The Canadian Pandemic Model

By Brian – Re-Blogged From WUWT

Introduction

A detailed analysis of the University of Manitoba’s recent model prepared on behalf of the Canadian Government illustrates exaggerated and incalculable conclusions. These explicitly theoretical projections, which have little evidence to support them, set an unrealistic foundation of what is considered a success or not with regards to Dr. Tam’s policies. In this case, the models that are used to predict the effects of Sars-Cov-2 adapts a completely unrealistic and unattainable worst-case scenario. Essentially any result, and every result possible, will be hailed as a resounding success – which is disingenuous. The virus would not come close to manifesting the chaos projected, even among a society with the loosest of policies. Fortunately, there are examples as many countries had their own approach in fighting the virus.

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Weekly Climate and Energy News Roundup #412

Re-Blogged From WUWT

Quote of the Week: “Aqueous vapor [water vapor] is a blanket, more necessary to the vegetable life of England than clothing is to man. Remove for a single summer-night the aqueous vapor from the air which overspreads this country, and you would assuredly destroy every plant capable of being destroyed by a freezing temperature. The warmth of our fields and gardens would pour itself unrequited into space, and the sun would rise upon an island held fast in the iron grip of frost.” – John Tyndall (“Heat: A Mode of Motion”, 1861) [H/t William Happer]

Number of the Week: Daily change of 100⁰C (or daily change of 180⁰F)

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Models Can’t Accurately Predict Next Week’s Weather, So Why Should We Trust Them To Predict Climate Change?

By Daniel Turner, The Daily Caller – Re-Blogged From WUWT

It’s curious … SpaceX has all the money in the world, and they didn’t hire someone who could have accurately predicted the afternoon weather in Florida on May 27, 2020.  Seems like a huge oversight, doesn’t it?  And to think there are scores of nonprofit leaders and academics in Washington, DC who can accurately predict global temperatures 10, 15, even 50 years into the future.

Oh, stop it with the “climate isn’t weather” rebuttal. It’s trite and silly. The guys who says “food isn’t cuisine” is a food critic, and by default, haughty and obnoxious.

How about this one: science isn’t semantics.

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Why the Current Economic Slowdown Won’t Show Up in the Atmospheric CO2 Record

By Dr. Roy Spencer – Re-Blogged From WUWT

Summary: Atmospheric levels of carbon dioxide (CO2) continue to increase with no sign of the global economic slowdown in response to the spread of COVID-19. This is because the estimated reductions in CO2 emissions (around -11% globally during 2020) is too small a reduction to be noticed against a background of large natural variability. The reduction in economic activity would have to be 4 times larger than 11% to halt the rise in atmospheric CO2.

Changes in the atmospheric reservoir of CO2 occur when there is an imbalance between surface sources and sinks of CO2. While the global land and ocean areas emit approximately 30 times as much CO2 into the atmosphere as humans produce from burning of fossil fuels, they also absorb about an equal amount of CO2. This is the global carbon cycle, driven mostly by biological activity.

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Researchers, Lawmakers Cry Foul After Harvard Quietly Edits Study Suggesting Pollution Leads To More COVID Deaths

Chris White, From The Daily Caller – Re-Blogged From WUWT

  • Maryland Rep. Andy Harris wants the Environmental Protection Agency to review a Harvard University study suggesting pollution could create an 8% increase in the United States’s coronavirus death rate. 
  • One top critic of the study told the Daily Caller News Foundation that the university’s research is unfounded and relies on faulty modeling and testing. 
  • The university’s researchers initially claimed that people in certain areas of the country are 15% more likely to die of the virus, but quietly edited the study to dramatically change the nature of the study’s findings.

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Fauci-Birx Climate Models?

By Paul Driessen and David R. Legates – Re-Blogged From WUWT

Honest, evidence-based climate models could avoid trillions of dollars in policy blunders

President Trump and his Coronavirus Task Force presented some frightening numbers during their March 31 White House briefing. Based on now 2-week-old data and models, as many as 100,000 Americans at the models’ low end, to 2.2 million at their high end, could die from the fast-spreading virus, they said.

However, the President, Vice President Pence, and Drs. Anthony Fauci and Deborah Birx hastened to add, those high-end numbers are based on computer models. And they are “unlikely” if Americans keep doing what they are doing now to contain, mitigate and treat the virus. Although that worst-case scenario “is possible,” it is “unlikely if we do the kinds of things that we’re essentially outlining right now.”

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Futile Fussings – a History of Graphical Failure From Cattle to #Coronavirus

By Kevin Kilty – Re-Blogged From WUWT

No planning is likely possible without calculations of what the future may hold, but such calculations are fraught with uncertainty when they also involve exponential processes. Indeed, as the author of one chapter in a recent book [1] states:

“One characteristic of an exponential growth process that humans find it really difficult to comprehend is how fast such a process actually is. Our daily experiences do not prepare us to judge such a process accurately, or to make sensible predictions.” [emphasis is mine.]

Quests to reveal a future governed by exponential processes, or what people guess to be exponential processes, run through many themes here at WUWT — future climate, energy demand, economics, epidemics. This guest contribution takes a selected look at exponential growth. Two examples are historical, and perhaps obscure, but pertinent. The third one, which comprises the bulk of this essay, is an examination of R0, which dominates the present imagination.

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Two More Degrees by 2100!

By Vaughan Pratt – Re-Blogged From WUWT

An alternative perspective on 3 degrees C?

