a halt once it hits the blocking effect from the high. As the low pressure system over West Virginia move east, it will eventually grab hold of Henri and eject it out over eastern Massachusetts and up into the Gulf of Maine. If you’ve looked at the 5 AM EDT outlook from the Hurricane Center this morning, that’s why there’s such a big kink in the track. We’ll come back to this shortly.

Current Watches and Warnings for Henri in New England

As of 11 AM EDT, Hurricane Warnings are now in effect from

• The Massachusetts/Rhode Island State Line to New Haven, CT
• Block Island
• Port Jefferson, NY to the west end of Fire Island, NY

Likewise, Tropical Storm Warnings are now in effect from

• Chatham, MA to the Massachusetts/Rhode Island State Line
• Martha’s Vineyard and Nantucket
• New Haven, CT to Port Jefferson, NY, including all of New York City
• The west end of Fire Island, NY to Point Pleasant, NJ

Storm Surge Warnings are also in effect for the entire south coast of New England and Long Island as Henri approaches. While the surge will not be catastrophic, it will likely flood low-lying coastal areas with 3 to 5 foot storm surge. If you live in an area that often floods, I would expect it to flood as Henri comes ashore. Please be aware there will likely be very dangerous rip currents in the warning area as well.

Model Overview

Models are finally converging on a solution after a lot of uncertainty over the past 48 hours. Remember, don’t focus on one particular outcome. Instead, you want to look for patterns. Where do they agree? Where do they disagree? If they disagree, why do they disagree? Are there any anomalous runs that should be immediately discounted? Models that have been consistently accurate that are in agreement are the ones you want to focus on.

The GFS (American) Model

The GFS has been the most stable, consistent, and accurate model over Henri’s lifecycle, so we will once again use it for the basis of our forecast. This morning’s runs remain consistent with both Friday’s and Thursday’s runs. Neither Henri’s track nor strength have changed much in the GFS runs over the past two to three days.

The ECMWF (European) Model

Over the past two or three days, the ECMWF’s strength forecast has been very much an outlier. This morning, it is finally coming into agreement with the other models. It still shows weaker wind speeds at landfall than any of the other models. However, because it is now in close agreement with the other models, we can give it much more weight when we make our official forecast.

The UKMET (United Kingdom) Model

In yesterday’s model run, the track of the UKMET was quite anomalous, tracking much further west than any of the other models. As expected, that too, has largely come back into agreement with the rest of the models this morning.

It’s also worth noting that the UKMET has Henri making landfall sooner and with slightly stronger winds than any of the other models. That’s a result of the model having Henri moving faster. In the UKMET scenario, Henri spends less time over the cooler waters off the coast of New Jersey, and thus has less time to weaken. We will need to take that into account when we make our official forecast.

The GDPS (Canadian) Model

The GDPS has been in lockstep with the GFS for days. This morning, it remains that way, bringing Henri ashore at the Connecticut/Rhode Island state line. Much like the GFS, the GDPS has been very consistent, stable, and accurate over the past few days. As a result, we can use it to make forecasts with a high degree of confidence.

Despite our confidence in the model, this individual snapshot is actually a bit misleading with regards to wind speed. You may look at this map and think, oh boy, that’s in line with the weaker winds of the ECMWF. And that’s true…to a degree. All models have Henri weakening rapidly once it makes landfall on the south coast of New England. If you look at the GDPS snapshot for six hours earlier (Sunday at 8 AM EDT), winds are much stronger.

As a result, much of southern New England and Long Island will likely experience stronger winds than the 2 PM EDT snapshot indicates as the eye of Henri approaches landfall. Additionally, a small uptick in Henri’s forward speed means that it could come ashore with much stronger winds.

Model Summary for Henri in Southern New England

This morning’s model runs are in close agreement with each other. After all of the uncertainty of the past few days, it’s about as good of an agreement as we can ask for. In our official forecast, we’ll be able to give each model close to equal weight and make our forecast with a high degree of confidence.

Our Official Forecast for the Impact of Henri in New England

With the models now aligning with each other, our forecast should be pretty easy to make. However, there is one parameter that I think we can discount. Based on over a decade of experience with working with mathematical models, my meteorological intuition is telling me that there is basically no way that Henri will have 90 mph winds at landfall like the UKMET says. I don’t want to discount its prediction fully, but we’ll give much less weight to it.

