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  1. The Kauppinen & Malmi 2019 paper (KM2019) [LINK] with the provocative title “NO EXPERIMENTAL EVIDENCE FOR THE SIGNIFICANT ANTHROPOGENIC CLIMATE CHANGE” (SIC), uses recently published satellite data for low cloud cover (Figure 1) along with HadCRUT4 global surface temperature data to display a visual correlation between temperature and low cloud cover (Figure 6).  Obvious departures from the correlation are  explained in terms of the 1991 Mt Pinatubo eruption (temperature too low) and the strong 1998 El Nino (temperature too high) and concludes that declining low cloud cover, and not rising atmospheric CO2 concentration, explains global warming.
  2. Based on the charts of overlaid temperature and low cloud cover data shown in Figure 6 (See Figure 2 and Figure 3 in the source document [LINK] ), the authors claim that the observed warming trend in surface temperature is explained by declining low cloud cover and not by rising atmospheric CO2. The rationale for the low cloud effect is that clouds reflect incoming solar radiation and that therefore rising cloud cover causes cooling and declining cloud cover causes warming. The decline in low cloud cover in the study period 1983 to 2008 is well established in the ISSCP datasets [LINK] and is displayed above in Figure 1. A relationship between low cloud cover over and temperature over the tropics is presented in the Climate4You blog [SOURCE] and is displayed in Figure 3 above. It shows rising temperature in the tropics coincident with declining low cloud cover and appears to be consistent with the KM2019 finding that the declining low cloud cover (LCC) causes warming globally and not just in the tropics. The causation rationale is that clouds reflect incoming solar radiation and thus lower surface temperature.
  3. It is noted however, that correlation between time series source data do not always imply causation and that when they do, no information about the direction of the causation can be inferred from these data. For example, in {McCoy, Daniel T., et al. “The change in low cloud cover in a warmed climate inferred from AIRS, MODIS, and ERA-Interim.” Journal of Climate 30.10 (2017): 3609-3620} the authors find that warming surface temperatures have caused a decline in low cloud cover over sub-tropical regions in the same period of study as the KM2019 paper. The reverse causation is suggested in the Somerville 1985 paper in which he finds that CO2 induced global warming is self correcting because warming increases cloud formation and clouds reflect sunlight back into space. {Richard Somerville, Scripps Institute of Oceanography, UC San Diego}. 
  4. An added complication is that in the instrumental record, global warming is found mostly in nighttime daily TMIN and not in daytime daily TMAX  {Related posts [LINK] [LINK] }. G. Kukla, PD Jones, and others (Kukla 1993) describe this apparent anomaly in terms of low cloud cover that reflects solar radiation upward and the earth’s long wave radiation downward. At night, with no solar radiation to reflect upward, the net effect of low clouds is warming by reflecting terrestrial radiation downward. The relationship between low cloud cover and warming is therefore more complicated than the reflection of solar radiation upward.
  5. The significant claim of the KM2019 paper relating to AGW is that since the observed warming in surface temperature can be explained in terms of declining low cloud cover, no meaningful role for atmospheric CO2 concentration is possible and that therefore, the correlation between low cloud cover and surface temperature proves the falsehood of AGW theory. In this post, we test this KM2019 hypothesis that by comparing the relationship between atmospheric CO2 and global mean surface temperature below low clouds (HadCRUT4 surface temperature) with the corresponding relationship between atmospheric CO2 and global mean temperatures in the lower troposphere above low clouds (UAH). The study period is constrained to 1979-2018 by the availability of UAH satellite data for lower troposphere temperatures.
  6. The results are displayed in Figure 4 and Figure 5 above. Figure 4 displays the rate of warming in the study period for each calendar month labeled 1=January to 12=December along with the strength of the regression in terms of the T-statistic for both the surface temperature below low clouds (HAD) and the lower troposphere temperature (UAH) above low clouds. The warming rate is seen to be much stronger under low clouds than above low clouds. This result is consistent with the low cloud effect assumed in the KM2019 paper.
  7. The further conclusion in KM2019  that the observed warming during a time of decreasing low cloud cover proves the CO2 effect in AGW to be false is tested in Figure 5. If this KM2019 finding is correct, we would expect to find that temperatures below low clouds (HAD) would be relatively unrelated to atmospheric CO2 concentration but that temperatures above low clouds (UAH) would show a stronger correlation. What we see in Figure 5, however, is the exact opposite. Correlation of surface temperature below low clouds have a stronger correlation with Ln(CO2) {the natural logarithm of atmospheric CO2 concentration} than do lower troposphere temperatures above low clouds. In case of detrended correlations, though all values are generally very low, values above DETCORR=0.2 are statistically significant and are found only in the HAD surface temperatures below low clouds. These data are inconsistent with the KM2019 finding that the warming trend during a time of declining low cloud cover proves CO2 forcing of surface temperature to be false.
  8. An additional consideration is that cloud albedo is not just in low clouds but also from high clouds that have the greater cooling effect along with stratospheric aerosols. No declining trend in high clouds is evident in the data (Figure 2) that appear to show only cyclical variations. In light of these considerations, the emphasis on low clouds in the KM2019 analysis appears to be a form of data selection bias.
  9. CONCLUSION: The data show that the relationship between measures of AGW and low cloud cover is more complicated than implied by the KM2019  paper and that the correlation of warming above and below low clouds with atmospheric CO2 concentration are inconsistent with the interpretation of the data in the KM2019 study. As a reference, the cloud page in the climate4You blog [LINK] may contain more useful information on the interpretation of ISSCP cloud cover data than the relatively simplistic analysis contained in KM2019. Atmospheric water vapor content, low clouds, high clouds, and their combined surface temperature effects are more complicated and these effects vary regionally.


CNN: November, 2019: It’s all quite devastating! 

Documenting the rapid loss of Arctic sea ice


  1. The Arctic is heating twice as fast as the global average. Sea ice is rapidly shrinking, changing the delicate composition of one of the world’s most pristine ecosystems and the traditional way of life that indigenous communities have preserved for hundreds of years. What happens in the Arctic has far-reaching consequences, altering global weather patterns and endangering coastal communities, but for many people these problems are out of sight and out of mind.
  2. For those who explore the planet’s northernmost reaches, these problems have become a harsh reality. CNN spoke to three photographers and filmmakers who have made it their mission to document an evolving Arctic landscape — for the sake of raising awareness, for the sake of highlighting the individuals fighting to save it, and for the sake of posterity.
  3. Faces on the frontlines of climate science: Esther Horvath is currently drifting through Arctic sea ice aboard German research icebreaker the RV Polarstern as part of what has been billed as the largest polar expedition ever undertaken by humankind. As a photographer and the communications manager of the MOSAiC expedition, a €140 million scientific mission comprising 19 nations, the Hungarian sailed into the Arctic Ocean to document the unknown faces on the frontlines of climate science.
  4. “Who are the scientists? They deliver this crucial information for all of us,” she says. “This is what I’m extremely interested in; to show climate change stories through the eyes of scientists, showing how they live in such an extreme, remote location.”
    Captain Stefan Schwarze and Lutz Peine First officer on the bridge of Polarstern on October 2, 2019. Photographer Esther Horvath is onboard the Polarstern as part of the year-long MOSAiC expedition.
  5. Over the course of the next year, the Polarstern and Horvarth will drift, locked in sea ice, from north of the Siberian coast, through the central Arctic then southwards. Six hundred experts on rotation across six legs are conducting experiments, taking measurements from deep beneath the ice to high up into the atmosphere to assess how the Arctic is changing, and how that impacts the Earth’s climate. “With this expedition, scientists will be able to create much better models, which may be extremely important for politicians and decision makers,
  6. Horvath followed the years of preparations which led to the MOSAiC expedition finally departing in September 2019. As well as documenting the crew, from biogeochemists to balloon operators, she is also photographing nature in all its majesty, including polar bears taking an interest in the expedition. “If I can make this human connection between the audience and the scientists who live and work in this remote location, I hope that I can raise more awareness,” she adds.
  7. Capturing nature’s last stand: Martin Hartley recounts a climate horror story from February 2018, when an area of sea ice pulled away from the floating ice pack off the northern coast of Greenland. It was winter and should have been a stable time of year for sea ice, but images showed it drifting back towards the North Pole, exposing mile upon mile of Arctic Ocean below. “That’s never happened before,” he says, concern in his voice.
  8. Hartley says the melting ice is also making the North Pole a harder place to explore on foot. Historically, surface expeditions could depart from land in certain places within the Arctic Circle and walk on to sea ice to journey to the pole. Now, Hartley says, ships are being used to venture further and further into the Arctic Ocean in search of stable ice on which to disembark. Expeditions carry thick waterproof immersion suits should they fall through the ice, or if they are forced to swim between ice floes. Reaching the North Pole is becoming harder on foot, says Hartley (the last successful expedition from land was in 2014).
  9. “Water rules out most North Pole expeditions — 99.9% of them, anyway,” Hartley says. The last people to successfully trek from land to the North Pole were Americans Ryan Waters and Eric Larsen in 2014. Hartley has traveled to the Arctic Ocean since 2002. Now he’s preparing to return in 2020 for his most ambitious expedition yet. With the help of NASA, the US National Oceanic and Atmospheric Administration and the European Space Agency, Hartley will be searching north of Greenland for the last multi-year ice, a rapidly shrinking percentage of Arctic ice that survives the summer. Multi-year sea ice is more resistant to melting and better at insulating the cold atmosphere from the warmer ocean water.
  10. Hartley is to photograph what he calls “ice sentinels,” where multi-year sea ice has been pushed up into hulking monoliths. “It’s magnificent and peaceful and you cannot help but be affected by this ice,” Hartley says, “(it’s) like something out of a fairy tale.” Hartley will travel with guides and scientists to take ice samples and leave satellite trackers on ice sentinels to chart them drifting and melting away.
    “There’s a lot of risk involved,” he says. “But the risk of not at least trying, to me, is almost a moral sin.”
  11. The social and geopolitical implications of ice loss is Maya Craig’s line of inquiry. An American photographer and filmmaker, Craig is embarking on a documentary feature about a changing Arctic across multiple countries. “Receding sea ice is impacting countless communities across the Arctic, and stakes are high as nations vie for control of newly accessible shipping routes and resources,” she explains. “I’m honing a grouping of stories that weave a portrait of the changing Arctic as diminishing sea ice gives way to newly open ocean.”
  12. In the summer of 2019, Craig traveled to the Native Village of Savoonga on St Lawrence Island, part of Alaska in the Bering Strait, to interview its president Delbert Pungowiyi, who is a vocal advocate for the island’s Yupik people. “Historically the Bering Sea around St Lawrence Island was frozen 9-10 months each year, while today it freezes for just a few months,” she explains. “The villages subsisted primarily by ice hunting whale and walrus, which is increasingly less viable and putting their entire way of life in peril.
  13. Craig also spent time on the Healy, a US Coast Guard (USCG) vessel and the only US icebreaker operating in the Arctic, documenting the life of the coast guards and scientists on board. “Ice breakers are essentially the infrastructure of the Arctic,” she explains, comparing them to roads and bridges. “Even as the sea ice recedes more, ice breakers are required for consistent operation and can make year-long operation viable.” Russia has built 14 new icebreakers since 2013 according to a USCG report, and there are plans to increase shipping traffic through Russia’s Arctic coast tenfold by 2024.
  14. How nations will fare in the race for resource exploration and extraction, cargo transportation and tourism in the Arctic is a major outstanding question for the 21st century. And even while summer sea ice remains, it cannot be ignored. “It’s all quite devastating,” she adds. “The fact that by mid-century it’s expected that in summer months there will be no ice at all in the Arctic Ocean — this is a huge, historic milestone



