At Niwa and MetService, predicting the future involves sophisticated technology and an absurd amount of data, while climate change adds urgency to meteorologists’ work. Shanti Mathias reports for IRL. 

Maybe you’re planning a picnic, or choosing which outfit to wear. Checking the weather is an automatic reflex, a tap of fingers to see a sunshine emoji or a picture of rain on your weather app of choice. 

This simplicity belies an intricate network of tools, data, technology and human ingenuity responsible for creating the weather forecast. Above Paraparaumu, shiny, beanbag-sized hydrogen weather balloons are released daily, sending readings from throughout the atmosphere to MetService. As the balloons rise, the hydrogen within them expands until they are the size of a small house. MetService receives the data. The balloon explodes.

The forecast also depends on the buoy offshore from Hokitika, measuring waves and sending the data to Niwa for analysis; on photographs of clouds beamed down from a Japanese satellite orbiting 35,000 kilometres above the Pacific; on a radar in Taranaki processing microwaves reflected from raindrops. 

To generate the weather forecast everyone accesses, meteorologists turn torrents of data – information about air and water from around the country and the world – into a forecast that can be a sentence on the radio or a cloud emoji beneath a touch screen. At MetService, New Zealand’s national weather authority, and Niwa, a Crown Research Institute focusing on climate and water science, meteorologists work around the clock to process data into forecasts. 

“People haven’t realised how good forecasting has gotten in the last few decades,” says Tristan Meyers, a meteorologist and forecaster at Niwa. A generation ago, knowing the weather beyond two or three days was largely guesswork. Now, he says, forecasts up to five days away are at least 80% accurate, and longer range forecasts are getting better, too. 

The improvement is largely thanks to technology, especially data processing, says Lisa Murray, meteorologist and science communicator at MetService. “We’d be up there with the most data-heavy industry in the world,” she says. Think of it like this: weather is about the temperature and rainfall, yes, but also about wind strength and direction, humidity, pressure and more. Effective weather forecasting requires estimates of these measurements at, say, 10 metre intervals above points on land, all the way up through the atmosphere and forward through time. 

Both MetService and Niwa input these many, many data points into their own weather models, which are essentially representations of the state of atmosphere, extrapolated into the future. MetService uses three “global models” – computer simulations of the entire atmosphere – to predict the weather. The models, which are from the American, British and European weather bureaus, are combined with forecaster knowledge of how weather systems interact with New Zealand geography to produce the most accurate prediction. 

Meyers sketches on the table, showing me how observations from around the country are fed to models. His finger draws intersecting gridded lines, a representation of how these models imagine the heat and air and water that shift through the atmosphere to create weather. 

Whether weather models are produced at MetService and Niwa or adapted from overseas, running this enormous volume of information requires supercomputers. Niwa’s supercomputers, Mahuika, Kupe and Māui, can process more than two thousand trillion calculations per second. MetService run their simulations on Amazon Web Services’ cloud. 

Despite this processing power, some weather models “take a long time to run”, Meyers says, so they are updated only twice or four times a day, and longer term climatic or seasonal models are updated once a week or less. He shows me some of the different versions of weather over the next few days and the probability of each, clouds of orange – that’s precipitation – skidding across the ocean and catching on the Southern Alps. 

The volume of data weather forecasting requires offers a glimpse into how humans use technology to grasp almost unimaginably complex systems. Murray refers to the “butterfly effect”, the idea that in a big system like the atmosphere, a butterfly flapping its wings in Mozambique could cause a cyclone in Manila. “There are millions of observations and variations,” she says, “and each has a knock-on effect.” 

“There’s chaos in the weather,” Meyers says, a candid admission by someone whose job is turning that chaos into order. Different kinds of modelling, including “ensemble techniques” where multiple models are run at once to give a spread of outcomes, and machine learning, where models are fed the actual weather compared to their predictions so they can learn, help to diminish the “inherent unpredictability”, but the atmosphere is large and ever shifting, and no model is perfect.

Forecasts predict the weather, the air we breathe, the salient effects of the atmosphere in the very near future. But weather is inseparable from climate, the long term trends of temperature and rainfall. Is climate change altering how predictions are done? 

Not really, says Murray. “The increases in temperature are automatically fed into the model, it starts at a warmer temperature and produces predictions from there.” The forecaster’s role is to respond when the model produces extreme weather events, like flooding in Westport or Canterbury. “We [can’t] look at it and think, ‘The model must be wrong’, because these extreme events are possible.” 

