NPR Defends Pseudo-Science

This morning in the car doing some errands I listened to an NPR broadcast regarding a NYT article claiming the Trump administration is attacking the fundamentals of climate science. Two journalists involved in the NYT article made two revealing defenses of IPCC climate ideology.

First they objected to the Geological Survey decision to limit consideration (required by US law) of climate change to impacts foreseen between now and 2040, setting aside projections out to 2100. Their reasoning: We won’t see any significant effects from our reducing (or not) CO2 emissions until the second half of this century. All of the forecasted temperature rise of 8F, along with sea level rise, storms, droughts, floods, etc. is only seen to occur after 2040. How do they know this? It is certain because it comes directly from the Oracle of Delphi the Climate Models, which have so accurately forecast the climate in the past (sic).  All the pressure to unplug industrial civilization now, with results to appear many decades later.

Then they expressed shock that a Presidential Commission may be set up to review and questions climate assumptions put into agency planning. They said everyone agrees on the science of global warming, and this is not the way climate science is done. The two journalists, without a single bit of self-awareness, proceeded to discredit the possible chairman William Happer by saying he was not a “climate scientist.” Like, how would they know? He is a world expert on atmospheric gases responses to infrared radiation, which is the supposed mechanism of man made global warming, and something about which they  are  clueless.

In other news today, Arnold Swartzenegger was “starstruck” to meet with teen climate activist Greta Thunberg. How bad will this nightmare get before people wake up?

See Also Stop Fake Science. Approve the PCCS!

Get a Second Opinion Before Climate Surgery

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Required Reading: NIPCC 2019 Summary on Fossil Fuels

Those who seek the truth about global warming/climate change should welcome this latest publication from the Nongovernmental International Panel on Climate Change (NIPCC). Excerpts from the Coauthors’ introduction in italics with my bolds. H/T Lubos Motl

Climate Change Reconsidered II: Fossil Fuels assesses the costs and benefits of the use of fossil fuels (principally coal, oil, and natural gas) by reviewing scientific and economic literature on organic chemistry, climate science, public health, economic history, human security, and theoretical studies based on integrated assessment models (IAMs). It is the fifth volume in the Climate Change Reconsidered series and, like the preceding volumes, it focuses on research overlooked or ignored by the United Nations’ Intergovernmental Panel on Climate Change (IPCC).

NIPCC was created by Dr. S. Fred Singer in 2003 to provide an independent peer review of the reports of the United Nations’ Intergovernmental Panel on Climate Change (IPCC). Unlike the IPCC and as its name suggests, NIPCC is a private association of scientists and other experts and nonprofit organizations. It is not a government entity and is not beholden to any political or corporate benefactors. This and previous volumes in the CCR series, along with other publications and information about NIPCC, are available for free on NIPCC’s website .

The NIPCC authors do something their IPCC counterparts never did: conduct an evenhanded cost-benefit analysis of the use of fossil fuels. Despite calling for the end of reliance on fossil fuels by 2100, the IPCC never produced an accounting of the opportunity cost of restricting or banning their use. That cost, a literature review shows, would be enormous.

We thank the more-than-100 scientists, scholars, and experts who participated over the course of four years in writing, reviewing, editing, and proofreading this volume. This was a huge undertaking that involved thousands of hours of effort, the vast majority of it unpaid. The result exceeded our hopes, and we trust it meets your expectations.

The NIPCC authors cite thousands of books, scholarly articles, and reports that contradict the IPCC’s alarmist narrative. We once again tried to remain true to the facts when representing the findings of others, often by quoting directly and at some length from original sources and describing the methodology used and qualifications that accompanied the stated conclusions. The result may seem tedious at times, but we believe this was necessary and appropriate for a reference work challenging many popular beliefs.

The NIPCC authors conclude, “The global war on energy freedom, which commenced in earnest in the 1980s and reached a fever pitch in the second decade of the twenty-first century, was never founded on sound science or economics. The world’s policymakers ought to acknowledge this truth and end that war.”

Footnote:

Lubos Motl commented on this publication following his translating of the SPM into Czech.  Some excerpts in italics.

The NIPCC reports are actually amazing

Previous NIPCC volumes have also been extensive and they dedicated more space to the physical and biological scientific foundations. The newest 2019 report dedicated to the fossil fuels is unavoidably more practical and economics-oriented.

But it rationally discusses all the extra layers of the causal chains of the climate warning. Even if one assumes that there will be a warming, does it hurt the environment? The economy? Don’t the benefits exceed the costs? Don’t the costs of the mitigation policies exceed their benefits? As you may guess, the correct answers to all these questions – advocated in the NIPCC report – are almost universally the “skeptical ones”.

It’s so unfortunate that despite the higher quality of the NIPCC report (or at least comparable quality, if one were really generous to the IPCC), the left-wing media establishment – in some loose alliance with the governments – was capable of promoting the IPCC reports as if they were the Holy Scriptures while the NIPCC reports remained almost completely hidden from the world public. 

Washing Methane Away: Atmospheric Chemistry

The good news comes from NASA published at Science Daily Greenhouse gas ‘detergent’ recycles itself in atmosphere.  The study explains how the atmosphere functions as a methane sink, and why the process is resilient and handles whatever CH4 is emitted.  Scientists had worried that the atmospheric capacity to wash away methane might decay over time, but that fear turns out to be unfounded. Excerpts in italics with my bolds.

Summary:
A simple molecule in the atmosphere that acts as a ‘detergent’ to break down methane and other greenhouse gases has been found to recycle itself to maintain a steady global presence in the face of rising emissions, according to new research. Understanding its role in the atmosphere is critical for determining the lifetime of methane, a powerful contributor to climate change.

The hydroxyl (OH) radical, a molecule made up of one hydrogen atom, one oxygen atom with a free (or unpaired) electron is one of the most reactive gases in the atmosphere and regularly breaks down other gases, effectively ending their lifetimes. In this way OH is the main check on the concentration of methane, a potent greenhouse gas that is second only to carbon dioxide in contributing to increasing global temperatures.

With the rise of methane emissions into the atmosphere, scientists historically thought that might cause the amount of hydroxyl radicals to be used up on the global scale and, as a result, extend methane’s lifetime, currently estimated to be nine years. However, in addition to looking globally at primary sources of OH and the amount of methane and other gases it breaks down, this new research takes into account secondary OH sources, recycling that happens after OH breaks down methane and reforms in the presence of other gases, which has been observed on regional scales before.

