In this chapter we will introduce and examine the use of Ethernet networking with Arduino over local networks and the greater Internet.

It will be assumed that you have a basic understanding of computer networking, such as the knowledge of how to connect computers to a hub/router with RJ45 cables, what an IP and MAC address is, and so on. Furthermore, here is a good quick rundown about Ethernet.

Getting Started

You will need an Arduino Uno or compatible board with an Ethernet shield that uses the W5100 Ethernet controller IC (pretty much all of them):

Furthermore you will need to power the board via the external DC socket – the W5100 IC uses more current than the USB power can supply. A 9V 1.5A plug pack/wall wart will suffice.

Finally it does get hot – so be careful not to touch the W5100 after extended use. In case you’re not sure – this is the W5100 IC:

Once you have your Ethernet-enabled Arduino, and have the external power connected – it’s a good idea to check it all works. Open the Arduino IDE and select File > Examples > Ethernet > Webserver. This loads a simple sketch which will display data gathered from the analogue inputs on a web browser. However don’t upload it yet, it needs a slight modification.

You need to specify the IP address of the Ethernet shield – which is done inside the sketch. This is simple, go to the line:

IPAddress ip(192,168,1, 177);

And alter it to match your own setup. For example, in my home the router’s IP address is 10.1.1.1, the printer is 10.1.1.50 and all PCs are below …50. So I will set my shield IP to 10.1.1.77 by altering the line to:

IPAddress ip(10,1,1,77);

byte mac[] = { 0xDE, 0xAD, 0xBE, 0xEF, 0xFE, 0xED };

However if you only have one shield just leave it be. There may be the very, very, statistically rare chance of having a MAC address the same as your existing hardware, so that would be another time to change it.

Once you have made your alterations, save and upload the sketch. Now open a web browser and navigate to the IP address you entered in the sketch, and you should be presented with something similar to the following:

What’s happening? The Arduino has been programmed to offer a simple web page with the values measured by the analogue inputs. You can refresh the browser to get updated values.

At this point – please note that the Ethernet shields use digital pins 10~13, so you can’t use those for anything else. Some Arduino Ethernet shields may also have a microSD card socket, which also uses another digital pin – so check with the documentation to find out which one.

Nevertheless, now that we can see the Ethernet shield is working we can move on to something more useful. Let’s dissect the previous example in a simple way, and see how we can distribute and display more interesting data over the network. For reference, all of the Ethernet-related functions are handled by the Ethernet Arduino library. If you examine the previous sketch we just used, the section that will be of interest is:

 for (int analogChannel = 0; analogChannel < 6; analogChannel++) 
          {
            int sensorReading = analogRead(analogChannel);
            client.print("analog input ");
            client.print(analogChannel);
            client.print(" is ");
            client.print(sensorReading);
            client.println("<br />");       
          }
          client.println("</html>");

Hopefully this section of the sketch should be familiar – remember how we have used serial.print(); in the past when sending data to the serial monitor box? Well now we can do the same thing, but sending data from our Ethernet shield back to a web browser – on other words, a very basic type of web page.

However there is something you may or may not want to  learn in order to format the output in a readable format – HTML code. I am not a website developer (!) so will not delve into HTML too much.

However if you wish to serve up nicely formatted web pages with your Arduino and so on, here would be a good start. In the interests of simplicity, the following two functions will be the most useful:

client.print(" is ");

Client.print (); allows us to send text or data back to the web page. It works in the same way as serial.print(), so nothing new there. You can also specify the data type in the same way as with serial.print(). Naturally you can also use it to send data back as well. The other useful line is:

client.println("<br />");

which sends the HTML code back to the web browser telling it to start a new line. The part that actually causes the carriage return/new line is the <br /> which is an HTML code (or “tag”) for a new line. So if you are creating more elaborate web page displays, you can just insert other HTML tags in the client.print(); statement.

If you want to learn more about HTML commands, here’s a good tutorial site. Finally – note that the sketch will only send the data when it has been requested, that is when it has received a request from the web browser.

Accessing your Arduino over the Internet

So far – so good. But what if you want to access your Arduino from outside the local network?

You will need a static IP address – that is, the IP address your internet service provider assigns to your connection needs to stay the same. If you don’t have a static IP, as long as you leave your modem/router permanently swiched on your IP shouldn’t change. However that isn’t an optimal solution.

