Produce your own Climate Doom Scenarios – online tools for laymen and scientists alike

By Dennis Ambler

You too can become a climate scientist – just download these handy tools and generate your own doom-laden scenario, see how your town will be inundated in 12 years time, or create an attribution study, send it off to PNAS for guaranteed acceptance and perhaps launch a lawsuit against an oil company for climate justice compensation, funding unlikely to be a problem:

https://eidclimate.org/who-is-earthrights-international-the-shadowy-group-behind-the-latest-climate-lawsuit/

Here are your climate tools:

https://climateanalytics.org/tools/

Sea level: 

At locations where no tide gauged station is available, gridded sea level projections can be selected (yellow squares). Gridded sea level projections come with substantially higher uncertainities. Therefore, we strongly recommend to use projections for tide gauged stations whenever this is possible!

Source for these projections is a NASA/GISS paper from 2014: Kopp et al, one of the et al’s being Michael Oppenheimer of Princeton, formerly of Environmental Defense and still advising them. https://pubs.giss.nasa.gov/abs/ko01500z.html.

There is a notable high level of scientific accuracy, because…

We provide complete probability distributionsinformed by a combination of expert community assessment, expert elicitation, and process modeling.”
 

The experts of course, are themselves and their colleagues, who think, (because they are experts), that this is all “90% likely.”

Find out what’s in store for your geographic region based on IPCC climate models…
http://regioclim.climateanalytics.org/choices

Crop projections?

Projected changes in yields (%) relative to 2000 (multi-model ensemble median) for each crop grown in the country at different warming levels.

http://regiocrop.climateanalytics.org/choices

http://wlcalc.climateanalytics.org/choices

This online tool is a resource for climate scientists which allows relating climate impact studies to warming targets like 1.5°C and 2°C.

This is a random example:

“year of exceedance (period of exceedance)

1.5 °C 2.0 °C 3.0 °C 4.0 °C
rcp85 2022 (2007-2037) 2040 (2025-2055) 2068 (2053-2083) 2092 (2077-2107)

The above-projected values are averages over the models:
bcc-csm1-1-m.
The above given periods in brackets refer to the running mean window of 31 years. The warming is calculated from the preindustrial period 1850-1900. We use the observed warming (hadcrut4) until the base period 1980-2000 and then add the projected warming from your model choice.

“Science”, but not as we know it…

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