  1. CLAIM: “Sea ice is rapidly shrinking, changing the delicate composition of one of the world’s most pristine ecosystems and the traditional way of life that indigenous communities have preserved for hundreds of years“.  COMMENT: The sea ice extent in the Arctic undergoes a seasonal cycle with a very large range that varies from 50 to more than 100 years of year to year changes [LINK] . The issue here is the relatively very small seasonal minimum sea ice extent in September that sustains an apocalyptic fear that AGW climate change will reduce the September minimum sea ice extent to zero to deliver an ice free Arctic in that month that is thought to be able to accelerate the rate of warming by way of an albedo loss feedback mechanism. The so called “Ice Free Arctic” fear has been invoked repeatedly since 1999 with failed forecasts of an ice free Arctic in September listed in a related post [LINK] .  The evidence presented that relates year to year changes in September minimum sea ice extent to AGW climate change is that they are consistent with climate model predictions. However, a very different evaluation is implied by the observational data that show no evidence that year to year changes in September minimum sea ice extent is related to AGW [LINK] [LINK] .
  2. CLAIM: Scientists sailed into the Arctic Ocean to document the unknown faces on the front lines of climate science. COMMENT: There is more truth in this sentence than was probably intended by the authors. From the very inception of the modern version of AGW climate change since Hansen 1988 (as distinct from the original theory of Callendar 1938), climate science has steadfastly held that all observed sea ice melt events in the Arctic are caused by changes to atmospheric composition due to fossil fuel emissions and that they can and must be attenuated by reducing and eventually eliminating the use of fossil fuels. Though these relationships are seen in climate models, the data have not cooperated and so since the 1990s, repeated and alarming forecasts of an ice free Arctic in September, of catastrophic methane release, of runaway feedback warming due to albedo loss, and of catastrophic losses in the mass balance of the Greenland Ice sheet  have failed to materialize. So dismal has been the performance of climate science in this arena, that climate scientists have developed a language of making predictions without making a commitment to the prediction as in the sentence “I am not saying that there will be a catastrophic methane release in the Arctic any time soon but only that there is a possibility of such catastrophic event and it could initiate a cataclysmic runaway global warming (Dr. Peter Wadhams) [LINK] . In terms of predictions and evaluations of events in the Arctic, climate science, though armed with sophisticated climate models, have performed very poorly and this poor  performance of climate science in the Arctic is succinctly stated in the source document above when the Arctic is described as “the unknown faces on the front lines of climate science“. In other words, the Arctic is where the we-know-it-all climate science ends and the mystery begins. 
  3. CLAIM: Climate scientists are taking measurements from deep beneath the ice to high up into the atmosphere to assess how the Arctic is changing, and how that impacts the Earth’s climate. With this expedition, scientists will be able to create much better models, which may be extremely important for politicians and decision makersCOMMENT: This claim accurately describes and thereby exposes a fatal flaw in climate science research. In climate science the research question is not constructed for objective scientific inquiry such that the absence of the effect being tested for as the null hypothesis; but rather the suspected effect is itself the null hypothesis that portends catastrophic consequences and it remains for climate science researchers only to determine just how bad its going to be. Here for example, the research question is not whether the Arctic is changing and whether the changes can be attributed to AGW climate change and not whether the findings will have policy implications for politicians and decision makers; but HOW the Arctic is changing and HOW that impacts Earth’s climate and HOW important these results are for politicians and decision makers. In other words, assume the worst and frame research questions and design the research agenda to just how bad things are and how catastrophic the climate impacts that are expected to create an overwhelming motivation for politicians and decision makers to take climate action.
  4. CLAIM: A climate horror happened in February 2018, when an area of sea ice pulled away from the floating ice pack off the northern coast of Greenland. It was winter and should have been a stable time of year for sea ice, but images showed it drifting back towards the North Pole, exposing mile upon mile of Arctic Ocean below. “That’s never happened before“.  COMMENT:  This claim exposes the extreme atmosphere bias of climate science. More evidence is exposed here that climate science research is not unbiased scientific inquiry but contains a heavy bias for the finding that all bad things are climate impacts and an overriding bias that all ice melt events are driven by AGW climate change by way of surface warming caused by rising atmospheric CO2 concentration. Ultimately all observed changes are found to be catastrophic and interpreted as an impact of fossil fuel emissions – thus leading to the required conclusion that the changes observed can and must be attenuated with climate action in the form off emission reduction.
  5. CLAIM: Melting sea ice is making the North Pole a harder place to explore on foot. Historically, surface expeditions could depart from land in certain places within the Arctic Circle and walk on to sea ice to journey to the pole. Now, ships are being used to venture further and further into the Arctic Ocean in search of stable ice on which to disembark. Expeditions carry thick waterproof immersion suits should they fall through the ice, or if they are forced to swim between ice floes.  COMMENT: As in CLAIM#4 above, the atmosphere bias and the prior null hypothesis that all ice melt events in the Arctic are ultimately caused by fossil fuel emissions and that they can therefore be controlled or moderated by emission reduction form the overriding context in which all observed changes are interpreted. In the context of the ice melt alarms raised in claims #4 and #5 it is noted that the absolute atmosphere bias of climate science makes it impossible for them to consider other sources of heat that could melt sea ice. In related posts it has been shown that the Arctic is a very geologically active region of the planet not unlike the Ring of Fire in the Pacific [LINK] [LINK] [LINK] [LINK] and that the observed changes in September minimum sea ice extent cannot be related to AGW temperature rise because the required correlation is not found in the data [LINK] . The specific claim that even winter sea ice (in February) is melting due to CO2 forcing of surface temperature exposes an extreme form of bias and circular reasoning in climate science such that even at a time of year when the Arctic does not see the sun, sea ice melt events are attributed to an enhancement of solar radiation heating due to a carbon dioxide concentration of the atmosphere attributed to fossil fuel emissions. The atmosphere bias in climate science is so strong that it makes it impossible to consider the impact of geothermal heat even when CO2 forcing is not possible.
  6. CLAIM: Russia has built 14 new icebreakers since 2013 according to a USCG report, and there are plans to increase shipping traffic through Russia’s Arctic coast tenfold by 2024. How nations will fare in the race for resource exploration and extraction, cargo transportation and tourism in the Arctic is a major outstanding question for the 21st century. And even while summer sea ice remains, it cannot be ignored. COMMENT:  Climate science has presented no scientific argument that relates Arctic ship traffic to AGW such that ship traffic in the Arctic should be considered an undesirable AGW variable. Yet, the science of climate science appears to be opposed to the idea of growing ship traffic in the region whether by way of technological ship innovations or by way of ice melt. This oddity is just one of many that appears to use AGW climate change as the science that backs up old environmental activism now rationalized in terms of AGW. This relationship is consistent with the view that AGW climate science serves to rationalize and revitalize radical environmentalism of all colors in search of a reason why.
  7. CLAIM: By mid-century it’s expected that in summer months there will be no ice at all in the Arctic Ocean — this is a huge, historic milestone. COMMENT: A black mark in the science of AGW climate change is its obsession with the ice free Arctic idea and its long history of failed ice free Arctic predictions described in a related post [LINK] . The forecast of an ice free Arctic in September of “mid century” is likely derived from a published paper that makes a forecast of an ice free summer in the Arctic at sometime between 2044 and 2067. In the related post cited above it is shown that the seasonal cycle was used as the model of ice melt in the forecast and that significant differences between the seasonal cycle and year to year changes make the comparison impossible [LINK]The mid-century ice free Arctic forecast follows a long list of failed ice free Arctic forecast fear mongering activism including the high profile “the Arctic is screaming” alarm of 2007. Not much credibility remains for climate science in this area of what is still being presented as science.







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  1. THE SOURCE STUDY BY GROTHE & COBB of the Georgia Institute of Technology’s School of Earth and Atmospheric Sciences: Grothe, Pamela R., et al. “Enhanced El Niño‐Southern Oscillation variability in recent decades.” Geophysical Research Letters, 2019}  Abstract: The El Niño‐Southern Oscillation (ENSO) represents the largest source of year‐to‐year global climate variability. While earth system models suggest a range of possible shifts in ENSO properties under continued greenhouse gas forcing, many centuries of pre-industrial climate data are required to detect a potential shift in the properties of recent ENSO extremes. Here, we reconstruct the strength of ENSO variations over the last 7,000 years with a new ensemble of fossil coral oxygen isotope records from the Line Islands, located in the central equatorial Pacific. The corals document a significant decrease in ENSO variance of ~20% from 3,000 to 5,000 years ago, coinciding with changes in spring/fall precessional insolation. We find that ENSO variability over the last five decades is ~25% stronger than during the preindustrial. Our results provide empirical support for recent climate model projections showing an intensification of ENSO extremes under greenhouse forcing. 
  2. The authors have kindly provided a translation of their scientific language into plain English as follows: Our climate models tell us that El Niño will intensify due to greenhouse warming. Here, new coral reconstructions of the El Niño‐Southern Oscillation (ENSO) record show sustained, significant changes in ENSO variability over the last 7,000yrs, and at the same time we have found ENSO extremes over the last 50 years that are stronger than ENSO cycles of pre-industrial times.These results tell us that El Niño events are intensifying due to anthropogenic climate change. Key Point: (1) Data from Line Island corals show ENSO strength significantly weaker between 3,000 and 5,000 years ago compared to the 2,000‐year ago. (2) ENSO extremes of the last 50 years are significantly stronger than those of the pre‐industrial era in the central tropical Pacific. (3) Therefore, AGW climate change is causing ENSO cycles to become more extreme.
  3. A further translation into plain language has been kindly provided by Sci-Tech-Daily online magazine [LINK] as follows: Compelling Hard Evidence: El Nino Swings More Violently in the Industrial Age: El Ninos have become more intense in the industrial age, which stands to worsen storms, drought, and coral bleaching in El Nino years. A new study has found compelling evidence in the Pacific Ocean that the stronger El Ninos are part of a climate pattern that is new and strange.It is the first known time that enough physical evidence spanning millennia has come together to allow researchers to say definitively that: El Ninos, La Ninas, and the climate phenomenon that drives them have become more extreme in the times of human-induced climate change. The industrial age ENSO swings are 25% stronger than in the pre-industrial records. The evidence had slumbered in and around shallow Pacific waters, where ENSO and El Ninos originate. The corals’ recordings of sea surface temperatures proved to be astonishingly accurate when bench-marked. Coral records from 1981 to 2015 matched sea surface temperatures measured via satellite in the same period exactly. In 2018, enough coral data had amassed to distinguish ENSO’s recent activity from its natural pre-industrial patterns. To stress-test the data, Grothe left out chunks to see if the industrial age ENSO signal still stuck out. She removed the record-setting 1997/1998 El Nino-La Nina and examined industrial age windows of time between 30 and 100 years long. The signal held in all windows, but the data needed the 97/98 event to be statistically significant. This could mean that changes in the ENSO activities have just now reached a threshold that makes the impact of the industrial economy detectable.




