The Greenhouse Deception Explained

NOT A LOT OF PEOPLE KNOW THAT

By Paul Homewood

A nice and concise video, well worth watching and circulating:

View original post

Continuous observations in the North Atlantic challenges current view about ocean circulation variability

Reblogged from Watts Up With That:

Kevin Kilty

May 10, 2019

[HiFast Note:  Figures A and B added:

osnap_array_schematic_v2_13Nov14

Figure A. OSNAP Array Schematic, source:  https://www.o-snap.org/]

20160329_OSNAP_planeview-1Figure B. OSNAP Array, source:  https://www.o-snap.org/observations/configuration/]

clip_image002Figure 1: Transect of the North Atlantic basins showing color coded salinity, and gray vertical lines showing mooring locations of OSNAP sensor arrays. (Figure from OSNAP Configuration page)

Figure 1: Transect of the North Atlantic basins showing color coded salinity, and gray vertical lines showing mooring locations of OSNAP sensor arrays. (Figure from OSNAP Configuration page)

From Physics Today (April 2019 Issue, p. 19)1:

The overturning of water in the North Atlantic depends on meridional overturning circulation (MOC) wherein warm surface waters in the tropical Atlantic move to higher latitudes losing heat and moisture to the atmosphere along the way. In the North Atlantic and Arctic this water, now saline and cold, sinks to produce north Atlantic Deep water (NADW). It completes its circulation by flowing back toward the tropics or into other ocean basins at depth, and then subsequently upwelling through a variety of mechanisms. The time scale of this overturning is 600 years or so2.

The MOC transports large amounts of heat from the tropics toward the poles, and is thought to be responsible for the relatively mild climate of northern Europe. The heat being transferred from the ocean surface back into the atmosphere at high latitudes is as large as 50W/m2, which is roughly equivalent to solar radiation reaching the surface at high latitudes during winter months2.

In order to evaluate models of ocean overturning oceanographers have relied upon hydrographic research cruises. But the time increment between successive cruises is often long, and infrequent sampling cannot measure long term trends reliably nor gauge current ocean dynamics.

To get a better handle on MOC behavior an array of sensors to continuously monitor temperature, salinity, and velocity measurements known as the Overturning in the Subpolar North Atlantic Program (OSNAP) was recently deployed across the region at multiple depths. Figure 1 shows sensor moorings in relation to the various ocean basins of the North Atlantic. Figure 2 shows data from the first 21 months of operation, and displays a rather large variability of overturning in the eastern North Atlantic between Greenland and Scotland that reaches +/-10 Sverdrup (Sv=one million cubic meters per second) monthly, and amounts to one-half the MOC’s total annual transport. Researchers had thought that such variability was only possible on time scales of decades or longer.

Figure 2: Twenty-one months of observational data showing large month to month variation in MOC flows.

Figure 2: Twenty-one months of observational data showing large month to month variation in MOC flows.

The original experimental design for sensor placement in OSNAP was predicated on much smaller variability of a few Sv per month3. The report does not address what impact this surprising level of transport variability has on validity of the experiment design; but the surprisingly large variations in flow challenge expectations derived from climate models regarding the relative amount of overturning between the Labrador Sea and the gateway to the Arctic between Greenland and Scotland.

As one oceanographer put it, the process of deep water formation and sinking of the MOC is more complex than people believed, and these results should prepare people to modify their ideas about how the oceans work. This improved data should not only help test and improve climate models, but also produce more realistic estimates of CO2 uptake and storage.

References:

1. Alex Lopatka, Altantic water carried northward sinks farther east of previous estimates, Physics Today, 72, 4, 19(2019).

2. J. Robert Toggweiler, The Ocean’s Overturning Circulation, Physics Today, 47, 11, 45(1994).

3. Susan Lozier, Bill Johns, Fiamma Straneo, and Amy Bower, Workshop for the Design of a Subpolar North Atlantic Observing System, URL= https://www.whoi.edu/fileserver.do?id=163724&pt=2&p=175489, accessed 05/10/2019.

Curious Correlations

Reblogged from Watts Up With That:

Guest Post by Willis Eschenbach

I got to thinking about the relationship between the Equatorial Pacific, where we find the El Nino/La Nina phenomenon, and the rest of the world. I’ve seen various claims about what happens to the temperature in various places at various lag-times after the Nino/Nina changes. So I decided to take a look.