If your ISP cannot offer you a static IP at all, you can still move forward with the project by using an organisation that offers a Dynamic DNS. These organisations offer you your own static IP host name (e.g. mojo.monkeynuts.com) instead of a number, keep track of your changing IP address and linking it to the new host name. From what I can gather, your modem needs to support (have an in-built client for…) these DDNS services. As an example, two companies are No-IP andDynDNS.com. Please note that I haven’t used those two, they are just offered as examples.

Now, to find your IP address… usually this can be found by logging into your router’s administration page – it is usually 192.168.0.1 but could be different. Check with your supplier or ISP if they supplied the hardware. For this example, if I enter 10.1.1.1 in a web browser, and after entering my modem administration password, the following screen is presented:

What you are looking for is your WAN IP address, as you can see in the image above. To keep the pranksters away, I have blacked out some of my address.

The next thing to do is turn on port-forwarding. This tells the router where to redirect incoming requests from the outside world. When the modem receives such a request, we want to send that request to the port number of our Ethernet shield. Using the:

EthernetServer server(125);

function in our sketch has set the port number to 125. Each modem’s configuration screen will look different, but as an example here is one:

So you can see from the line number one in the image above, the inbound port numbers have been set to 125, and the IP address of the Ethernet shield has been set to 10.1.1.77 – the same as in the sketch.

After saving the settings, we’re all set. The external address of my Ethernet shield will be the WAN:125, so to access the Arduino I will type my WAN address with :125 at the end into the browser of the remote web device, which will contact the lonely Ethernet hardware back home.

Furthermore, you may need to alter your modem’s firewall settings, to allow the port 125 to be “open” to incoming requests. Please check your modem documentation for more information on how to do this.

Now from basically any Internet connected device in the free world, I can enter my WAN and port number into the URL field and receive the results. For example, from a phone when it is connected to the Internet via LTE mobile data:

So at this stage you can now display data on a simple web page created by your Arduino and access it from anywhere with unrestricted Internet access. With your previous Arduino knowledge you can now use data from sensors or other parts of a sketch and display it for retrieval.

Displaying sensor data on a web page

As an example of displaying sensor data on a web page, let’s use an inexpensive and popular temperature and humidity sensor – the DHT22. You will need to install the DHT22 Arduino library which can be found on this page. If this is your first time with the DHT22, experiment with the example sketch that’s included with the library so you understand how it works.

Connect the DHT22 with the data pin to Arduino D2, Vin to the 5V pin and GND to … GND.

Now for our sketch – to display the temperature and humidity on a web page. If you’re not up on HTML you can use online services such as this to generate the code, which you can then modify to use in the sketch.

In the example below, the temperature and humidity data from the DHT22 is served in a simple web page:

#include <SPI.h>
#include <Ethernet.h>

// for DHT22 sensor
#include "DHT.h"
#define DHTPIN 2
#define DHTTYPE DHT22

// Enter a MAC address and IP address for your controller below.
// The IP address will be dependent on your local network:
byte mac[] = {   0xDE, 0xAD, 0xBE, 0xEF, 0xFE, 0xED };
IPAddress ip(10,1,1,77);

// Initialize the Ethernet server library
// with the IP address and port you want to use 
// (port 80 is default for HTTP):
EthernetServer server(125);
DHT dht(DHTPIN, DHTTYPE);

void setup() 
{
  dht.begin();
 // Open serial communications and wait for port to open:
  Serial.begin(9600);
   while (!Serial) {
    ; // wait for serial port to connect. Needed for Leonardo only
  }
  // start the Ethernet connection and the server:
  Ethernet.begin(mac, ip);
  server.begin();
  Serial.print("server is at ");
  Serial.println(Ethernet.localIP());
}

void loop() 
{
  // listen for incoming clients
  EthernetClient client = server.available();
  if (client) {
    Serial.println("new client");
    // an http request ends with a blank line
    boolean currentLineIsBlank = true;
    while (client.connected()) {
      if (client.available()) {
        char c = client.read();
        Serial.write(c);
        // if you've gotten to the end of the line (received a newline
        // character) and the line is blank, the http request has ended,
        // so you can send a reply
        if (c == 'n' && currentLineIsBlank) 
        {
          // send a standard http response header
          client.println("HTTP/1.1 200 OK");
          client.println("Content-Type: text/html");
          client.println("Connection: close");  // the connection will be closed after completion of the response
	  client.println("Refresh: 30");  // refresh the page automatically every 30 sec
          client.println();
          client.println("<!DOCTYPE HTML>");
          client.println("<html>");