Additionally, because Henri is expected to weaken so rapidly once it makes landfall, the greatest coastal wind impacts will likely be felt prior to landfall. This is particularly true for areas in the eastern half of the storm…Rhode Island and southeastern Massachusetts, I’m looking at you here. Flooding will remain a threat until either Henri weakens sufficiently or it exits the area.

Post-Landfall

Henri will continue to be pulled into the upper-level low that currently sits over West Virginia as it approaches landfall. Interestingly, the moment that the sling-shot effect (when a mid-latitude low grabs hold of a hurricane and flings it north) occurs will be at the same time as Henri runs into the road block from the strong high over Québec.

As a result, you’ll see Henri make a sharp left (westward) turn right after landfall, which is from the low trying to fling Henri up into Ontario. It will almost immediately run into the roadblock from the high over Québec and temporarily stall out over northern Connecticut and/or western Massachusetts. As the upper-level low moves east, it will push Henri east with it, eventually sling-shotting it across southern New Hampshire and eastern Massachusetts and up into the Canadian Maritimes.

The National Hurricane Center Forecast

Our forecast remains largely in agreement with the National Hurricane Center. However, from model analysis and my meteorological intuition, I believe that Henri will track slightly east of the center of the official Hurricane Center cone. While I don’t think landfall in western Rhode Island is the most likely outcome at this time, it’s certainly possible. It’s not a major difference, but it certainly could make for an interesting ride on Block Island much of the Rhode Island coast if it verifies.

Conclusion

The picture is certainly coming into focus as Henri approaches Southern New England. It remains a flip of a coin whether Henri will be a tropical storm or a hurricane when it makes landfall, but you will likely see hurricane-force wind gusts across much of southern New England. If you’re in the path of Henri, please stay safe and enjoy the ride. Please let me know if you have any questions, and stay tuned for tomorrow morning’s update.

The post Hurricane Henri in New England: Saturday Morning Outlook appeared first on Matthew Gove Blog.

Big Picture Overview

Before we jump into models, let’s look at the big picture. Here’s what the upper-level winds across the continental US look like. Henri is currently sitting in the bight between the Bahamas and Cape Hatteras.

Looking at the map, there are a couple things that will impact Henri as it churns towards New England.

1. A large ridge of high pressure sits over Ontario and Québec
2. A mini-trough (it’s a little big to call it a shortwave) currently centered over Pittsburgh is passing through the Ohio Valley

So how will they impact Henri? Quite a bit. The high pressure system will slow Henri down as it approaches New England. The mini-trough, which is a weak area of low pressure, will pull Henri towards it. That trough is the culprit behind why the track has so drastically shifted west over the past 24 hours.

Additionally, Henri has been in a sheared environment for the past 24-36 hours. That shear has dissipated, creating very favorable conditions for Henri to strengthen as it moves north.

Current Watches and Warnings for Henri in New England

As expected, the National Hurricane Center issued Hurricane and Tropical Storm watches for southern New England and parts of New York this morning with its 5 AM EDT advisory for Henri.

Hurricane watches extend from Plymouth, MA to New Haven, CT, and include all of Cape Cod and the Islands. If you’re on Long Island, you’re under a hurricane watch if you’re east of a line from Port Jefferson to the west end of Fire Island. Tropical Storm Watches cover the rest of Long Island Sound and the south coast of Long Island. As of right now, New York City is not under any watches, but that will likely change over the next 12 to 24 hours. The same goes for Boston.

What Do The Models Predict for Henri’s Impact in New England

A good forecaster knows how to look at the models and determine which ones to give the most weight to when they make their forecast. I have my favorite collection of models I turn to when forecasting hurricanes. I want to emphasize when you look at the models, don’t focus on one particular outcome. Instead, you want to look for patterns. Where do they agree? Where do they disagree? If they disagree, why do they disagree? Are there any anomalous runs that should be immediately discounted? Models that have been consistently accurate that are in agreement are the ones you want to focus on.