To do that, I’ve gotten the temperature of the NINO34 region of the Equatorial Pacific. The NINO34 region stretches from 90°W, near South America, out to 170° West in the mid-Pacific, and from 5° North to 5° South of the Equator. I’ve calculated how well correlated that temperature is with the temperatures in the whole world, at various time lags.

To start with, here’s the correlation of what the temperature of the NINO34 region is doing with what the rest of the world is doing, with no time lag. Figure 1 shows which areas of the planet move in step with or in opposition to the NINO34 region with no lag.

Figure 1. Correlation of the temperature of the NINO34 region (90°-170°W, 5°N/S) with gridcell temperatures of the rest of the globe. Correlation values greater than 0.6 are all shown in red.

Now, perfect correlation is where two variables move in total lockstep. It has a value of 1.0. And if there is perfect anti-correlation, meaning whenever one variable moves up the other moves down, that has a value of minus 1.0.

There are a couple of interesting points about that first look, showing correlations with no lag. The Indian Ocean moves very strongly in harmony with the NINO34 region (red). Hmmm. However, the Atlantic doesn’t do that. Again hmmm. Also, on average northern hemisphere land is positively correlated with the NINO34 region (orange), and southern hemisphere land is the opposite, negatively correlated (blue).

Next, with a one-month lag to give the Nino/Nina effects time to start spreading around the planet, we see the following:

Figure 2. As in Figure 1, but with a one month lag between the NINO34 temperature and the rest of the world. In other words, we’re comparing each month’s temperature with the previous month’s NINO34 temperature.

Here, after a month, the North Pacific and the North Atlantic both start to feel the effects. Their correlation switches from negative (blues and greens) to positive (red-orange). Next, here’s the situation after a two-month lag.

Figure 3. As in previous figures, but with a two month lag.

I found this result most surprising. Two months after a Nino/Nina change, the entire Northern Hemisphere strongly tends to move in the same direction as the NINO34 region moved two months earlier … and at the same time, the entire Southern Hemisphere moves in opposition to what the NINO34 region did two months earlier.

Hmmm …

And here’s the three-month lag:

Figure 4. As in previous figures, but with a three month lag.

An interesting feature of the above figure is that the good correlation of the north-eastern Pacific Ocean off the west coast of North America does not extend over the continent itself.

Finally, after four months, the hemispherical pattern begins to fall apart.

Figure 5. As in previous figures, but with a four & five month lag.

Even at five months, curious patterns remain. In the northern hemisphere, the land is all negatively correlated with NINO34, and the ocean is positively correlated. But in the southern hemisphere, the land is all positively correlated and the ocean negative.

Note that this hemispheric land-ocean difference with a five-month lag is the exact opposite of the land-ocean difference with no lag shown in Figure 1.

Now … what do I make of all this?

The first thing that it brings up for me is the astounding complexity of the climate system. I mean, who would have guessed that the two hemispheres would have totally opposite strong responses to the Nino/Nina phenomenon? And who would have predicted that the land and the ocean would react in opposite directions to the Nino/Nina changes right up to the very coastlines?

Second, it would seem to offer some ability to improve long-range forecasting for certain specific areas. Positive correlation with Hawaii, North Australia, Southern Africa, and Brazil is good up to four-five months out.

Finally, it strikes me that I can run this in reverse. By that, I mean I can find all areas of the planet that are able to predict the future temperature at some pre-selected location. Like, say, what areas of the globe correlate well with whatever the UK will be doing two months from now?

Hmmm indeed …

Warmest regards to all, the mysteries of this wondrous world are endless.

w.

The Cooling Rains

Reblogged from Watts Up With That:

Guest Post by Willis Eschenbach

I took another ramble through the Tropical Rainfall Measurement Mission (TRMM) satellite-measured rainfall data. Figure 1 shows a Pacific-centered and an Atlantic-centered view of the average rainfall from the end of 1997 to the start of 2015 as measured by the TRMM satellite.

Figure 1. Average rainfall, meters per year, on a 1° latitude by 1° longitude basis. The area covered by the satellite data, forty degrees north and south of the Equator, is just under 2/3 of the globe. The blue areas by the Equator mark the InterTropical Convergence Zone (ITCZ). The two black horizontal dashed lines mark the Tropics of Cancer and Capricorn, the lines showing how far north and south the sun travels each year (23.45°, for those interested).