Climate change is even having an effect on the weather observation stations around the country that relay information to forecasters. “We’re working on moving the wind anemometer in Westport,” Murray says, as the instrument, which measures wind speed and direction, is at risk from coastal erosion. While weather-observing instruments are built to withstand extreme conditions, flooding can render the stations unable to transmit. In the February 2020 floods in Fiordland, for instance, the rain gauge at Milford Sound was submerged. “I was quite surprised. We’re seeing more of these extremes,” says Murray. 

Aspersions are often cast at those trying to make a profit from the future: horoscope writers, owners of psychic octopuses, or financial speculators. Weather forecasting, however, is a scientifically legitimate way to augur the future, a future of which climate change is a part.  

“Looking into the future becomes a habit,” Murray says. Living with the data makes climate change something concrete to her. “There’s already one degree of warming. That means more moisture in the air, systems have more punch to them.” 

Predicting the future means nothing, of course, if people don’t understand it. For both MetService and Niwa, climate change ups the stakes of weather communication. Having the data and the technology to create forecasts is only one piece of the weather puzzle. 

“It’s no longer good enough to do a good forecast if people don’t know about it,” Murray says. One of the main parts of her job is to use social media, both to relay forecasts and view photos from across the country sent in by followers. “The feedback we get on social media helps the forecast room,” she says. “We know what hail in Timaru or flooding in Gisborne actually looks like.” 

The forecasts are important for public safety; MetService is the national provider of severe weather warnings, delivered through their app and website as well as media channels. “I make sure all my friends have the MetService app so they can get watches and warnings,” Murray says. “It’s life-or-death forecasting … In a changing climate, we’re going to see more extreme events. I want to keep people safe.”

Weather apps, which most of us have in our pockets, may bely the complexity of the information that goes into a forecast, but that’s a good thing, Meyers says. 

“You want people to have that information [about the weather],” he says. “You don’t want them to have to do this.” He pulls up the interface he uses to talk to the supercomputer, lines of green code on a black background. My brain immediately goes into ‘I do not understand the computer’ panic mode and I instantly decide that I love the simplicity of my emoji-based weather apps and could never work as a meteorologist. 

“The way the internet interacts with weather is in its infancy,” says Meyers. Behind him, the weather is coming in; the overcast sky gathering plump streaks of grey, the northerly puffing against the windows of the Niwa building at Greta Point.

I ask Meyers how it feels to think constantly about what lays ahead. “It just doesn’t stop,” he says, and I’m not sure if he’s referring to the future, the weather, or both. 

In buying a cheap ring, Shanti Mathias found herself part of the business of dropshipping, a model based on social media ads, instant digital storefronts, and opaque global supply chains. What was she really buying? And who benefitted? She explores for IRL. 

I had seen ads for the ring for weeks on Facebook. The images looked beautiful and interesting, with strange suckered tentacles coiling around the model’s fingers. The ring was free, the ad said, but the sale would end soon. Eventually, I clicked the image and paid for shipping, and imagined becoming the kind of person who wore intriguing rings. 

Two months later, the ring arrived in a white bubble-wrapped packet, the shipping slip mostly in Chinese, with none of the branding of the shop I’d bought it from. It looked nothing like the octopus it was supposed to be, the markings on the tentacles off-centre, disappearing when I rubbed them and leaving a smudge on my thumb. When I put it on, it made my skin itch. Online, other customer reviews shared my feelings that the products were sort of (but not really) the same as the pictures, the brand not exactly the small business it had seemed.

The ring I bought had probably been dropshipped. Dropshipping is a business model where people sell goods via an online shopfront with no physical location or warehouse. When you order a product from a dropshipper, they don’t handle or interact with your item at any time; instead, they forward your order to an ultra-cheap retailer/wholesaler such as AliExpress or Shein, who process your order and send you the item. 

Dropshipping and the digital advertising industry go hand-in-hand. Searching “dropshipping” on YouTube or any search engine will bring up a host of websites and articles promising to teach you – yes, you! – how to start your dropshipping business and become rich nearly instantly.

There is an appeal to this ease of access. Using the platform Shopify, it is the work of minutes to set up a website, with plug-in Oberlo allowing users to directly import and re-price items from AliExpress and list them for sale. Dropshippers might also list items on marketplace platforms like TradeMe, Amazon, or eBay. 

