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No. We can quantify its radiative forcing via the well known 5.35 * ln(Ct/Cr) formula where Ct is the target concentration and Cr is the reference concentration. The difference between the Maunder Minimum and Modern Maximum is +0.25 W/m^2 (see Kopp 2016 and data). 2xCO2 comes out to 5.35 * ln(2) = +3.7 W/m^2 (see Myhre 1998). It is about an order of magnitude stronger than the solar forcing. For the Quaternary Period...mostly yes. But it is complicated and most of the lag claims are based solely on Antarctica (see Shakun 2012). For other eras like the hyperthermals...no. The Paleo-Eocene Thermal Maximum is an era in which CO2 catalyzed increases in temperature. The PETM is considered to be the best analog to the contemporary era. Yes. But these are terms that had always been meant to represent cool and warm eras in the North Atlantic region. They were never meant to be applied globally (see Lamb 1982). Globally temperatures have been relatively stable during the Holocene and especially the last 2000 years (see Kaufman 2020). No. Of course not. But neither do I believe that the position he advocates for aligns with the body of evidence either. The warming is likely unprecedented for the Holocene. Meh...it's complicated. Global warming will certainly shift the bell curve of extreme events to the right, but to claim that any one particular event is wholly attributable to global warming is a bigger stretch than most scientists are willing to make in the vast majority of cases.

TD21 is now Tropical Storm Vicky.

Right. I get that you don't accept the evidence that is contrary to the hypothesis...CO2 always lags T, CO2 forcing is small and insignificant, natural forcing is larger than anthroprogenic forcing, positive CO2 feedbacks do not exist, etc. What I'm asking is...what kind of evidence would you accept that would convince you that the above hypothesis are false?

So what kind of evidence would you accept that would falsify the natural hypothesis and convince you that the anthroprogenic hypothesis can survive falsification?

I had not read through that publication yet. Thanks. It is from the University of Washington in Seattle. It is an independent review. Summarizing the trends for the mid-troposphere in the tropical region... as-is tls-corrected UW-obs 0.115 0.160 UW-gcm 0.124 0.170 NOAAv3.0 0.105 0.149 RSSv3.3 0.089 0.125 UAHv5.6 0.029 0.064 UW deployed two analysis methods for handling the diurnal bias: obs for observational and gcm for global circulation model. They also corrected for the stratospheric cooling contamination in the tls-corrected column. UAH is clearly the outlier here.

Exactly. Which is why IGRA especially should not be used for climate research and the type of comparison's presented in the graph above.

Right. Okay. So that comes from Dr. Spencer's blog here and references their paper here. Note the following. 1. It is not independent. 2. This is not a comparison of the global surface mean temperature. It is a comparison of the more narrowly focused tropical region at the mid troposphere layer (which is probably contaminated by the cooling stratosphere BTW). 3. The radiosonde dataset is IGRA whose maintainers specifically warn against using for this type of comparison. 4. The reanalysis dataset is ERA. So based on this chart I'm left with the impression that ERA is the next "best" characterization of reality; according Dr. Spencer anyway. And guess what...ERA says the global surface warming trend is +0.19C/decade which is more inline with Berkeley Earth, GISTEMP, NOAA, RSS, etc. So while UAH may (I question the use of IGRA) have superior skill in the mid troposhere layer in the tropical region it is certainly an outlier on the broader and more widely disseminated global mean surface temperature measure. Given Dr. Spencer and Dr. Christy's history of focusing on the tropical mid troposhere I think this makes sense. But the thing is...most of the other datasets are designed to estimate the global surface temperature instead.