There’s lots of interesting stuff in those two graphs. I was surprised by how much of the planet in general, and the ocean in particular, are bright red, meaning they get less than half a meter (20″) of rain per year.

I was also intrigued by how narrowly the rainfall is concentrated at the average Inter-Tropical Convergence Zone (ITCZ). The ITCZ is where the two great global hemispheres of the atmospheric circulation meet near the Equator. In the Pacific and Atlantic on average the ITCZ is just above the Equator, and in the Indian Ocean, it’s just below the Equator. However, that’s just on average. Sometimes in the Pacific, the ITCZ is below the Equator. You can see kind of a mirror image as a light orange horizontal area just below the Equator.

Here’s an idealized view of the global circulation. On the left-hand edge of the globe, I’ve drawn a cross section through the atmosphere, showing the circulation of the great atmospheric cells.

Figure 2. Generalized overview of planetary atmospheric circulation. At the ITCZ along the Equator, tall thunderstorms take warm surface air, strip out the moisture as rain, and drive the warm dry air vertically. This warm dry air eventually subsides somewhere around 25-30°N and 25-30S of the Equator, creating the global desert belts at around those latitudes.

The ITCZ is shown in cross-section at the left edge of the globe in Figure 2. You can see the general tropical circulation. Surface air in both hemispheres moves towards the Equator. It is warmed there and rises. This thermal circulation is greatly sped up by air driven vertically at high rates of speed through the tall thunderstorm towers. These thunderstorms form all along the ITCZ. These thunderstorms provide much of the mechanical energy that drives the atmospheric circulation of the Hadley cells.

With all of that as prologue, here’s what I looked at. I got to thinking, was there a trend in the rainfall? Is it getting wetter or drier? So I looked at that using the TRMM data. Figure 3 shows the annual change in rainfall, in millimeters per year, on a 1° latitude by 1° longitude basis.

Figure 3. Annual change in the rainfall, 1° latitude x 1° longitude gridcells.

I note that the increase in rain is greater on the ocean vs land, is greatest at the ITCZ, and is generally greater in the tropics.

Why is this overall trend in rainfall of interest? It gives us a way to calculate how much this cools the surface. Remember the old saying, what comes down must go up … or perhaps it’s the other way around, same thing. If it rains an extra millimeter of water, somewhere it must have evaporated an extra millimeter of water.

And in the same way that our bodies are cooled by evaporation, the surface of the planet is also cooled by evaporation.

Now, we note above that on average, the increase is 1.33 millimeters of water per year. Metric is nice because volume and size are related. Here’s a great example.

One millimeter of rain falling on one square meter of the surface is one liter of water which is one kilo of water. Nice, huh?

So the extra 1.33 millimeters of rain per year is equal to 1.33 extra liters of water evaporated per square meter of surface area.

Next, how much energy does it take to evaporate that extra 1.33 liters of water per square meter so it can come down as rain? The calculations are in the endnotes. It turns out that this 1.33 extra liters per year represents an additional cooling of a tenth of a watt per square meter (0.10 W/m2).

And how does this compare to the warming from increased longwave radiation due to the additional CO2? Well, again, the calculations are in the endnotes. The answer is, per the IPCC calculations, CO2 alone over the period gave a yearly increase in downwelling radiation of ~ 0.03 W/m2. Generally, they double that number to allow for other greenhouse gases (GHGs), so for purposes of discussion, we’ll call it 0.06 W/m2 per year.

So over the period of this record, we have increased evaporative cooling of 0.10 W/m2 per year, and we have increased radiative warming from GHGs of 0.06 W/m2 per year.

Which means that over that period and that area at least, the calculated increase in warming radiation from GHGs was more than counterbalanced by the observed increase in surface cooling from increased evaporation.

Regards to all,

w.

As usual: please quote the exact words you are discussing so we can all understand exactly what and who you are replying to.

Additional Cooling

Finally, note that this calculation is only evaporative cooling. There are other cooling mechanisms at work that are related to rainstorms. These include:

• Increased cloud albedo reflecting hundreds of watts/square meter of sunshine back to space

• Moving surface air to the upper troposphere where it is above most GHGs and freer to cool to space.