          // get data from DHT22 sensor
          float h = dht.readHumidity();
          float t = dht.readTemperature();
          Serial.println(t);
          Serial.println(h);

          // from here we can enter our own HTML code to create the web page
          client.print("<head><title>Office Weather</title></head><body><h1>Office Temperature</h1><p>Temperature - ");
          client.print(t);
          client.print(" degrees Celsius</p>");
          client.print("<p>Humidity - ");
          client.print(h);
          client.print(" percent</p>");
          client.print("<p><em>Page refreshes every 30 seconds.</em></p></body></html>");
          break;
        }
        if (c == 'n') {
          // you're starting a new line
          currentLineIsBlank = true;
        } 
        else if (c != 'r') {
          // you've gotten a character on the current line
          currentLineIsBlank = false;
        }
      }
    }
    // give the web browser time to receive the data
    delay(1);
    // close the connection:
    client.stop();
    Serial.println("client disonnected");
  }
}

It is a modification of the IDE’s webserver example sketch that we used previously – with a few modifications. First, the webpage will automatically refresh every 30 seconds – this parameter is set in the line:

client.println("Refresh: 30");  // refresh the page automatically every 30 sec

… and the custom HTML for our web page starts below the line:

// from here we can enter our own HTML code to create the web page

You can then simply insert the required HTML inside client.print() functions to create the layout you need.

Finally – here’s an example screen shot of the example sketch at work:

You now have the framework to create your own web pages that can display various data processed with your Arduino.

Conclusion

I hope you enjoyed making this or at least reading about it. If you find this sort of thing interesting, please consider ordering one or more of my books from amazon.

And as always, have fun and make something.

To keep up to date with new posts at tronixstuff.com, please subscribe to the mailing list in the box on the right, or follow us on twitter @tronixstuff.

The strongest geomagnetic storm in 20 years made the colorful northern lights, or aurora borealis, visible Friday night in areas of the US that are normally too far south to see them. And the show may not be over. Tonight may offer another chance to catch the aurora if you have clear skies, according to the NOAA, and Sunday could bring yet more displays reaching as far as Alabama.

The NOAA’s Space Weather Prediction Center said on Saturday that the sun has continued to produce powerful solar flares. That’s on top of previously observed coronal mass ejections (CMEs), or explosions of magnetized plasma, that won’t reach Earth until tomorrow. The agency has been monitoring a particularly active sunspot cluster since Wednesday, and confirmed yesterday that it had observed G5 conditions — the level designated “extreme” — which haven’t been seen since October 2003. In a press release on Friday, Clinton Wallace, Director, NOAA’s Space Weather Prediction Center, said the current storm is “an unusual and potentially historic event.”

Geomagnetic storms happen when outbursts from the sun interact with Earth’s magnetosphere. While it all has kind of a scary ring to it, people on the ground don’t really have anything to worry about. As NASA explained on X, “Harmful radiation from a flare cannot pass through Earth’s atmosphere” to physically affect us. These storms can mess with our technology, though, and have been known to disrupt communications, GPS, satellite operations and even the power grid.

A machine learning-based weather prediction program developed by DeepMind researchers called “GraphCast” can predict weather variables over the span of 10 days, in under one minute. In a report, scientists highlight that GraphCast has outperformed traditional weather pattern prediction technologies at a 90% verification rate.

The AI-powered weather prediction program works by taking in “the two most recent states of Earth’s weather,” which includes the variables from the time of the test and six hours prior. Using that data, GraphCast can predict what the state of the weather will be in six hours. 

In practice, AI has already showcased its applicability in the real world. The tool predicted the landfall of Hurricane Lee in Long Island 10 days before it happened, while the traditional weather prediction technologies being used by meteorologists at the time lagged behind. Forecasts made by standard weather simulations can take longer because traditionally, models have to account for complicated physics and fluid dynamics to make accurate predictions.

Not only does the weather prediction algorithm outperform traditional technologies to forecast weather patterns in terms of pace and scale, GraphCast can also predict severe weather events, which includes tropical cyclones and waves of extreme temperatures over regions. And because the algorithm can be re-trained with recent data, scientists believe that the tool will only get better at predicting oscillations in weather patterns that coincide with grander changes that align with climate change.