This post was originally intended as a short comment questioning certain aspects of the methodology in JC’s post of December 23, “3 degrees C?”. But every methodology is bound to have shortcomings, raising the possibility that Judith’s methodology might nevertheless be best possible, those shortcomings notwithstanding. I was finding my arguments for a better methodology getting too long for a mere comment, whence this post. (But if actual code is more to your fancy than long-winded natural language explanations, Figures 1 and 2a can be plotted with only 31 MATLAB commands .)

Judith’s starting point is “It is far simpler to bypass the attribution issues of 20th century warming, and start with an early 21st century baseline period — I suggest 2000-2014, between the two large El Nino events.” The tacit premise here would appear to be that those “attribution issues of 20th century warming” are harder to analyze than their 21st century counterparts.

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Epidemiology, Diet Soda and Climate Science

By Kip Hansen – Re-Blogged From WUWT

Epidemiologyis the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in defined populations. “

“It is the cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare.”

featured_image_epidemiology

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Robots Recreating Past Temperatures

From Jennifer Marohasy’s Blog – Re-Blogged From WUWT

AI research over the last couple of years at the University of Tasmania could have been a check on the existing mess with historical temperature reconstructions. Reconstructions that suggest every next year is hotter than the last the world over. Except that Jaco Vlok began with the Australian Bureau of Meteorology’s temperature datasets without first undertaking adequate quality assurance (QA).

BlueTeam-LookingDown-copy-1024x819

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Scientists Find Bounds of Weather Forecasting is 2 Weeks

Re-Blogged From WUWT

From Penn State University and the “but we guarantee you there’s no predictability limit in climate science” department comes this interesting study.

UNIVERSITY PARK, Pa. — In the future, weather forecasts that provide storm warnings and help us plan our daily lives could come up to five days sooner before reaching the limits of numerical weather prediction, scientists said.

“The obvious question that has been raised from the very beginning of our whole field is, what’s the ultimate limit at which we can predict day-to-day weather in the future,” said Fuqing Zhang, distinguished professor of meteorology and atmospheric science and director of the Center for Advanced Data Assimilation and Predictability Techniques at Penn State. “We believe we have found that limit and on average, that it’s about two weeks.”

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Global Energy Balances … Except When It Doesn’t

By Willis Eschenbach – Re-Blogged From WUWT

I came across an interesting 2014 paper called The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models. In it, they make a number of comparisons between observational data and 43 climate models regarding the large-scale energy flows of the planet. Here’s a typical graphic:

Figure 1. ORIGINAL CAPTION: “Fig. 7 Average biases (model—observations) in downward solar radiation at Earth’s surface calculated in 43 CMIP5 models at 760 sites from GEBA. Units Wm−2”. The “CMIP5” is the “Computer Model Intercomparison Project 5”, the fifth iteration of a project which compares the various models and how well they perform.

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Environmental Groups Claim Coal Killed 7,600 People in Europe in 2016… Can’t Name Any of the Victims

By David Middleton – Re-Blogged From WUWT

[Sue the Bastards! -Bob]

Groups target Europe’s coal companies over harmful emissions

FILE – In this Feb. 27, 2018 file photo a coal-fired power station steams in the cold winter air in Gelsenkirchen, Germany. Environmental groups say 10 utility companies are responsible for the majority of premature deaths caused by emissions from coal-fired power plants in Europe. In a report published Tuesday, Nov. 20, 2018 five campaign groups, including Greenpeace, blame the companies for 7,600 premature deaths and millions of work days lost across Europe in 2016. (AP Photo/Martin Meissner, file) (Martin Meissner)

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A Day in the Life of a Model

By Amy Bebbington – Re-Blogged From https://www.ukmodels.co.uk

One of the most desirable aspects of the model industry is the flexible nature. No day is the same moving away from the dull and mundane office hours. Attracted to the photoshoot life, aspiring models yearn for the glamour of the world of the fashion pages. But what is life really like for successful models. What does their day-to-day look like? The reality may be slightly different.

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2016 Global Surface Temperatures

By Bob Tisdale – Re-Blogged From http://www.WattsUpWithThat.com

Figure 1 presents two model-data comparisons for global sea surface temperatures, not anomalies, for the past 30-years. I’ve included a comparison for the global oceans (90S-90N) in the top graph and a comparison for the global oceans, excluding the polar oceans (60S-60N), in the bottom graph. Excluding the polar oceans doesn’t seem to make a significant difference. It’s obvious that global sea surfaces simulated by the GISS climate model were warmer than observed and that the GISS model warming rate is too high over the past 3 decades. The difference between modeled and observed warming rates is approximately 0.07 to 0.08 deg C/decade, more than 60% higher than the observed rate. And in both cases the 30-year average sea surface temperature as simulated by the GISS models is too high by about 0.6 deg C.

figure-1

Figure 1 – Global Oceans

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An IT Expert’s View on Climate Modelling

By Eric Worrall – Re-Blogged From http://www.WattsUpWithThat.com

One point struck me, reading Anthony’s fascinating account of his meeting with Bill McKibben. Bill, whose primary expertise is writing, appears to have an almost magical view of what computers can do.

Computers are amazing, remarkable, incredibly useful, but they are not magic. As an IT expert with over 25 years commercial experience, someone who has spent a significant part of almost every day of my life, since my mid teens, working on computer software, I’m going to share some of my insights into this most remarkable device – and I’m going to explain why my experience of computers makes me skeptical, of claims about the accuracy and efficacy of climate modelling.

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