Month: March 2018

U.S. chance of Tiangong-1 sighting now less than 2%

The latest Aerospace Corp. prediction of the reentry time for the Chinese Space Station Tiangong-1 is now 3:30 p.m. CDT (plus or minus 8 hours) on Sunday, April 1. As reentry approaches, the predictions will get better, and the potential paths of the satellite will be narrowing.

The latest potential paths of reentry look like this:

Potential Tiangong-1 reentry orbital paths on April 1 2018 (Aerospace Corp.)

The paths over the U.S. are morning paths, and would be quite early in the time window of reentry. The total time these orbits are visible from the contiguous U.S. is only about 25 minutes (you could see the satellite burning up as far as 400 miles away from these paths, assuming no clouds are in the way). That is only 2.6 percent of the total time of the reentry window (16 hours), so given the the fact the U.S. paths are quite early in the window (and thus lower probability), I’d say the chances of anyone in the U.S. getting to see the fireworks show is less than 2%. Once you factor in cloud cover, it’s probably more like 1%.

Of course, we always knew the probability was very small.

And I think Michigan can now deactivate their Emergency Operations Center.

But, if you are feeling lucky and live within a few hundred miles of one of the paths show in the above graphic, I suggest visiting heavens-above.com, (1) enter your location (or nearest city), (2) click on “Tiangong-1”, and (3) change from “Visible only” to “All”, to see exactly what time(s) the satellite will be passing near you. Click on one of those times to see the path it will be making across the sky.

via Roy Spencer, PhD.

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March 31, 2018 at 11:13AM

Wilson & Sidorenkov: A Luni-Solar Connection to Weather and Climate I: Centennial Time Scales

Ian Robert George Wilson and Nikolay S Sidorenkov

Wilson and Sidorenkov, J Earth Sci Clim Change 2018, 9:1, p. 446

https://www.omicsonline.org/open-access/a-lunisolar-connection-to-weather-and-climate-i-centennial-times-scales-2157-7617-1000446.pdf

Abstract

Lunar ephemeris data is used to find the times when the Perigee of the lunar orbit points directly toward or away from the Sun, at times when the Earth is located at one of its solstices or equinoxes, for the period from 1993 to 2528 A.D. The precision of these lunar alignments is expressed in the form of a lunar alignment index (ϕ). When a plot is made of ϕ, in a frame-of-reference that is fixed with respect to the Perihelion of the Earth’s orbit, distinct periodicities are seen at 28.75, 31.0, 88.5 (Gleissberg Cycle), 148.25, and 208.0 years (de Vries Cycle). The full significance of the 208.0-year repetition pattern in ϕ only becomes apparent when these periodicities are compared to those observed in the spectra for two proxy time series. The first is the amplitude spectrum of the maximum daytime temperatures (Tm ) on the Southern Colorado Plateau for the period from 266 BC to 1997 AD. The second is the Fourier spectrum of the solar modulation potential (ϕm) over the last 9400 years. A comparison between these three spectra shows that of the nine most prominent periods seen in ϕ, eight have matching peaks in the spectrum of ϕm, and seven have matching peaks in the spectrum of Tm. This strongly supports the contention that all three of these phenomena are related to one another. A heuristic Luni-Solar climate model is developed in order to explain the connections between ϕ, Tm and ϕm.

Wilson_Sidorenkov_Fig_04

Discussion and Conclusions:

Lunar ephemeris data is used to find all the times when the Perigee of the lunar orbit points directly at, or away, from the Sun, at times when the Earth is located at one of the cardinal points of its seasonal calendar (i.e., the summer solstice, winter solstices, spring equinox or autumnal equinox). All of the close lunar alignments are identified over a 536-year period between January 1st 1993 A.D. 00:00 hrs UT and December 31st 2528 A.D 00:00 hrs UT.

When a plot is made of the precision of these alignments, in a frame-of-reference that is fixed with respect to the Perihelion of the Earth’s orbit, the most precise alignments take place in an orderly pattern that repeats itself once every 208.0 years:

0 × (28.75 + 31.00) + 28.75 years = 28.75 years ≈ 25.5 FMC’s
1 × (28.75 + 31.00) + 28.75 years = 88.5 years ≈ 78.5 FMC’s
2 × (28.75 + 31.00) + 28.75 years = 148.25 years ≈ 131.5 FMC’s
3 × (28.75 + 31.00) + 28.75 years = 208.0 years ≈ 184.5 FMC’s

A simple extension of this pattern gives additional precise alignments at periods of: 236.75, 296.50, 356.25, 416.0, 444.75 and 504.5 years. The full significance of the 208-year repetition pattern in the periodicities of lunar alignment index (ϕ) only becomes apparent when these periodicities are compared to those observed in the spectra for two proxy time series.