The guy brings up good points. Physical parameterization schemes are fraught with assumptions and other problems. Solving partial differential equations is done numerically only with errors that propagate (chaos theory). Model parameters must be approximated and tuned. Everybody who is anybody understands this. Global circulation models will NEVER be perfect; not even remotely. But...just like any other approximation of reality they still perform reasonably well and are quite useful. In fact, GCMs provide a reasonable (dare I say best) match to the contemporary warming era on decadal scales than any other type of model. Why then would anyone chose to abandon a model with demonstrable skill for an inferior model or no model at all? These kinds of arguments that Mr. Browning is making are what I often call "nuh-uh" arguments. Convince people that an imperfect, but useful model of reality should be abandoned in favor of inferior models or no model at all. Sorry, but I and most other scientists are convinced not by "nuh-uh" arguments but by "here's how to do it better" arguments. Show me a model that performs better than what we already have and I'll be all over it. And besides the implication here is that climate sensitivity is only determined via global circulation models. That could not be further from the truth. As I've already pointed out scientists consider many lines of evidence including modeling (radiative transfer models, energy budget models, GCMs, etc.), observational (paleoclimate, instrumental, etc.), and physical laws (thermodynamics, molecular physics, etc.) for determining climate sensitivity. It is possible that Mr. Browning is unfamiliar with the state of climate science in this regard. I don't know.

This is a challenge other scientists and myself must accept as well. Here is how I select the temperature dataset that best characterizes reality. In lieu of having any compelling reason to select a single representation of reality I equally weight and blend all of the representations available into an ensemble and use the mean as the "best guess" at reality. I take the month-to-month temperature anomalies from as many datasets as are available and let that be my baseline for comparison. When you do this you will see that UAH deviates significantly from the ensemble mean; more so then any other dataset. It is an outlier in most respects. To claim that UAH is the best is to claim that UAH has a monopoly on correctness and that all of the other datasets using wildly different techniques and available input data somehow managed to mistakenly come up with the same wrong answer. How likely do you think that scenario is? I'll answer that...not very likely. And I'd miss a great opportunity for discussion if I didn't point out that many weather forecasters use this same basic approach to make weather forecasts. I have no idea which model will best characterize the state of the atmosphere at some random point in the future. Sometimes the GFS does better. Sometimes the ECMWF does better. Sometimes the UKMET does better. How does one decide which to choose? Well...we don't. We blend them together into a model of models. You've probably noticed that the NHC heavily weights their official forecast on the TVCN and IVCN ensembles because historically the ensemble mean of many models performs better than any individual model alone. In fact, it is my understanding that the human element at the NHC was actually making forecasts worse (OFCL performed worse than TVCN and IVCN) and so the NHC forecasters were encouraged to essentially carbon copy the TVCN and IVCN ensemble means for track and intensities forecasts going forward. It was a lesson in humility that adding human intuition and feeling to the forecasts only made things worse.

I don't see how you can say UAH is the best. What dataset/model are you comparing UAH to to assess its "bestnest". And why did you select that dataset/model for comparison to begin with? Why not just call that chosen dataset/model the best? RSS used to use a GCM to make diurnal bias corrections. The academic community criticized them for it. They changed their methodology in this regard in v4. The warming trend went up. Perhaps the GCM method was more correct afterall? (see Mears 2017). Karl did not adjust SSTs upward. He gets SSTs from ERSST (see Karl 2015). I read the ERSSTv4 papers (see Haung 2015 part 1 and part 2 and supplemental). Now, understanding that I'm not an expert, I did not see any adjustments documented that I felt were mistakes. In fact, quite the opposite. I think it would be a mistake to omit these adjustments and not publish v4 of ERSST. BTW...I believe ERSST is now up to v5. And GISTEMP and others also uses ERSST as well. I don't know about the early 1800's but at least since the 1880's the unadjusted data show MORE warming; not less. (see figure 2B Karl 2015). And again...show me a dataset/model that you feel best characterizes reality so that we can make objective comparisons between it and UAH (or any dataset really). Justify why you think that chosen dataset/model best characterizes reality.

I have to be pedantic here...the cause of the +0.87 W/m^2 EEI is the net effect of ALL radiative forcing agents. CO2 is but one component. What you actually mean is...the dominating factor in the current +0.87 W/m^2 EEI is CO2. Though I must point out that other GHGs like CH4, N2O, O3, CFCs have significant components as well. There are some components for which the uncertainty envelope on their contribution is frustratingly large. I'll throw out clouds and aerosols as examples here.