“OH concentrations are pretty stable over time,” said atmospheric chemist and lead author Julie Nicely at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “When OH reacts with methane it doesn’t necessarily go away in the presence of other gases, especially nitrogen oxides (NO and NO2). The break down products of its reaction with methane react with NO or NO2 to reform OH. So OH can recycle back into the atmosphere.”

OH in the atmosphere also forms when ultraviolet sunlight reaches the lower atmosphere and reacts with water vapor (H2O) and ozone (O3) to form two OH molecules. Over the tropics, water vapor and ultraviolet sunlight are plentiful. The tropics, which span the region of Earth to either side of the equator, have shown some evidence of widening farther north and south of their current range, possibly due to rising temperatures affecting air circulation patterns. This means that the tropical region primed for creating OH will potentially increase over time, leading to a higher amount of OH in the atmosphere. This tropical widening process is slow, however, expanding only 0.5 to 1 degree in latitude every 10 years. But the small effect may still be important, according to Nicely.

She and her team found that, individually, the tropical widening effect and OH recycling through reactions with other gases each comprise a relatively small source of OH, but together they essentially replace the OH used up in the breaking down of methane.

“The absence of a trend in global OH is surprising,” said atmospheric chemist Tom Hanisco at Goddard who was not involved in the research. “Most models predict a ‘feedback effect’ between OH and methane. In the reaction of OH with methane, OH is also removed. The increase in NO2 and other sources of OH, such as ozone, cancel out this expected effect.” But since this study looks at the past thirty-five years, it’s not guaranteed that as the atmosphere continues to evolve with global climate change that OH levels will continue to recycle in the same way into the future, he said.

Ultimately, Nicely views the results as a way to fine-tune and update the assumptions that are made by researchers and climate modelers who describe and predict how OH and methane interact throughout the atmosphere. “This could add clarification on the question of will methane concentrations continue rising in the future? Or will they level off, or perhaps even decrease? This is a major question regarding future climate that we really don’t know the answer to,” she said.

Abstract from AGU publication Changes in Global Tropospheric OH Expected as a Result of Climate Change Over the Last Several Decades  Julie M. Nicely
The oxidizing capacity of the troposphere is controlled primarily by the abundance of hydroxyl radical (OH). The global mean concentration of tropospheric OH, [OH]TROP (the burden of OH in the global troposphere appropriate for calculating the lifetime of methane) inferred from measurements of methyl chloroform has remained relatively constant during the past several decades despite rising levels of methane that should have led to a decline.

Here we examine other factors that may have affected [OH]TROP such as the changing values of stratospheric ozone, rising tropospheric H2O, varying burden of NOx (=NO+NO2), rising temperatures, and widening of the climatological tropics due to expansion of the Hadley cell. Our analysis suggests the positive trends in [OH]TROP due to H2O, NOx, and overhead O3, and tropical expansion are large enough (Δ [OH]TROP = +0.95 ± 0.18%/decade) to counter almost all of the expected decrease in [OH]TROP due to rising methane (Δ [OH]TROP = −1.01 ± 0.05%/decade) over the period 1980 to 2015, while variations in temperature contribute almost no trend (Δ [OH]TROP = −0.02 ± 0.02%/decade) in [OH]TROP. The approximated impact of Hadley cell expansion on [OH]TROP is also a small but not insignificant factor partially responsible for the steadiness of tropospheric oxidizing capacity over the past several decades, which free‐running models likely do not capture.

Slowing expanding tropical regions seems like a good thing all around.

 

Tweak the Sun’s Rotation, and We’re Not Here

Watch the Sun rotate for over a month brought to you by SDO. Since the Sun rotates once every 27 days on average, this movie presents more than an entire solar rotation. From March 30 through Apr. 29, 2011, the Sun sported quite a few active regions and magnetic loops. The movie shows the Sun in the 171 Angstrom wavelength of extreme ultraviolet light (capturing ionized iron heated to about 600,000 degrees), color coded to appear gold. The movie is based on a frame taken every 15 minutes being shown at 24 frames per second, with very few data gaps in this almost two-minute movie. Source Solar Dynamics Observatory

Another fresh reminder we owe our existence to the sun along with the climate in which we evolved and adapted. The Forbes article is Early Sun’s ‘Goldilocks’ Rotation Rate May Be Why We’re Here  Excerpts in italics with my bolds.

Our early Sun’s rate of rotation may be one reason we’re here to talk about it, astrobiologists now say. The key likely lies in the fact that between the first hundred million to the first billion years of its life, our G-dwarf star likely had a ‘Goldilocks’ rotation rate; neither too slow nor too fast.

Instead, its hypothetical ‘intermediate’ few days rate of rotation guaranteed our Sun was active enough to rid our newly-formed Earth of its inhospitable, hydrogen-rich primary atmosphere. This would have enabled a more habitable, secondary atmosphere composed of nitrogen, carbon dioxide, hydrogen and oxygen to eventually form.

If it had been a ‘fast’ (less than one day rotator), our Sun might have continually stripped our young planet of its secondary atmosphere as well. However, if it took more than 10 days to rotate, it might not have been active enough to strip Earth of its hypothetical primary atmosphere.

Such ideas were recently bandied about in oral presentations at last month’s the General Assembly of the International Astronomical Union (IAU) in Vienna.

Earth’s very first atmosphere would have been too hot and too thick, more like Venus’ present-day atmosphere, Theresa Luftinger, an astrophysicist at the University of Vienna, told me. No known organisms could have evolved under such an atmosphere.  A secondary atmosphere cannot evolve in the presence of a primordial atmosphere , says Luftinger.

It’s the star’s magnetic dynamo that drives its magnetic fields. And these magnetic fields, in turn, interact with the star itself, creating an interplay of extreme stellar activity.

“So, the quicker the star rotates, the higher the interaction between the magnetic field and the stellar body ,” said Luftinger.

Faster rotation means higher extreme ultra-violet and x-ray activity, Helmut Lammer, an astrophysicist at Austria’s Space Science Institute in Graz, told me. This would lead to atmospheric stripping and water loss on earthlike planets around an active young star, he says. 

