MW&A

Long time readers would be aware of MWA developments in Solar based hydroclimatological forecasting.  There is a peer reviewed publication as well [1], which outlines the theory and the practice.  It happens to feature the Animas River which emerges from the high altitude catchments of the Southern Rocky Mountains.

In the featured image above, I’ve built upon the discussion section of that paper and simply have shifted the Sunspot Number time series forward by 5 years to see how it aligns with the Animas flows. This Solar comparison to the Animas River is highly correlated (R = 0.85) and statistically significant (p << 0.01).  The significance is accordingly such that there is over a 99.9% probability that Solar forcing and flows of the Animas River are related.

One might wonder where else in the world can such strong correlations be found between terrestrial moisture and Solar cycles.  I recommend that you download and read [1] as a start.  But I don’t mind sharing some ongoing work, in which I’ve plotted the zero lag correlation (R) between atmospheric moisture (UCAR ERAI “EP” value) over the headwaters of the Animas River to everywhere else on the planet.  This coverage is featured in the following two graphics.

You can begin to interpret by considering that any region which is highly correlated to the Animas moisture signature, may also be highly correlated to the Solar cycle signature.

There will always be more questions, even for a Solar forcing paradigm, and those questions are most welcome.  I’ll continue to follow moisture patterns across the Western US and beyond as time permits.  This year I plan to examine snowfalls and more ENSO and PDO news, along with glaciations and related (as I see it) sea level changes.  But rivers will always be key, and among rivers, the Animas will always be premier [1].

I haven’t been to the Animas this season yet so these pics of the nearby Rio Grande will have to do for now.

PREVIEW OF PENDING POSTS

THE BOGUS BUTTERFLY EFFECT?

MWA has demonstrated that one can forecast climate beyond a year or even beyond 3 years.  So I’m motivated to challenge another precious and popular icon known as CHAOS THEORY (CT).  Is CT merely a “complexity crutch” that benefits scientists who can’t account for their poor projections?  The featured image happens to capture the weird transposition of butterfly metaphors in the CT lexicon.  The solution trajectory (right panel) from Lorenz’s numerically crude weather equations couldn’t find a place to alight, and ended up looking like a butterfly. 

In Strogatz’s narrative (a fellow academic to Lorenz at MIT), the metaphor explained why Lorenz couldn’t forecast weather.  It wasn’t Lorenz’s equation that was deficient, it was all of mathematics being usurped by wild chaos.  With CHAOS,  not only did scientists get a pass from forecasting accountability, now the merest microflap of a butterfly’s wings could be attributed to have caused a major coastal – threatening cyclone.    In addition to the fact that Solar forcing paradigm can project climate years in advance (at least in some places) here’s why one can entertain skepticism of the butterfly effect:  [to be continued in the actual post]

 

REFERENCES

[1] Wallace, M.G., 2019, Application of lagged correlations between solar cycles and hydrosphere components towards sub-decadal forecasts of streamflows in the Western US.   Hydrological Sciences Journal, Oxford UK  Volume 64 Issue 2.   doi: 10.1080/02626667.2019.

[2] Strogatz, S.H., 2015  NONLINEAR DYNAMICS AND CHAOS  Westview Press

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