• Increased ocean surface albedo from whitecaps, foam, and spume.

• Cold rain falling from a layer of the troposphere that is much cooler than the surface.

• Rain re-evaporating as it falls to cool the atmosphere

• Cold wind entrained by the rain blowing outwards at surface level to cool surrounding areas

• Dry descending air between rain cells and thunderstorms allowing increased longwave radiation to space.

Between all of these, they form a very strong temperature regulating mechanism that prevents overheating of the planet.

Calculation of energy required to evaporate 1.33 liters of water.

#latent heat evaporation joules/kg @ salinity 35 psu, temperature 24°C

> latevap = gsw_latentheat_evap_t( 35, 24 ) ; latevap

[1] 2441369

# joules/yr/m2 required to evaporate 1.33 liters/yr/m2

> evapj = latevap * 1.33 ; evapj

[1] 3247021

# convert joules/yr/m2 to W/m2

> evapwm2 = evapj / secsperyear ; evapwm2

[1] 0.1028941

Note: the exact answer varies dependent on seawater temperature, salinity, and density. These only make a difference of a couple percent (say 0.1043 vs 0.1028941). I’ve used average values.

Calculation of downwelling radiation change from CO2 increase.

#starting CO2 ppmv Dec 1997

> thestart = as.double( coshort[1] ) ; thestart

[1] 364.38

#ending CO2 ppmv Mar 2015

> theend = as.double( last( coshort )) ; theend

[1] 401.54

# longwave increase, W/m2 per year over 17 years 4 months

> 3.7 * log( theend / thestart, 2)/17.33

[1] 0.0299117

Natural climate processes overshadow recent human-induced Walker circulation trends

Reblogged from Watts Up With That:

Institute for Basic Science

Normal conditions (top), strengthening due to natural variability (middle) and weakening due to greenhouse warming (bottom). Black arrows represent horizontal and vertical winds with the shading on the background map illustrating ocean temperatures. Over the past few decades, natural variability has strengthened the Pacific Walker circulation leading to enhanced cooling in the equatorial central-to-eastern Pacific (middle). Climate models forced by increasing greenhouse gas concentrations simulate weakening of the Walker circulation (bottom). (Right) Temporal evolution of model-simulated Walker circulation trends, with the dark blue line and orange shading denoting anthropogenically-induced changes and the impact of natural processes, respectively. Credit IBS

Normal conditions (top), strengthening due to natural variability (middle) and weakening due to greenhouse warming (bottom). Black arrows represent horizontal and vertical winds with the shading on the background map illustrating ocean temperatures. Over the past few decades, natural variability has strengthened the Pacific Walker circulation leading to enhanced cooling in the equatorial central-to-eastern Pacific (middle). Climate models forced by increasing greenhouse gas concentrations simulate weakening of the Walker circulation (bottom). (Right) Temporal evolution of model-simulated Walker circulation trends, with the dark blue line and orange shading denoting anthropogenically-induced changes and the impact of natural processes, respectively. Credit IBS

A new study, published this week in the journal Nature Climate Change, shows that the recent intensification of the equatorial Pacific wind system, known as Walker Circulation, is unrelated to human influences and can be explained by natural processes. This result ends a long-standing debate on the drivers of an unprecedented atmospheric trend, which contributed to a three-fold acceleration of sea-level rise in the western tropical Pacific, as well as to the global warming hiatus.

Driven by the east-west sea surface temperature difference across the equatorial Pacific, the Walker circulation is one of the key features of the global atmospheric circulation. It is characterized by ascending motion over the Western Pacific and descending motion in the eastern equatorial Pacific. At the surface trade winds blow from east to west, causing upwelling of cold water along the equator. From the early 1990s to about 2013, this circulation has intensified dramatically, cooling the eastern equatorial Pacific and triggering shifts in global winds and rainfall (see Figure 1). These conditions further contributed to drying in California, exacerbating mega-drought conditions and impacting agriculture, water resources and wild fires. Given these widespread impacts on ecosystems and society, the recent Walker circulation trends have become subject of intense research.

In contrast to the observed strengthening, the majority of climate computer models simulates a gradual weakening of the Walker Circulation when forced by increasing greenhouse gas concentrations (see Figure 1). “The discrepancy between climate model projections and observed trends has led to speculations about the fidelity of the current generation of climate models and their representation of tropical climate processes”, said Eui-Seok Chung, researcher from the Center for Climate Physics, Institute for Basic Science, South Korea, and lead-author of the study.