The GFS (American) Model

The GFS has been the most consistently accurate model for both Hurricane Henri as well as Hurricane Grace, which is currently heading towards a second landfall on Mexico’s Gulf Coast after passing over the Yucatán. As a result, we’ll use it as the basis of our forecast to which we can compare the other models. This morning’s runs remain consistent with yesterday’s. The GFS has Henri following a very similar path to Hurricane Bob into southern New England. It makes landfall in Narragansett Bay with wind speeds of 74 knots (85 mph).

The ECMWF (European) Model

The ECMWF has been a bit of an outlier with Henri’s strength, but it has been in lockstep with the GFS for where Henri will track. While you can’t completely discount its wind speed forecast, you will notice that it is noticeably weaker than the other models. However, wind speeds in the ECMWF forecast for Henri have trended up over the past 24 hours, meaning that it will likely align with the GFS as Henri approaches New England.

The UKMET (United Kingdom) Model

While the ECMWF was an outlier for Henri’s strength, the UKMET has done the exact opposite. Its strength forecasts are in strong agreement with the GFS, but its forecast track for Henri has trended much further west than the other models. Interestingly, the UKMET is also showing signs of coming into agreement with the GFS. In its runs just yesterday, the UKMET showed landfall possibly as far west as New Jersey. This morning’s runs have pulled it much further back to the east and closer to both the GFS and the ECMWF tracks.

The GDPS (Canadian) Model

The GDPS has largely been in agreement with the GFS on both strength and track over the past 48 hours. From a forecasting standpoint, that’s a very good thing. It means we can give less weight to the ECMWF’s outlying strength and the UKMET’s outlying track. It also means that we should expect those outliers to align with the rest of the models that are in agreement within the next 36 hours or so.

Model Summary

Before we put our official forecast together, let’s stop and think about which models should get the most weight. Because the GFS (American) and GDPS (Canadian) are in close agreement, we’ll give the most weight to those. Additionally, the ECMWF’s track and the UKMET’s strength are also in close agreement with the other two models, so we can give them plenty of weight as well. As for the outliers, I don’t want to completely discount them because they are trending back towards the models that are all in agreement. If anything, the fact that they’re trending back only reinforces our confidence in the other models.

Our Official Forecast for the Impact of Henri in New England

Based on the models we looked at, along with a little intuition and gut feelings, we can make our own official forecast. Hurricane Henri making landfall is southern New England is all but guaranteed. The big questions are where will it hit, and how strong will it be. Here are our best guesses.

How Does It Compare to the National Hurricane Center’s Advisory?

If we did our forecasting correctly, our forecast should be pretty similar to the National Hurricane Center’s official forecast. Indeed, the center of the National Hurricane Center’s cone of uncertainty brings Henri ashore near the Connecticut/Rhode Island State line as a strong tropical storm.

Conclusion

Henri is a potent tropical cyclone that folks in New England should take seriously. If it makes landfall as a hurricane, it will be the first hurricane to hit New England since Hurricane Bob in 1991. Whether it can actually do that remains a flip of a coin. I’ll be posting daily updates about Henri at least until it makes landfall. Please don’t hesitate to reach out if you have any questions. Be smart and stay safe.

The post Hurricane Henri in New England: Friday Morning Outlook appeared first on Matthew Gove Blog.

I only ran the models out until early May because we need to focus on what’s going to happen in the next two to three weeks, not what’s going to be happening several months in the future. Additionally, model forecasts get less accurate the further into the future you go. This run assumes current social distancing restrictions remain in place through mid-May and does not account for any additional surges or waves of the virus that may occur later this spring, this summer, or this fall.

Don’t forget, you can always get more information about the model and view detailed case data on my COVID-19 Dashboard. Additionally, I will write up a separate post about the mathematics, equations, and methodologies used in my coronavirus model, which I’m hoping to get posted in the next day or two. Stay tuned for additional discussions about each hot zone as more data comes in.

Alberta

Arizona

British Columbia

California

Connecticut

Florida

Georgia

Illinois

Louisiana

Maryland

Massachusetts

Michigan

New Jersey

New York

Ohio

Oklahoma

Ontario

Oregon

Pennsylvania

Québec

Rhode Island

South Dakota

Tennessee

Texas

U.S. Virgin Islands

Washington (State)

After several requests, I updated this post on 16 April, 2020 to include additional states and provinces, bringing the total to 26 plots instead of 24.