  1. The ENSO data in the form of the Oceanic Nino Index (ONI) published by Jan Null [LINK]  is displayed in Figure 1. As of this writing, the data cover a 70-year time period from 1950 to 2019 and present the ONI data for a moving 3-month window. The period since 1950 {“mid century”} is claimed by NASA and also by climate scientists in general  to be one in which the theory of AGW in terms of CO2 forcing of surface temperature is most apparent [LINK] . Therefore, if there is an impact of AGW CO2 forcing of surface temperature on ENSO strength, it should be apparent in an analysis of the relevant trends and correlations with respect to the ONI (Oceanic Nino Index) and temperature.
  2. Trends in the 3-month running average of the Oceanic Nino Index are displayed graphically in Figure 2. The top frame of Figure 2 is a GIF animation that cycles through the ten 3-month moving average values of the ONI from June-July-Aug to April-May-June of the following year. The study period in these charts is 1950-2019. The red line through the data in these charts is a 3rd order polynomial regression line that should show the trends as well as changes if any in the trend midstream. These lines appear to be rather flat without any kind of trend information being apparent in the graphical representation.
  3. The bottom frame of Figure 2 presents the results of linear regression trend analysis of the ONI against time from 1950 to 2019. No evidence of a trend in the ONI is found in the data. This finding is inconsistent with the proposition that AGW climate change has caused an increase in El Nino strength. The mechanism of this change is assumed to be rising sea surface temperatures (SST) attributed to CO2 forcing of AGW climate change. A more direct analysis of this relationship is presented with correlation analysis presented in Figure 3, Figure 4, and Figure 5.
  4. The top frame of Figure 3 is a GIF animation that cycles through the six regions studied (global, northern hemisphere, southern hemisphere, northern extent, southern extent, and tropics. The graphic shows that the temperature above oceans in the tropics shows the strongest correlations. The somewhat weaker correlations found for the two hemispheres vanish when the tropical portion of the hemisphere is removed to define the northern and southern extents. The ordinate contains the ten three-month periods for which the mean ONI and temperature data are used in the correlation analysis. They are 1=June-July-August to 10=March-April-May.  The highest correlations are seen for the winter months along with late fall and early spring.
  5. Thus, we find that detrended correlation analysis shows a strong correlation between UAH lower troposphere temperature above ocean areas and ONI. The correlation supports a relationship between temperature and ONI. This correlation is strongest for temperatures above the tropics (TR). Statistically significant correlations are also seen for temperatures for the Northern and Southern Hemispheres (NH & SH) but these correlations disappear when the Tropical section of the hemisphere is removed in the hemispheric region being studied (NX & SX).
  6. These results suggest that there is a temperature phenomenon in the tropics that causes rising and falling ONI levels even in the absence of a trend. A rational explanation for this relationship is found in the geology of the tropical region near the Solomon Islands and Papua New Guinea as shown in Figure 6. A detailed description of this localized geological source of the energy that drives the ENSO variability is described in a related post [LINK] .
  7. We conclude from the results of the trend analysis and detrended correlation analysis presented above that the data do not support the hypothesis that AGW temperature trends since 1950 have caused ENSO intensity to increase. If that were so there would be a trend and that trend would show a strong correlation with temperature that is not restricted to the tropics. The Temperature trend above the tropics attributed to AGW for the ten 3-month means in the Jan Null analysis presented in Figure 7 below do not show an AGW forcing behavior. More importantly, the ONI does not show a rising trend. The data are consistent with the evaluation in a related post that ENSO variability is driven by geological forces rather than by atmospheric composition. 






  1. Yeh, Sang-Wook, et al. “El Niño in a changing climate.” Nature 461.7263 (2009): 511.  El Niño events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Niño events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies1,2,3,4,5 show that the canonical El Niño has become less frequent and that a different kind of El Niño has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Niño, termed the central Pacific El Niño (CP-El Niño; also termed the dateline El Niño2, El Niño Modoki3 or warm pool El Niño5), differs from the canonical eastern Pacific El Niño (EP-El Niño) in both the location of maximum SST anomalies and tropical–midlatitude teleconnections. Here we show changes in the ratio of CP-El Niño to EP-El Niño under projected global warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set6. Using calculations based on historical El Niño indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Niño compared to the EP-El Niño. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Niño to EP-El Niño, the occurrence ratio of CP-El Niño/EP-El Niño is projected to increase as much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.
  2. Timmermann, Axel, et al. “El Niño–southern oscillation complexity.” Nature 559.7715 (2018): 535-545.  El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño–Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.
  3. Grothe, Pamela R., et al. “Enhanced El Niño‐Southern Oscillation variability in recent decades.” Geophysical Research Letters (2019).  The El Niño‐Southern Oscillation (ENSO) represents the largest source of year‐to‐year global climate variability. While earth system models suggest a range of possible shifts in ENSO properties under continued greenhouse gas forcing, many centuries of preindustrial climate data are required to detect a potential shift in the properties of recent ENSO extremes. Here, we reconstruct the strength of ENSO variations over the last 7,000 years with a new ensemble of fossil coral oxygen isotope records from the Line Islands, located in the central equatorial Pacific. The corals document a significant decrease in ENSO variance of ~20% from 3,000 to 5,000 years ago, coinciding with changes in spring/fall precessional insolation. We find that ENSO variability over the last five decades is ~25% stronger than during the preindustrial. Our results provide empirical support for recent climate model projections showing an intensification of ENSO extremes under greenhouse forcing.





Figure 1 above is a map of the Arctic Ocean as seen from a point in space directly above the North Pole. From the North Pole, all directions are South. The Chuckhi Sea appears at the top of the map directly North of Beringia where Siberia meets Alaska. The Chukchi Sea is wedged in between Alaska and the Chukchi Peninsula of Siberia and extends as far North as Wrangel island. A close up of the Chukchi Sea area in a normal map where North is up and South is down is shown the two maps in Figure 2 below.











CLIMATE CHANGE: Some Arctic Sea Ice Is Acting Like It’s Mid-Summer

  1. Winter has extended its grip on the Arctic, dropping a curtain of darkness on the top of the world. But at least one part of the Arctic is resisting its grasp. In what’s becoming an unfortunately common story, seasonal sea ice growth is stalling out in one of the gateway seas leading to the heart of the Arctic Ocean. The Chukchi Sea currently has a sea ice extent more reminiscent of summer than early winter, a sign that something is not right in the waters at the highest latitudes of the globe.

  2. The Chukchi Sea sits between northern Alaska and Russia. That makes it a crucial bridge to the Bering Sea, a place for sea to latch on and spread its icy tendrils to the south. But this winter so far has seen ice suffer. After bottoming out in September, the ice in the Chukchi Sea has failed to rebound. Usually, the dip in temperatures coupled with the lack of sunlight causes ice to build back up quickly. This year, though, growth has been much slower. Sea ice data crunched by University of California, Irvine PhD candidate and Arctic watcher Zack Labe shows that sea ice extent in the Chukchi Sea is the lowest on record for this time of year by a long shot.
  3. Arctic sea ice as a whole sits at its third lowest extent on record for this time of year and is well below the long-term average. Part of the reason for the sluggish growth ties to this spring and summer of sweltering discontent. Temperatures were abnormally high much too often. It reached nearly 95 degrees Fahrenheit in the Swedish Arctic. 
  4. Lightning, which generally requires warm, humid conditions, struck near the North Pole.  The northernmost settlement on Earth hit 70 degrees Fahrenheit for the first time ever. That’s just a smattering of all the ways the Arctic was fucked this summer. 
  5. Don’t even get me started on the fires, but they all point to the culprit likely driving weak sea ice growth: heat, and lots of it. The intense heat this summer helped melt ice. This year’s Arctic sea ice minimum was the second lowest on record. That in turn meant more dark, open water was available to absorb the suns rays and heat up itself. So even now that the sun has gone down for much of the Arctic, the last rays of summer are still very much present in the form of toasty (by Arctic standards) waters and making it hard for sea ice to form.
  6. This feedback loop is one of the hallmarks of climate change. Carbon pollution has warmed the Arctic twice as fast as the rest of the world, and the system has rapidly destabilized in recent years. The more plentiful fires and melting permafrost are releasing more carbon that will further speed up the changes. Meanwhile, disappearing sea ice and thus more open water will ensure the region continues to heat faster than the rest of the world. The vicious cycle has put the Arctic on the brink of a tipping point into a more volatile state unrecognizable from the Arctic we know today. If you want to know what the transition could look like, the Chukchi Sea is offering quite the lesson right now.




It is noted and acknowledged by the authors (Zack Labe and Brian Kahn) that the sea ice phenomenon in question cannot be generalized to the Arctic Sea nor across the time span and time scale of AGW climate change that relates to long term trends in atmospheric heat balance. The event is localized to the Chukchi Sea, a small corner of the Arctic wedged in between Alaska and Siberia. The phenomenon is also time constrained to a singular event in time. A more rational explanation for this event than atmospheric heat energy trends since pre-industrial times is proposed in terms of the known geological features of the Chukchi Sea presented in the charts in Figure 4 below that include the Graben and Laptev rift systems. Anomalous events constrained by time and geography may not have a ready explanation in terms of long term atmospheric trends. It is shown in related posts that year to year changes in September minimum sea ice extent are unrelated to atmospheric temperature trends attributed to AGW climate change [LINK] [LINK] [LINK] . We therefore propose that Arctic sea ice dynamics should be understood not exclusively in terms of atmospheric phenomena but that their study should include effects of known geological dynamics of the Arctic particularly so when the the sea ice event in question is localized in time and space [LINK] [LINK] .




