Reddit reviews The Climate Files: The battle for the truth about global warming
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Read the linked papers:
CO2 is a greenhouse gas, but the debate is how potent of a climate gas CO2 is when added to our atmosphere. CO2 has increased from around 280 ppm in 1850 to around 410 in 2019 (due to human emissions), and in that time the temperature on earth has increased approximately 1 degC. Atmospheric CO2 looks to hit 560 ppm (double 1850-levels) late this century.
The potency of CO2 is expressed as "ECS"(Equilbrium Climate Sensitivity") in climate modeling. ECS expresses temperature increase at equilibrium from doubling CO2.
Due to climate's thermal inertia roughly half of a temperature change due to forcing is realized within 10 years, while 14-40% has still not arrived after a century. The IPCC in AR5 (2014) stated that ECS is "likely between 1.5 and 4.5" The climate models "CMIP5" cited by IPCC in AR5 have an average ECS of 3.2 *.
Lower ECS ~1.5 better fit satellite era observations. ECS can be estimated directly from data without climate models. AR5 WG1 stated "best fit to the observed surface and ocean warming for ECS values in the lower part of the likely range" (p.84). There is least uncertainty in temperature data after the start of satellite record ~1979, and for this timeframe ECS is estimated in 1.5-2 range [1], [2]
(In general, ECS-estimates vary based on temperature dataset**, choice of start- and end-dates, carbon-cycle*** modeling and warming attribution to other sources (overview)).
The significance of ECS=1.5 would be huge, implying almost no further warming this century. ECS of 1.5 will imply another 1.5-1=0.5 degC of eventual warming, while ECS=3.2 implies 3.2-1=2.2 degC eventual warming. ECS=1.5 thus implies four times less warming from CO2 increases this century than current IPCC models!
Removing multi-decadal oscillations from data yields ECS 0.5-1.5. Natural oscillations with multi-year periods such as El Niño(11y), AMO(~60y) and PDO(~50-60y) dominate data on the timescale since 1850. Climate models do not accurately [ch1.2] model these oscillations. Removing oscillations mathematically to isolate underlying warming results in much lower climate sensitivity than in AR5: ECS ~1.5,TCR ~1.2 on 150 years of instrumental data, and ECS=0.6 on ~1000 years of proxy-data. These papers remove oscillations without the need to attribute causes to them, but as some of the oscillations removed will be solar-induced, the work is related to the sections below.
Human CO2-emissions coincide with the end of the "Little Ice Age"(LIA) and with solar forcing transitioning from abnormally low to abnormally high. LIA had globally colder climate, coinciding with "Maunder" (1645-1715) and "Dalton"(1790-1830) solar minima. LIA average temperatures were 0.5-0.7 degC lower than Medieval Warm Period(MWP). 1850 at the end of LIA was unusually cold, is thus a poor baseline. Climate inertia should apply for solar as well as CO2-driven warming, implying a long post-LIA transient warming. Second half of the 20th century is the period of highest solar activity in the last 8000 years. A link between solar forcing changes and LIA/MWP has been found, so solar variation partially explaining modern warming up to the early 00ies is also plausible.
There is disagreement on if solar variability is "high variability" or "low variability"
Modeling solar activity is challenging because no direct measurements of solar variability exist prior to satellite record from ~1980, and because the record is "grafted" together from a data from many short-lived satellites, (review of challenges given in ch1).
CMIP5 uses a "low-variability" estimate of solar variation "PMOD" based on work by Kopp&Lean,
that has been strongly critized(ch9) for being an unverified theoretical model which implements alterations not recognized by the original experimental teams to drifts that are postulated but not verified. The alternative to "PMOD" are "high-variability" TSI-estimates such as that of Hoyt&Schatten that agree with "ACRIM" satellite data. Evidence that high-variability TSI-estimates are more accurate are:
Solar forcing variability is key to climate modeling, because just a 0.3% (5 W/m2) increase is enough to explain the 1 degC warming since 1850. TSI ~1360 W/m2 raises the earth's temperature from around -268 degC to 15 degC (283 degC), a gain of ~0.2 degC per W/m2.
"High-variability" TSI vary by 3-4 W/m2 over the past centuries, and could thus explain 50-80% of observed modern warming.