I trust models to predict the location and timing of solar eclipses. I trust models to predict the behavior of drugs in my body. I trust models to predict how solutions to engineering problems will behave before those solutions are implemented so that I don't waste time and money. I trust models to produce temperature readings from RTDs and thermocouples. I trust models to produce satellite images of clouds and water vapor. I trust models to forecast hurricane track and intensities several days out. I trust models to forecast severe weather outbreaks. Everyone trusts scientific models and even bets their lives on them on a daily basis. We calibrate our trust based on the ability of the model to explain and predict observations. Invoking a model is not something to be ashamed of. It is something to embrace because if you aren't invoking a scientific model then you're just guessing.

I'm not aware of a NH or global temperature reconstruction published in a reputable peer reviewed journal that shows anything other stability during the most recent 2000 years of the Holocene. This is possibly the most comprehensive global Holocene temperature reconstruction to date. It is a composite of hundreds of datasets using various proxy techniques. https://www.nature.com/articles/s41597-020-0530-7 As you can see if anything the MBH98/99 reconstructions and "hockey stick" shape is a bit more "tame" compared to what we know today. Keep in mind that MBH98/99 is a NH reconstruction only.

That is a great paper! This is the kind of study that could very well end up being cited in the IPCC's AR6 report. And the bibliography is HUGE. Of note is that they estimate the EEI at +0.87 W/m^2 with an error of only +- 0.12. In terms of heat uptake dispatching 1% goes into the atmosphere, 4% into the cryosphere, 6% into land, and 89% into the hydrosphere.

ENSO does not create long term planetary scale energy imbalances. It just moves heat around. ONI has averaged 0.1 from 1979 to present with a trend of -0.028/decade +- 0.031. The AMOC, on the other hand, probably does play a big role. But scientists already consider its role. It helps explain the magnitude of the MWP and LIA in the North Atlantic during the holocene for example. It has also been invoked to help explain the last deglaciation (see Shakun 2012). It is believed the AMOC will play a critical role in the contemporary warming period in the not so distant future as well. The point...there are many agents that help drive the climate. They are all important and should be considered. That in no way takes away from the fact that CO2 (and other GHGs) plays a crucial role as well. We just happen to be living in an era where CO2, CH4, CFCs, O3, and other GHGs have dominated the positive side of the radiative forcing budget by about an order of magnitude.

That's right. Water so greedily absorbs IR radiation that it is completely absorbed in the skin layer. It is an effect that is exploited by IR lamps to keep our food warmer for longer than it would be otherwise in restaurants. I think this publication has been misinterpreted. This publication does NOT claim or even imply that IR radiation does not warm the ocean. It is quite the opposite actually. What it does do is present a hypothesis for the exact mechanism by which increased downwelling IR radiation causes the oceans to warm. In a nutshell the hypothesis is that a temperature gradient in the skin is reduced thus reducing the conductivity of heat from the subsurface to the ocean-air interface. Read what they conclude. and This publication is all-in that an increase in downwelling IR is consistent with broad depth oceanic heat content increases. and IR radiation is a mechanism by which the depths of the ocean warm. The paper even provides us with a microphysical mechanism by which the heat is "trapped" below the skin layer.

Yep. I'm well aware of that publication. It is authored by Dr. Christy and Dr. Spencer. First...they are the maintainers of the UAH satellite dataset so this is not an independent assessment. Second...they use the IGRA radiosonde dataset for the assessment. This dataset is NOT to be used for climate research. Let me just post the text as it appears exactly on the IGRA website. https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosonde-archive Third...notice what they've done in that graphic. This is not a global assessment of differences. It is a narrowly focused assessment centered on the tropical region in the mid troposphere. And only up to 2005 even though the paper was published in 2018. Fourth...look at the UW entry on the graph. That is the University of Washington which attempts to remove the stratospheric cooling contamination from both RSS and UAH. They come to a different conclusion than what this paper is advertising.

