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Wow. Eta is definitely highlighting the problem with the CI number needing to be spooled in. ADTv9 has it clamped at 1.3T/6hr so it can't catch up with the raw value quickly enough.

A raw T# > 8.0 suggests a sub 900mb cyclone. I'll go 895 mb 150 kts.

ADT continues to show intensification. ADTv9 is at 5.4 at 21:20Z ADTv8 is at 5.8 at 21:00Z And based on the satellite presentation in the last hour I would not be surprised to see another tick up on these T numbers with the next update.

According to the best estimate from this study anthropogenic manipulation of the climate made the 2020 Siberean Heat Wave 100,000x more likely as compared to a purely natural evolution of the climate.

It's complicated. First understand that this is not entirely unexpected. In fact, the IPCC AR5 WG1 prediction for SH sea ice, although significantly more uncertain than predictions for the NH, shows a slight preference for increases through about 2030 with the possibility of record highs persisting even through 2060 before things turn south (pun intended) down there too. I must caveat that by saying the uncertainty envelope does include the possibility of the secular decline starting around 2020 as well. The unfortunate state of affairs with SH sea ice is that our understanding of its behavior in a warming world is still quite nebulous compared to our understanding of NH sea ice behavior. Second understand that the see-sawing of temperatures and sea ice between hemisphere has been shown to occur during previous significant climatic change events so it is not unprecedented nor is it inconsistent with climatic shifts. Anyway here are some things to consider... The NH is characterized by ocean surrounded by land whereas the SH is land surrounded by ocean. This trivial fact accounts for the bulk of the differences between NH and SH sea ice behavior. The consequences of this can be quite dramatic and contradictory between the NH vs. SH. A positive phase of the Southern Annular Mode (SAM) is associated with increasing SH sea ice. Global warming tips the SAM toward a positive phase. ENSO negative/positive phases reinforce positive/negative SAM phases. The Montreal Protocol through its ban of CFCs, repair of stratospheric ozone, associated cooling tendencies and other effects on weather patterns has been linked to SH sea ice increases. Increasing GHGs actually have a cooling effect on the Antarctica continent itself especially during the SH winter when the upper atmosphere is often warmer than the surface. Remember, GHGs act like a thermal barrier preventing IR radiation from passing through. This causes the warm/cool side of the barrier to warm/cool further. Positive/negative lapse rates get more positive/negative. Antarctica often has a negative lapse rate during the winter so GHGs cause cooling at the surface and warming in the upper atmosphere. This effect (among others) suppresses polar amplification in the SH. Disclaimer...I'm not well informed regarding SH sea ice so hopefully others who know more about the behavior down there can chime in on points I've missed or mischaracterized. The main take away here is that sea ice is mainly a NH issue right now. Most scientists do not expect NH-style declines in sea ice down in the SH anytime soon. And the fact that the SH responds differently than the NH is probably more the rule than the exception.

HWRF gets this down to 937mb at landfall near the Nicaragua/Honduras border...nearly the same spot as HMON.

Using a simple extrapolation I'm going to guess 10.18e6 km^2 for the 2020 annual mean. This would be 2nd lowest between 10.163 in 2016 and 10.201 in 2019. The current 3rd lowest figure is 10.335 so I still feel pretty confident that 2020 will end at least in the bottom 3. In fact, even if 2020's freeze trajectory catches up to the 1981-2010 mean by year end we'd still see a finish in the bottom 3. And if freeze rates continue to stay muted then a new record low for the annual mean extent is a definite possibility.

As of 10/20 the NSIDC extent YtD mean is 10.26. This is a tad higher than the current record holder set all the way back in 2019 at 10.23.. The gap is closing though. I think there is a good chance that 2020 will at least end in the bottom 3 in terms of annual mean extent. A new record is certainly a possibility as well.

As of October 13th the 5 day NSIDC average extent is at a record low again beating out 2012.

https://apps.ecmwf.int/webapps/opencharts

Keep in mind that HadCRUT only covers 84% of the Earth. The nature of the coverage is such that the warming trend is biased low. Other datasets like those provided by NASA and Berkeley Earth address the coverage issue. And of course reanalysis datasets like that provided by ERA has homogeneous and complete coverage natively due to 3DVAR/4DVAR assimilation. Cowtan & Way 2013: Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends http://www.ysbl.york.ac.uk/~cowtan/applets/trend/trend.html When you apply the "kriging" technique to HadCRUT to correct for the coverage bias the warming trend is +0.191C/decade which is spot on with other datasets like ERA (+0.1910C/decade), BEST (+0.1908C/decade), GISTEMP (+0.190C/decade). Trends are valid from 1979-present. In terms of using UAH and RSS as a proxy for the surface warming trend RSS (+0.214C/decade) is closer to the consensus than UAH (+0.137C/decade).