CMIP5 models are running hot as solar activity falls, indicating that variability in their solar forcing estimate is too low. Because solar forcing and CO2-concentrations co-incident rise 1850-2000, underestimating climate solar sensitivity would wrongfully raise CO2-sensitivity (ECS),explaining why:
Compensating for "high-variability" TSI-changes results in ECS<1.5. "Hoyt&Schatten" TSI-estimate results in ECS of 0.44. Paleo-analysis of climate, CO2 and sun variability similarly found ECS=0.5.
Persistent flaws in climate research are plausible, outside investigators have commented on the the tendency to downplay flaws in climate research and to withhold data requests.
* "TCR" (Transient Climate Response) is temperature change immediately after doubling CO2 gradually (before transients settle). TCR and ECS both express the potency of CO2, TCR is often lower than ECS by 30-40% (or 0.5-0.8 degC). TCR likely range is given as 1-2.5 degC in AR5.
** Estimates of ECS from data prior to 1979 require use of GIS/HADCRUT instrument records, adjusted by proprietary algorithms using climate models and homogenized which can create spurious warming. Audits of these datasets have uncovered data-quality issues, but datasets are generally hard to independently verify. The sea/surface global temperature record is only globally complete for the satellite era. A reason for skepticism is that recent warming is not corroborated by an accelerated sea level rise at tidal gauges. Prior to~1880 proxies are used, but suffer from «the divergence problem» of not describing recent warming.
***Carbon cycle simulations indicate TCR below 1
TESTING COPY PASTE OF TEXT:::: PLEASE IGNORE.
Read the linked papers:
CO2 is a greenhouse gas, but the debate is how potent of a climate gas CO2 is when added to our atmosphere. CO2 has increased from around 280 ppm in 1850 to around 410 in 2019 (due to human emissions), and in that time the temperature on earth has increased approximately 1 degC. Atmospheric CO2 looks to hit 560 ppm (double 1850-levels) late this century.
The potency of CO2 is expressed as "ECS"(Equilbrium Climate Sensitivity") in climate modeling. ECS expresses temperature increase at equilibrium from doubling CO2.
Due to climate's thermal inertia roughly half of a temperature change due to forcing is realized within 10 years, while 14-40% has still not arrived after a century. The IPCC in AR5 (2014) stated that ECS is "likely between 1.5 and 4.5" The climate models "CMIP5" cited by IPCC in AR5 have an average ECS of 3.2 *.
Lower ECS ~1.5 better fit satellite era observations. ECS can be estimated directly from data without climate models. AR5 WG1 stated "best fit to the observed surface and ocean warming for ECS values in the lower part of the likely range" (p.84). There is least uncertainty in temperature data after the start of satellite record ~1979, and for this timeframe ECS is estimated in 1.5-2 range [1], [2]
(In general, ECS-estimates vary based on temperature dataset**, choice of start- and end-dates, carbon-cycle*** modeling and warming attribution to other sources (overview)).
The significance of ECS=1.5 would be huge, implying almost no further warming this century. ECS of 1.5 will imply another 1.5-1=0.5 degC of eventual warming, while ECS=3.2 implies 3.2-1=2.2 degC eventual warming. ECS=1.5 thus implies four times less warming from CO2 increases this century than current IPCC models!
Removing multi-decadal oscillations from data yields ECS 0.5-1.5. Natural oscillations with multi-year periods such as El Niño(11y), AMO(~60y) and PDO(~50-60y) dominate data on the timescale since 1850. Climate models do not accurately [ch1.2] model these oscillations. Removing oscillations mathematically to isolate underlying warming results in much lower climate sensitivity than in AR5: ECS ~1.5,TCR ~1.2 on 150 years of instrumental data, and ECS=0.6 on ~1000 years of proxy-data. These papers remove oscillations without the need to attribute causes to them, but as some of the oscillations removed will be solar-induced, the work is related to the sections below.
Human CO2-emissions coincide with the end of the "Little Ice Age"(LIA) and with solar forcing transitioning from abnormally low to abnormally high. LIA had globally colder climate, coinciding with "Maunder" (1645-1715) and "Dalton"(1790-1830) solar minima. LIA average temperatures were 0.5-0.7 degC lower than Medieval Warm Period(MWP). 1850 at the end of LIA was unusually cold, is thus a poor baseline. Climate inertia should apply for solar as well as CO2-driven warming, implying a long post-LIA transient warming. Second half of the 20th century is the period of highest solar activity in the last 8000 years. A link between solar forcing changes and LIA/MWP has been found, so solar variation partially explaining modern warming up to the early 00ies is also plausible.