The Atlantic Meridional Overturning Circulation is a pretty compelling explanation for the swings in temperature on the periphery of the North Atlantic. I'm only aware of McKitrick and McIntyre's shots across the bow of that ship. In the two plus decades since MBH98 a whole squadron of ships have launched. All are still floating.

Nobody has erased the MWP or LIA. It has always be suspected that the MWP and LIA were most acute from Canada to Europe. Hubert Lamb, who was an early pioneer of MWP and LIA research and even coined the term "Medieval Warm Epoch", stated that the MWP was not global in nature and that many areas of the world actually cooled during this period (Lamb 1982). MBH98 and subsequent reconstructions of the holocene temperature have essentially confirmed what had already been believed regarding the matter. Mann definitely accepts that the MWP and LIA were real phenomenon (see Mann 2002). Like you said...there is tons of evidence. That same body of evidence says that global mean temperature response was far more muted than the North Atlantic temperature response.

It's not just a hockey stick, its a whole hockey league of hockey sticks now. There are so many hockey stick publications corroborating MBH98 that it's hard to collate them all anymore. I will post this recent study which I believe represents the best compilation of the available datasets and reconstruction of the holocene temperature to date. A global database of Holocene paleotemperature records And using that database... Holocene global mean surface temperature, a multi-method reconstruction approach

You've missed a crucial point. Moving heat around does not change how much heat the Earth is accumulating. It just moves it around. Heat accumulation/uptake is an instantaneous concept. It is not lagged in any significant way (with a caveat we can discuss later). Changes in solar radiation have an instant and immediately effect on Earth Energy Imbalance (EEI). What is lagged are the individual responses that arise from that trapped heat. Atmospheric temperature is a lagged response due mostly to the thermal inertia of the oceans. When you turn down the burner on a stove with a pot of water the water may continue to warm. But it will warm at a SLOWER rate if it continues to warm at all. Likewise, if you turn down the Sun the heat uptake of Earth will slow down if Earth continues to accumulate heat at all. All other things being equal of course. But what we observe is that both the total heat uptake and the atmospheric temperature have accelerated while EEI remains persistently high despite this warming since the Sun entered a more quiescent state. Energy trapping is instant. Atmospheric temperature response is what is lagged. The solar hypothesis is not being challenged from atmospheric temperature measurements alone. It is being challenged from total heat uptake, EEI measurements among other lines of evidence.

Sure. But... What we observe is an acceleration of the heat uptake and warming rates and roughly at about the same time the Sun began a more quiescent period. At the very least a quieter Sun would result in a reduction of the trapping of energy.