Our Sun is now a very slow rotator at 27 days. But that wasn’t always the case. As for why some stars seem to inherently rotate faster than others?

Astrophysicists suspect that initial conditions within star-forming clouds cause newborn stars to have different rotation rates.

Researchers are able to roughly pinpoint the Sun’s early rotation rates by studying the isotopic ratios of neon, argon, potassium, and uranium here in Earth’s crust. That is, elements which have atoms that have the same numbers of protons in their atomic nucleus, but different numbers of neutrons. The researchers also considered such isotopic ratios from decades’-old Venus surface samples taken by Soviet Venus lander missions.

 

 

Ocean Air Temps Tepid in July

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The July update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for July. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201807The anomalies are holding close to the same levels as 2015. In July, both the Tropics and SH rose, while NH rose very slightly, resulting in a small increase in the Global average of air over oceans. Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades.  On that basis we can see the plateau in ocean temps is persisting. Since last October all oceans have cooled, with offsetting bumps up and down.

UAHv6 TLT 
Monthly Ocean
Anomalies
Average Since 1995 Ocean 7/2018
Global 0.13 0.21
NH 0.16 0.3
SH 0.11 0.15
Tropics 0.13 0.29

As of July 2018, global ocean temps are slightly higher than June and the average since 1995.  NH remains virtually the same,  while both SH and Tropics rose making the global temp warmer.  Global, NH and SH are matching July temps in 2015, while the Tropics are the lowest July since 2013.

The details of UAH ocean temps are provided below.  The monthly data make for a noisy picture, but seasonal fluxes between January and July are important.

Open image in new tab to enlarge.

The greater volatility of the Tropics is evident, leading the oceans through three major El Nino events during this period.  Note also the flat period between 7/1999 and 7/2009.  The 2010 El Nino was erased by La Nina in 2011 and 2012.  Then the record shows a fairly steady rise peaking in 2016, with strong support from warmer NH anomalies, before returning to the 22-year average.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  They started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

Dr. Indrani Roy on Solar and Climate Cycles

The last solar eclipse was in 2017. The totality in the picture lasted a little more than 2 minutes, while the process lasted about 2.5 hours.

One of the great disputes in climate research is between those (IPCC) who dismiss solar cycles as a factor in climate change and those who see correlations in the past and keep seeking to understand the mechanisms. To be clear, there is considerable agreement that earth’s atmosphere can and does reduce or increase the amount of incoming solar energy (albedo effect), thereby contributing to surface warming or cooling. The science and research into the “global dimming and brightening” is discussed in the post Nature’s Sunscreen.

The above image of the eclipse is intended to remind us that humans down through history have been terrified of the sun going dark because they knew intuitively that no sun means no life. A more modern and sophisticated concern is that even slightly falling energy from the sun brings cooling, ice and death.  Quite apart from the sunscreen, this post is focused a different matter, namely that changes in the sun’s output radiation cause changes in earth climate parameters. One theory of such a mechanism is espoused by Henrik Svensmark and concerns solar particles effect upon albedo. That line of research is discussed in the post The Cosmoclimatology theory

A different investigation has been advanced by Dr.Indrani Roy, her most recent publication this month being a book Climate Variability and Sunspot Activity Analysis of the Solar Influence on Climate (H/T NoTricksZone).

The book is behind a paywall, but the abstract and chapter headings indicate a comprehensive approach.

Overview Climate Variability and Sunspot Activity (2018)

This book promotes a better understanding of the role of the sun on natural climate variability. It is a comprehensive reference book that appeals to an academic audience at the graduate, post-graduate and PhD level and can be used for lectures in climatology, environmental studies and geography.

This work is the collection of lecture notes as well as synthesized analyses of published papers on the described subjects. It comprises 18 chapters and is divided into three parts: Part I discusses general circulation, climate variability, stratosphere-troposphere coupling and various teleconnections. Part II mainly explores the area of different solar influences on climate. It also discusses various oceanic features and describes ocean-atmosphere coupling. But, without prior knowledge of other important influences on the earth’s climate, the understanding of the actual role of the sun remains incomplete. Hence, Part III covers burning issues such as greenhouse gas warming, volcanic influences, ozone depletion in the stratosphere, Arctic and Antarctic sea ice, etc. At the end of the book, there are few questions and exercises for students. This book is based on the lecture series that was delivered at the University of Oulu, Finland as part of M.Sc./ PhD module.

Chapter Titles

  • Climatology and General Circulation
  • Major Modes of Variability
  • Stratosphere-Troposphere Coupling
  • Teleconnection Among Various Modes
  • Solar Influence Around Various Places: Robust Solar Signal on Climate
  • Total Solar Irradiance (TSI): Measurements and Reconstructions
  • Atmosphere-Ocean Coupling and Solar Variability
  • Ocean Coupling
  • The Sun and ENSO Connection–Contradictions and Reconciliations
  • A Debate: The Sun and the QBO
  • Solar Influence: ‘Top Down’ vs. ‘Bottom Up’
  • An Overview of Solar Influence on Climate
  • Other Major Influences on Climate
  • Sun: Atmosphere-Ocean Coupling – Possible Limitations
  • The Arctic and Antarctic Sea Ice
  • CMIP5 Project and Some Results
  • Green House Gas Warming
  • Volcanic Influences
  • Ozone Depletion in the Stratosphere
  • Influence of Various Other Solar Outputs

To better appreciate Roy’s viewpoint, two of her previous publications provide the evidence and analytical thought behind her conclusions.  Published in 2010 with J.D. Haigh was Solar cycle signals in sea level pressure and sea surface temperature  Excerpts in italics with my bolds.

Summary of SLP and SST signals

We identify solar cycle signals in the North Pacific in 155 years of sea level pressure and sea surface temperature data. In SLP we find in the North Pacific a weakening of the Aleutian Low and a northward shift of the Hawaiian High in response to higher solar activity, confirming the results of previous authors using different techniques. We also find a broad reduction in pressure across the equatorial region but not the negative anomaly in the sub-tropics detected by vL07. In SST we identify the warmer and cooler regions in the North Pacific found by vL07 but instead of the strong Cold Event-like signal in tropical SSTs we detect a weak WE-like pattern in the 155 year dataset.