There is disagreement on if solar variability is "high variability" or "low variability"
Modeling solar activity is challenging because no direct measurements of solar variability exist prior to satellite record from ~1980, and because the record is "grafted" together from a data from many short-lived satellites, (review of challenges given in ch1).
CMIP5 uses a "low-variability" estimate of solar variation "PMOD" based on work by Kopp&Lean,
that has been strongly critized(ch9) for being an unverified theoretical model which implements alterations not recognized by the original experimental teams to drifts that are postulated but not verified. The alternative to "PMOD" are "high-variability" TSI-estimates such as that of Hoyt&Schatten that agree with "ACRIM" satellite data. Evidence that high-variability TSI-estimates are more accurate are:
Solar forcing variability is key to climate modeling, because just a 0.3% (5 W/m2) increase is enough to explain the 1 degC warming since 1850. TSI ~1360 W/m2 raises the earth's temperature from around -268 degC to 15 degC (283 degC), a gain of ~0.2 degC per W/m2.
"High-variability" TSI vary by 3-4 W/m2 over the past centuries, and could thus explain 50-80% of observed modern warming.
CMIP5 models are running hot as solar activity falls, indicating that variability in their solar forcing estimate is too low. Because solar forcing and CO2-concentrations co-incident rise 1850-2000, underestimating climate solar sensitivity would wrongfully raise CO2-sensitivity (ECS),explaining why:
Compensating for "high-variability" TSI-changes results in ECS<1.5. "Hoyt&Schatten" TSI-estimate results in ECS of 0.44. Paleo-analysis of climate, CO2 and sun variability similarly found ECS=0.5.
Persistent flaws in climate research are plausible, outside investigators have commented on the the tendency to downplay flaws in climate research and to withhold data requests.
* "TCR" (Transient Climate Response) is temperature change immediately after doubling CO2 gradually (before transients settle). TCR and ECS both express the potency of CO2, TCR is often lower than ECS by 30-40% (or 0.5-0.8 degC). TCR likely range is given as 1-2.5 degC in AR5.
** Estimates of ECS from data prior to 1979 require use of GIS/HADCRUT instrument records, adjusted by proprietary algorithms using climate models and homogenized which can create spurious warming. Audits of these datasets have uncovered data-quality issues, but datasets are generally hard to independently verify. The sea/surface global temperature record is only globally complete for the satellite era. A reason for skepticism is that recent warming is not corroborated by an accelerated sea level rise at tidal gauges. Prior to~1880 proxies are used, but suffer from «the divergence problem» of not describing recent warming.
***Carbon cycle simulations indicate TCR below 1
Read the linked papers:
CO2 is a greenhouse gas, but the debate is how potent of a climate gas CO2 is when added to our atmosphere. CO2 has increased from around 280 ppm in 1850 to around 410 in 2019 (due to human emissions), and in that time the temperature on earth has increased approximately 1 degC. Atmospheric CO2 looks to hit 560 ppm (double 1850-levels) late this century.
The potency of CO2 is expressed as "ECS"(Equilbrium Climate Sensitivity") in climate modeling. ECS expresses temperature increase at equilibrium from doubling CO2.
Due to climate's thermal inertia roughly half of a temperature change due to forcing is realized within 10 years, while 14-40% has still not arrived after a century. The IPCC in AR5 (2014) stated that ECS is "likely between 1.5 and 4.5" The climate models "CMIP5" cited by IPCC in AR5 have an average ECS of 3.2 *.
Lower ECS ~1.5 better fit satellite era observations. ECS can be estimated directly from data without climate models. AR5 WG1 stated "best fit to the observed surface and ocean warming for ECS values in the lower part of the likely range" (p.84). There is least uncertainty in temperature data after the start of satellite record ~1979, and for this timeframe ECS is estimated in 1.5-2 range [1], [2]
(In general, ECS-estimates vary based on temperature dataset**, choice of start- and end-dates, carbon-cycle*** modeling and warming attribution to other sources (overview)).