Those are fair points. Two additional ones we might add... 8) UAH TLT may be contaminated by the cooling stratosphere. 9) Concerns with their satellite merging process have raised.

Copernicus just released the September 2020 report based off the ERA reanalysis. https://climate.copernicus.eu/surface-air-temperature-september-2020 It is the warmest September on record. This brings the warming trend since 1979 up to +0.1910C/decade +- 0.005. In the last 24 months the trend has increased by 0.01C/decade. Using the baseline defined in the IPCC Global Warming of 1.5C report and taking the average of the last 12 months from ERA the warming since the industrial revolution is now 1.3C.

It is hard. No one said it was easy. That does not mean that scientists are incapable of measuring the global mean temperature and quantifying the uncertainty in that measurement. The uncertainty envelope is narrow enough that conclusions about Earth's rate of warming can be made with confidence. FWIW...I think RSS's 0.214C/decade rate of warming is likely higher than the true surface warming rate. Taking the mean of a sampling of several satellite, balloon, surface, and reanalysis datasets suggests that the true surface warming rate is probably closer to the 0.18C/decade from 1979 to present. This means UAH and RSS probably underestimate and overestimate the true warming rate respectively. Interestingly when you equally weight UAH and RSS you get a warming rate of +0.175C/decade which is pretty close to the mean warming rate suggested by other datasets. As I've said before I do not prefer either UAH or RSS over the other. Remember...in lieu of any compelling reason to discount a line of evidence the skeptical thing to do is equally weight those lines of evidence.

ADT is not handling this storm well. ADTv8 score is 4.8 at 15:30Z but ADTv9 score is only 3.9 at 15:50Z with an estimated pressure of 988mb. Just a bit off...

Here are the relevant publications. Karl 2015: Possible artifacts of data biases in the recent global surface warming hiatus Haung 2015: Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4). Part I: Upgrades and Intercomparisons Haung 2015: Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4): Part II. Parametric and Structural Uncertainty Estimations Rennie 2014: The international surface temperature initiative global land surface databank: monthly temperature data release description and methods Karl did not adjust temperatures upward. The upward revised estimate in the warming trend was a product of changes to the inputs and methodology used to analyze those inputs. What he did was switch from ERSSTv3 to ERSSTv4 and incorporated the International Surface Temperature Initiative into the analysis. In his own words here are the changes that he felt were most impactful. an increasing amount of ocean data from buoys, which are slightly different than data from ships an increasing amount of ship data from engine intake thermometers, which are slightly different than data from bucket seawater temperatures a large increase in land-station data, which enables better analysis of key regions that may be warming faster or slower than the global average First, SSTs are increasingly being acquired from buoys (like the ARGO network) which have been shown be more accurate than ship measurements. This provides the opportunity to use the buoy data as a means of calibrating or bias correcting the ship data especially when there is adequate colocation of the two. ERSSTv4 does that. Second, there was a dramatic shift in ship measurement technique after WWII in which the dominant method switched from bucket thermometers to engine intake thermometers. ERSSTv3 assumed that all measurements were bucket style after WWII, but it was discovered that several ships were, in fact, still performing the bucket measurements even up to 2015. ERSSTv4 fixed this discrepancy. Third, the incorporation of the ISTI into the analysis improved spatial coverage of land temperatures especially in the Arctic where the warming is significantly higher than the global average. As a side note...John Christy (the primary maintainer of the UAH satellite dataset) is listed as a contributor to the ISTI dataset (see Rennie 2014 above) which Karl felt represented the biggest impact to the upwardly revised warming trend. And it's important to note that despite these changes the net effect of all adjustments to the data still results in a lower warming trend than would be computed otherwise over the entire period of record. Again...the warming is not a result of Karl's changes. Karl's changes result in a better estimate of the warming that was already there and which occurred because of the positive Earth Energy Imbalance which itself is driven by the net effect of all climate forcing agents. And besides, Karl is but one among many maintainers of the dozen or more datasets that publish a global mean temperature. His dataset is not significantly different from the other datasets.

18Z COAMPS is tame with the potential Yukatan landfall , but then explodes Delta into major hurricane in the GOM. One of those members is a cat 5.

And on the 6Z parallel GFS it is the other way around. Gamma ends up swallowing up Delta. It does seem like odds are increasing that we see a binary interaction.

12Z ECMWF is more aggressive with development now. It does seem like it is missing or at least underestimating initial development this year. 92L may end up developing enough that it tugs on Gamma and pulls that system north eventually as well.

There is a wide envelop of possible tracks from model guidance. GEFS shows it loitering in the GOM away from land for awhile. EPS shows it creeping south and hugging the coast. UKMET shows it moving into the northern GOM eventually.