Top Photo: Palo Duro Canyon State Park – Amarillo, Texas – August, 2019

The post A Look at the Best-Fit COVID-19 Model Curves for 24 Key States and Provinces appeared first on Matthew Gove Blog.

Overview of SIR Model Output

Each city has four plots. The top row is the “working” model output, with the model curve best fit to the actual data. The bottom row is an experimental model output showing the effect of social distancing. In the “working” model runs on the top row, there are 5 lines on each plot. The middle line is the R Naught value that was reverse-engineered by fitting the model output to the actual data, and there are two lines on each side of the best-fit line showing different R Naught values in steps of 0.2.

Note: The y-axis on some of the experimental social distancing plots showing the total case count (bottom right plot for each city) is mislabeled. It should read “Total Cases”, not “Number of Infected”.

Finally, don’t forget that the plots below assume the R Naught values and the amount of social distancing remains constant throughout the entire time series. In reality, additional social distancing restrictions will dampen the curve and shift it to the right, while removing social distancing restrictions will cause the curve to accelerate and shift to the left.

Confidence in SIR Model Predictions

My confidence level in the “working”/top row model outputs is as follows:

• Predicting the apex of the outbreak: medium-high to high. The curves should at least be “in the ballpark.”
• Predicting the total number of cases: low to very low. With how fast things are changing right now and how fast new data is coming in, we just don’t know at this point. My gut feeling is that the case count projections in these model runs are likely high overall, but from a public health perspective, I would much rather have the model overestimate case counts than underestimate them.

Plots are in alphabetical order by city, with a table of additional cities at the bottom. Click on any plot to view it full size.

Boston, Massachusetts

Chicago, Illinois

Detroit, Michigan

Los Angeles, California

Montréal, Québec

New Orleans, Louisiana

New York, New York

Oklahoma City, Oklahoma

Ottawa, Ontario

Portland, Oregon

Phoenix, Arizona

San Francisco, California

Tampa, Florida

Toronto, Ontario

SIR Model Outputs for Additional Cities

Please note that this table contains outputs of just this single model run and does not necessarily reflect what my actual predictions are. I will be putting this table on my COVID-19 Pandemic Tracker later this week and regularly updating it there.

Data points I’m skeptical of in this output (with some comments):

• Chicago, IL: Case count is likely overestimated. I’m not sure why, but the most likely reason is good social distancing.
• Los Angeles, CA: Case count is likely overestimated due to California being better at social distancing than what was input into the model
• Seattle, WA: Peak date is incorrect due to the State of Washington’s 100th case occurring before John’s Hopkins began breaking down data by state.
• Washington, DC: Not enough data to accurately fit the curve
• Winnipeg, MB: Not enough data to accurately fit the curve

The post Complete Revised SIR Model Forecasts (8 April): USA and Canada appeared first on Matthew Gove Blog.

Disclaimer: As I’ve mentioned many times before, I claim zero knowledge about anything in the medical field, including infectious disease. These analyses are based solely on my expertise in mathematical modeling.

An Important Note on Making Predictions From Mathematical Models

One of the most common uses of mathematical models to make predictions in day-to-day life is weather forecasting. Luckily, meteorology happens to be a field in which I do have extensive knowledge. When forecasting any type of weather, it’s important to look at multiple models. Do not make any predictions based solely on any one model. In an ideal world, the models are all in agreement. In reality, you need to use your knowledge and expertise to gauge how much weight to give each model when you make your prediction. The same principle applies to the current pandemic.

Additionally, from a purely mathematical standpoint, all outbreaks follow roughly the same bell-shaped curve when plotted over time. Different types of outbreaks can use vastly different equations in their models. While I do not have much experience with outbreaks of infectious disease, I have worked with and extensively studied outbreaks of tornadoes and severe weather during my time as a meteorology student at the University of Oklahoma. We can apply that knowledge when making predictions about the current COVID-19 outbreak.

Adding a Social Distancing Factor to the SIR Model

I have been running a lot of possible scenarios in Python using the Susceptible – Infected – Removed, or SIR model. I recenly covered the mathematics of the model, so I’m not going to state all of that again. You just need to know that the model is based on a system of three ordinary differential equations.