Soon, GraphCast, or at least the basis of the AI algorithm that powers its predictions, might pop up into more mainstream services. According to Wired, Google might be exploring how to integrate GraphCast into its products. The call for better storm modeling has already paved a path for supercomputers in the space. The NOAA (National Oceanic and Atmospheric Administration) says it has been working to develop models that will provide more accurate readings on when severe weather events might occur and importantly, the intensity forecasts for hurricanes.

On Monday, meteorologists documented the hottest day in recorded history, according to US National Centers for Environmental Prediction (via Reuters). July 3rd, 2023 saw average global temperatures edge past 17-degrees Celsius (62.62 Fahrenheit) for the first time since satellite monitoring of global temperatures began in 1979. Scientists believe Monday is also the hottest day on record since humans began using instruments to measure daily temperatures in the late 19th century. The previous record was set in August 2016 when the world’s average temperature climbed to 16.92C (62.45 Fahrenheit).

This week, the southern US is sweltering under a heat dome that has sent local temperatures past the 110 Fahrenheit mark (43C). Even places that normally aren’t known for their warm weather have been unseasonably hot in recent days and weeks, with the Vernadsky Research Base in Antarctica recording a July high of 8.7C.

Scientists attribute the recent heat to a combination of El Niño and ongoing human-driven emissions of greenhouse gases. Studies have shown that climate change is contributing to heat waves that are more frequent, last longer and hotter than ever. "The average global surface air temperature reaching 17C for the first time since we have reliable records available is a significant symbolic milestone in our warming world," climate researcher Leon Simons told BBC News. "Now that the warmer phase of El Niño is starting we can expect a lot more daily, monthly and annual records breaking in the next 1.5 years.”

Amazon told lawmakers it wouldn’t build storm shelters in its warehouses after a December 2021 tornado killed six employees at an Illinois location. Although the company changed its severe-weather response strategy after the incident, it essentially told the elected officials that since building storm shelters isn’t required by law, it won’t do that.

The company responded to lawmakers Senator Elizabeth Warren (D-MA) and Representatives Alexandria Ocasio-Cortez (D-NY) and Cori Bush (D-MO), who sent a letter on December 15th, questioning the company’s lack of storm shelters or safe rooms at its warehouses. “Amazon’s apparent unwillingness to invest in a storm shelter or safe room at its Edwardsville facility is made even more concerning by the fact that installing one could be done by Amazon at relatively low cost,” the lawmakers wrote. “This cost is negligible for a company like Amazon, which brought in more than $500 billion in revenue over the 12-month period ending September 30, 2022 and clearly has the resources necessary to protect its workers should it have the will to do so.”

Company vice president of public policy Brian Huseman responded (via CNBC), “Amazon requires that its buildings follow all applicable laws and building codes. We have not identified any jurisdiction in the United States that requires storm shelters or safe rooms for these types of facilities.”

Lawrence Bryant / reuters

Huseman added that Amazon follows Occupational Safety and Health Administration (OSHA) and National Weather Service guidelines and will continue using a “severe weather assembly area” for sheltering in place instead of the requested storm shelters. The six employees and contractors who died at the warehouse tried to protect themselves in a bathroom; the surviving workers took refuge in an assembly area.

OSHA investigated the incident last April and ordered Amazon to review its severe weather policies, but it fell short of penalizing the company for its response. Additionally, Amazon hired a meteorologist, launched an internal center for monitoring severe weather and created emergency cards pointing out evacuation points and assembly areas.

Amazon reportedly began rebuilding the warehouse last June. The families of two of the employees killed there have sued the company for wrongful death.

Self-driving cars frequently have trouble with poor weather, but Waymo thinks it can overcome these limitations by using its autonomous taxis as weather gauges. The company has revealed that its latest car sensor arrays are creating real-time weather maps to improve ride hailing services in Phoenix and San Francisco. The vehicles measure the raindrops on windows to detect the intensity of conditions like fog or rain.

The technology gives Waymo a much finer-grained view of conditions than it gets from airport weather stations, radar and satellites. It can track the coastal fog as it rolls inland, or drizzle that radar would normally miss. While that's not as important in a dry locale like Phoenix, it can be vital in San Francisco and other cities where the weather can vary wildly between neighborhoods.