We find that the peak SSN years of the solar cycles have often coincided with the negative phase of ENSO so that analyses, such as that of vL07, based on composites of peak SSN years find a La Nina response. As the date of peak annual SSN generally falls a year or more in advance of the broader maximum of the 11-year solar cycle it follows that the peak of the DSO is likely to be associated with an El Nino-like pattern, as seen by White et al. (1997). An El Nino pattern is clearly portrayed in our regression analysis using only data from second half of the last century, but inclusion of ENSO as an independent regression index results in a significant diminution of the solar signal in tropical SST, showing further how an ENSO signal might be interpreted as due to the Sun.

Any mechanisms proposed to explain a solar influence should be consistent with the full length of the dataset, unless there are reasons to think otherwise, and analyses which incorporate data from all years, rather than selecting only those of peak SSN, represent more coherently the difference between periods of high and low solar activity on these timescales.

The SLP signal in mid-latitudes varies in phase with solar activity, and does not show the same modulation by ENSO phase as tropical SST, suggesting that the solar influence here is not driven by coupled-atmosphere-ocean effects but possibly by the impact of changes in the stratosphere resulting in expansion of the Hadley cell and poleward shift of the subtropical jets (Haigh et al., 2005). Given that climate model results in terms of tropical Pacific SST can be dependent on different ENSO variability within the models, our analysis indicates that the robustness of any proposed mechanism of the response to variations in solar irradiance needs to be analyzed in the context of ENSO variability where timing plays a crucial role.

Comment on Dr. Roy’s Methodology

It is challenging to grasp this approach and results because she respects the complexity of solar and climate dynamics.  For starters, she is not mining climate data in search of 11 year periodicities as others have done.  Dr. Roy takes the dates of observed SSN maxima and minima and compares with repeated effects in climate measurements.  Many readers will know that solar cycles are only quasi-11 years long; there is considerable irregularity.

Even more importantly, SSN do not peak midway in the cycle, but can appear early on and show additional peak(s) afterward. She defines minima and maxima in terms of SSN significantly lower or higher than the mean.  So Roy’s analysis is not simplistic, but correlates all years in the datasets comparing SSN with climate measures.

Dr. Roy also diligently analyzes confounding factors such as oceanic circulations and the influence of previous years upon succeeding years (system momentum).  For example, the above study discussed solar influence on Pacific SST and SLP.  This is presented in the following image:

Tropical Pacific SST composites using NOAA Extended V4 (ERSST) data for solar Max (Top) and Min years (Bottom) during DJF. Levels usually significant up to 95% level are overlaid by opposite coloured contour. Plots are generated using IDL software, version 8 with the data from NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at (http://www.esrl.noaa.gov/psd/).

Importantly, the analysis shows little to no solar influence upon the ENSO 3.4 ocean sector, but as the graph above shows the effect is much broader. Roy concludes that ENSO operates mostly independently of solar influence. Even more striking is the result for NH winter, showing solar minima associated with generally warmer SST and maxima generally cooler. Dr. Roy explains the solar influence in terms of two separate processes.  Bottom up is fluctuations in SSTs while top-down is UV effects upon the stratosphere extending downward expressed in SLP differentials.

For a discussion of the solar/climate mechanism there is  Solar cyclic variability can modulate winter Arctic climate by Indrani Roy  Scientific Reportsvolume 8, Article number: 4864 (2018). Excerpts in italics with my bolds.

Abstract

This study investigates the role of the eleven-year solar cycle on the Arctic climate during 1979–2016. It reveals that during those years, when the winter solar sunspot number (SSN) falls below 1.35 standard deviations (or mean value), the Arctic warming extends from the lower troposphere to high up in the upper stratosphere and vice versa when SSN is above. The warming in the atmospheric column reflects an easterly zonal wind anomaly consistent with warm air and positive geopotential height anomalies for years with minimum SSN and vice versa for the maximum. Despite the inherent limitations of statistical techniques, three different methods – Compositing, Multiple Linear Regression and Correlation – all point to a similar modulating influence of the sun on winter Arctic climate via the pathway of Arctic Oscillation. Presenting schematics, it discusses the mechanisms of how solar cycle variability influences the Arctic climate involving the stratospheric route. Compositing also detects an opposite solar signature on Eurasian snow-cover, which is a cooling during Minimum years, while warming in maximum. It is hypothesized that the reduction of ice in the Arctic and a growth in Eurasia, in recent winters, may in part, be a result of the current weaker solar cycle.

Results

In summary, for solar Min years, the warm air column is associated with positive geopotential height anomalies and an easterly wind, which reverses during Max years. Such NAM feature is clearly evident supporting the hypothesis of communicating a solar signal to Arctic via winter NAM (North Annular Mode).

Above: Mechanism to describe the stratospheric pathway for solar cycle variability to influence the Arctic climate. Mechanisms for (a) discuss a route where perturbation in the upper stratospheric polar vortex is transported downwards and impacts the Arctic on a seasonal scale via the winter NAM (flowchart is presented on the right). Mechanisms for (b) discusses the route that involves upper stratospheric polar vortex, tropical lower stratosphere, Brewer-Dobson circulation and Ferrel cell (flowchart is presented to the left). It is created using images or clip art available from Powerpoint.

During DJF, Arctic sea ice extent suggests a strong correlation with SSN (99% significant) and even with AOD (95% significant) (Table 3a). SSN is also found to be strongly correlated with AO (95% significant). Figure 8a shows that significant correlation between Arctic sea ice extent and SSN is still present in other seasons as well. However, the correlation between SSN and AO is only significant in DJF, confirming that the possible route of solar influence on winter Arctic sea ice is via the AO. On the other hand, the influence of AO on Arctic sea ice extent is not present during winter. It is strongest during JJA, though fails to exceed a significant threshold of 95% level.

Results of Correlation Coefficient (c.c) between Sea Ice Extent and various other parameters. (a) Seasonal c.c. for four different seasons are presented using other parameters as SSN and AO, and (b) c.c. for the winter season in different regions using other parameters as AO and AMO. Significant levels of 95% and 99% using a students ‘t-test’ are marked by dashed line and dotted line respectively. Plots are prepared using IDL software, version 8.