With the help of my uncle, who also has a lot of experience with mathematical models, we set out to add a parameter, which we’ll call f, to the SIR model. f represents the percentage of the population who are strictly complying with social distancing guidelines.

Accounting for Social Distancing in the Model

To incorporate f into the SIR model, we need to look at the terms that are modeling the contacts between the infected and susceptible people. The rate of contact would be reduced by (1 – f)² because the fraction of both the susceptible and infected population interacting would be reduced by a factor of (1 – f). The removed (recovered/dead) population would not be affected by the social distancing parameter. Therefore, the differential equations for the susceptible and infected population would then become:

We are still working on fine-tuning these equations, but this is what we’re going with for now.

Estimating a Baseline Infection Rate

The final piece of the puzzle is to set the baseline for beta. That baseline is the infection rate assuming 0% social distancing compliance. In other words, beta is the number of infecting contacts per day between an infected and susceptible person. Beta is also part of the equation that calculates R Naught.

Since I only plan to model the effect of social distancing at the city level, I simply scaled beta based on the city’s population density to set the baseline infection rate. Cities with higher population densities would have a higher rate of infection than those with lower population densities. COVID-19 is spreading much faster in New York or Chicago than it is in Topeka, Kansas or Bismarck, North Dakota.

The scaled baseline for the infection rate at 0% social distancing compliance is simply:

where d is the population density in units of people per square kilometer. The “plus one” is because some small cities in Alaska have population densities of less than 10 people per square kilometer. Low population densities result in very small and unrealistic beta and R Naught values. It’s not an exact science, so the equation will be tweaked as we go along.

Limitations of the SIR Model

Not surprisingly, mathematical models are only as good as the assumptions that they make. The COVID-19 models make plenty of them. Some of the assumptions and limitations the SIR model (plus our revisions) make include, but are not limited to:

• Uniform population density across the entity being modeled. This means the SIR model predicts outbreaks in individual cities much more accurately than it does in states and countries.
• Population remains constant – i.e. people are not being born or dying of causes other than the disease. The SIR model has terms to account for birth and death rates, but its effect on the model is negligible. I don’t have birth and death rates in my database, so we will simply set those terms to zero.
• R Naught and the percentage of people social distancing are constant throughout the outbreak of the disease. This can cause both the peak of the outbreak and the date of that peak to be either over- or under-estimated.

Outputs From Our Revised SIR Model

We now have enough data from the United States, Canada, and Australia. Let’s fit the model output to each state’s existing curve. We can then use that output to model major cities in each state.

I’ve included model outputs from a few cities in the United States, and will include more in a separate post. When looking at the model outputs, you want to focus on general trends. Do not look at specific dates or case counts. Instead, focus on something happening in periods such as “mid-April” or “early May” instead of “April 15th” or “May 1st”.

Our Revised SIR Model’s Assumptions

Don’t forget that our revised SIR model assumes a constant level of social distancing. We are just starting to see the effects of stricter social distancing show up in the data set. As a result, the model will likely underestimate the amount of social distancing being done. Therefore, it will overestimate the number of cases. I’ve included curves for several R Naught values both less than and greater than the R Naught values that I reverse engineered by fitting the model curve to the existing data.

The revised SIR model seems to do a decent job predicting the apex of the outbreak. I have checked the apexes on the first plot you see below in each city against what health officials in Arizona, New York, Michigan, Massachusetts, and Louisiana have said. They’re at least “in the ballpark” with what health officials are saying. The social distancing plot is primarily to drive home the importance of social distancing and flattening the curve during the pandemic.

Speaking of social distancing, don’t forget about assumptions. The plots below assume the amount of social distancing remains constant throughout the entire time series. In reality, additional social distancing restrictions will dampen the curve and shift it to the right. Removing social distancing restrictions will cause the curve to accelerate and shift to the left.

Confidence Levels in the Model

My confidence level in these model outputs is as follows:

• Predicting the apex of the outbreak: medium-high to high. The curves should at least be “in the ballpark.”
• Predicting the total number of cases: low to very low. With how fast things are changing right now and how fast new data is coming in, we just don’t know at this point. My gut feeling is that the case count projections in these model runs may be high. From a public health perspective, I would much rather have the model overestimate case counts than underestimate them.