Let's be precise. The 2σ error on a 5yr centered mean 150 years ago is about 0.100C. 100 years ago it is about 0.085C. 60 years ago it is about 0.035C. Obviously everyone agrees that 0.1C error is larger than 0.035C of error. But I don't think many people are going to consider these measurements to be BS because of it. Source. Then it should have been easy to identify. Of course, you'd still have the problem of figuring out where all of that accumulated (aka "trapped") energy that GHGs yielded went if not into warming the atmosphere and hydrosphere. This is tough nut to crack for sure. Yes and no. First...that's no different than using Kepler's model of planetary motion or Einsteins model of general relatively to "prove" that the Sun is the primary component of Earth's movement in the solar system for example. I mean science constructs models specifically to address to question like these. It's ubiquitous across all disciplines of science so I don't see what the problem is here. Second...there are many observational lines of evidence that corroborate CO2's role while simultaneously eliminating other candidates (like the cooling stratosphere simultaneous with the warming troposphere and hydrosphere). And the various models like radiative transfer schems, energy balance, and GCMs are developed from observational evidence themselves. So if the implication is that "model" means "no observations" then that's not giving the state of the science a fair shake. Science constructs models that approximate reality. That's kind of the point of science actually. And when more than one model exists scientists, engineers, or other decision makers typically choose the one that provides the best match to reality with no more complexity than is absolutely necessary for the task. Ah...when you say model you actually mean "global circulation model". Not all climate models are GCMs, but GCMs are a type of climate model. The most primitive climate model came in the late 1800's (see Arrhenius 1896). Models got more sophisticated and by the 1950's were using radiative transfer schemes (see Plass 1956). By the 70's climate models achieved a level of sophistication requiring numerical weather prediction techniques via global circulation models. By the 1980's these GCMs were incorporating many GHG species, solar effects, aerosol effects, etc. (see Hansen 1988). Radiative transfer schemes themselves were improving as well (see Myhre 1998). We also have energy balance models (see Wild 2013). More to the point...in the GCM arena even the primitive ones from 30 years ago ended up performing reasonably well (see Hausfather 2020). So while they may be considered crude they still work well and are orders of magnitude more complex than their non-GCM counterparts appearing between 60-120 years ago. All models have problems. That's why they are only approximations of reality. It's a good thing scientists do not base their conclusions on future warming from GCMs alone. As expected. CO2 is both in a forcing AND a feedback relationship with the temperature. When something else catalyzes the temperature change CO2 acts via its feedback first and then as a forcing agent second to amplify the temperature change. When CO2 itself catalyzes the temperature change it acts as a forcing agent first and then via its feedback it will amplify the change through the perturbation of existing source/sink fluxes. It would be rather odd if we had discovered that CO2 lead the temperature changes during the glacial cycles. But there are other events in the paleoclimate record in which CO2 did lead the temperature. These include the hyperthermal events. The most notable of which and the one that is most analogous to the contemporary warning is the PETM. There was a sudden and dramatic release of carbon (possibly CH4 or CO2 or both) that preceded the hyperthermal just like the other ETMx events. Because it is a radiative forcing agent and because it is being released during an era in which other modulating factors have remained relatively unchanged or may have actually caused a cooling tendency. It has happened. Many times in fact. I would consider the glacial cycles of the Quaternary Period a flip from one extreme to another. But of course their have been snowball Earth and hothouse Earth conditions as well. But remember...H2O is a condensing gas. CO2 is non-condensing. H2O produces a radiative forcing but due to its condensing nature it is not considered a forcing agent since it cannot, on its own, catalyze a long term change in temperature. It is happy to remain in its stable equilibrium with the temperature via the Clausius-Clapeyron relationship all other things remaining equal. In other words, H2O can amplify an already catalyzed change, but it cannot actually catalyze that change on its own. Ocean currents are important. But not in terms in of Earth's Energy Imbalance (EEI). Ocean currents do not create energy or directly change EEI. Their contribution to the EEI is thus 0 W/m^2. CO2's contribution from 280 to 410 ppm is +2.0 W/m^2. That makes CO2 vastly more important to Earth's secular climate trends than ocean currents which only have a cyclic effect through their ebb and flow of heat transfer fluxes to/from the atmosphere and deep ocean and how this heat is distribution over the Earth. Yes it does. Quite literally in fact. In the context in which it is used in climate science the word "trap" means energy (and by extension heat) is accumulating via a planetary scale energy imbalance. This imbalance is currently +0.6 W/m^2. Therefore 0.6 W/m^2 is being "trapped" in the geosphere. CO2's un-equilibriated radiative force is a significant contributor to this "trapped" energy. The Sun is not THE control knob, but only A control knob. There are other factors that modulate the climate. It is the net effect of all of them matters. Sometimes the Sun does dominate. Sometimes volcanoes dominate. Sometimes orbital cycles provide the nudge to hit the tipping point. We just happen to be living in an era when GHGs are dominating. BTW...it's really easy to falsify the "It's the Sun stupid" hypothesis. First...like all main sequence stars the Sun brightens and warms with age. The rate is about 1% every 120 million years see (Gough 1981). The paleoclimate record shows secular cooling over million year time scales despite solar luminosity increasing. If the Sun where THE control knob then we should have expected the Earth to warm. But that didn't happen. This is the crux of the faint young paradox. Why was Earth so warm in the distant past when the Sun was significantly less bright? Second...over the contemporary warming period and especially since 1960 solar radiation has been mostly flat and has even started to decline in the most recent decades. Yet the warming rate didn't turn negative. In fact, the warming actually accelerated during this period and in complete opposition to total solar irradiance (see SORCE). This leaves only solar magnetic flux as a candidate for influence. But as I've pointed in other posts there are far too many problems with the galactic cosmic ray hypothesis to consider it a viable hypothesis at this point. I can provide references if necessary.

