Bird strikes against the windows are always a bummer. Window stickers do little, and before the earthquake we had a variety of stained glass hung that also wasn’t 100%, but it is mostly down now. I looked at a few birding sites, and rope strands outside the window seem to do the trick, so I tricked it out. All the rest of the windows get covered outside with a mesh heat/light shield, later in the season.
Methane road trip.
Real world errors in statistical logic and logarithms are not the fault of statistics, as statistics are meant to show a framed process and outcome. They are not meant to reflect the real world. One such example is projected forced warming of methane. This one bugged me enough today to scribble on a notepad and use a calculator…
Projected forced warming of methane spread over 10yrs gives a rate of 80x where x=carbon dioxide’s heating potential. However methane in its first 2yrs gives an annual rate of 200x. Basing projections of atmospheric warming on the 10yr/80x linear cycle ignores the higher burn of the first two years. This is a statistical error of grave consequences. 10yr to 80x avg per year is 800x total, with a burn of 400x in the first 2yr cycle (200x per year) and a remainder rate of 75x per year for the remaining 8yrs; 50% of the total energy of a ten year span is expressed over the initial 20% of measurement. Yet statistically, this can be misrepresented as 10yrs at 80x.
A method to demonstrate the necessity for including the higher initial burn rate; a simple analogy of a road trip that experiences a headwind for the first part of the trip. Our destination is 400 flat miles away and we have one tank of gas to get us there.
The vehicle holds 20 gallons and makes 20 miles per gallon, giving a range of 400 miles. If we equate that distance to the 10yr / 80x, then we travel 40 miles per 80x on a tank of 800x. Let’s say a headwind blows the first 40 miles bringing our energy use up to 200x, or 117x over normal. This draws down 197x of total energy (80 + 117) the first 40 miles, or 24% of 800x. Can we now reach our destination on our one tank of gas? No. Of our 800x of energy, we burned 197x for the first 1/10 of the trip, leaving us 603x, enough to travel 7.5/10 of the remaining 9/10. Each 1/10 unit requires 80x, and we have only 67x per unit remaining, and will fail 58.5 miles short at marker 341.5, which is 85% of the total, or 1.5/10 or 15% short from our destination.
Of course, the wind blows for the second 40 miles as well; so we can double the initial energy drawdown: 80x + 117x + 80x + 117x = 394x for the first 80 miles (49% of 800x) and a remainder of 406x / 80x = 5.075 x 40 mile/unit for a total of 203 mile range remaining. We will travel a total of 283 (80 +203) miles of our 400 mile trip factoring for 80 miles of initial headwind, traveling only 7/10s of the total, or 30% short of our destination.
This is because 80x/ 200x is a 150% increase over the standard of 80x. So I hope we can now see that many statistical apologetics are grossly misleading, such as blending the forced warming of methane down to 80x/10years, or 23x/100 years. There is currently a massive inversion of methane over the arctic, an entirely new phenomena: so this line of reasoning may prove informational come springtime.
Methane emissions year on year are rising quickly, so year on year the compounding effect of the first two years of measurement is on a non-linear exponential increase. So a singular measure, or the idea of a singular journey is too static a model, but we’ll stay with it anyway. We can alter the model as a point of departure: take the 400 mile trip (everything’s fine til 2050) and reset the distance and the landscape. 2022 is proxy to 1994’s equivalent “everything’s fine til” date, and we’ve more than doubled the amount of global heating / extinctions / environmental degradation in this 28 yr span, and 2022 is also the year portrayed in the sci-fi classic 1973 film “Soylent Green”. So here we are in 1994’s 2050, driving a little truck 10 miles up a canyon that climbs to a steep mountain pass (representing existing CO2 loading) ending at a scenic turn-out on a remote mountain peak. A road to nowhere. We are also pulling the steadily increasing weight of our own emissions on a trailer so vast I have put the truck in 4×4 low-range to get out of the parking lot. The grade of the road has tanked our mileage and it will continue to drop as we climb. The wind maps show the methane gale increases exponentially as the road climbs, for the entirety of the journey. The temperature drops and the snow begins and we can’t stop or turn around, and the fuel light has come on after only a few miles. I’m sure we’ll all be fine though, as math and physics are malleable to hope.
Or we can just drop the analogy and look at global temperature vs regional temperature, and set arctic regional temperature at 4x higher than elsewhere, as a driver for regional temperature in the northern hemisphere. Methane falls through the atmosphere and toward the north pole where it pools, concentrating all winter from around the world, then in spring/summer/fall becoming a methane emission giant through amplifying natural feedback loops. This is a gain-on-gain scenario, where all new methane emissions are 150% (80x divided by 200x)more energetic than methane background 10-year IPCC modeling. Measuring all carbon equivalents brings us from 420 (CO2 only) to 500ppm CO2+equivalent, yet the factor of new methane should be adjusted to 150% additional heating. This in turn means that scenarios of warming are an underestimation for rate of change across the board, as a hot spike in an overheated system; say a redlined engine (CO2 loaded into the atmosphere) with twin turbo’s inter-cooled by engine oil (Methane heat spike) often cause the engine to burst into flame and seize. There are entire you-tube channels dedicated to Supercars & Bro-Dozers (diesel trucks) bursting into flame for just this reason. When climate modelers say “Faster than expected”, they share a commonality with the drivers standing helplessly aside their fireball engulfed vehicle having no idea what went wrong.