There are a number of practical advantages to gathering this data, as you might guess. Waymo is using the info to improve its Driver AI's ability to handle rough weather, including more realistic simulations. The company also believes it can better understand the limits of its cars and set higher requirements for new self-driving systems. The tech also helps Waymo One better serve ride hailing passengers at a given time and place, and gives Waymo Via trucking customers more accurate delivery updates.

The current weather maps have their limitations. They may help in a warm city like San Francisco, where condensation and puddles are usually the greatest problems, but they won't be as useful for navigating snowy climates where merely seeing the lanes can be a challenge. There's also the question of whether or not it's ideal to have cars measure the very conditions that hamper their driving. This isn't necessarily the safest approach.

This could still go a long way toward making Waymo's driverless service more practical, though. Right now, companies like Waymo and Cruise aren't allowed to operate in heavy rain or fog using their California permits — the weather monitoring could help these robotaxi firms serve customers looking for dry rides home.

Almost exactly five years after Hurricane Maria left Puerto Rico in the dark, the US territory is once again facing a power crisis. On Sunday, LUMA Energy, the company that operates the island’s electrical grid, announced that all of Puerto Rico had suffered a blackout due to Hurricane Fiona, reports Reuters.

With the storm nearing the island’s southwest coast, the National Hurricane Center warned of “catastrophic” flooding as Fiona began producing winds with recorded speeds of 85 miles per hour. Without even making landfall, the storm left a third of LUMA’s customers without power. On Twitter, Puerto Rico Governor Pedro Pierluisi said the government was working to restore power, but after the events of five years ago, there’s worry there won’t be an easy fix.

In 2017, Hurricane Maria caused the largest blackout in US history when the Category 5 storm battered Puerto Rico, leaving 3.4 million people without power. The island had only recently begun rebuilding its weakened infrastructure, with blackouts a daily occurrence in some areas. Officials have tried to stress that Hurricane Fiona won’t bring a repeat of 2017. “This is not Maria, this hurricane will not be Maria,” Abner Gomez, the head of public safety and crisis management at LUMA Energy, told CNN before Sunday’s power outage.

Hurricane season is currently in full swing across the Gulf Coast and Eastern Seaboard. Following a disconcertingly quiet start in June, meteorologists still expect a busier-than-usual stretch before the windy weather (hopefully) winds down at the end of November. Meteorologists like Matthew Cappucci who, in his new book, Looking Up: The True Adventures of a Storm-Chasing Weather Nerd, recounts his career as a storm chaser — from childhood obsession to adulthood obsession as a means of gainful employment. In the excerpt below, Cappucci explains the inner workings of tropical storms.

Simon and Schuster

Excerpted from Looking Up: The True Adventures of a Storm-Chasing Weather Nerd by Matthew Cappucci. Published by Pegasus Books. Copyright © 2022 by Matthew Cappucci. All rights reserved.

Hurricanes are heat engines. They derive their fury from warm ocean waters in the tropics, where sea surface temperatures routinely hover in the mid- to upper-eighties between July and October. Hurricanes and tropical storms fall under the umbrella of tropical cyclones. They can be catastrophic, but they have a purpose—some scholars estimate they’re responsible for as much as 10 percent of the Earth’s annual equator-to-pole heat transport.

Hurricanes are different from mid-latitude systems. So-called extratropical, or nontropical, storms depend upon variations in air temperature and density to form, and feed off of changing winds. Hurricanes require a calm environment with gentle upper-level winds and a nearly uniform temperature field. Ironic as it may sound, the planet’s worst windstorms are born out of an abundance of tranquility.

The first ingredient is a tropical wave, or clump of thunderstorms. Early in hurricane season, tropical waves can spin up on the tail end of cold fronts surging off the East Coast. During the heart of hurricane season in August and September, they commonly materialize off the coast of Africa in the Atlantic’s Main Development Region. By October and November, sneaky homegrown threats can surreptitiously gel in the Gulf of Mexico or Caribbean.

Every individual thunderstorm cell within a tropical wave has an updraft and a downdraft. The downward rush of cool air collapsing out of one cell can suffocate a neighboring cell, spelling its demise. In order for thunderstorms to coexist in close proximity, they must organize. The most efficient way of doing so is through orienting themselves around a common center, with individual cells’ updrafts and downdrafts working in tandem.

