The Weather Revolution: Innovations and Imminent Breakthroughs in Accurate Forecasting

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Charles Talcott Orloff of the Blue Hill Observatory tells the tale of Carol 50 years later through the stories and pictures of those who remember.

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This softcover book has pages including photographs and diagrams with detailed descriptions of the impact throughout New England of this significant and historic flooding event. A page soft cover book detailing the destruction from the remarkable and devastating storm. Over photographs - some never before published - are included. Minsinger and Charles T.

Orloff Click on front and back covers for a larger view. In addition to recent breakthroughs, this fascinating work also describes pioneering scientists throughout history who used great technological innovations, from the advent of the computer to rocketry, to further our knowledge of weather and climate. Meteorology has rapidly evolved into a cutting-edge science that has irrevocably increased our understanding of the Earth. This remarkable work shows us the force of weather in all its glory and danger. And it paves the way for the revolution in weather science that will lead us into the future.

First Name:. Send Message. Compiled and Volume 1. The Language of Rocks: Geology for the Novice.

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Language Education and Applied Linguistics: Bridging the two fields. For vaccines to work, we needed patients willing to introduce a potential pathogen into their bodies for a lifetime of protection against disease. We are born with a singular gift for imagining the future, but we have been enhancing those gifts since the dawn of civilization.

Today, new enhancements are on the horizon, in the form of machine-learning algorithms that already outperform humans at certain kinds of forecasts. Though the ancients imagined immortality and rebirth and lands of the dead, time machines were beyond their ken. Time travel is a fantasy of the modern era. But machines have been soothsayers from the beginning. In , sponge divers stranded after a storm in the Mediterranean discovered an underwater statuary on the shoals of the Greek island Antikythera.

It turned out to be the wreck of a ship more than 2, years old. During the subsequent salvage operation, divers recovered the remnants of a puzzling clocklike contraption with precision-cut gears, annotated with cryptic symbols that were corroded beyond recognition. For years, the device lay unnoticed in a museum drawer, until a British historian named Derek de Solla Price rediscovered it in the early s and began the laborious process of reconstructing it — an effort that scholars have continued into the 21st century.

We now know that the device was capable of predicting the behavior of the sun, the moon and five of the planets. The Antikythera mechanism, as it has come to be known, is sometimes referred to as an ancient computer. The analogy is misleading: The underlying technology behind the device was much closer to a clock than a programmable computer.

But at its essence, it was a prediction machine.

Tech advancements improving accuracy in predicting weather

A clock is there to tell you about the present. The mechanism was there to tell you about the future. What seems far more useful is the sense of magic and wonder that such a prediction could provide, and the power that could be acquired as a result. Imagine standing in front of the masses and announcing that tomorrow the sun will transform for more than a minute into a fire-tinged black orb.

Then imagine the awe when the prophecy comes true. Prediction machines have only multiplied since the days of the ancient Greeks. Where those original clockwork devices dealt with deterministic futures, like the motions of solar bodies, increasingly our time-traveling tools forecast probabilities and likelihoods, allowing us to imagine possible futures for more complex systems.

In the late s, thanks to improvements in public-health records and mathematical advances in statistics, the British astronomer Edmund Halley and the Dutch scientist Christiaan Huygens separately made the first rigorous estimates of average life expectancy. Around the same time, there was an explosion of insurance companies, their business made possible by this newfound ability to predict future risk.

Initially, they focused on the commercial risk of new shipping ventures, but eventually insurance would come to offer protection against just about every future threat imaginable: fire, floods, disease. In the 20th century, randomized, controlled trials allowed us to predict the future effects of medical interventions, finally separating out the genuine cures from the snake oil.


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In the digital age, spreadsheet software took accounting tools that were originally designed to record the past activity of a business and transformed them into tools for projecting out forecasts, letting us click through alternate financial scenarios in much the way our minds wander through various possible futures. But cognitive time travel has been enhanced by more than just science and technology.

Stories do not just allow us to conjure imaginary worlds; they also free us from being mired in linear time. A defining trick of recent popular narrative is the contorted timeline, with movies and TV shows embracing temporal schemes that would have baffled mainstream audiences just a few decades ago. The final five minutes of the Season 3 opener, which aired earlier this fall, jump back and forth seven times among , and some unspecified future that looks to be about These narrative developments suggest an intriguing possibility: that popular entertainment is training our minds to get better at cognitive time travel.

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Debate rages over 5G impact on US weather forecasting

Back then, even a single flashback required extra hand-holding — remember the rippling screen? Only experimental narratives dared challenge the audience with more complex time schemes. The elaborate timelines of popular narrative may be training our minds to contemplate more complex temporal schemes, but could new technology augment our skills more directly?

In a way, those advances are already around us, but in the form of software, not pharmaceuticals. If you have ever found yourself mentally running through alternate possibilities for a coming outing — what happens if it rains?

An algorithm might be trained to predict future mortgage defaults by analyzing thousands of home purchases and the financial profiles of the buyers, testing its hypotheses by tracking which of those buyers ultimately defaulted. A result of that training would not be an infallible prediction, of course, but something similar to the predictions we rely on with weather forecasts: a range of probabilities.

That time-traveling exercise, in which you imagine buying a house in the neighborhood with the great schools, could be augmented by a software prediction as well: The algorithm might warn you that there was a 20 percent chance that your home purchase would end catastrophically, because of a market crash or a hurricane. Or another algorithm, trained on a different data set, might suggest other neighborhoods where home values are also likely to increase. These algorithms can help correct a critical flaw in the default network: Human beings are famously bad at thinking probabilistically.

Algorithms can help us compensate for that cognitive blind spot. Machine-learning systems will also be immensely helpful when mulling decisions that potentially involve a large number of distinct options. Humans are remarkably adept at building imagined futures for a few competing timelines simultaneously: the one in which you take the new job, the one in which you turn it down. But our minds run up against a computational ceiling when they need to track dozens or hundreds of future trajectories.

The prediction machines of A.