It is marketing which allows dropshippers to sell cheap things at inflated prices. The ring I bought was on a website selling other quirky jewellery just like it, for $5 – $15 each. On AliExpress, I can find a similar ring for less than a dollar. Offering something for free so customers will buy other items is a marketing technique dropshippers are encouraged to use, as artist Jenny Odell found in her investigation of a free watch somebody brought to the Museum of Capitalism.  

With a mix of stock images, Photoshop editing, and adjustments to template Shopify websites, dropshippers create a brand that makes what they’re selling seem like it’s worth more than the rock bottom prices on AliExpress or other cheap wholesalers. Dropshippers are encouraged to find a niche so they can target social media users by topic, using ad tools. When I looked at the advertising topics Facebook has tagged me with, I found that I had been marked as being interested in “water”, which may have been why the dropshipping shop targetted me with ocean-related products. Other users might be picked for their interests in purportedly handmade clothing or car repair. 

Ad spend is one of the main expenditures for those with dropshipping businesses. Otherwise, there is little upfront capital required, other than the cost of registering a website; by not holding any product themselves, dropshippers can start a business with less than a hundred dollars. 

Those who dropship are almost always opaque about their business model, but the system is not necessarily a scam. After all, people usually get the item they paid for, even if the quality is not what they expected. In New Zealand, dropshipping is legal – it’s even permitted on TradeMe – although sellers should be registered for a New Zealand Business Number. 

The attraction of dropshipping is the simplicity of starting a website from a template, with little to no capital required. But this means the model is easy to replicate. There is no shortage of cheaply made things available on the internet, so to effectively shill cheap products requires expertise in branding, marketing, and customer service.

However, while exact statistics are difficult to come by, many find that dropshipping does not offer the instant riches that are often promised. 

Those who claim to have made thousands of dollars from dropshipping, including New Zealanders, are often reluctant to demonstrate concrete evidence of their income. As journalist Sirin Kale documents, the most successful dropshippers tend to eventually abandon their businesses, saying that there is no long-term future in the model, and instead sell expensive courses promising to teach others their secrets.

When I held my ring, not at all the thing I had thought it was going to be, resolute in its cheapness, I was at the endpoint of a globalised supply chain astonishing in its opacity. I didn’t know whether the person behind the shop I had bought it from lived in New Zealand or Nepal; the packaging seemed Chinese, but it could have been dispatched from a warehouse, rather than a factory. Jenny Odell highlights this in her digital museum exhibit: dropshipped goods are symptoms of a system that creates cheap things, then erases the connections between the maker and the end consumer. 

Of course, much of contemporary retail is built on streamlined, fuzzy supply chains. High street retailers have faced increasing scrutiny over their sourcing in recent years, including calls for a Modern Slavery Act in Aotearoa to make companies transparent about the labour that produces what they sell. The third-party fulfilment model used by dropshippers existed before the internet, too, with mail-order catalogues and use of warehouses. Whether dropshipped or sold through a traditional retailer, items manufactured in places with few labour and environmental regulations are cheap because the consumer does not bear the cost—but someone does. 

With dropshipped goods as with so much else, that which seems too cheap to be true probably is. I eventually threw out my free ring, which tarnished quickly on encountering my bread-kneading lifestyle. I now know what to look out for next time I click an advertisement that has been following me around social media: stock imagery branding, no clear person who runs the business, products that can be found on AliExpress with a reverse image search, “sales” that never go away, and reviews that mention long shipping times and disappointing product quality. 

I looked for the shop I bought my ring from the other day, and found that it had disappeared, bar a few angry reviews on third party websites. Did the person behind it stop selling to start a dropshipping course, or did they spend thousands of dollars on marketing cheap jewellery and only get a few hundred sales? 

The model of dropshipping is usually not good for customers, who receive cheap goods at marked-up prices with little customer service if something goes wrong. Nor is it good for labourers and the environment, due to minimal oversight into the processes which produce these objects. But dropshipping isn’t really good for sellers, either: making a viable income from dropshipping requires a lot more work than the YouTube videos suggest, and those that hope dropshipping can become their main income will likely be let down.

Whether it comes from a major retailer or a single person importing AliExpress products into a digital storefront, money is the same to social media companies like Facebook, Instagram, and e-commerce giants like Shopify and Amazon. In the digital economy, the house always wins.