In terms of oceanic longer-term variability, here we particularly focus on the AMO and find a strong connection between sea ice and AMO in winter, agreeing with previous studies45,46. Earlier discussions suggested that there are few differences in region A and B relating to trend (Figs S6 and S7), but correlation technique indicated a very strong anti-correlation between the winter AMO index and sea ice in all regions of our considerations (Fig. 8b)). Even using two different data sources (HadSST and ERSST) we arrive at similar results, and it is also true for overall sea ice extent. It could also be possible that, in region B, due to a strong presence of AO influence of the sun, it may mask some of the influence of the longer-term trend (seen in Fig. 2) to suggest a lesser trend, as also noted in Figs S6 and S7.

This Matters As We Reach Solar Minimum for Cycle 24

The latest observations show this solar cycle is over, perhaps the next one beginning.  With no sunspots seen since June, this is unusually quiet.

The solar surface at the moment is “Spotless” and has been for a month.

Summary

The sun is the primary source of energy in the earth/atmosphere system, but the actual role of the sun and related mechanisms to support varied regional climate responses and its seasonality around the world, are still poorly understood. Solar energy output varies in cycles, of which the 11-year cyclic variability is one of the most crucial ones. It causes differences in the amount of solar energy absorbed in the UV part of the spectrum within the upper stratosphere, varying from 6 to 8%. Such variation is believed to be one of the most important solar energy outputs to influence the climate of the earth and that knowledge of cyclic behaviour can also be used for future prediction purposes. Apart from solar UV related effects on earth’s climate, studies also identified effects related to solar particle precipitation.

Various studies have also detected an influence of the El Nino Southern Oscillation (ENSO)22 and the Pacific Decadal Oscillation (PDO) on Arctic sea ice. An association between the sun and ENSO are discussed in various research. Because of related complexities along with various linear and nonlinear couplings among major modes of variability, the role of the sun on Arctic air temperatures and sea ice extent and related mechanisms remains poorly understood/explored.

While many studies point to anthropogenic influences on the long-term sea ice decline, this study is motivated by the potential links between the sun and the surface climate through stratospheric processes. Alongside warming in the Arctic, a cooling is noticed around Eurasian sector despite continuing rise of greenhouse gas concentrations. Various modelling groups, however, made unsuccessful efforts to detect an association between Eurasian cooling and Arctic sea-ice decline. In this work, we evaluate the impact of the solar 11-year cycle, measured in terms of solar sunspot number (SSN), as a driving factor to modulate Arctic and surrounding climate. The influences of SSN on various surface parameters, such as Sea Level Pressure (SLP), Sea Surface Temperature (SST), and the polar stratosphere are well recognised. If there is indeed a link between the solar cycle and Arctic climate, it is possible that the 11-year solar cycle can be used to improve seasonal and decadal predictions of sea ice.  In the present study, we use a combination of observational and reanalysis datasets to uncover relationships between the sun’s variability and Arctic surface climate, via the modulation of NAM and downward propagation of anomaly from upper stratospheric winter polar vortex.

Our result suggests the latest rapid decline of sea ice around the Arctic in the recent winter decade/season could also have contributions from the current weaker solar cycle. The last 14 years are dominated by solar Min years and have only one Max. This is unlike other previous years, where the number of Max and Min years were evenly distributed (five each). The cumulative effect from the past 13 solar Min years could have played a role in the current record decline of the last winter, 2017. The current weaker solar cycle may also have contributions on increase in winter snow cover around the Eurasian sector.

Presenting schematics and flowcharts, we discussed mechanisms of how solar cycle variability influences Arctic climate. In the first route, perturbation in the upper stratospheric polar vortex is transported downwards and modulates the Arctic in a seasonal scale via the winter NAM. Another route was shown, which could involve upper stratospheric polar vortex, tropical lower stratosphere, Brewer-Dobson circulation and Ferrel cell. It could also reinforce the findings of the ‘Solar Max (Min) – cold (warm) Arctic’ scenario.

 

 

Snowing and Freezing in the Arctic

The image from IMS shows snow and ice on day 296 (yesterday) 2007 to 2017, with focus on Eurasia but also showing Canada and Alaska.  You can see that low Arctic ice years, like 2007, 2012 and 2016 have a smaller snow extent on both sides of the Arctic.  Conversely, higher Arctic ice years like 2013, 2014 and 2015 show snow spreading into northern Europe, as well as Alaska.  The pattern appears as gaining snow and ice 2008 to 10, losing 2011 and 2012, then regaining 2013 to 15, before retreating in 2016.  So far 2017 is looking more like 2013 to 15.

From Post Natural Climate Factors: Snow 

Previously I posted an explanation by Dr. Judah Cohen regarding a correlation between autumn Siberian snow cover and the following winter conditions, not only in the Arctic but extending across the Northern Hemisphere. More recently, in looking into Climate Model Upgraded: INMCM5, I noticed some of the scientists were also involved in confirming the importance of snow cover for climate forecasting. Since the poles function as the primary vents for global cooling, what happens in the Arctic in no way stays in the Arctic. This post explores data suggesting changes in snow cover drive some climate changes.

The Snow Cover Climate Factor

The diagram represents how Dr. judah Cohen pictures the Northern Hemisphere wintertime climate system.  He leads research regarding Arctic and NH weather patterns for AER.

cohen-schematic2

Dr. Cohen explains the mechanism in this diagram.

Conceptual model for how fall snow cover modifies winter circulation in both the stratosphere and the troposphere–The case for low snow cover on left; the case for extensive snow cover on right.

1. Snow cover increases rapidly in the fall across Siberia, when snow cover is above normal diabatic cooling helps to;
2. Strengthen the Siberian high and leads to below normal temperatures.
3. Snow forced diabatic cooling in proximity to high topography of Asia increases upward flux of energy in the troposphere, which is absorbed in the stratosphere.
4. Strong convergence of WAF (Wave Activity Flux) indicates higher geopotential heights.
5. A weakened polar vortex and warmer down from the stratosphere into the troposphere all the way to the surface.
6. Dynamic pathway culminates with strong negative phase of the Arctic Oscillation at the surface.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen.

Variations in Siberian snow cover October (day 304) 2004 to 2016. Eurasian snow charts from IMS.