To determine whether the observed changes in the tropical atmospheric circulation are due to natural climate processes or caused by human-induced climate change, scientists from South Korea, the United States and Germany came together to conduct one of the most comprehensive big-data analyses of recent atmospheric trends to date. “Using satellite data, improved surface observations and a large ensemble of climate model simulations, our results demonstrate that natural variability, rather than anthropogenic effects, were responsible for the recent strengthening of the Walker circulation”, said Prof. Axel Timmermann, Director of the IBS Center for Climate Physics at Pusan National University and co-author of this study.

In their integrated analysis, the researchers found that the satellite-inferred strengthening of the Walker circulation is substantially weaker than implied by other surface observations used in previous studies. “Putting surface observations in context with latest satellite products was a key element of our study”, said co-author Dr. Lei Shi from NOAA’s National Centers for Environmental Information in the United States.

Analyzing 61 different computer model simulations forced with increasing greenhouse gas concentrations, the authors showed that, although the average response is a Walker circulation weakening, there are substantial discrepancies amongst the individual model experiments, in particular when considering shorter-term trends. “We found that some models are even consistent with the observed changes in the tropical Pacific, in stark contrast to other computer experiments that exhibit more persistent weakening of the Walker circulation during the observational period”, said co-author Dr. Viju John from EUMETSAT in Germany. The authors were then able to tease apart what caused the spread in the computer model simulations.

Co-author Prof. Kyung-Ja Ha from the IBS Center for Climate Physics and Pusan National University explains “Natural climate variability, associated for instance with the El Niño-Southern Oscillation or the Interdecadal Pacific Oscillation can account for a large part of diversity in simulated tropical climate trends”.

“The observed trends are not that unusual. In climate model simulations we can always find shorter-term periods of several decades that show similar trends to those inferred from the satellite data. However, in most cases, and when considering the century-scale response to global warming, these trends reverse their sign eventually”, said co-author Prof. Brian Soden from the Rosenstiel School of Marine and Atmospheric Science, at the University of Miami, United States.

The study concludes that the observed strengthening of the Walker circulation from about 1990-2013 and its impact on western Pacific sea level, eastern Pacific cooling, drought in the Southwestern United States, was a naturally occurring phenomenon, which does not stand in contrast to the notion of projected anthropogenic climate change. Given the high levels of natural decadal variability in the tropical Pacific, it would take at least two more decades to detect unequivocally the human imprint on the Pacific Walker Circulation (see Figure 1, right panel).

Solar variability weakens the Walker cell

Tallbloke's Talkshop

Credit: PAR @ Wikipedia
This looks significant, pointing directly at solar influences on climate patterns. The researchers found evidence that atmosphere-ocean coupling can amplify the solar signal, having detected that wind anomalies could not be explained by radiative considerations alone.

An international team of researchers from United Kingdom, Denmark, and Germany has found robust evidence for signatures of the 11-year sunspot cycle in the tropical Pacific, reports Phys.org.

They analyzed historical time series of pressure, surface winds and precipitation with specific focus on the Walker Circulation—a vast system of atmospheric flow in the tropical Pacific region that affects patterns of tropical rainfall.

They have revealed that during periods of increased solar irradiance, the trade winds weaken and the Walker circulation shifts eastward.

View original post 249 more words

Satellite Evidence Affirms Solar Activity Drove ‘A Significant Percentage’ Of Recent Warming

Reblogged from the NoTricksZone:

In a new paper, two astrophysicists shred the IPCC-preferred and model-based PMOD solar data set and affirm the ACRIM, which is rooted in observation and shows an increase in total solar irradiance (TSI) during the 1980-2000 period. They suggest a “significant percentage” of recent climate change has been solar-driven.