The significance of ECS=1.5 would be huge, implying almost no further warming this century. ECS of 1.5 will imply another 1.5-1=0.5 degC of eventual warming, while ECS=3.2 implies 3.2-1=2.2 degC eventual warming. ECS=1.5 thus implies four times less warming from CO2 increases this century than current IPCC models!
Removing multi-decadal oscillations from data yields ECS 0.5-1.5. Natural oscillations with multi-year periods such as El Niño(11y), AMO(~60y) and PDO(~50-60y) dominate data on the timescale since 1850. Climate models do not accurately [ch1.2] model these oscillations. Removing oscillations mathematically to isolate underlying warming results in much lower climate sensitivity than in AR5: ECS ~1.5,TCR ~1.2 on 150 years of instrumental data, and ECS=0.6 on ~1000 years of proxy-data. These papers remove oscillations without the need to attribute causes to them, but as some of the oscillations removed will be solar-induced, the work is related to the sections below.
Human CO2-emissions coincide with the end of the "Little Ice Age"(LIA) and with solar forcing transitioning from abnormally low to abnormally high. LIA had globally colder climate, coinciding with "Maunder" (1645-1715) and "Dalton"(1790-1830) solar minima. LIA average temperatures were 0.5-0.7 degC lower than Medieval Warm Period(MWP). 1850 at the end of LIA was unusually cold, is thus a poor baseline. Climate inertia should apply for solar as well as CO2-driven warming, implying a long post-LIA transient warming. Second half of the 20th century is the period of highest solar activity in the last 8000 years. A link between solar forcing changes and LIA/MWP has been found, so solar variation partially explaining modern warming up to the early 00ies is also plausible.
There is disagreement on if solar variability is "high variability" or "low variability"
Modeling solar activity is challenging because no direct measurements of solar variability exist prior to satellite record from ~1980, and because the record is "grafted" together from a data from many short-lived satellites, (review of challenges given in ch1).
CMIP5 uses a "low-variability" estimate of solar variation "PMOD" based on work by Kopp&Lean,
that has been strongly critized(ch9) for being an unverified theoretical model which implements alterations not recognized by the original experimental teams to drifts that are postulated but not verified. The alternative to "PMOD" are "high-variability" TSI-estimates such as that of Hoyt&Schatten that agree with "ACRIM" satellite data. Evidence that high-variability TSI-estimates are more accurate are:
Solar forcing variability is key to climate modeling, because just a 0.3% (5 W/m2) increase is enough to explain the 1 degC warming since 1850. TSI ~1360 W/m2 raises the earth's temperature from around -268 degC to 15 degC (283 degC), a gain of ~0.2 degC per W/m2.
"High-variability" TSI vary by 3-4 W/m2 over the past centuries, and could thus explain 50-80% of observed modern warming.
CMIP5 models are running hot as solar activity falls, indicating that variability in their solar forcing estimate is too low. Because solar forcing and CO2-concentrations co-incident rise 1850-2000, underestimating climate solar sensitivity would wrongfully raise CO2-sensitivity (ECS),explaining why:
Compensating for "high-variability" TSI-changes results in ECS<1.5. "Hoyt&Schatten" TSI-estimate results in ECS of 0.44. Paleo-analysis of climate, CO2 and sun variability similarly found ECS=0.5.
Persistent flaws in climate research are plausible, outside investigators have commented on the the tendency to downplay flaws in climate research and to withhold data requests.
* "TCR" (Transient Climate Response) is temperature change immediately after doubling CO2 gradually (before transients settle). TCR and ECS both express the potency of CO2, TCR is often lower than ECS by 30-40% (or 0.5-0.8 degC). TCR likely range is given as 1-2.5 degC in AR5.
** Estimates of ECS from data prior to 1979 require use of GIS/HADCRUT instrument records, adjusted by proprietary algorithms using climate models and homogenized which can create spurious warming. Audits of these datasets have uncovered data-quality issues, but datasets are generally hard to independently verify. The sea/surface global temperature record is only globally complete for the satellite era. A reason for skepticism is that recent warming is not corroborated by an accelerated sea level rise at tidal gauges. Prior to~1880 proxies are used, but suffer from «the divergence problem» of not describing recent warming.
***Carbon cycle simulations indicate TCR below 1