Statistics

The Danger of Making #Coronavirus Decisions Without Reliable Data

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From STAT – Re-Blogged From WUWT

A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data

By John P.A. Ioannidis

The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.

At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.

Draconian countermeasures have been adopted in many countries. If the pandemic dissipates — either on its own or because of these measures — short-term extreme social distancing and lockdowns may be bearable. How long, though, should measures like these be continued if the pandemic churns across the globe unabated? How can policymakers tell if they are doing more good than harm?

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Diamond Princess Mysteries

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By Willis Eschenbach – R4e-Blogged From WUWT

OK, here are my questions. We had a perfect petri-dish coronavirus disease (COVID-19) experiment with the cruise ship “Diamond Princess”. That’s the cruise ship that ended up in quarantine for a number of weeks after a number of people tested positive for the coronavirus. I got to wondering what the outcome of the experiment was.

So I dug around and found an analysis of the situation, with the catchy title of Estimating the infection and case fatality ratio for COVID-19 using age-adjusted data from the outbreak on the Diamond Princess cruise ship (PDF), so I could see what the outcomes were.

As you might imagine, before they knew it was a problem, the epidemic raged on the ship, with infected crew members cooking and cleaning for the guests, people all eating together, close living quarters, lots of social interaction, and a generally older population. Seems like a perfect situation for an overwhelming majority of the passengers to become infected.

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Corona Virus Map

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  By Bob Shapiro

Johns Hopkins has a Corona Virus map that appears to be updated daily showing where confirmed cases have been reported, along with stats on deaths and recoveries. It gives a breakdown by country – I was surprised that the US showed 15 confirmed cases.

Take a look at: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

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Explaining the Discrepancies Between Hausfather et al. (2019) and Lewis&Curry (2018)

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[This is a technical analysis of climate models vs observations by an econometrician who helped show that Michael Mann’s “Hockey Stick” was false.  –Bob]

By Ross McKitrick – Re-Blogged From WUWT

Challenging the claim that a large set of climate model runs published since 1970’s are consistent with observations for the right reasons.

Introduction

Zeke Hausfather et al. (2019) (herein ZH19) examined a large set of climate model runs published since the 1970s and claimed they were consistent with observations, once errors in the emission projections are considered. It is an interesting and valuable paper and has received a lot of press attention. In this post, I will explain what the authors did and then discuss a couple of issues arising, beginning with IPCC over-estimation of CO2 emissions, a literature to which Hausfather et al. make a striking contribution. I will then present a critique of some aspects of their regression analyses. I find that they have not specified their main regression correctly, and this undermines some of their conclusions. Using a more valid regression model helps explain why their findings aren’t inconsistent with Lewis and Curry (2018) which did show models to be inconsistent with observations.

Outline of the ZH19 Analysis:

A climate model projection can be factored into two parts: the implied (transient) climate sensitivity (to increased forcing) over the projection period and the projected increase in forcing. The first derives from the model’s Equilibrium Climate Sensitivity (ECS) and the ocean heat uptake rate. It will be approximately equal to the model’s transient climate response (TCR), although the discussion in ZH19 is for a shorter period than the 70 years used for TCR computation. The second comes from a submodel that takes annual GHG emissions and other anthropogenic factors as inputs, generates implied CO2 and other GHG concentrations, then converts them into forcings, expressed in Watts per square meter. The emission forecasts are based on socioeconomic projections and are therefore external to the climate model.

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Wet Years, Dry Years

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By Willis Eschenbach – Re-Blogged From WUWT

I keep reading all kinds of claims that the slight warming we’ve been experiencing over the last century has already led to an increase in droughts. A few years ago there were a couple of very dry years here in California, and the alarmists were claiming that “global warming” had put us into “permanent drought”.

Of course, the rains returned. This season we’re at about 120% of normal … it’s called “weather”.

In any case, I thought I’d take a look at the severity of droughts in the US over the last century. I always like to take a look at the longest dataset I can find. In this case, I got the data from NOAA’s CLIMDIV dataset. Figure 1 shows the monthly variations from 1895 to the present. Note that I’ve inverted the Y-axis on the graph, so higher on the graph is dryer, and down near the bottom is wetter.

Figure 1. Monthly Palmer Drought Severity Index for the continental US, 1895-2019. Above the dashed line is dryer, below the line is wetter.

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What if There is no Climate Emergency ?

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By edmhdotme – Re-Blogged From WUWT

What if there is no Catastrophic Risk from Man-made Global Warming ?
What if Man-made CO2 emissions are not the “Climate Control Knob” ?
What if Man-made CO2 emissions really are a non-problem ?
But what if there is a real Global Cooling Catastrophe in the offing ?
screenshot-2019-11-20-at-17.57.06

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If You Put Junk Science In, You’ll Get Junk Science Out

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By Chris Martz – Re-Blogged From WUWT

 

There are plenty of climate scientists in the world that I highly respect, many of whom I don’t share the same views with on climate change. However, these scientists are respectful towards others, they’re pretty honest with their data, and still have scientific integrity.

There are a select few scientists out there, however, whom I have lost all respect for － Dr. Michael Mann being one of them.

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