Scafetta and Willson, 2019

I. The PMOD is based on proxy modeled predictions, “questionable” modifications, and degraded, “misinterpreted” and “erroneously corrected” results 

• “The PMOD rationale for using models to alter the Nimbus7/ERB data was to compensate for the sparsity of the ERBS/ERBE data and conform their gap results more closely to the proxy predictions of solar emission line models of TSI behavior.”
• “PMOD’s modifications of the published ACRIM and ERB TSI records are questionable because they are based on conforming satellite observational data to proxy model predictions.”
• “The PMOD trend during 1986 to 1996 is biased downward by scaling ERB results to the rapidly degrading ERBE results during the ACRIM-Gap using the questionable justification of agreement with some TSI proxy predictions first proposed by Lee III et al.(1995).”
• PMOD misinterpreted and erroneously corrected ERB results for an instrument power down event.”
• “PMOD used overlapping comparisons of ACRIM1 and ACRIM2 with ERBE observations and proxy models to construct their first composite. Other PMOD composites [17, 18] used different models of the ERBE-ACRIM-Gap degradation. The result of these various modifications during the ACRIM-Gap was that PMOD introduced a downward trend in the Nimbus7/ERB TSI data that decreased results by 0.8 to 0.9 W/m2 (cf. [18, 20]).”

II. The PMOD TSI composite “flawed” results were an “unwarranted manipulation” of data intended to support AGW, but are  “contraindicated”

• “The dangers of utilizing ex-post-facto corrections by those who did not participate in the original science teams of satellite experiments are that erroneous interpretations of the data can occur because of a lack of detailed knowledge of the experiment and unwarranted manipulation of the data can be made based on a desire to support a particular solar model or some other nonempirical bias. We contend that the PMOD TSI composite construction is compromised in both these ways.”
 “[O]ur scientific knowledge could be improved by excluding the more flawed record from the composite. This was the logic applied by the ACRIM team. In point of fact PMOD failed to do this, instead selecting the ERBE results that were known to be degraded and sparse, because that made the solar cycle 21–22 trend agrees with TSI proxy models and the CAGW explanation of CO2 as the driver of the global warming trend of the late 20th century.”
• “The use of unverified modified data has fundamentally flawed the PMOD TSI satellite composite construction.”
• “The consistent downward trending of the PMOD TSI composite is negatively correlated with the global mean temperature anomaly during 1980–2000. This has been viewed with favor by those supporting the COanthropogenic global warming (CAGW) hypothesis since it would minimize TSI variation as a competitive climate change driver to CO2, the featured driver of the hypothesis during the period (cf.: [IPCC, 2013, Lockwood and Fröhlich, 2008]).”
• “Our summary conclusion is that the objective evidence produced by all of the independent TSI composites [3,5, 6, 9] agrees better with the cycle-by-cycle trending of the original ACRIM science team’s composite TSI that shows an increasing trend from 1980 to 2000 and a decreasing trend thereafter. The continuously downward trending of the PMOD composite and TSI proxy models is contraindicated.”

III. The ACRIM TSI supports the conclusion that “a significant percentage” of climate change in recent decades was driven by TSI variation

Graph Source: Soon et al., 2015
• ACRIM shows a 0.46 W/m2 increase between 1986 and 1996 followed by a decrease of 0.30 W/m2 between 1996 and 2009. PMOD shows a continuous, increasing downward trend with a 1986 to 1996 decrease of 0.05 W/m2 followed by a decrease of 0.14 W/m2 between 1996 and 2009. The RMIB composite agrees qualitatively with the ACRIM trend by increasing between the 1986 and 1996 minima and decreasing slightly between 1996 and 2009.”
• “ACRIM composite trending is well correlated with the record of global mean temperature anomaly over the entire range of satellite observations (1980–2018) [Scafetta. 2009]. The climate warming hiatus observed since 2000 is inconsistent with CO2 anthropogenic global warming (CAGW) climate models [Scafetta, 2013, Scafetta, 2017]. This points to a significant percentage of the observed 1980–2000 warming being driven by TSI variation [Scafetta, 2009, Willson, 2014, Scafetta. 2009]. A number of other studies have pointed out that climate change and TSI variability are strongly correlated throughout the Holocene including the recent decades (e.g., Scafetta, 2009,  Scafetta and Willson, 2014, Scafetta, 2013Kerr, 2001, Bond et al., 2001, Kirkby, 2007, Shaviv, 2008, Shapiro et al., 2011, Soon and Legates, 2013, Steinhilber et al., 2012, Soon et al., 2014).”
• “The global surface temperature of the Earth increased from 1970 to 2000 and remained nearly stable from 2000 and 2018. This pattern is not reproduced by CO2 AGW climate models but correlates with a TSI evolution with the trending characteristics of the ACRIM TSI composite as explained in Scafetta [6,12, 27] and Willson [7].”