TECTONIC FEATURES OF THE AMERASIA BASIN: (KONONOV 2013): In the bottom frame of Figure 4 above, the black circles are the points of the heat flux measurements, and the digits in the circles are the average heat flux values. The straight lines are the magnetic anomalies. The double arrows denote the Aptian–Albian sublatitudinal extension of the Eurasian margin. The dashed line delineates the central block of the Arctida continent, which was fragmented as a result of rifting and diffuse spreading into the provinces of basins and ridges. Bathymetry simulation indicates that the Mesozoic Arctic Plume is in the lithosphere of the Alpha-Mendeleev and Lomonosov ridges (map above). The study also presents a model of the thermal subsidence to the asthenosphere. The calculated coefficients are compared with those obtained for the Greenland-Iceland and Iceland-Faeroe ridges, which were formed in response to hotspot activity. It was shown that the coefficients of the thermal subsidence in the central part of the Alpha-Mendeleev and Lomonosov Ridges are similar to those calculated for the Greenland-Iceland and Iceland-Faeroe ridges. This indicates the thermal regime of the subsidence of the Alpha-Mendeleev and Lomonosov ridges since the Early Miocene and the increased influence of the Arctic plume on the ridge genesis.





  1. Neal, Victor T., Stephen Neshyba, and Warren Denner. “Thermal stratification in the Arctic Ocean.” Science 166.3903 (1969): 373-374.  Fine scale measurements of the vertical temperature profile in an Arctic water column show the presence of several cascaded isothermal layers. Layers between the depths of 300 anid 350 meters range from 2 to 10 meters in thickness, while the temperature change between adjacent layers is approximately 0.026°C. The individual layers are isothermal to within ± 0.001°C.
  2. Van, Hulsen A. “Geothermal channel and harbor ice control system.” U.S. Patent No. 3,807,491. 30 Apr. 1974A thermo-arctic sea passage is formed and maintained by providing a series of geothermal wells spaced along the intended route. Heat energy transferred from a deep geothermal strata to the surface melts the ice to form a water channel. Reformation of ice is inhibited by efficient and active water movement and wave action induced by wind action.
  3. von Quillfeldt, Cecilie H., William G. Ambrose, and Lisa M. Clough. “High number of diatom species in first-year ice from the Chukchi Sea.” Polar Biology 26.12 (2003): 806-818.  Our study describes the species composition of microalgae, primarily diatoms, in two ice cores collected from the Chukchi Sea in early June 1998. At least 251 species were present in 2 cores collected 10 m apart in first-year ice. This is a greater number of algal species in ice from one locality than has been recorded from any other area of the Arctic. Microalgae were distributed throughout the 173-cm-long core, but abundance and species composition varied among different sections of the core, with maximum species richness (108 and 103 species in the 94- to 103- and 103- to 113-cm sections, respectively) occurring in the middle sections. More than 237 species were recorded from this core. Only the bottom 20 cm of the shorter (110 cm) core was analysed and it contained 135 algal species, still an extraordinarily high number of species. Marine species dominated both cores, but typical brackish and freshwater species were also present. None of these species, however, had more than 1% relative abundance. It should be noted, though, that there were several distinct, but unidentified, species of unknown origin. Characteristic ice algal species (e.g. Nitzschia frigida, Navicula pelagica, solitary Navicula spp., in addition to Cylindrotheca closterium) were the numerical dominants in most sections of the long core, but phytoplankton and benthic species were quite abundant in some sections. One section was dominated by a blue-green bacterium, presumably of the genus Anabaena. The species composition is consistent with several different mechanisms for algal incorporation into ice (i.e. seawater filtration ice, seeding from the sea floor, freshwater input). Over time, ice dynamics and sources of ice in the Chukchi Sea appear to result in high numbers of algal species in the ice. It is also likely that season of collection contributed to the high number of species observed. Determining the geographical area of origin for the different species is however difficult, due to the large-scale pattern of ice circulation.
  4. Martin, Seelye, et al. “Estimation of the thin ice thickness and heat flux for the Chukchi Sea Alaskan coast polynya from Special Sensor Microwave/Imager data, 1990–2001.” Journal of Geophysical Research: Oceans 109.C10 (2004).  One of the largest Arctic polynyas occurs along the Alaskan coast of the Chukchi Sea between Cape Lisburne and Point Barrow. For this polynya (iceless sea surface surrounded by sea ice), a new thin ice thickness algorithm is described that uses the ratio of the vertically and horizontally polarized Special Sensor Microwave/Imager (SSM/I) 37‐GHz channels to retrieve the distribution of thicknesses and heat fluxes at a 25‐km resolution. Comparison with clear‐sky advanced very high resolution radiometer data shows that the SSM/I thicknesses and heat fluxes are valid for ice thicknesses less than 10–20 cm, and comparison with several synthetic aperture radar (SAR) images shows that the 10‐cm ice SSM/I ice thickness contour approximately follows the SAR polynya edge. For the twelve winters of 1990–2001, the ice thicknesses and heat fluxes within the polynya are estimated from daily SSM/I data, then compared with field data and with estimates from other investigations. The results show the following: First, our calculated heat losses are consistent with 2 years of over‐winter salinity and temperature field data. Second, comparison with other numerical and satellite estimates of the ice production shows that although our ice production per unit area is smaller, our polynya areas are larger, so that our ice production estimates are of the same order. Because our salinity forcing occurs over a larger area than in the other models, the oceanic response associated with our forcing will be modified.
  5. De Vernal, Anne, Claude Hillaire‐Marcel, and Dennis A. Darby. “Variability of sea ice cover in the Chukchi Sea (western Arctic Ocean) during the Holocene.” Paleoceanography 20.4 (2005).  Dinocysts from cores collected in the Chukchi Sea from the shelf edge to the lower slope were used to reconstruct changes in sea surface conditions and sea ice cover using modern analogue techniques. Holocene sequences have been recovered in a down‐slope core (B15: 2135 m, 75°44′N, sedimentation rate of ∼1 cm kyr−1) and in a shelf core (P1: 201 m, 73°41′N, sedimentation rate of ∼22 cm kyr−1). The shelf record spanning about 8000 years suggests high‐frequency centennial oscillations of sea surface conditions and a significant reduction of the sea ice at circa 6000 and 2500 calendar (cal) years B.P. The condensed offshore record (B15) reveals an early postglacial optimum with minimum sea ice cover prior to 12,000 cal years B.P., which corresponds to a terrestrial climate optimum in Bering Sea area. Dinocyst data indicate extensive sea ice cover (>10 months yr−1) from 12,000 to 6000 cal years B.P. followed by a general trend of decreasing sea ice and increasing sea surface salinity conditions, superimposed on large‐amplitude millennial‐scale oscillations. In contrast, δ18O data in mesopelagic foraminifers (Neogloboquadrina pachyderma) and benthic foraminifers (Cibicides wuellerstorfi) reveal maximum subsurface temperature and thus maximum inflow of the North Atlantic water around 8000 cal years B.P., followed by a trend toward cooling of the subsurface to bottom water masses. Sea‐surface to subsurface conditions estimated from dinocysts and δ18O data in foraminifers thus suggest a decoupling between the surface water layer and the intermediate North Atlantic water mass with the existence of a sharp halocline and a reverse thermocline, especially before 6000 years B.P. The overall data and sea ice reconstructions from core B15 are consistent with strong sea ice convergence in the western Arctic during the early Holocene as suggested on the basis of climate model experiments including sea ice dynamics, matching a higher inflow rate of North Atlantic Water.
  6. Björk, Göran, and Peter Winsor. “The deep waters of the Eurasian Basin, Arctic Ocean: Geothermal heat flow, mixing and renewal.” Deep Sea Research Part I: Oceanographic Research Papers 53.7 (2006): 1253-1271.  Hydrographic observations from four separate expeditions to the Eurasian Basin of the Arctic Ocean between 1991 and 2001 show a 300–700 m thick homogenous bottom layer. The layer is characterized by slightly warmer temperature compared to ambient, overlying water masses, with a mean layer thickness of 500±100 m and a temperature surplus of 7.0±2×10−3 °C. The layer is present in the deep central parts of the Nansen and Amundsen Basins away from continental slopes and ocean ridges and is spatially coherent across the interior parts of the deep basins. Here we show that the layer is most likely formed by convection induced by geothermal heat supplied from Earth’s interior. Data from 1991 to 1996 indicate that the layer was in a quasi steady state where the geothermal heat supply was balanced by heat exchange with a colder boundary. After 1996 there is evidence of a reformation of the layer in the Amundsen Basin after a water exchange. Simple numerical calculations show that it is possible to generate a layer similar to the one observed in 2001 in 4–5 years, starting from initial profiles with no warm homogeneous bottom layer. Limited hydrographic observations from 2001 indicate that the entire deep-water column in the Amundsen Basin is warmer compared to earlier years. We argue that this is due to a major deep-water renewal that occurred between 1996 and 2001.
  7. Francis, Jennifer A., and Elias Hunter. “New insight into the disappearing Arctic sea ice.” Eos, Transactions American Geophysical Union 87.46 (2006): 509-511. The dramatic loss of Arctic sea ice is ringing alarm bells in the minds of climate scientists, policy makers, and the public. The extent of perennial sea ice—ice that has survived a summer melt season—has declined 20% since the mid‐1970s [Stroeue et al., 2005]. Its retreat varies regionally, driven by changes in winds and heating from the atmosphere and oceanLimited data have hampered attempts to identify which culprits are to blame, but new satellite‐derived information provides insight into the drivers of change. A clear message emerges. The location of the summer ice edge is strongly correlated to variability in longwave (infrared) energy emitted by the atmosphere (downward longwave flux; DLF), particularly during the most recent decade when losses have been most rapid. Increasing DLF, in turn, appears to be driven by more clouds and water vapor in spring over the Arctic.
  8. McKay, J. L., et al. “Holocene fluctuations in Arctic sea-ice cover: dinocyst-based reconstructions for the eastern Chukchi Sea.” Canadian Journal of Earth Sciences 45.11 (2008): 1377-1397.  Cores from site HLY0501-05 on the Alaskan margin in the eastern Chukchi Sea were analyzed for their geochemical (organic carbon, δ13Corg, Corg/N, and CaCO3) and palynological (dinocyst, pollen, and spores) content to document oceanographic changes during the Holocene. The chronology of the cores was established from 210Pb dating of near-surface sediments and 14C dating of bivalve shells. The sediments span the last 9000 years, possibly more, but with a gap between the base of the trigger core and top of the piston core. Sedimentation rates are very high (∼156 cm/ka), allowing analyses with a decadal to centennial resolution. The data suggest a shift from a dominantly terrigenous to marine input from the early to late Holocene. Dinocyst assemblages are characterized by relatively high concentrations (600–7200 cysts/cm3) and high species diversity, allowing the use of the modern analogue technique for the reconstruction of sea-ice cover, summer temperature, and salinity. Results indicate a decrease in sea-ice cover and a corresponding, albeit much smaller, increase in summer sea-surface temperature over the past 9000 years. Superimposed on these long-term trends are millennial-scale fluctuations characterized by periods of low sea-ice and high sea-surface temperature and salinity that appear quasi-cyclic with a frequency of about one every 2500–3000 years. The results of this study clearly show that sea-ice cover in the western Arctic Ocean has varied throughout the Holocene. More importantly, there have been times when sea-ice cover was less extensive than at the end of the 20th century.
  9. Grebmeier, Jacqueline M., et al. “Biological response to recent Pacific Arctic sea ice retreats.” Eos, Transactions American Geophysical Union 91.18 (2010): 161-162.  Although recent major changes in the physical domain of the Arctic region, such as extreme retreats of summer sea ice since 2007, are well documented, large uncertainties remain regarding responses in the biological domain. In the Pacific Arctic north of Bering Strait, reduction in sea ice extent has been seasonally asymmetric, with minimal changes until the end of June and delayed sea ice formation in late autumn. The effect of extreme ice retreats and seasonal asymmetry in sea ice loss on primary production is uncertain, with no clear shift over time (2003–2008) in satellite‐derived chlorophyll concentrations. However, clear changes have occurred during summer in species ranges for zooplankton, bottom‐dwelling organisms (benthos), and fish, as well as through the loss of sea ice as habitat and platform for marine mammals.
  10. Nicolsky, D., and N. Shakhova. “Modeling sub-sea permafrost in the East Siberian Arctic Shelf: the Dmitry Laptev Strait.” Environmental Research Letters 5.1 (2010): 015006The present state of sub-sea permafrost modeling does not agree with certain observational data on the permafrost state within the East Siberian Arctic Shelf. This suggests a need to consider other mechanisms of permafrost destabilization after the recent ocean transgression. We propose development of open taliks wherever thaw lakes and river paleo-valleys were submerged shelf-wide as a possible mechanism for the degradation of sub-sea permafrost. To test the hypothesis we performed numerical modeling of permafrost dynamics in the Dmitry Laptev Strait area. We achieved sufficient agreement with the observed distribution of thawed and frozen layers to suggest that the proposed mechanism of permafrost destabilization is plausible. Two basic mechanisms are proposed to explain permafrost dynamics after the inundation: the so-called upward degradation under geothermal heat flux in the areas underlain by fault zones (Romanovskii and Hubberten 2001), and the so-called downward degradation under the warming effect of large river bodies (Delisle 2000).
  11. Douglas, David C. Arctic sea ice decline: projected changes in timing and extent of sea ice in the Bering and Chukchi Seas. No. 2010-1176. US Geological Survey, 2010 The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of ice extent and seasonality. At the end of the 21st century (2090-2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement among models. High agreement also accompanies projections that the Chukchi Sea will be completely ice covered during February, March, and April at the end of the century. Large uncertainties, however, are associated with the timing and amount of partial ice cover during the intervening periods of melt and freeze. For the Bering Sea, median March ice extent is projected to be about 25 percent less than the 1979-1988 average by mid-century and 60 percent less by the end of the century. The ice-free season in the Bering Sea is projected to increase from its contemporary average of 5.5 months to a median of about 8.5 months by the end of the century. A 3-month longer ice- free season in the Bering Sea is attained by a 1-month advance in melt and a 2-month delay in freeze, meaning the ice edge typically will pass through the Bering Strait in May and January at the end of the century rather than June and November as presently observed.
  12. Carmack, Eddy C., et al. “The Arctic Ocean warms from below.” Geophysical Research Letters 39.7 (2012).  The old (∼450‐year isolation age) and near‐homogenous deep waters of the Canada Basin (CBDW), that are found below ∼2700 m, warmed at a rate of ∼0.0004°C yr−1 between 1993 and 2010. This rate is slightly less than expected from the reported geothermal heat flux (Fg ∼ 50 mW m−2). A deep temperature minimum Tmin layer overlies CBDW within the basin and is also warming at approximately the same rate, suggesting that some geothermal heat escapes vertically through a multi‐stepped, ∼300‐m‐thick deep transitional layer. Double diffusive convection and thermobaric instabilities are identified as possible mechanisms governing this vertical heat transfer. The CBDW found above the lower continental slope of the deep basin maintains higher temperatures than those in the basin interior, consistent with geothermal heat being distributed through a shallower water column, and suggests that heat from the basin interior does not diffuse laterally and escape at the edges.
  13. Jay, Chadwick V., Anthony S. Fischbach, and Anatoly A. Kochnev. “Walrus areas of use in the Chukchi Sea during sparse sea ice cover.” Marine Ecology Progress Series 468 (2012): 1-13. The Pacific walrus Odobenus rosmarus divergens feeds on benthic invertebrates on the continental shelf of the Chukchi and Bering Seas and rests on sea ice between foraging trips. With climate warming, ice-free periods in the Chukchi Sea have increased and are projected to increase further in frequency and duration. We radio-tracked walruses to estimate areas of walrus foraging and occupancy in the Chukchi Sea from June to November of 2008 to 2011, years when sea ice was sparse over the continental shelf in comparison to historical records. The earlier and more extensive sea ice retreat in June to September, and delayed freeze-up of sea ice in October to November, created conditions for walruses to arrive earlier and stay later in the Chukchi Sea than in the past. The lack of sea ice over the continental shelf from September to October caused walruses to forage in nearshore areas instead of offshore areas as in the past. Walruses did not frequent the deep waters of the Arctic Basin when sea ice retreated off the shelf. Walruses foraged in most areas they occupied, and areas of concentrated foraging generally corresponded to regions of high benthic biomass, such as in the northeastern (Hanna Shoal) and southwestern Chukchi Sea. A notable exception was the occurrence of concentrated foraging in a nearshore area of northwestern Alaska that is apparently depauperate in walrus prey. With increasing sea ice loss, it is likely that walruses will increase their use of coastal haul-outs and nearshore foraging areas, with consequences to the population that are yet to be understood.
  14. Arrigo, Kevin R., et al. “Massive phytoplankton blooms under Arctic sea ice.” Science 336.6087 (2012): 1408-1408Phytoplankton blooms over Arctic Ocean continental shelves are thought to be restricted to waters free of sea ice. Here, we document a massive phytoplankton bloom beneath fully consolidated pack ice far from the ice edge in the Chukchi Sea, where light transmission has increased in recent decades because of thinning ice cover and proliferation of melt ponds. The bloom was characterized by high diatom biomass and rates of growth and primary production. Evidence suggests that under-ice phytoplankton blooms may be more widespread over nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in these waters may be underestimated by up to 10-fold.
  15. Arrigo, Kevin R., et al. “Phytoplankton blooms beneath the sea ice in the Chukchi Sea.” Deep Sea Research Part II: Topical Studies in Oceanography 105 (2014): 1-16.  In the Arctic Ocean, phytoplankton blooms on continental shelves are often limited by light availability, and are therefore thought to be restricted to waters free of sea ice. During July 2011 in the Chukchi Sea, a large phytoplankton bloom was observed beneath fully consolidated pack ice and extended from the ice edge to >100 km into the pack. The bloom was composed primarily of diatoms, with biomass reaching 1291 mg chlorophyll a m−2 and rates of carbon fixation as high as 3.7 g C m−2 d−1. Although the sea ice where the bloom was observed was near 100% concentration and 0.8–1.2 m thick, 30–40% of its surface was covered by melt ponds that transmitted 4-fold more light than adjacent areas of bare ice, providing sufficient light for phytoplankton to bloom. Phytoplankton growth rates associated with the under-ice bloom averaged 0.9 d−1 and were as high as 1.6 d−1. We argue that a thinning sea ice cover with more numerous melt ponds over the past decade has enhanced light penetration through the sea ice into the upper water column, favoring the development of these blooms. These observations, coupled with additional biogeochemical evidence, suggest that phytoplankton blooms are currently widespread on nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in waters where under-ice blooms develop are ~10-fold too low. These massive phytoplankton blooms represent a marked shift in our understanding of Arctic marine ecosystems.
  16. Carmack, Eddy, et al. “Toward quantifying the increasing role of oceanic heat in sea ice loss in the new Arctic.” Bulletin of the American Meteorological Society 96.12 (2015): 2079-2105.  The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions.