With regards to the projected case counts, look at the how the University of Washington model has been all over the place over the past week. That is how the model tells us it doesn’t know. We can’t make any meaningful forecasts from it at least until it starts to stabilize from day to day. This would be like trying to make a forecast and issue warnings for a hurricane using a model that keeps flip-flopping between the hurricane making landfall in Houston and making landfall in Miami.

View the full output from our revised SIR model for most major cities in the United States and Canada.

New York, NY

New Orleans, LA

Detroit, MI

Plots for additional cities will be posted in a separate post.

Looking at the University of Washington Model

A model developed by the University of Washington has made headlines over the past several weeks. It is one of the most trusted models out there for predicting the pandemic (at least in the United States). However, I worry that too many people are focusing only on this one model and are not considering what other models are forecasting.

Like every model, the University of Washington model makes its fair share of assumptions:

• The model accounts for social distancing restrictions, such as closing businesses and schools and issuing stay-at-home orders. However, it does not address how social distancing restrictions are lifted. It assumes that Americans continue to practice full social distancing practices through at least sometime between June 1 and August 1.
• The model does not account for any resurgences or additional waves that may occur later this summer or fall.
• The model does not account for hospital staff shortages due to being out sick, running out of supplies, or any other reason.
• It is also important to note that the University of Washington model forecasts deaths and hospital usage. It does not predict the total number of cases.

I believe that this is probably the most accurate model out there right now. My gut instinct is that because of the assumptions, it may slightly underestimate both the hospital needs and death counts.

Also note that the plots below are for hospital needs. It looks like 20 to 25 percent of all COVID-19 cases require hospitalization. Multiply the y-axis values by 4 to 5 to get the approximate number of cases the model is predicting.

My Predictions

Because of the fluidity of the situation and how fast everything seems to be changing, focusing my predictions on exact numbers will only contribute to the spread of misinformation. Instead, I will be focused on general trends, as I discussed earlier. These predictions are based on the two models I discussed in this post, as well as several others.

Expectations for the United States and Canada

• Nearly every city and state in the United States will reach its apex within the next 4 to 5 weeks. I’m still working on projections for Canada.
• At the end of the pandemic, total case counts in every major city in both the US and Canada will be in the tens of thousands, if not more. New York City is currently just shy of 80,000 cases.
• Total or cumulative case counts for the both the United States and Canada will be in the millions. I think Canada can still keep their case count below 1 million with proper social distancing. That ship has long since sailed for the US.
  • For perspective, let’s use the Centers for Disease Control’s recent prediction of 80,000 deaths in the United States. Using the current death rate based on data from the past week, it works out to about 2.5 to 3.5 million total cases in the US.
  • In Canada, the Government of Ontario recently released a study projecting at least 15,000 deaths in the province. Using the same calculation as above, that works out to 500,000 to 750,000 cases in Ontario alone.
• New cases will be reported in both the US and Canada every day through at least late June/early July. Expect government mandated social distancing protocols to remain in effect through at least the end of May in most states/provinces. These restrictions include stay-at-home orders, closures of restaurants, schools, and other places of gathering, etc.
• The outbreak in Canada will have a flatter curve and grow slower than the outbreak in the United States. As a result, Canada will peak later than the outbreak in the US.
• Don’t forget that like weather forecasting, the models get less accurate the further into the future you get. I will be posting routine updates as new case data comes in.

One Final Thought

When a hurricane makes landfall, it ravages the coast with the eye wall – the most powerful part of the storm – before the calm of the eye passes over. Inside the eye, winds drop down close to zero, the sun comes out, and it looks like a beautiful day. In the first half of the 20th century, before weather radar became mainstream, coastal residents commonly mistook being inside the eye to mean the storm was over. They then went back to their normal lives. As a result, they were then blindsided when the back side of the eye wall came ripping ashore like a buzzsaw. They didn’t realize that they still had the whole second half of the hurricane to go. Such a mistake undoubtedly caused numerous injuries and deaths that should have been preventable.