The first is the amplitude spectrum of the maximum daytime temperatures (Tm ) on the Southern Colorado Plateau for a 2,264-year period from 266 BC to 1997 AD. Tm is believed to be a proxy for how warm it gets during the daytime in any given year i.e., it is an indicator of annual mean maximum daytime temperature. Tm is derived from the tree ring widths of Bristlecone Pines (P. aristata) located near the upper tree-line of the San Francisco Peaks (= 3,536 m).

The second is the Fourier spectrum of the solar modulation potential (ϕm) for the last 9400 years. ϕm is a proxy for the ability of the Sun’s magnetic field to deflect cosmic rays, and as such, it is a good indicator of the overall level of solar activity. It is derived from production rates of the cosmogenic radionuclides 10Be and 14C. When a comparison is made between these three spectra it shows that, of the nine most prominent periods seen in the lunar alignment index, eight have closely matching peaks in the spectrum of solar modulation potential (ϕm), and seven have closely matching peaks in the spectrum of the maximum daytime temperatures (Tm). The fact that the so many of the most prominent peaks that are seen in the lunar alignment index spectrum closely match those seen in the spectra of ϕm and Tm, strongly supports the contention that all three of these phenomena are closely related to one another.

The critical piece of observational evidence that explains why Tm might be related to ϕm is provided [32]. These authors find that there is a good correlation between the de-trended GCR flux and the semiannual component of the Earth’s LOD. Our analysis confirms the correlation found [32] and shows that the correlation is causal, with the changes in the GCR flux preceding those seen in the semi-annual component of the Earth’s LOD by roughly one year.

This result leads us to develop a heuristic luni-solar model in order to explain the connection between Tm and ϕm. Firstly, the model proposes that there must be some as yet unknown factor associated with the level of solar activity on the Sun (e.g. possibly the overall level GCR hitting the Earth) that is producing long-term systematic changes in the amount and/or type of regional cloud cover. Secondly, it proposes that the resulting changes in regional cloud cover lead to variations in the temperature differences between the tropics and the poles which, in turn, result in changes to the peak strength of the zonal tropical winds. Thirdly, the model proposes that it is the long-term changes in the amount and/or type of regional cloud cover, combined with the variations in the temperature differences between the tropics and the poles that lead to the long-term changes in the poleward energy and momentum flux. And finally, it proposes that it is this flux which governs the rate at which the Earth warms and cools, and hence, determines the long-term changes in the world mean temperature.

The close matches between the periods of the prominent peaks that are seen in spectra of ϕ Figure 4a and Tm Figure 4c, indicate that a factor associated with the times at which the Perigee of the lunar orbit points directly towards or directly away from the Sun, at times when the Earth is at one of its Solstices or Equinoxes, has an influence on the Earth’s mean temperature [N.B. these alignments take place in frame of reference that is fixed with respect to the Perihelion of the Earth’s orbit].

The proposed Luni-Solar Model suggests one possible mechanism that might explain the influence of ϕ upon Tm. This model proposes that the periodicities associated with the long-term alignments between the times when the Perigee of the lunar orbit points directly towards or directly away from the Sun (i.e., half multiples of the FMC) and the seasons (i.e., the Solstices and Equinoxes – which, by definition, are synchronized with annual and semi-annual variations in LOD), produce comparable periodicities in the zonal wind speeds of the Earth’s atmosphere. These wind speed changes, in turn, produce longterm periodicities in the Earth’s mean temperature through their influence upon the efficiency with which the Earth warms and cools.

Finally, if we accept the hypothesis that planetary gravitational and tidal forces could influence the overall level of the Sun’s magnetic activity, then the observed synchronicity between ϕ and ϕm could be explained if these same planetary forces played a role in shaping the present-day orbit of the Moon.

This is a repost from Ian Wilson’s blog at http://astroclimateconnection.blogspot.co.uk/

via Tallbloke’s Talkshop

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March 31, 2018 at 10:12AM

Climate Change on Trial

With the international political, financial and reputational stakes so high, it was only a matter of time before climate change appeared in the dock, handcuffed to its partner in prognostication, the dodgy discipline of extreme weather attribution.

Attribution, n., the art of evaluating the relative contributions of multiple causal factors to a change or an event, according to one’s prejudices.