Arctic Ocean could be ice-free for part of the year as soon as 2044







  1. The fate of Arctic sea ice is a key topic for climate scientists because of its role in temperatures around the rest of the world. It’s hard to imagine the Arctic without sea ice. But according to a new study by UCLA climate scientists, human-caused climate change is on track to make the Arctic Ocean functionally ice-free for part of each year starting sometime between 2044 and 2067. 
  2. As long as humans have been on Earth, the planet has had a large cap of sea ice at the Arctic Circle that expands each winter and contracts each summer. The knowledge that sea ice is on the decline is not new: Satellite observations show that since 1979, the amount of sea ice in the Arctic in September—the month when there is the least sea ice, before water starts freezing again—has declined by 13 percent per decade.
  3. Scientists have been attempting to predict the future of Arctic sea ice for several decades, relying on an array of global climate models that simulate how the climate system will react to the carbon dioxide entering the atmosphere. But the models’ predictions have disagreed widely. Some show ice-free Septembers as early as 2026; others suggest the phenomenon will begin as late as 2132.
  4. The UCLA study, which was published in Nature Climate Change, narrows the predictions to a 25-year period. Sea ice loss diverge because they differ in how their estimation of sea ice loss albedo feedback is expected to cause greater local warming, which in turn leads to further ice melt. This feedback exacerbates warming and is one reason why the Arctic is heating up twice as fast as the rest of the globe.
  5. Thackeray and co-author Alex Hall, UCLA professor of atmospheric and oceanic sciences, determined which models are most realistic in sea ice albedo feedback estimation that would lead them to the most realistic projections for sea ice. They used the seasonal sea ice cycle to estimate the albedo feedback effect. Satellite observations track the seasonal melt cycle that includes the albedo feedback. Of 23 different climate models, the authors identified six models that were closest to the observational data in the period 1980-2015.
  6. The approach of using an observable process in the current climate to evaluate global climate model projections of future climate was pioneered by Hall and his group in 2006, in a study focused on snow albedo feedback. It has since become widely used in climate science as researchers try to improve the precision of their projections. The fate of Arctic sea ice is a key topic for climate scientists because of its global impact on temperature. “Arctic sea ice is a key component of the earth system because of its highly reflective nature, which keeps the global climate relatively cool“, Thackeray said.
  7. There are other environmental and economic implications to ice loss as well. Sea ice is critical to the Arctic ecosystem, and to the fishing industry and indigenous peoples who depend on that ecosystem. And as Arctic ice is lost, more waters are used for commercial shipping and oil and gas exploration, which presents economic opportunity for some nations, but which also contributes to further greenhouse gas emissions and climate change. “The changes to come will have broad environmental, ecological and economic implications,” Thackeray said. “By reducing the uncertainty in in our ice free prediction, we can be better prepared.”
  8. CITATION AND ABSTRACT: Thackeray, Chad W., and Alex Hall. “An emergent constraint on future Arctic sea-ice albedo feedback.” Nature Climate Change (2019): 1-7Arctic sea ice has decreased substantially over recent decades, a trend projected to continue. Shrinking ice reduces surface albedo, leading to greater surface solar absorption, thus amplifying warming and driving further melt. This sea-ice albedo feedback (SIAF) is a key driver of Arctic climate change and an important uncertainty source in climate model projections. Using an ensemble of models, we demonstrate an emergent relationship between future SIAF and an observable version of SIAF in the current climate’s seasonal cycle. This relationship is robust in constraining SIAF over the coming decades (Pearson’s r = 0.76), and then it degrades. The degradation occurs because some models begin producing ice-free conditions, signalling a transition to a new ice regime. The relationship is strengthened when models with unrealistically thin historical ice are excluded. Because of this tight relationship, reducing model errors in the current climate’s seasonal SIAF and ice thickness can narrow SIAF spread under climate change. 