Observations of the Snow Climate Factor

For several decades the IMS snow cover images have been digitized to produce a numerical database for NH snow cover, including area extents for Eurasia. The NOAA climate data record of Northern Hemisphere snow cover extent, Version 1, is archived and distributed by NCDC’s satellite Climate Data Record Program. The CDR is forward processed operationally every month, along with figures and tables made available at Rutgers University Global Snow Lab.

This first graph shows the snow extents of interest in Dr. Cohen’s paradigm. The Autumn snow area in Siberia is represented by the annual Eurasian averages of the months of October and November (ON). The following NH Winter is shown as the average snow area for December, January and February (DJF). Thus the year designates the December of that year plus the first two months of the next year.

Notes: NH snow cover minimum was 1981, trending upward since.  Siberian autumn snow cover was lowest in 1989, increasing since then.  Autumn Eurasian snow cover is about 1/3 of Winter NH snow area. Note also that fluctuations are sizable and correlated.

The second graph presents annual anomalies for the two series, each calculated as the deviation from the mean of its entire time series. Strikingly, the Eurasian Autumn flux is on the same scale as total NH flux, and closely aligned. While NH snow cover declined a few years prior to 2016, Eurasian snow is trending upward strongly.  If Dr. Cohen is correct, NH snowfall will follow. The linear trend is slightly positive, suggesting that fears of children never seeing snowfall have been exaggerated. The Eurasian trend line (not shown) is almost the same.

What About Winter 2017-2018?

These data confirm that Dr. Cohen and colleagues are onto something. Here are excerpts from his October 2 outlook for the upcoming season AER. (my bolds)

The main block/high pressure feature influencing Eurasian weather is currently centered over the Barents-Kara Seas and is predicted to first weaken and then strengthen over the next two weeks.

Blocking in the Barents-Kara Seas favors troughing/negative geopotential height anomalies and cool temperatures downstream over Eurasia but especially Central and East Asia. The forecast for the next two weeks across Central Asia is for continuation of overall below normal temperatures and new snowfall.

Currently the largest negative anomalies in sea ice extent are in the Chukchi and Beaufort Seas but that will change over the next month or so during the critical months of November-February. In my opinion low Arctic sea ice favors a more severe winter but not necessarily hemisphere-wide and depends on the regions of the strongest anomalies. Strong negative departures in the Barents-Kara Seas favors cold temperatures in Asia while strong negative departures near Greenland and/or the Beaufort Sea favor cold temperatures in eastern North America.

Siberian snow cover is advancing quickly relative to climatology and is on a pace similar to last year at this time. My, along with my colleagues and others, research has shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. The atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH. It is very early in the snow season but recent falls have been snowy across Siberia and therefore I do expect another upcoming snowy fall across Siberia.

Summary

In summary the three main predictors that I follow in the fall months most closely, the presence or absence of high latitude blocking, Arctic sea ice extent and Siberian snow cover extent all point towards a more severe winter across the continents of the NH.

Uh oh.  Now where did I put away my long johns?

Update: October 16 Snow and Ice

Yesterday at AER Dr. Judah Cohen provided his Arctic Oscillation and Polar Vortex Analysis and Forecasts biweekly report and outlook regarding the arctic oscillation and the coming winter in Northern Hemisphere. Excerpts with my bolds.

  • As is often the case, the current positive AO is associated with a relatively mild weather pattern across the NH continents including Europe and much of North America.
  • However over the next two weeks with the predicted overall negative trend in the AO a concomitant cooling trend is predicted across the NH continents including the British Isles and Western Europe but especially the Eastern United States (US).
  • Across East Asia troughing will allow a series of fronts to swing through the region keeping temperatures variable but overall close to seasonable.
  • Looking ahead to this upcoming winter, in my opinion both below normal Arctic sea ice and above normal Siberian snow cover so far this month favor more severe winter weather especially mid and late winter across the NH mid-latitudes. Though it is still early and there is much uncertainty in predictions of winter weather.

The flow across the NH is currently mostly zonal especially across North America and this is resulting in an overall mild weather pattern including Europe and the US. The exception to the zonal flow is a block over the Laptev Sea resulting in troughing/negative geopotential height anomalies over both Western and Eastern Asia and colder temperatures.

Expanding Eurasian snow cover and Arctic ice extent October 1 to 16, 2017. Watch the ice growing toward the Siberian snow. Also at the top note ice growing toward Canadian snow cover.

Siberian snow cover has advanced at a relatively rapid pace so far this fall, which has been the recent trend. However snow cover extent this October is so far lagging the pace of last October. My, along with my colleagues and others, research have shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. This atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH.

Strong negative departures in the Barents-Kara Seas favors cold temperatures in Asia while strong negative departures near Greenland and/or the Beaufort Sea favor cold temperatures in eastern North America. However sea ice is currently more extensive in the Barents-Kara-Laptev Seas than last year at this time and even more than two years ago. I believe that low sea ice in the Barents Kara sea the past two winters helped anchor blocking in the region that favored cold temperatures in Eurasia relative to North America. That same forcing may not be as strong for the upcoming winter.

I would conclude that the three factors that I consider favorable for severe winter weather increased atmospheric blocking in the fall, more extensive Siberian snow cover and low Arctic sea ice have become the norm more than the exception over the past decade. I do believe that the lack of variability in these three factors, likely reduces their utility in winter predictions.

From Post Natural Climate Factors: Snow 

Previously I posted an explanation by Dr. Judah Cohen regarding a correlation between autumn Siberian snow cover and the following winter conditions, not only in the Arctic but extending across the Northern Hemisphere. More recently, in looking into Climate Model Upgraded: INMCM5, I noticed some of the scientists were also involved in confirming the importance of snow cover for climate forecasting. Since the poles function as the primary vents for global cooling, what happens in the Arctic in no way stays in the Arctic. This post explores data suggesting changes in snow cover drive some climate changes.

The Snow Cover Climate Factor

The diagram represents how Dr. judah Cohen pictures the Northern Hemisphere wintertime climate system.  He leads research regarding Arctic and NH weather patterns for AER.

cohen-schematic2

Dr. Cohen explains the mechanism in this diagram.

Conceptual model for how fall snow cover modifies winter circulation in both the stratosphere and the troposphere–The case for low snow cover on left; the case for extensive snow cover on right.