When a center forms, a broken band of thunderstorms begins to materialize around it. Warm, moist air rises within those storms, most rapidly as one approaches the broader system’s low-level center. That causes atmospheric pressure to drop, since air is being evacuated and mass removed. From there, the system begins to breathe.

Air moves from high pressure to low pressure. That vacuums air inward toward the center. Because of the Coriolis force, a product of the Earth’s spin, parcels of air take a curved path into the fledgling cyclone’s center. That’s what causes the system to rotate.

Hurricanes spin counterclockwise in the Northern Hemisphere, and clockwise south of the equator. Though the hottest ocean waters in the world are found on the equator, a hurricane could never form there. That’s because the Coriolis force is zero on the equator; there’d be nothing to get a storm to twist.

As pockets of air from outside the nascent tropical cyclone spiral into the vortex, they expand as barometric pressure decreases. That releases heat into the atmosphere, causing clouds and rain. Ordinarily that would result in a drop in temperature of an air parcel, but because it’s in contact with toasty ocean waters, it maintains a constant temperature; it’s heated at the same rate that it’s losing temperature to its surroundings. As long as a storm is over the open water and sea surface temperatures are sufficiently mild, it can continue to extract oceanic heat content.

Rainfall rates within tropical cyclones can exceed four inches per hour thanks to high precipitation efficiency. Because the entire atmospheric column is saturated, there’s little evaporation to eat away at a raindrop on the way down. As a result, inland freshwater flooding is the number one source of fatalities from tropical cyclones.

The strongest winds are found toward the middle of a tropical storm or hurricane in the eyewall. The greatest pressure gradient, or change of air pressure with distance, is located there. The sharper the gradient, the stronger the winds. That’s because air is rushing down the gradient. Think about skiing — you’ll ski faster if there’s a steeper slope.

When maximum sustained winds surpass 39 mph, the system is designated a tropical storm. Only once winds cross 74 mph is it designated a hurricane. Major hurricanes have winds of 111 mph or greater and correspond to Category 3 strength. A Category 5 contains extreme winds topping 157 mph.

Since the winds are derived from air rushing in to fill a void, or deficit of air, the fiercest hurricanes are usually those with the lowest air pressures. The most punishing hurricanes and typhoons may have a minimum central barometric pressure about 90 percent of ambient air pressure outside the storm. That means 10 percent of the atmosphere’s mass is missing.

Picture stirring your cup of coffee with a teaspoon. You know that dip in the middle of the whirlpool? The deeper the dip, or fluid deficit, the faster the fluid must be spinning. Hurricanes are the same. But what prevents that dip from filling in? Hurricane eyewalls are in cyclostrophic balance.

That means a perfect stasis of forces makes it virtually impossible to “fill in” a storm in steady state. Because of their narrow radius of curvature, parcels of air swirling around the eye experience an incredible outward-directed centrifugal force that exactly equals the inward tug of the pressure gradient force. That leaves them to trace continuous circles.

If you’ve ever experienced a change in altitude, such as flying on an airplane, or even traveling to the top of a skyscraper, you probably noticed your ears popping. That’s because they were adjusting to the drop in air pressure with height. Now imagine all the air below that height vanished. That’s the equivalent air pressure in the eye a major hurricane. The disparity in air pressure is why a hurricane is, in the words of Buddy the Elf, “sucky. Very sucky.”

Sometimes hurricanes undergo eyewall replacement cycles, which entail an eyewall shriveling and crumbling into the eye while a new eyewall forms around it and contracts, taking the place of its predecessor. This usually results in a dual wind maximum near the storm’s center as well as a brief plateau in intensification.

In addition to the scouring winds found inside the eyewall, tornadoes, tornado-scale vortices, mini swirls, and other poorly understood small-scale wind phenomena can whip around the eye and result in strips of extreme damage. A mini swirl may be only a couple yards wide, but a 70 mph whirlwind moving in a background wind of 100 mph can result in a narrow path of 170 mph demolition. Their existence was first hypothesized following the passage of Category 5 Hurricane Andrew through south Florida in 1992, and modern-day efforts to study hurricane eyewalls using mobile Doppler radar units have shed light on their existence. Within a hurricane’s eye, air sinks and warms, drying out and creating a dearth of cloud cover. It’s not uncommon to see clearing skies or even sunshine. The air is hot and still, an oasis of peace enveloped in a hoop of hell.