Don’t Repeat Past Mistakes

I am a bit concerned that a lot of people will be making the same mistake by going back to their normal lives once their city and state hits the apex of the pandemic. Like the eye of a hurricane, the apex is only the half-way point. You still need to come down the back side of the curve. Look at any of the plots above. In fact, the apex is likely not even the half-way point. It almost always takes longer to come down the back of the curve than it does to go up the front of it. Expect the Stay at Home orders to remain in place for at least 4 to 6 weeks after your state passes its apex. We will likely be into June before we can even begin to think about going back to our normal lives.

Look, I understand the cabin fever is real. You want to go see your friends and loved ones. Be patient and be smart. We don’t need any more people dying from this virus than already are.

The post Latest SIR Model Outlooks: COVID-19 Pandemic appeared first on Matthew Gove Blog.

You can say the same thing about the COVID-19 pandemic. We all have a job to do to beat this thing. Every single one of us. Please use common sense, stay informed, and heed the warnings, guidance, and orders from your local, state, and federal government. Just like Hurricane and Tornado Warnings, there is a reason they are issuing warnings right now. Let’s have a look at why.

A New Type of Model: The SIR Model

Last week, we took a look at modeling the COVID-19 pandemic in the United States using Gaussian functions. Gaussian functions are also known as bell curves. Not surprisingly, there are more accurate ways to model a pandemic like this than with bell curves. Today, we are going to look at different scenarios using the SIR (Susceptible, Infected, Resistant) model. The SIR model is a simple model that uses a system of three differential equations to specifically model disease outbreaks.

The relationship between the equations is:

Getting into how to solve the differential equations is a discussion for another time. In English, the equations and variables describe:

• S(t) – The number of susceptible people (people who have not yet contracted the disease) over time
• I(t) – The number of infected people (people who are currently sick) over time
• R(t) – The number of resistant people (people who have either recovered or died) over time. The model assumes that recovered people cannot get sick a second time.
  • Note: In the model outputs below, I have broken R(t) down into recovered and dead.
• β – controls how often a susceptible-infected contact results in a new infection
• γ – The rate an infected person recovers and moves into the resistant phase

Introduction to R Naught

Now, you’re probably wondering where the “R naught” parameter comes in. R naught, denoted as R0, is the reproduction number. It is just a fancy way to say the average number of susceptible people to which an infected person spreads the disease. For example, if R naught is 3, it means that one infected person spreads the disease to an average of 3 other people over the course of their illness. We’ll define R naught as:

R0 = β / γ

Now, before we jump into the model, let’s have a look at the model inputs. Within the model, we need to define the population N. The population of the United States is about 330 million. We also need to define the average duration of infection, which according to the CDC is about 14 days. The initial conditions for each equation [S(t), I(t), and R(t)] were set so the numbers mirror the actual data of the outbreak in the United States so far.

The only input to the model is the R naught parameter. While we will be running the model for different scenarios, we’ll start with what the US Federal Government currently defines for R naught: R0 = 2.3. Keep in mind that these figures assume R0 is constant, while in the real world R0 is changing constantly.

A Few Short-Term SIR Model Predictions for the United States

First, a couple of short-term predictions from the SIR model, again assuming a constant R0.

Before we plot everything out over the course of the pandemic, I need to point out a few very important things:

• The plot (and the above plots) assumes R0 stays constant at 2.3. In the real world, R0 is constantly changing.
• Because R0 stays constant, it means that this scenario does not account for preventative measures, such as restrictions on large crowds, restaurant and bar closings, travel bans, and shelter-in-place orders.
• This is a worst-case scenario and the odds of this actually playing out are very slim.

Flattening the Curve

Flattening the curve. You hear it all over the news. What does it mean? If you leave the virus unchecked, it will grow exponentially and quickly overwhelm the hospital system when all of the sick patients show up at once. Instead, health authorities want to slow down the rate the disease is spreading and spread the sick patients out over time so hospitals can handle the volume of patients.