Yet another study with significant implications. Official: Li et al 2020: Increasing ocean stratification over the past half-century Open access: use this link News article: Mixing of the planet’s ocean waters is slowing down, speeding up global warming, study finds, Washington Post, September 29, 2020 Abstract: Seawater generally forms stratified layers with lighter waters near the surface and denser waters at greater depth. This stable configuration acts as a barrier to water mixing that impacts the efficiency of vertical exchanges of heat, carbon, oxygen and other constituents. Previous quantification of stratification change has been limited to simple differencing of surface and 200-m depth changes and has neglected the spatial complexity of ocean density change. Here, we quantify changes in ocean stratification down to depths of 2,000 m using the squared buoyancy frequency N2 and newly available ocean temperature/salinity observations. We find that stratification globally has increased by a substantial 5.3% [5.0%, 5.8%] in recent decades (1960–2018) (the confidence interval is 5–95%); a rate of 0.90% per decade. Most of the increase (~71%) occurred in the upper 200 m of the ocean and resulted largely (>90%) from temperature changes, although salinity changes play an important role locally. This finding has a few implications. Reduced heat transport into the ocean depths means more heat is available to drive atmospheric temperatures upward. The faster warming of the ocean surface will reduce carbon uptake since uptake is inversely proportion to the ocean temperature thus resulting in less carbon buffering and an increase in the rate at which CO2 is accumulating in the atmosphere. The rate at which additional energy is becoming available to tropical cyclones is increasing. The increased stratification may disrupt the Atlantic Meridional Overturning Circulation causing it to slow down.

That is absolutely how the atmosphere works. Just considering ocean circulations alone is enough to explain persistent anomalies in atmospheric temperature. For example, if the AMOC slows down some regions will likely cool while others warm as the poleward heat movement is impeded. Sure, tropical cyclone activity (among other mechanisms) may increase and work to pull this heat poleward via atmospheric circulation as opposed to ocean circulation, but the distribution of that heat would almost certainly not be exactly the same as before. The paleoclimate record is convincing...climatic shifts do not work in perfect harmony between regional and global scales. The global mean temperature can warm while specific regional mean temperatures cool and vice versa.

Indeed, we are "rebounding" from the LIA. But "rebounding" is a NOT a cause. It is an observation. That rebound happened for a reason that likely includes many contributing factors. CO2 is certainly among those factors and its significance became most acute after 1950. UHI effects are NOT ignored. Every conventional surface based database I'm aware of gives the UHI effect its well deserved consideration. Berkeley Earth has a great publication detailing how much the UHI bias impacts global mean temperatures (see Rohde 2013). "We observe the opposite of an urban heating effect over the period 1950 to 2010, with a slope of -0.10 ± 0.24°C/100yr (2σ error) in the Berkeley Earth global land temperature average.. The confidence interval is consistent with a zero urban heating effect, and at most a small urban heating effect (less than 0.14°C/100yr, with 95% confidence) on the scale of the observed warming (1.9 ± 0.1°C/100 yr since 1950 in the land average from Figure 5A)." As you can see their conclusion is that the UHI effect is more likely to have a negative bias than a positive bias on global mean temperature trends after 1950 when the warming became most acute. The observed trends in the global mean surface temperature datasets is NOT a result of the UHI effect. It is a result of the planet actually warming.

This actually comes from Myhre 1998. Well...the 5.35 sensitivity parameter anyway. Myhre used radiative transfer models (LBL, NBM, BBM) using data from the well known HITRAN database. The logarithmic behavior was first diagnosed by Arrhenius 1896 so he usually gets credit for this mind numbingly simple back-of-the-envelope model of the climate system's response to changes in CO2 concentration. This model is so well know that it is typically regarded as common knowledge and is referenced ubiquitously often without citations in the climate community. BTW...Arrhenius' final computation (which is said have been very laborious) from 1908 using his more complex 1896 model yields 4C of warming for 2xCO2 (see Worlds in the Making by Arrenhius 1908). It is interesting that this falls comfortably within the official IPCC range and despite his primitive (by today's standards) understanding of the climate system. Wouldn't that be a remarkable feat of brilliance if his 4C estimate turns out to be close to the observed value?

The data says the Earth's climate was that steady for almost 2000 years on a global scale. Global/hemisphere proxy data temperature reconstructions do not ignore the MWP or LIA. Remember, the MWP and LIA were names given to periods of climatic shifts primarily in the North Atlantic periphery area (see Lamb 1982) though most scientist do accept some global influence albeit by a smaller amount. These North Atlantic sites are included in Holocene temperature reconstructions regardless. CO2 did lead temperatures in the past. The PETM is probably the best analog. Nevermind that an agent does not have to lead a variable for it to be a significant contributing factor to the trajectory of that variable anyway. CO2 is leading now because it is being released in huge quantities independent of any climate modulation.