1. Snow cover increases rapidly in the fall across Siberia, when snow cover is above normal diabatic cooling helps to;
2. Strengthen the Siberian high and leads to below normal temperatures.
3. Snow forced diabatic cooling in proximity to high topography of Asia increases upward flux of energy in the troposphere, which is absorbed in the stratosphere.
4. Strong convergence of WAF (Wave Activity Flux) indicates higher geopotential heights.
5. A weakened polar vortex and warmer down from the stratosphere into the troposphere all the way to the surface.
6. Dynamic pathway culminates with strong negative phase of the Arctic Oscillation at the surface.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen.

Variations in Siberian snow cover October (day 304) 2004 to 2016. Eurasian snow charts from IMS.

Observations of the Snow Climate Factor

The animation above shows from remote sensing that Eurasian snow cover fluctuates significantly from year to year, taking the end of October as a key indicator. Snowfall in 2016 was especially early and extensive, 2017 similar but slightly less at this point.

For several decades the IMS snow cover images have been digitized to produce a numerical database for NH snow cover, including area extents for Eurasia. The NOAA climate data record of Northern Hemisphere snow cover extent, Version 1, is archived and distributed by NCDC’s satellite Climate Data Record Program. The CDR is forward processed operationally every month, along with figures and tables made available at Rutgers University Global Snow Lab.

This first graph shows the snow extents of interest in Dr. Cohen’s paradigm. The Autumn snow area in Siberia is represented by the annual Eurasian averages of the months of October and November (ON). The following NH Winter is shown as the average snow area for December, January and February (DJF). Thus the year designates the December of that year plus the first two months of the next year.

Notes: NH snow cover minimum was 1981, trending upward since.  Siberian autumn snow cover was lowest in 1989, increasing since then.  Autumn Eurasian snow cover is about 1/3 of Winter NH snow area. Note also that fluctuations are sizable and correlated.

The second graph presents annual anomalies for the two series, each calculated as the deviation from the mean of its entire time series. Strikingly, the Eurasian Autumn flux is on the same scale as total NH flux, and closely aligned. While NH snow cover declined a few years prior to 2016, Eurasian snow is trending upward strongly.  If Dr. Cohen is correct, NH snowfall will follow. The linear trend is slightly positive, suggesting that fears of children never seeing snowfall have been exaggerated. The Eurasian trend line (not shown) is almost the same.

What About Winter 2017-2018?

These data confirm that Dr. Cohen and colleagues are onto something. Here are excerpts from his October 2 outlook for the upcoming season AER. (my bolds)

The main block/high pressure feature influencing Eurasian weather is currently centered over the Barents-Kara Seas and is predicted to first weaken and then strengthen over the next two weeks.

Blocking in the Barents-Kara Seas favors troughing/negative geopotential height anomalies and cool temperatures downstream over Eurasia but especially Central and East Asia. The forecast for the next two weeks across Central Asia is for continuation of overall below normal temperatures and new snowfall.

Currently the largest negative anomalies in sea ice extent are in the Chukchi and Beaufort Seas but that will change over the next month or so during the critical months of November-February. In my opinion low Arctic sea ice favors a more severe winter but not necessarily hemisphere-wide and depends on the regions of the strongest anomalies. Strong negative departures in the Barents-Kara Seas favors cold temperatures in Asia while strong negative departures near Greenland and/or the Beaufort Sea favor cold temperatures in eastern North America.

Siberian snow cover is advancing quickly relative to climatology and is on a pace similar to last year at this time. My, along with my colleagues and others, research has shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. The atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH. It is very early in the snow season but recent falls have been snowy across Siberia and therefore I do expect another upcoming snowy fall across Siberia.

Summary

In summary the three main predictors that I follow in the fall months most closely, the presence or absence of high latitude blocking, Arctic sea ice extent and Siberian snow cover extent all point towards a more severe winter across the continents of the NH.

Uh oh.  Now where did I put away my long johns?

Overview Winter Climate for NH

cohen-schematic2

The diagram represents how Dr. judah Cohen pictures the Northern Hemisphere wintertime climate system.  He leads research regarding Arctic and NH weather patterns for AER.  He explains the dynamics in an interview at Washington Post (here):

My colleagues, at AER and at selected universities, and I have found a robust relationship between two October Eurasian snow indices and the large-scale winter hemispheric circulation pattern known as the North Atlantic or Arctic Oscillation pattern (N/AO).

The N/AO is more highly correlated with or explains the highest variance of winter temperatures in eastern North America, Europe and East Asia than any other single or combination of atmospheric or coupled ocean-atmosphere patterns that we know of. Therefore, if we can predict the winter N/AO (whether it will be negative or positive) that provides the best chance for a successful winter temperature forecast in North America but certainly does not guarantee it.

[Of the two indices we’ve analyzed], the first and longer [more data points] index is simply the monthly mean snow cover extent (SCE) for the entire month [of October] as measured from satellites. This record dates back to at least 1972 and is available on the Rutger’s Global Snow Lab website.

The second index that we developed last year, with the support of NSF and NOAA grants, measures the daily rate of change of Eurasian snow cover extent also during the entire month of October, which we refer to as the Snow Advance Index or SAI.

There have been recent modeling studies that demonstrate that El Nino modulates the strength and position of the Aleutian Low that then favors stratospheric warmings and subsequently a negative winter N/AO that are consistent with our own research on the relationship between snow cover and stratospheric warmings. So the influence of ENSO on winter temperatures in the Mid-Atlantic and the Northeast may be greater than I acknowledge or that is represented in our seasonal forecast model.

How It Works

Conceptual model for how fall snow cover modifies winter circulation in both the stratosphere and the troposphere–The case for low snow cover on left; the case for extensive snow cover on right.

1. Snow cover increases rapidly in the fall across Siberia, when snow cover is above normal diabatic cooling helps to;
2. Strengthen the Siberian high and leads to below normal temperatures.
3. Snow forced diabatic cooling in proximity to high topography of Asia increases upward flux of energy in the troposphere, which is absorbed in the stratosphere.
4. Strong convergence of WAF (Wave Activity Flux) indicates higher geopotential heights.
5. A weakened polar vortex and warmer down from the stratosphere into the troposphere all the way to the surface.
6. Dynamic pathway culminates with strong negative phase of the Arctic Oscillation at the surface.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen

Extensive 2016 Siberian snowfall led to unusually rapid recovery of Arctic sea ice following relatively low September 2016 minimum.