There’s such a discontinuity between the raucous winds of the eyewall and deathly stillness of the eye that the atmosphere struggles to transition. The eyes of hurricanes are often filled with mesovortices, or smaller eddies a few miles across, that help flux and dissipate angular momentum into the eye. Sometimes four or five mesovortices can cram into the eye, contorting the eyewall into a clover-like shape. That makes for a period of extraordinary whiplash on the inner edge of the eyewall as alternating clefts of calamitous wind and calm punctuate the eye’s arrival.

Last year, hurricanes hammered the Southern and Eastern US coasts at the cost of more than 160 lives and $70 billion in damages. Thanks to climate change, it's only going to get worse. In order to quickly and accurately predict these increasingly severe weather patterns, the National Oceanic and Atmospheric Administration (NOAA) announced Tuesday that it has effectively tripled its supercomputing (and therefore weather modelling) capacity with the addition of two high-performance computing (HPC) systems built by General Dynamics.

“This is a big day for NOAA and the state of weather forecasting,” Ken Graham, director of NOAA’s National Weather Service, said in a press statement. “Researchers are developing new ensemble-based forecast models at record speed, and now we have the computing power needed to implement many of these substantial advancements to improve weather and climate prediction.”

General Dynamics was awarded the $505 million contract back in 2020 and delivered the two computers, dubbed Dogwood and Cactus, to their respective locations in Manassas, Virginia, and Phoenix, Arizona. They'll replace a pair of older Cray and IBM systems in Reston, Virginia, and Orlando, Florida.

Each HPC operates at 12.1 petaflops or, "a quadrillion calculations per second with 26 petabytes of storage," Dave Michaud, Director, National Weather Service Office of Central Processing, said during a press call Tuesday morning. That's "three times the computing capacity and double the storage capacity compared to our previous systems... These systems are amongst the fastest in the world today, currently ranked at number 49 and 50." Combined with its other supercomputers in West Virginia, Tennessee, Mississippi and Colorado, the NOAA wields a full 42 petaflops of capacity. 

With this extra computational horsepower, the NOAA will be able to create higher-resolution models with more realistic physics — and generate more of them with a higher degree of model certainty, Brian Gross, Director, NOAA’s Environmental Modeling Center, explained during the call. This should result in more accurate forecasts and longer lead times for storm warnings.

"The new supercomputers will also allow significant upgrades to specific modeling systems in the coming years," Gross said. "This includes a new hurricane forecast model named the Hurricane Analysis and Forecast System, which is slated to be in operation at the start of the 2023 hurricane season," and will replace the existing H4 hurricane weather research and forecasting model.

While the NOAA hasn't yet confirmed in absolute terms how much of an improvement the new supercomputers will grant to the agency's weather modelling efforts, Ken Graham, the Director of National Weather Service, is convinced of their value. 

"To translate what these new supercomputers will mean for for the average American," he said during the press call, "we are currently developing models that will be able to provide additional lead time in the outbreak of severe weather events and more accurately track the intensity forecasts for hurricanes, both in the ocean and that are expected to hit landfall, and we want to have longer lead times [before they do]."

When the United Arab Emirates launched the Arab world’s first-ever mission to Mars in the summer of 2020, its desire was that its Hope probe would help provide scientists with a better understanding of the Red Planet’s weather systems. And it’s now done exactly that. According to The National, the probe recently spent two weeks tracking a massive dust storm across the surface of Mars.

Hope began following the weather event on December 29th. The probe entered the orbit of Mars equipped with a high-resolution camera and an infrared spectrometer. It used those tools to track the geographic distribution of dust, water vapor and carbon dioxide ice clouds displaced by the raging storm. Its orbital position allowed Hope to observe any variance in those elements in timescales measured in minutes and days, a feat previous missions to Mars didn’t have the ability to do. 

What it saw was how quickly a storm can spread across the red planet. In the span of a single week, the storm it was tracking grew to stretch across more than 1,550 miles of Martian surface. In the process, it completely obscured geographic landmarks like the Hellas impact crater and sent dust haze as far as 2,485 miles away from the origin point of the storm. In addition to providing a play-by-play of a Martian storm, scientists hope the data Hope collected will allow them to gain a better understanding of how those storms can help water escape the planet's atmosphere.