#climate modeling

Venus is an Earth sized planet 500° hot with sulfuric acid in its atmosphere. It was speculated that if Venus had water it could maintain life even under hostile conditions. If Venus was less hot and more temperate in the ancient past it is possible for Oceans to form.

1. Introduction Brief overview of quantum computing. Importance of quantum computing in the future of technology. 2. Understanding Quantum Computing Explanation of qubits, superposition, and entanglement. How quantum computing differs from classical computing. 3. The Current State of Quantum Computing Advances by major players (Google, IBM, Microsoft). Examples of quantum computing…

Excerpt from this story from BBC News:

Top climate scientists have admitted they failed to predict the intensity of the German floods and the North American heat dome.

They've correctly warned over decades that a fast-warming climate would bring worse bursts of rain and more damaging heatwaves.

But they say their computers are not powerful enough to accurately project the severity of those extremes.

They want governments to spend big on a shared climate super-computer.

Computers are fundamental to weather forecasting and climate change, and computing will underpin the new climate science “Bible”, from the Intergovernmental Panel on Climate Change (IPCC) next month.

But former Met Office chief scientist Prof Dame Julia Slingo told BBC News: "We should be alarmed because the IPCC (climate computer) models are just not good enough.

"(We need) an international centre to deliver the quantum leap to climate models that capture the fundamental physics that drive extremes.

"Unless we do that we will continue to underestimate the intensity/frequency of extremes and the increasingly unprecedented nature of them."

She said the costs of the computer, which would be in the hundreds of millions of pounds, would "pale into insignificance" compared with the costs of extreme events for which society is unprepared.

Climate models correctly interpreted Holocene climate

When used to make a scientific prediction, a good model is one that tells you something you don’t know because you don’t have the best data. You put in everything you do know, the basic laws of chemistry and physics and everything else you can do to calibrate it, run the model, and see what it tells you about the world. Figuring out what areas they need to better understand is one of the best uses of models. When there is a disagreement between a model result and data about something, a scientist would ask why the model and the data are disagreeing. It might mean that there is something missing from the model, it might mean that there is something missing with the data currently available.

During the latter part of the Holocene, the time after the ice sheets had fully collapsed, climate models consistently suggested that global temperature remained mostly constant. This time of unusually constant global climate is the time humans built much of their civilization; cities are located where they could find food, water, and resources during this stable climate. However, the available temperature data from a 2013 study showed that the world was slowly cooling during this time, contradicting the model results.

To try to resolve this discrepancy, researchers led by a scientist at the University of Wyoming collected hundreds of pollen samples from around lakes in North America, including the one in this photo. Pollen is a direct record of the type of plants growing in an area, and also can be used as a temperature record. When they analyzed these pollen records, they found that there was a cooling trend, but it was mostly isolated to North America. It turns out that the climate models were right; they were hitting the right temperature and because the measured data was focused on North America, it was underestimating global temperature.

In other words, the model result was accurate and the real world data needed to be updated to bring it in accordance with the model.

The worry with the model being right is, of course, today. That same climate model suggests that without greenhouse gases released by humans, the world would have been cooling for the last several centuries. Furthermore, the last decade was warmer than any decade in their entire model reconstruction, and that’s before the last 3 years that have been dramatically warmer than the last decade. The model data told us where in the geologic record we needed to acquire more data, and that same model is now telling us that humans have ended the long era of a stable climate where we built our civilization.

-JBB

Image credit: David Foster http://bit.ly/2o9EjjQ

Since at least the release of “Star Wars”, we have wondered what life would be like on a circumbinary planet -- a planet orbiting two stars. In the past few decades, we have discovered several such planets, but we are still in the early days of modeling the climate of these worlds. One recent study uses the stars of the Kepler 35 system, which are only slightly less luminous than our sun, to explore the climate of an Earth-like water planet. 

Excerpt from this story from Vice:

Sea levels will rise by more than 3 feet. Up to a fifth of everything living in the world’s oceans will die. More than 200 million people will be displaced by rising seas or forced to move to cooler places.

Those are science’s current predictions for what a climate-changed world will look like in 2100. But those estimates could be lowballing how bad the crisis will get.

Scientists rely on elaborate computer simulations that use data from the past to predict what will happen in the future, as people pump more greenhouse gases into the atmosphere. The first climate models, developed in the 1960s, were eerily accurate: They correctly predicted how much hotter the world would be today given the increase in greenhouse gas emissions.

Since then, models have been the basis for the UN’s gold-standard reports that have helped policymakers glimpse into what the climate will look like in the coming decades. They’ve also helped politicians figure out, for example, how high to build sea walls to protect cities from sea level rise.

But scientists worry that today’s climate models might not be as good at predicting the next fifty years — even as tools and data have gotten better. Why? Models are only as good as their inputs. Because the facts on the ground are changing so fast, predictive climate models are getting less reliable, and scientists know it.

“It’s not a surprise that we’re being surprised,” said Theodore Scambos, who studies Antarctic ice sheets at the University of Colorado at Boulder. “We're seeing things occur now that we weren’t anticipating because the world has never been like this before.”

Excerpt from this story from CNBC:

Investors are turning to a new breed of high-tech start-ups that can measure the risk climate change poses to real estate — from an hour to decades into the future.

And these firms count major corporations and cities as clients. One of them is Jupiter.

“We’re essentially physically modeling what’s happening with the atmosphere and the water or the fire at a very specific level of detail, and typically at the asset level, which is now only possible because computers have gotten so powerful and relatively inexpensive,” said Rich Sorkin, CEO of Jupiter.

Launched barely three years ago, the Silicon Valley-based company already has over $40 million in investor capital from firms including Energize Ventures, Ignition Partners and Data Collective. It also receives funding from the National Science Foundation and NASA for work in cloud computing and satellite observations.

The company’s primary goal is to incorporate climate impact data on flood, fire, heat, drought, cold, wind and hail events into risk modeling for real estate assets. Its clients include the coastal cities of New York and Miami.

“We’re seeing a dramatic expansion in large corporations coming to us, unsolicited, and saying, ‘We need to understand the risk to this office complex or the risk to this hotel, or the risk to this power plant, or refinery, or neighborhood where we have hundreds of millions of dollars of mortgages out,’” Sorkin said.