  1. 1999, STUDY SHOWS ARCTIC ICE SHRINKING BECAUSE OF GLOBAL WARMING. Sea ice in the Arctic Basin is shrinking by 14000 square miles per year because of global warming caused by human activity according to a new international study that used 46 years of data and sophisticated computer simulation models to tackle the specific question of whether the loss of Arctic ice is a natural variation or caused by global warming. The computer model says that the probability that these changes were caused by natural variation is 1% but when global warming was added to the model the ice melt was a perfect fit. Therefore the ice melt is caused by human activities that emit greenhouse gases.
    Soot that lands on snow has caused ¼ of the warming since 1880 because dirty snow traps more solar heat than pristine snow and induces a strong warming effect, according to a new computer model by James Hansen of NASA. It explains why sea ice and glaciers are melting faster than they should. Reducing soot emissions is an effective tool to curb global warming. It is easier to cut soot emissions than it is to cut CO2 emissions but we still need to reduce CO2 emissions in order to stabilize the atmosphere.
    An unprecedented 4-year study of the Arctic shows that polar bears, walruses, and some seals are becoming extinctArctic summer sea ice may disappear entirely. Combined with a rapidly melting Greenland ice sheet, it will raise the sea level 3 feet by 2100 inundating lowlands from Florida to Bangladesh. Average winter temperatures in Alaska and the rest of the Arctic are projected to rise an additional 7 to 13 degrees over the next 100 years because of increasing emissions of greenhouse gases from human activities. The area is warming twice as fast as anywhere else because of global air circulation patterns and natural feedback loops, such as less ice reflecting sunlight, leading to increased warming at ground level and more ice melt. Native peoples’ ways of life are threatened. Animal migration patterns have changed, and the thin sea ice and thawing tundra make it too dangerous for humans to hunt and travel.
    The Arctic Climate Impact Assessment (ACIA) report says: increasing greenhouse gases from human activities is causing the Arctic to warm twice as fast as the rest of the planet; in Alaska, western Canada, and eastern Russia winter temperatures have risen by 2C to 4C in the last 50 years; the Arctic will warm by 4C to 7C by 2100. A portion of Greenland’s ice sheet will melt; global sea levels will rise; global warming will intensify. Greenland contains enough melting ice to raise sea levels by 7 meters; Bangkok, Manila, Dhaka, Florida, Louisiana, and New Jersey are at risk of inundation; thawing permafrost and rising seas threaten Arctic coastal regions; climate change will accelerate and bring about profound ecological and social changes; the Arctic is experiencing the most rapid and severe climate change on earth and it’s going to get a lot worse; Arctic summer sea ice will decline by 50% to 100%polar bears will be driven towards extinction; this report is an urgent SOS for the Arctic; forest fires and insect infestations will increase in frequency and intensity; changing vegetation and rising sea levels will shrink the tundra to its lowest level in 21000 years; vanishing breeding areas for birds and grazing areas for animals will cause extinctions of many species; “if we limit emission of heat trapping carbon dioxide we can still help protect the Arctic and slow global warming”.
    Climate science declares that the low sea ice extent in the Arctic is the leading indicator of climate change. We are told that the Arctic “is screaming”, that Arctic sea ice extent is the “canary in the coal mine”, and that Polar Bears and other creatures in the Arctic are dying off and facing imminent extinction. Scientists say that the melting sea ice has set up a positive feedback system that would cause the summer melts in subsequent years to be greater and greater until the Arctic becomes ice free in the summer of 2012. We must take action immediately to cut carbon dioxide emissions from fossil fuels. [DETAILS] 
    The unusual summer melt of Arctic sea ice in 2007 has encouraged climate science to warn the world that global warming will cause a steep decline in the amount of ice left in subsequent summer melts until the Arctic becomes ice free in summer and that could happen as soon as 2080 or maybe 2060 or it could even be 2030. This time table got shorter and shorter until, without a “scientific” explanation, the ice free year was brought up to 2013. In the meantime, the data showed that in 2008 and 2009 the summer melt did not progressively increase as predicted but did just the opposite by making a comeback in 2008 that got even stronger in 2009. [DETAILS]
    Our use of fossil fuels is devastating the Arctic where the volume of sea ice “fell to its lowest recorded level to date” this year and that reduced ice coverage is causing a non-linear acceleration in the loss of polar ice because there is less ice to reflect sunlight. [DETAILS]
  8. 2008: THE ARCTIC WILL BE ICE FREE IN SUMMER IN 2008, 2013, 2030, OR 2100
    The unusually low summer sea ice extent in the Arctic in 2007
    The IPCC has taken note and has revised its projection of an ice free Arctic first from 2008 to 2013 and then again from 2013 to 2030. The way things are going it may be revised again to the year 2100. [DETAILS]
    When there was a greater focus on Antarctica climate scientists said that global warming was melting the West Antarctic Ice Shelf; but the melting was found to be localized and with an active volcano underneath the melting and the attention of “melt forecast” climate science shifted to Arctic sea ice after the an extensive summer melt was observed in September 2007. [DETAILS]
    The survival of the polar bear is threatened because man made global warming is melting ice in the Arctic. It is true that the Arctic sea ice extent was down in negative territory in September 2007. This event emboldened global warming scaremongers to declare it a climate change disaster caused by greenhouse gas emissions from fossil fuels and to issue a series of scenarios about environmental holocaust yet to come. [DETAILS]
    The second lowest was 2008 and the first lowest was 2007. This is not a trend that shows that things are getting worse. It shows that things are getting better and yet it is being sold and being bought as evidence that things are getting worse due to rising fossil fuel emissions. [DETAILS]
    An alarm is raised that the extreme summer melt of Arctic sea ice in 2007 was caused by humans using fossil fuels and it portends that in 20 years human caused global warming will leave the Arctic Ocean ice-free in the summer raising sea levels and harming wildlife. [DETAILS]
    Climate scientists continue to extrapolate the extreme summer melt of Arctic sea ice in 2007 to claim that the summer melt of 2007 was a climate change event and that it implies that the Arctic will be ice free in the summer from 2012 onwards. This is a devastating effect on the planet and our use of fossil fuels is to blame. [DETAILS]
    Summer melt of Arctic ice was the third most extensive on record in 2009, second 2008, and the most extensive in 2007. These data show that warming due to our carbon dioxide emissions are causing summer Arctic ice to gradually diminish until it will be gone altogether. [DETAILS]




  1. The premise of this paper is “Yes, there were a few ice-free-Arctic forecasts that didn’t happen but this time around we got the ice free forecast right because we tuned the climate model with the seasonal cycle“. This premise is supported by the claim that the climate models that were used to predict the ice free condition were pre-tested against the seasonal cycle and those climate models that could correctly predict the September minimum sea ice extent in the seasonal cycle were taken to be accurate predictors of long term trends in sea ice extent and these models were used to make the long term prediction of an ice free September. It is proposed that the long term forecast is validated by the ability of the same climate model to forecast the seasonal September minimum sea ice extent. Therefore the forecast of that validated climate model that the long awaited ice-free September will occur sometime between 2044 and 2067 {at some point 28 to 48 years from now} is is finally the correct forecast of an ice free Arctic. 
  2. This argument is flawed in a number of ways. First, the seasonal cycle in Arctic air temperature above the Ocean imposes a range of surface air temperatures equivalent to more than 70 years (range = 40 to 130 years) of warming at the current long term warming rate in September temperature of 0,026C per year (Figure 1). Also the regression for the trend contains large uncertainties (Figure 2) so that temperature forecasts contain large uncertainties regardless of the quality of the climate model (Figure 4). Note in Figure 3 that the regression residuals when expressed as multiples of the regression coefficient are in a range of -40 to +25 times the long term trend contained in the regression coefficient. Therefore, the seasonal cycle of the year and the year to year long term trend and very different phenomena such that the forecast for future years cannot be based on seasonal cycle dynamics. Uncertainties in year to year September temperature when compared with the predictable seasonal cycle imply that year to year surface air temperatures are not as exactly predictable as one might presume from the more predictable nature of the seasonal cycle.
  3. An added consideration in the frustration of climate science with ice free Arctic predictions is the atmosphere bias of climate science such that all ice melt events in the Arctic region are assumed to be governed by air temperature and by changes in air temperature without empirical evidence of this relationship. This overarching assumption of climate science derives from a reliance on climate models as we see in the Thackeray paper presented here. Yet it is not possible to use climate models in a test of theory because climate models are themselves an expression of theory. A lopsided reliance of climate science on climate models diminishes the role of observational data and and emphasizes theoretical considerations. This aberration in climate science is particularly severe in the case of their evaluation of sea ice dynamics.
  4. In related posts on this site it is shown that this assumption derived from climate models is not supported by the empirical data. Detrended correlation analysis does not provide the needed evidence in the form of a statistically significant negative correlation between temperature and sea ice extent that is a necessary condition for a causal relationship between surface air temperature and sea ice extent [LINK] [LINK] . Thus, no empirical evidence exists that Arctic sea ice extent is responsive to surface air temperature at an annual time scale and yet this responsiveness is assumed in the attribution of changes in Arctic sea ice extent to changes in surface air temperature.
  5. Yet another relevant consideration is that the Arctic is a known to be a geologically active region with large flows of geothermal heat from the mantle into the ocean. The continued attribution of sea ice dynamics whether in extent, area, or volume, to AGW climate change and without consideration for known geothermal heat flows likely derives from the atmosphere bias of climate science such that there is a tendency to explain all observed changes in the Arctic, such as sea ice melt, in terms of AGW climate change and to overlook the extensive geothermal heat sources in the Arctic. Some of the geological features of the Arctic including the Mid Arctic Rift system and the Jan Mayen Trend are described in related posts [LINK] [LINK] and in the Graphic in Figure 5. A detailed study of the geology of the Arctic is presented in a related post [LINK] .