To make sense of the climate change scene today, it is best to begin with the end game: the orthodoxy’s search for an argument, however abstruse, that will stand up in court. It needs one sufficiently “robust” to ensure developed countries—still effectively on trial in the United Nations, where a protracted “loss and damages” claim awaits resolution—and fossil fuel companies are legally liable to pay multi-billion-dollar “climate reparations” to the alleged victims of “carbon pollution”, be they in the developing world or in the path of a natural disaster.

Indeed, the credibility of the “relatively young science” of extreme weather attribution, the legitimacy of its ambition to “tease out the influence of human-caused climate change from other factors”, the whole alarmist movement and fate of the UN’s Green Climate Fund, all crucially depend on delivering such a legal argument.

How did we get to this point? When the climate change meme was planted successfully in the collective mind a decade ago as the most serious existential threat facing humankind, the orthodoxy wanted it to stay there. A sense of public anxiety had to be maintained, despite the risk of apocalypse fatigue syndrome.

So it created an Attribution of Climate-related Events (ACE) initiative. The international research agenda gradually shifted to the tricky territory of extreme weather attribution.

ACE’s first workshop was held on January 26, 2009, in Boulder, Colorado, at the Pei-designed National Center for Atmospheric Research (NCAR) Mesa Lab. Attendees included Myles Allen (Oxford University), Martin Hoerling (NOAA, USA), Peter Stott (UK Met Office, Hadley Centre), Kevin Trenberth (NCAR) and David Karoly (University of Melbourne). Its objective was to:

develop a conceptual framework for attribution activities to be elevated in priority and visibility, leading to substantial increases in resources (funds, people, computers) and both a research activity and a framework for an “operational” activity, that sets forth a goal of providing a lot more concrete information in near real time about what has happened and why in weather and climate.

ACE later released a four-paragraph statement. Its mission would be: “to provide authoritative assessments of the causes of anomalous climate conditions and EWEs” (extreme weather events), presumably for government agencies and the Intergovernmental Panel on Climate Change’s 2013/2014 Fifth Assessment Report (AR5).

But just how “robust”—one of the orthodoxy’s favourite adjectives—was the climate modelling underpinning this grand design? How could it be sold to the public, given the challenging uncertainties? ACE participants agreed they would need “increased real-time numerical experimentation activity” and something else too, a narrative that would ensure public interest.

To succeed, everyone would have to sing from the same song-sheet. There would have to be consistent use of terminology and close collaborative teamwork “to maintain an authoritative voice when explaining complex multi-factorial events such as the recent Australian bushfires” (my italics).

Full post

via The Global Warming Policy Forum (GWPF)

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March 31, 2018 at 09:46AM

Central Europe’s Wintry Spring Start…March Mean Temp Almost 2°C Below Normal…2nd White Easter In A Row

Germany’s DWD national weather service has released the preliminary mean weather results for the country for March, 2018: “In summary a cold March, again snow in the north and east.”

Wintry 2018 spring start in Germany. Hase River, Lower Saxony. Photo: P Gosselin

The reason for the cold March, according to the DWD: “Germany was in a mostly dry, very cold easterly air pattern. Atlantic lows from the west could hardly make any headway.”

According to data collected from the country’s 2000 weather stations, Germany’s preliminary mean temperature for the first month of spring came in at only 2.5°C, which is 1.8°C below the 1981-2010 reference period mean.

The coldest treading recorded was -19.2°C  occurring at Barth near Stralsund. March, 2018, was the second month in a row with below mean temperatures in Central Europe.

The following chart gives the mean temperature for each state (Source: DWD):

März 2018 / DWD (Quelle DWD)

March was drier than normal as well, with 50 l/m2 of precipitation falling (mean = 57 l/m2). However, the DWD writes that March 2018 was “characterized by extreme wintery periods, with considerable snowfall in some regions.” Also some “lake-effect” areas near the Baltic sea saw 40 cm of snow. “

At 110 hours of sunshine, Germany almost hit the dead mean of 11 hours.

Austria: “Unusual number of frost days”

Meanwhile Austria’s weather and climate service ZAMG reports that March has come in “cool and overcast”.

According to ZAMG climatologist Alexander Orlik, sunshine came in 20% below the mean and temperature came in at 1.3°C below the mean. There wasalso “an unusual number of frost days, where the temperature does not climb above the freezing point. the ZAMP reports. Vienna saw five such days and Graz saw four. Normally these cities see only one “frost day” every two or three years in March.

Another white Easter!

Meanwhile for some parts of Germany snow is forecast for the Easter holidays. According to Tag24, snow is expected to fall in Saxony. This will be the second easter in a row with snow

So, Europeans have been waiting 18 years for snow to become a thing of the past. Increasingly it’s becoming a thing of spring.

via NoTricksZone

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March 31, 2018 at 08:06AM