Hmm...I'm not sure what you mean by "artificially inflate". Here is RSS's paper describing their changes in v4. https://journals.ametsoc.org/jcli/article/30/19/7695/342699/A-Satellite-Derived-Lower-Tropospheric-Atmospheric RSS matches other observational sources including but not limited to. STAR: https://www.ncdc.noaa.gov/temp-and-precip/msu/global/mt/dec/ytd RATPAC: https://www.ncdc.noaa.gov/sotc/upper-air/201913 ERA: https://climate.copernicus.eu/sites/default/files/2020-08/ts_1month_anomaly_Global_ERA5_2T_202007_v01.csv Berkeley Earth: http://berkeleyearth.lbl.gov/auto/Global/Land_and_Ocean_complete.txt GISTEMP: https://data.giss.nasa.gov/gistemp/graphs_v4/graph_data/Monthly_Mean_Global_Surface_Temperature/graph.txt Cowtan & Way: https://www-users.york.ac.uk/~kdc3/papers/coverage2013/series.html JMA: https://ds.data.jma.go.jp/tcc/tcc/products/gwp/temp/ann_wld.html HadCRUT: https://crudata.uea.ac.uk/cru/data/temperature/ NOAA Global Temp: https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v5/access/timeseries/aravg.ann.land_ocean.90S.90N.v5.0.0.202007.asc All datasets are adjusted. That is a good thing. We want dataset developers and maintainers to make adjustments to correct for mistakes, biases, data quality issues, non-climatic effects, etc. That does not mean these datasets are fundamentally flawed. adjusted != flawed and adjusted == good And remember UAH makes all kinds of adjustments too. They don't even directly measure the temperature. They have to derive it using a complex model that maps microwave emissions from O2 molecules into a meaningful temperature. And they have to make adjustments to correct for things like orbital decay, diurnal drift, and instrument body effect. Then they have to homogenize the data to provide global coverage while dealing with subtle nuances in the polar regions. No source code is provided by UAH. Not that I think this is a problem. Many datasets decline to publish the details of their techniques. However many datasets like GISTEMP openly publish their source code for all to review. Out of the more than a dozen datasets in existence that publish a global mean temperature UAH is the outlier; perhaps even a lone outlier compared against the backdrop of the more well known GMST datasets. Many are suspicious that the UAH TLT product is being contaminated by the cooling stratosphere. RSS TLT != UAH TLT. RSS weights their TLT product much lower than UAH's TLT product. And from their TMT products it is RSS that has a better match to balloon observations. https://www.ncdc.noaa.gov/sotc/upper-air/201913 There are also data merging issues. https://journals.ametsoc.org/jtech/article/34/1/225/342433/A-Comparative-Analysis-of-Data-Derived-from Please review the published data linked to above concerning the global mean temperature. Scientists do have an idea. The uncertainty envelope is definitely wider in the past. But it is not infinitely wide. For example Berkeley Earth lists less than 0.10C for the annual mean error from 1880 onward. This is reduced to less than 0.07C error if using the 5 year centered running mean. Annual mean errors drop to 0.05C after 1960. The science says climate change IS a component. Even with non-climatic changes controlled for the Phoenix area trend is clearly upwards. It's hard to say how much of Phoenix's warming is due to the broad increase in the global mean temperature or more cyclic climate phenomenon like the PDO, AMO, etc. But we know from first principal reasoning that climate change HAS to be factor because temperature trends are a product of ALL modulating effects. https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=USW00093140&ds=14&dt=1 https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=USW00023183&ds=14&dt=1

The NSIDC extent change was -196k yesterday. The daily extent as of 9/1 is 4.004e6 km^2 and easily locks 2020 into 2nd place for the daily summer minimum.