FIGURE 5: SOURCES OF GEOTHERMAL HEAT IN THE ARCTICbandicam 2019-07-01 16-29-44-526














  1. ISSUE #1 > THE RESPONSIVENESS OF ATMOSPHERIC COMPOSITION TO FOSSIL FUEL EMISSIONS: The human cause of warming begins with the argument that our use of fossil fuels has caused atmospheric CO2 concentration to rise and conversely, that causal relationship implies that climate action in the form of reducing or eliminating fossil fuel emissions will reduce or halt the rise in atmospheric CO2 and thus attenuate the rate of warming attributed to atmospheric composition. Thus, a fundamental and necessary condition for AGW is that a causal relationship must exist between atmospheric composition and fossil fuel emissions such that the observed changes in atmospheric composition since pre-industrial times can be explained in terms of fossil fuel emissions of the industrial economy. An annual time scale is assumed in climate science. This relationship is tested in four different posts on this site and the results are summarized below.
  2. TEST#1[LINK] > Is atmospheric CO2 concentration responsive to emissions at an annual time scale? Detrended correlation analysis is used to test this relationship. The detrending procedure removes the spurious effect of shared trends on correlation so that only the responsiveness at the specified time scale is measured in the correlation. Although climate science assumes an annual time scale, time scales from one to five years are tested. The results are tabulated in Paragraph#3 below. There are two columns of results for each time scale, the correlation and the detrended correlation. Although strong correlations from ρ=0.742 for a 1-year time scale to ρ=0.931 for a 5-year time scale are seen in the source data time series, these correlations do not survive into the detrended series where no statistically significant correlation is found. We conclude that the data do not provide sufficient evidence that atmospheric CO2 concentration is responsive to fossil fuel emissions.
  4. TEST#2 > [LINK] > Can nature’s carbon cycle flows be measured with sufficient accuracy to detect the presence of fossil fuel emissions? As seen in the IPCC carbon cycle flows presented in the linked document, the estimated mean values of the flows of the carbon cycle, with flow uncertainties not considered, provide an exact mass balance in the presence of fossil fuel emissions with the so called “Airborne Fraction” computed as 50%, meaning that the mass balance shows that 50% of the CO2 in fossil fuel emissions remain in the atmosphere where they change atmospheric CO2 concentration and cause anthropogenic global warming (AGW). Yet, these flow estimates contain very large uncertainties because they cannot be directly measured but must be inferred. In the related post a statistical test is devised to determine whether the much smaller emissions can be detected in the presence of much larger carbon cycle flows when their large uncertainties are considered. In the related post [LINK] , a Monte Carlo simulation is devised to estimate the highest value of the unknown standard deviations in carbon cycle flows at which we can detect the presence of CO2 in fossil fuel emissions. In the test, an uncertain flow account is considered to be in balance as long as the Null Hypothesis that the sum of the flows is zero cannot be rejected. The alpha error rate for the test is set to a high value of alpha=0.10 to ensure that any reasonable ability to discriminate between the flow account WITH Anthropogenic Emissions from a the flow account WITHOUT Anthropogenic Emissions is taken as evidence that the relatively small fossil fuel emissions can be detected in the presence of much larger and uncertain natural flows.
  5. In the simulation we assign different levels of uncertainty to the flows for which no uncertainty data are available and test the null hypothesis that the flows balance with anthropogenic emissions (AE) included and again with AE excluded. If the flows balance when AE are included and they don’t balance when AE are excluded then we conclude that the presence of the AE can be detected at that level of uncertainty. However, if the flows balance with and without AE then we conclude that the stochastic flow account is not sensitive to AE at that level of uncertainty. If the presence of AE cannot be detected no role for their effect on climate can be deduced from the data at that level of uncertainty in natural flows. The p-values for hypothesis tests for uncertainties in the natural flows from 1% of mean to 6.5% of mean are tabulated in Paragraph#6. The results show that when nature’s carbon cycle flows contain an uncertainty of 2% of the mean or less, the carbon cycle flow account can detect the presence of fossil fuel emissions. The presence of fossil fuel emissions cannot be detected at higher carbon cycle flow uncertainties. The lowest uncertainty found in the carbon cycle flows is 6.5% for photosynthesis. The other uncertainties are much larger and their flows are estimated to be higher than fossil fuel emissions by at least an order of magnitude. Therefore, given the uncertainty in our estimate of natural carbon cycle flows, it is not possible to determine the impact of fossil fuel emissions. 
  6. ISSUE #2 > THE RESPONSIVENESS OF SURFACE TEMPERATURE TO FOSSIL FUEL EMISSIONS: Anthropogenic global warming (AGW) theory says that fossil fuel emissions cause warming and that their reduction and eventual elimination can be used to attenuate the rate of warming and this option is offered and demanded as the “climate action” plan needed to save the world from the destructive effects forecast for uncontrolled AGW. These relationships imply that a correlation must exist between the rate of emissions and the rate of warming and in fact, climate science has presented just such a correlation. It is called the Transient Climate Response to Cumulative Emissions (TCRE) described more fully in a related post [LINK] . And in fact, the TCRE provides the structure and mathematics of the proposed climate action in terms of the so called carbon budgets proposed to constrain warming to a given target level. The TCRE derives from the observation by Damon Matthews and others in 2009 that a near perfect proportionality exists between cumulative emissions and cumulative warming.
  7. TEST#1 > Does the TCRE imply that the rate of warming is related to the rate of emissions such that climate action plans of reducing emissions can be used to attenuate the rate of warming? A test for this correlation is presented in a related post [LINK] where it is shown that a time series of the cumulative values of another time series has neither time scale nor degrees of freedom. The details of the proof of this condition are provided in the post on carbon budgets where it is also shown that the observed correlation derives not from responsiveness of warming to emissions but from a fortuitous sign pattern in which emissions are always positive and in a time of rising temperatures, annual warming is mostly positive [LINK] where it is shown for example, that the TCRE correlation exists in random numbers if the same sign pattern is inserted into the random numbers and disappears when the sign pattern is also random. The relevant GIF charts are reproduced here in {Paragraph#9 and Paragraph#10 below random numbers in the left frame and their cumulative values in the right frame}. The difference between the two charts is that in #9 the random numbers are truly random with no sign pattern imposed meaning that positive and negative values are equally likely; whereas in #10 the random number generator for both x and y favors positive values 55% to 45%. The analysis of the TCRE in these related posts implies that the observed correlation is illusory and spurious and has no implication for the real world phenomena the data apparently represent. Therefore, the TCRE has no interpretation in terms of a causal relationship between emissions and warming.
  10. The only information content of the TCRE is the sign pattern. If the the two time series have a common sign bias, either both positive or both negative, the correlation will be positive. If the the two time series have different sign biases, one positive and the other negative, the correlation will be negative. If the the two time series have no sign bias, no correlation will be found. Therefore, the only information content of the TCRE is the sign pattern and no rational interpretation of such a proportionality exists in terms of a causal relationship that can be used in the construction of carbon budgets. The TCRE carbon budgets of climate science is a a meaningless exercise with an illusory statistic. 
  11. TEST#2 > The problem with the TCRE correlation is that it has no time scale and no degrees of freedom. Both issues can be resolved by inserting a fixed time scale X into the TCRE computation such that the correlation is rendered statistically valid as TCREX. The second research question is therefore, {Does the TCREX show that the rate of warming is responsive to the rate of emissions} such that climate action plans of reducing emissions can be used to attenuate the rate of warming? This test is carried out in a related post [LINK] with time scales of ten to thirty years. The test is carried out with both climate model estimations of global mean temperature (RCP) and reconstructions of global mean temperature from the instrumental record  (HADCRUT4). The results of detrended correlation analysis are summarized in Paragraph#13 below. They show strong statistically significant detrended correlations in the theoretical temperatures from climate models but no statistically significant result is found in the observational data. The agreement with the theoretical temperature series validates the procedure and therefore the absence of evidence to relate observational data to emissions provides convincing evidence that when the TCRE measure is corrected to insert time scale and degrees of freedom, the “near perfect proportionality” of the TCRE disappears. We conclude from these results that no evidence is found in the observational data that the rate of warming is responsive to the rate of emissions. [DETAILS]
  13. ISSUE#3 > CARBON BUDGETS: The claimed catastrophic impacts of AGW Climate Change serve as the needed motivation for Climate Action. Climate action involves the reduction and eventual elimination of the use of fossil fuels – and thereby of fossil fuel emissions. The theoretical linkage between climate change and climate action is the Carbon Budget. A climate action plan specifies the maximum warming target over a specified time span. The corresponding carbon budget is the maximum amount of carbon in fossil fuel emissions that can be emitted over that time period to comply with the climate action plan. The statistical issue in this case arises because the carbon budget is based on the flawed TCRE – Transient Climate Response to Cumulative Emissions discussed  above in Issue#2.
  14. TEST#1 > The use of the illusory TCRE correlation in the construction of carbon budgets renders the carbon budget equally spurious and illusory as described in this related post [LINK] . It shows that the carbon budget computed from the TCRE has no interpretation in the real world because it is based on an illusory correlation that is the creation of sign patterns and not based on the responsiveness of temperature to emissions. The further consideration is that the absence of time scale and degrees of freedom in the carbon budget renders it a spurious statistic that has no interpretation in terms of the emissions and warming dynamics it apparently represents.
  15. TEST#2 > A further test of the validity of the carbon budget is seen in the Remaining Carbon Budget Puzzle (RCBPthat has created a state of confusion in climate science as described in a related post [LINK] . In brief, the RCBP issue is that the carbon budget for the full span of the budget period does not equal the sum of the carbon budgets computed for its sub-spans. There is a simple statistics explanation of this apparent oddity in terms of the spuriousness of the correlation and the TCRE regression coefficient. The positive TCRE correlation is a creation of a fortuitous sign pattern such that emissions are always positive and during a time of warming, annual warming values are mostly positive, as shown in a related post [LINK] . Thus, the TCRE regression coefficient is determined by the fraction of annual warming values that are positive; and this fraction is not likely to be the same in different sub-spans and not the same in any given sub-span as in the full span. It is this statistical oddity and not the absence of Earth System climate model variables that explains the RCBP. And yet, as seen in the literature, climate science reaches out to Earth System Models to explain and then to apparently solve the RCBP, as shown in a related post [LINK] . In summary, the Remaining Carbon Budget issue is a simple statistical issue that has been interpreted in climate science in terms of AGW climate forcing portfolio needed to implement carbon budgets.
  16. ISSUE#4: > WILL CLIMATE ACTION MODERATE THE RATE OF SEA LEVEL RISE? A principal argument for climate action has been the fear of sea level rise that threatens hundreds of millions of people in vulnerable small island states, low lying deltas such as Bangladesh, and coastal communities such as Florida [LINK] [LINK] [LINK] [LINK] and it is therefore proposed that climate action in the form of reducing or eliminating fossil fuel emissions must be taken to attenuate the rate of sea level rise [LINK] . The only empirical evidence presented to relate sea level rise to emissions is the paper by Professor Peter Clark of Oregon State University [LINK] [Reducing carbon emissions will limit sea level rise] . The Clark paper shows a strong and statistically significant correlation between cumulative emissions and cumulative sea level rise in the TCRE format and thus suffers from the same limitations as the TCRE in that there is no time scale and no degrees of freedom, and that the correlation derives from a sign pattern in that emissions are always positive and annual sea level rise values are mostly positive.
  17. TEST#1 > The correlation presented by the Peter Clark paper is evaluated in a related post and found to be spurious and illusory because it has neither time scale nor degrees of freedom [LINK] . This spurious correlation contains no information in terms of a causal relationship between emissions and sea level rise. It is necessary to test the correlation with time scale and degrees of freedom restored.
  18. TEST#2 > The Peter Clark correlation is tested in a related post [LINK] with finite time scales inserted. Time scales of 30, 35, 40, 45, and 50 years are used in the test. The correlation and detrended correlation between emissions and sea level rise are shown in the summary of results table in Paragraph#20 . A statistically significant positive correlation is required to support the causation hypothesis being tested. Although such correlations are seen in the source data, none of them survives into the detrended series where the correlations are negative. Note that source data correlations between time series data is influenced by shared trends and therefore have no interpretation in terms of responsiveness at a finite time scale. We conclude from these results that, although a significant correlation is seen between the cumulative values, no evidence of correlation between emissions and sea level rise is found in the data at finite time scales and with degrees of freedom restored. Thus there is no evidence that climate action in the form of reducing fossil fuel emissions will attenuate sea level rise.
  20. ISSUE#5 > THE IMPACT OF AGW ON TROPICAL CYCLONES:   This issue is presented in a related post [LINK]
  21. ISSUE#6 > THE IMPACT OF AGW ON SEA ICE: This issue is presented in three related posts [LINK] [LINK] [LINK] 