IV. The Correlation:

Graph Source: Soon et al., 2015
Image Source: Smith, 2017

V. The Mechanism: Higher solar activity on decadal-scales limits the seeding of clouds, which means more solar radiation is absorbed by the surface, warming the Earth 

Image Source: Fleming, 2018

Image Source: Sciencedaily.com

VI. The radiative forcing from the increase in surface solar radiation: +4.25 Wm-2/decade between 1984-2000

Image Source: Goode and Palle, 2007

Image Source(s): Hofer et al., 2017 and Kay et al., 2008

Retreating Greenland glacier is growing again

Tallbloke's Talkshop

Jakobshavn glacier, West Greenland [image credit: Wikipedia]
Without jumping to hasty conclusions, this is an interesting development not predicted by the IPCC’s supposed experts. Natural ocean/climate oscillations are implicated. Against assumptions, rising carbon dioxide levels cannot explain these latest observations.

A new NASA study finds a major Greenland glacier that was one of the fastest shrinking ice and snow masses on Earth is growing again, reports The GWPF.

The scientists were so shocked to find the change, Khazendar said: “At first we didn’t believe it.

“We had pretty much assumed that Jakobshavn would just keep going on as it had over the last 20 years.”

View original post 194 more words

Hurricanes & climate change: 21st century projections

Climate Etc.

by Judith Curry

Final installment in my series on hurricanes and climate change.

View original post 4,485 more words

China And The Pause

Reblogged from the GWPF:

Dr David Whitehouse, GWPF Science Editor, 08/03/19

Chinese climate scientists: The so-called hiatus in global temperature is illuminating, significant and real.

Chinese climate scientists are clearly off-message. They keep referring to the global warming hiatus which so many scientists and activists – those who shout on twitter and prowl the comment sections of off-colour articles on the subject – know has been trounced and discredited again and again. They clearly ought to have a word with the emerging science powerhouse that is China.

Writing recently in “Science of The Total Environment,” Li and Zha of Nanjing Normal University, say the global hiatus has played a prominent role in their thinking and they see it reflected in China. Using satellite data they found a hiatus in China between 2001-15. They found warming in western and southern China and a 15-year cooling trend in northern China. For China as a whole they estimate that the warming rate is just -0.02°C per decade. They conclude that, “there is a regional warming hiatus, a pause or slowdown in China, and (it) implies that greenhouse gas induced warming is suppressed by other natural forcing in the early 21st century.”

There is also Li et al writing in Climate Dynamics who are a little more forceful saying, “since the late 1990s, the global warming has ground to a halt, which has sparked a rising interest among the climate scientists. The hiatus is not only observed in globally average surface air temperature, but also in the China winter air temperature trend, which turns from warming during 1979-1997 to cooling during 1998-2013.” They attribute the effect to the melting of Arctic sea ice.

Gan et al (Lanzhou University and South Dakota State University), reporting in Earth and Space Science say that the hiatus, if not cooling, is seen over the Northern Hemisphere finding that the daily temperature minimum experienced an “obvious” decline in North America during the warming slowdown period. They relate the changes in daily temperature minimum to the Atlantic Multi-decadal Oscillation.

He at al (National Science Review) note that carbon budgets in ecosystems in China are coupled with changes in climate. They point out that in the past decade China has experienced changes in the characteristics of its summer monsoon as well as “decelerated warming.” They point out that in general changes in China’s ecosystems are poorly documented.

Looking at East Asian surface temperatures Xie et al in Climate Dynamics suggest that the effect of the North Atlantic Oscillation, operating through its influence on the African-Asian multi-decadal teleconnection pattern, will mean that East Asian surface ait temperatures will remain at their current levels or slightly cooler between 2018 -2034, and will then increase.

Elsewhere in the world Wanatabe et al in Nature Scientific Reports say that the Indian Ocean Dipole – an inter-annual mode of climate variability in the Indian Ocean – has intensified with 20th century global warming. However, the data shows a global-warming hiatus between the late-1990s and 2015. They say it is presently unclear how this global warming hiatus, as they put it, will affect regional ocean parameters.

All of these interesting papers come from mainstream journals, and all are food for thought. The so-called hiatus in global temperature is illuminating, significant and real.