What About Winter 2017-2018?

Dr. Cohen’s Winter Outlook for NH  September 18, 2017

Many important markers are currently being set indicating the atmosphere is beginning in earnest the transition from summer to winter. There are four features that I am monitoring closely over the coming weeks and months to gauge the evolving atmospheric circulation pattern and resultant weather across the NH.

The first is the nascent stratospheric polar vortex (PV). The PV has returned to the NH polar stratosphere. Much recent research including my own has shown that the relative strength of the PV if not forces, certainly leads prolonged periods of temperature anomalies across key regions of the NH. A strong PV is related to relatively milder temperatures across the mid-latitudes of the NH while a weak PV is related to relatively colder temperatures across the mid-latitudes of the NH. This relationship is strongest in mid-winter. Early signs are that the PV will start off relatively weak similar to last fall. This is somewhat surprising because increasing greenhouse gases favor colder stratospheric temperatures and hence a stronger PV. Poleward heat flux or vertical wave activity flux is predicted to be unusually active in the coming two weeks, which is likely the reason for the predicted relatively weak start to the PV.  (my bolds)

The active poleward heat flux is also likely related to the second feature that I will be following – high latitude blocking. The negative AO state is often a manifestation of strong high latitude blocking while the positive AO often reflects a lack of high latitude blocking. The predicted negative AO in the coming two weeks is a result of predicted strong high latitude blocking with the dominant block predicted to reside in the region of Scandinavia and the Barents-Kara seas. In the near term this will lead to a cold and snowy period across most of Siberia. Blocking in this region is favorable for weakening the stratospheric polar vortex and will likely lead to weakening of the PV over the next two weeks. If similar blocking occurs later on during the late fall and early winter it will favor a sudden stratospheric warming (SSW). SSW in the winter often precedes extended periods of severe winter weather across the continents of the NH. (my bolds)

The third feature is Arctic sea ice extent. The minimum in Arctic sea ice extent is achieved this time of year and if the minimum has not already been reached it should occur relatively soon. The past two blogs I suggested the possibility that the sea ice minimum could be similar to the years 2008 and 2010 and that is looking likely. Sea ice extent is extremely low compared to climatology but will not be a new record low. The largest anomalies are in the North Pacific side of the Arctic in the Beaufort Sea. This pattern matches recent Septembers. Typically, the largest anomalies migrate with the progression of fall to the North Atlantic side of the Arctic. It is my opinion that low sea ice favors high latitude blocking but the nature of the blocking is regionally dependent. For example, low sea ice in the Barents-Kara Seas favors blocking in the northwest Eurasia sector resulting in cold temperatures in parts of Asia. (my bolds)

The fourth feature is Siberian snow cover. My, along with my colleagues and others, research has shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. The atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH. With a predicted strong negative AO in the coming weeks, snow cover is likely to advance relatively quickly heading into October. It is very early in the snow season but recent falls have been snowy across Siberia and therefore I do expect another upcoming snowy fall across Siberia. Though admittedly, recent Siberian snow cover as a predictor of winter temperatures has been mixed.

Summary

Uh oh.  Now where did I put away my long johns?

Man Made Warming from Adjusting Data

trends and strings

Roger Andrews does a thorough job analyzing the effects of adjustments upon Surface Air Temperature (SAT) datasets. His article at Energy Matters is Adjusting Measurements to Match the Models – Part 1: Surface Air Temperatures. Excerpts of text and some images are below.  The whole essay is informative and supports his conclusion:

In previous posts and comments I had said that adjustments had added only about 0.2°C of spurious warming to the global SAT record over the last 100 years or so – not enough to make much difference. But after further review it now appears that they may have added as much as 0.4°C.

For example, these graphs show warming of the GISS dataset:

Figure 2: Comparison of “Old” and “Current” GISS meteorological station surface air temperature series, annual anomalies relative to 1950-1990 means

The current GISS series shows about 0.3°C more global warming than the old version, with about 0.2°C more warming in the Northern Hemisphere and about 0.5°C more in the Southern. The added warming trends are almost exactly linear except for the downturns after 2000, which I suspect (although can’t confirm) are a result of attempts to track the global warming “pause”. How did GISS generate all this extra straight-line warming? It did it by replacing the old unadjusted records with “homogeneity-adjusted” versions.

The homogenization operators used by others have had similar impacts, with Berkeley Earth Surface Temperature (BEST) being a case in point. Figure 3, which compares warming gradients measured at 86 South American stations before and after BEST’s homogeneity adjustments (from Reference 1) visually illustrates what a warming-biased operator does at larger scales. Before homogenization 58 of the 86 stations showed overall warming, 28 showed overall cooling and the average warming trend for all stations was 0.54°C/century. After homogenization all 86 stations show warming and the average warming trend increases to 1.09°C/century:

Figure 3: Warming vs. cooling at 86 South American stations before and after BEST homogeneity adjustments

The adjusted “current” GISS series match the global and Northern Hemisphere model trend line gradients almost exactly but overstate warming relative to the models in the Southern (although this has only a minor impact on the global mean because the Southern Hemisphere has a lot less land and therefore contributes less to the global mean than does the Northern). But the unadjusted “old” GISS series, which I independently verified with my own from-scratch reconstructions, consistently show much less warming than the models, confirming that the generally good model/observation match is entirely a result of the homogeneity adjustments applied to the raw SAT records.

Summary

In this post I have chosen to combine a large number of individual examples of “data being adjusted to match it to the theory” into one single example that blankets all of the surface air temperature records. The results indicate that warming-biased homogeneity adjustments have resulted in current published series overestimating the amount by which surface air temperatures over land have warmed since 1900 by about 0.4°C (Table 1), and that global surface air temperatures have increased by only about 0.7°C over this period, not by the ~1.1°C shown by the published SAT series.

Land, however, makes up only about 30% of the Earth’s surface. The subject of the next post will be sea surface temperatures in the oceans, which cover the remaining 70%. In it I will document more examples of measurement manipulation malfeasance, but with a twist. Stay tuned.

Footnote:

I have also looked into this issue by analyzing a set of US stations considered to have the highest CRN rating.  The impact of adjustments was similarly evident and in the direction of warming the trends.  See Temperature Data Review Project: My Submission