  1. The claimed causal connection between AGW climate change and the destructiveness of tropical cyclones did not emerge from the science nor from an extensive study of historical data but from an unlikely event in 2005 when Hurricane Katrina damaged a levee system that had not been properly maintained. The damage to the levee caused a catastrophic flooding of New Orleans that became the signature issue in the destructiveness of Hurricane Katrina as seen in the 2005-2009 reports in paragraph#2 below. The role of levee management in the destruction was downplayed and forgotten and the entire destruction was thus attributed to fossil fueled climate change with the subsumed climate action lesson of Katrina being that such destruction can and must be attenuated by reducing and eventually eliminating the use of fossil fuels.
  2. Hurricane Katrina Historical Notes: (i) HURRICANE KATRINA IS THE HARBINGER OF WORSE YET TO COME: The IPCC claimed that it had the scientific evidence to prove that our use of fossil fuels caused Hurricane Katrina to forecast with a great certainty that there was more to come in the 2006 hurricane season but the 2006 hurricane season turned out to be milder than normal. The IPCC blamed the dissipation of El Nino for the mild hurricane season in 2006 and issued a new warning that 2007 will be the hottest year on record and will bring a killer hurricane season worse than 2005 but the 2007 forecast also failed. The IPCC’s dream hurricane season has finally arrived in 2008 unannounced and unexpected with strong hurricanes Gustav and Hanna expected to be followed by Ike and a dozen others before the season is through. More info: [LINK] . (ii) The IPCC’s claim that Hurricane Katrina was caused by man-made global warming has been thoroughly discredited and their forecasts for more severe hurricane seasons in 2006 and 2007 have been proven wrong. They are merchants of fear and their method is the dissemination of convenient lies. More info: [LINK] . (iii) Climate science shows that AGW climate change is increasing the frequency and severity of extreme weather as for example Hurricane Katrina. Further research shows a causal link between AGW and increasing wave intensity that provides direct evidence of the extreme weather impacts of AGW. More info: [LINK] . (iv) 2009: In 2005 climate science declared that Hurricane Katrina was the harbinger of killer super storms yet to come created by fossil fueled global warming but after no further cyclone activity in the North Atlantic Basin in the next three years, new evidence for the destructiveness of AGW extreme weather was found in Cyclone Nargis in the North Indian Basin. Though not unusually strong, Nargis did create a freak storm surge in rising tides that swept up the Irrawaddy River in Burma and claimed a horrific death toll. Nargis thus became an AGW issue and climate scientists changed their extreme weather focus from the North Atlantic Basin to the North Indian Basin saying that Cyclone Nargis was a creation of climate change caused by fossil fuel emissions and as the harbinger of “destruction on a global scale” by human caused global warming. More [LINK] .
  3. The Climate Science of Hurricane Katrina:  It was thus that the climate science of the destructiveness of hurricanes did not predict Katrina but was in fact constructed from Katrina based only on the destructiveness of the flood caused by the break in the levee system and by discounting the greater climatology data that it was Wilma, not Katrina, that was by far the stronger hurricane of the 2005 season but Katrina, not Wilma, was clearly the better tool to sell AGW’s fear based climate action agenda. This relationship between climate science and real science is seen more clearly in the foundational and keynote paper by noted MIT climate scientist Professor Kerry Emanuel reviewed in detail in a related post [LINK] . There it is shown that the need by climate science to establish the fear of climate change in terms of hurricanes made it possible for Professor Emanuel to abandon all pretension to scientific principles and statistical rigor to publish in a peer reviewed journal a circular reasoning paper that begins with the assumption that AGW increases the destructiveness of hurricanes and then proves that AGW increases the destructiveness of hurricanes [LINK] .
  4. Yet another issue is that the single minded focus on the North Atlantic Basin (NA) for the detection of the impact of climate change on tropical cyclone destructiveness during periods when NA is unusually active is a form of circular reasoning; particularly so because NA by itself is not a globally important source of cyclone energy. An additional consideration is the finding by Knutson (2010) and others that total cyclone energy variance for a single basin is too large to come to meaningful conclusions about trends and recommended that only the aggregate of all six basins could contain useful trend information.
  5. There are six tropical cyclone basins in the world where tropical cyclones form.  These are the West Pacific (WP), South Indian Ocean (SI), East Pacific (EP), North Atlantic (NA), North Indian Ocean (NI), and the South Pacific (SP). The most intensive and active  basin is the West Pacific Basin where tropical cyclones are called Typhoons. The North Atlantic Basin, where tropical cyclones are called Hurricanes, is a lesser basin and not a significant source of total global cyclone energy. Of the other four basins, the South Indian Ocean basin is the most active. Together, WP and SI generate more than 60% of the total global cyclone energy with the East Pacific and the North Atlantic together coming in second with about 25% of the world’s cyclone energy. The North Atlantic generates about 14% of the world’s cyclone energy. The details of this comparison are tabulated in Paragraph#6.
  7. Since AGW climate change is proposed as a global phenomenon, its effect on tropical cyclones must be studied and understood only in terms of global measures of tropical cyclone activity and not in terms of convenient localized phenomena that fit the narrative or that might derive from a USA bias of American researchers and the American news media. Here we provide an integration and summary of three related posts where the global impact of AGW on tropical cyclone activity is measured as a global aggregate of all six cyclone basins.
  8. Study#1 > Trends[LINK] . The trend study presents data for total cyclone energy for all six basins for the 70-year study period 1945 to 2014. The object variable is the Accumulated Cyclone Energy (ACE) used as a measure of total cyclone energy. Knutson (2010) and others have suggested that year to year variance in cyclone energy is too large and random to draw meaningful interpretation of and recommended a decadal time scale for the study of tropical cyclone trends. Accordingly, the total global ACE for all six cyclone basins is computed for each of the seven decades in the 70-year study period. Trend analysis is carried out by comparing each decade against the other six. The results are summarized in the Table presented in Paragraph#9 below. They show that only two statistically significant differences are found. Specifically, we find that Decade#5 (1985-1994) and Decade#6 (1995-2004) show higher total global cyclone energy than Decade#1 (1945-1954). No other statistically significant difference is found among the seven decades studied.
  9. It is tempting here to conclude that the higher global cyclone energy in the two recent decades from 1985 to 2004 than in the decade 1945-1954 can and should be attributed to AGW climate change but there are other well understood considerations that explain this difference. It is well established and generally accepted in the tropical cyclone research community that the early decade in this study, 1945-1954, suffered from a measurement bias such that not all tropical cyclones were detected and of those that were not all were adequately measured. In other words the early data are incomplete and the incompleteness of the data provides a stronger and more rational explanation of the observed statistically significant trend in total cyclone energy. We conclude from these results that he data do not show an impact of AGW climate change in the form of increasing the destructiveness of tropical cyclones. 
  10. Study #2: > SST: [LINK] . Sea surface temperature (SST) is the link that connects climate change with tropical cyclone activity with the proposition that higher SST provides more energy for tropical cyclones that form on the basis of high SST. Cyclone theory tells us that cyclone formation, and intensification are related to SST (Vecchi, 2007) (Knutson, 2010). Testable implications of the theory for empirical research are derived from climate model simulations (Knutson, 2010). Knutson’s work also suggests that the high variance in tropical cyclone activity at an annual time scale or for any single cyclone basin means that data analysis must be carried out on a global basis for all six tropical cyclone basins and time scales longer than annual should be used. Detrended correlation analysis for total cyclone energy and SST are carried out at a decadal time scale 1945-2014. The results are tabulated in Paragraph#12. They show that the high correlation seen between total global cyclone energy (ACE) and global sea surface temperature (SST) derives from a rising trend in both time series and not from a responsiveness of ACE to SST at a decadal time scale.
  11. We conclude from the results presented in Paragraph#8 to Paragraph#12 that no evidence is found for the usual assumption in climate science that AGW climate change is intensifying tropical cyclone activity by way of SST.
  12. Study#3: > Pre-Industrial: [LINK] . The fundamental theoretical  basis for the theory of AGW climate change is a stark difference between “pre-industrial times” and the “era of the industrial economy” in terms of climate as assumed in climate science. A testable implication of the claimed impact of AGW climate change on tropical cyclones in terms of this dichotomy is that a comparison of the two eras should show a stark difference in tropical cyclone activity in terms of an absence of intense and destructive tropical cyclones in the pre-industrial era.
  13. The Treasure Coast Hurricanes of 1715 & 1733The Dreadful Hurricane of 1667, The Calcutta Cyclone of 1737, The Great Hurricane of 1780, The Great September Gale of 1815, The Coringa Cyclone of 1839, and The Last Island Hurricane of 1856, The San Diego Hurricane of 1858 are described and presented as tropical cyclones with intensity and destructiveness comparable to the high profile hurricanes cited by climate science as evidence of the impact of AGW climate change. We conclude from the comparison that it does not provide convincing evidence that tropical cyclones such as the destructive hurricanes cited by climate science as a creation of AGW are unique to the industrial economy that could not have occurred in pre-industrial times. It is also noted that the strongest and most destructive tropical cyclone of the post industrial era was the monster Bhola Cyclone [LINK][LINK]that killed half a million people in Bangladesh. It occurred way back in 1970 right in the middle of the 1970s cooling period[LINK]that had sparked fears of a return to Little Ice Age conditions[LINK] .
  14. CONCLUSION: The data and their interpretation presented in these posts reveal serious weaknesses in the claim by climate science that the industrial economy has caused greater intensity and destructiveness of tropical cyclones by way of global warming and rising sea surface temperature.







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