So how do we slow down the rate the disease is spreading? Simply lower the value of R naught. Okay, in the real world it’s quite a bit more complicated. Federal, state, and local governments across the country are putting measures in place to slow down the spread of the virus and reduce R naught, which may include:

• Bans on large gatherings
• Quarantines and Self-Isolation
• Closing of schools, restaurants, bars, museums, and other public places where people tend to gather
• Cancellations of Events
• Closing Borders and Travel Bans
• Shelter In Place Orders and Lockdowns

Still don’t believe me that flattening the curve works? Have a look at the following figure. I ran the SIR model several times with identical parameters, only varying the R naught values. Like the above examples, R naught remains constant for each run. These are just hypothetical scenarios and are not any kind of indication that anything like this will actually play out in the real world.

By reducing the R0 value from 2.6 down to 1.6, the number of infected people at the peak of the outbreak drops from 80 million down to about 25 million. For those of you that are mathematically challenged, that’s about 2/3, or 67% fewer infected people at the peak of the outbreak.

Modeling the Changing R Naught Values

The easiest way to model the changing R naught values is to use piecewise functions to solve the differential equations. That just means we will assign different values of R naught for different values of time (t in the differential equations at the top of this post). If you’ve ever done numerical analysis or numerical integration, you’ve probably come across piecewise functions at some point, but that’s a discussion for another day.

So how does this all translate to the real world? Consider a scenario that we’ve seen in a lot of countries so far in this pandemic. The virus spreads undetected within the community at the start of the outbreak. Then, federal, state, and local authorities put increasingly restrictive measures into place. Restrictions start with bans on large gatherings. They then escalate to closing down restaurants, bars, and other public places. Finally, officials order a mandatory shelter-in-place or lockdown.

To illustrate this visually, I modeled a hypothetical scenario where the virus starts with R0 = 2.3. It spreads undetected for about 45 days at the onset of the outbreak. The government orders restrictions, scaling down R Naught until the issuance of a shelter-in-place order. In this scenario, it takes about a month to go from issuing the first restriction to a full lockdown. In the real world, the restrictions are implemented much faster than that. For example, it took Italy 12 days to go from just a handful of cases to the entire country under lockdown. It took Spain 9 days to do the same.

Looking at the Real World

This is where it gets tricky. Because the United States is so big and diverse, let’s look at ten major cities instead. Different states, counties, and cities have enacted different bans to combat the virus, making it nearly impossible to accurately use this model at a national level. For example, the shelter-in-place that was just issued for the San Francisco Bay area is not going to affect what’s going on in Seattle, Chicago, or New York.

A Few Things to Keep in Mind

• These models consider the population of each metro area, which include the main city plus all of its suburbs.
• The R0 values on the plots are fixed for each run. In the real world, the R0 values will start high and then drop as restrictions are enacted.
• The high number of undetected or asymptomatic cases will help keep the R0 value of COVID-19 high.
• The “Peak” label in the legends refers to the number of infected people at the peak of the outbreak for that scenario.
• You want to focus on the number of infected people at the peak of each scenario. Do not worry about the exact dates of the peaks of the outbreaks.
  • As you look at those peak values, think of how you can help with social distancing to reduce R0.
• The current R0 value of the coronavirus in the United States is about 2.3, according to the federal government. That means that every infected person spreads the disease to an average of 2.3 other people. For comparison, the seasonal flu has an R0 value of 1.3.
• I don’t know what the hospital capacity is in each city, but for reference New York State (read: the whole state, not just NYC) has 54,000 hospital beds and 3,100 ICU beds.
• When the city of Wuhan, China enacted their total lockdown in January, the R0 value dropped from 2.35 to 1.05 in less than a week. You won’t see R0 drops this drastic in the United States. However, the goal to get R0 as low as possible remains the same.

SIR Model Outputs for Several US Cities

Conclusion

For this pandemic, I will say the same thing I say before just about every major weather disaster. Please heed your local, state, and federal government’s warnings. I can’t stress this enough. In a weather disaster, you’re only putting your own life at stake by being stupid. In a pandemic, you’re putting the lives of every one else who’s around you at stake as well.

I understand we are a society that rewards stupidity. If we all work together, there is still time to slow this thing down, but that window will slam shut in just a matter of a few days. All quarantining yourself from knowledge and common sense does is keep that critical R0 value high and put more lives at risk. I’ll leave you with one final plot of COVID-19 data comparing the US cases to Italy’s. This is actual data and is not generated by any models. Stay tuned for more updates.

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