StudentOfClimatology

Then tell me why the tree ring record represents the magnitude of previous CA droughts accurately?

What droughts are you referring to, specifically? The instrumental record is relatively short, so you run into sample-size issues when trying to analyze the proxy-instrument relationship. Interpolating it back in time can be tricky too because antecedent conditions governing tree growth can change.

And lol @ the bolded .. that's because you don't remotely have the qualifications to do it yourself

I'm an A.S student specializing in paleoclimate and seasonal forecasting. I've done tree ring analysis before.

I'm sure you could manage it. Interpreting tree rings doesn't require an advanced degree.

I would grant you that there's some uncertainty in the data, but I'm having a hard time seeing that it really has anything to do with temporal resolution. Tree rings are, by default, have basically 1-year resolution, right?

The authors do note that there is the possibility that a few years in the 16th century might possibly have been lower (due to the aforementioned uncertainty), but we're still talking a very long return period (centuries to millennia -- 3100 years according to their method).

The problem is there's so much contamination potential, given the slew of factors that influence tree growth, that isolating a single variable on a 1yr resolution using a tree ring proxy is extremely difficult. I would never attempt to do it myself.

Tree ring spacing is influenced by precipitation, temperature variation on multiple timescales , sunshine hours, wind speed/transevaporation rates, etc, and varies with different tree species. There are a lot of factors that need to be accounted for here.

What they're doing is risky and may flaw the entire study should there not be a way of isolating these phenomena and determining their role.

April 2015 snowpack in the Sierra Nevada was 5% of normal - unprecedented in snowpack record and 500 year tree-ring proxy.

http://www.nature.com/articles/nclimate2809.epdf?referrer_access_token=8U88K0Q

No tree ring proxy will capture snowpack variability on a year-to-year resolution. I'm fairly certain this paper doesn't claim otherwise.

The majority of the divergence between the satellite data and the radiosonde data can be attributed to the lack of spatial coverage in the radiosonde data. The RSS team did a thorough analysis of the this issue:

To account for the lack of spatial coverage in the radiosonde data, the RSS team sub-sampled the RSS data only in the regions where the radiosonde data measures. This corrected most of the divergence between RSS and the radiosonde data, suggesting that the lack of spatial coverage in the radiosonde is responsible for the majority of the divergence between the two.

http://www.remss.com/measurements/upper-air-temperature/validation

To illustrate the importance of sampling, we performed two comparisons using TLT data. In the first, we calculated area weighted global averages for each dataset, ignoring whether a given pixel in the satellite data was sampled by the radiosonde dataset - we will call these raw global averages. In the second, we calculated area-weighted dataset only using those pixels that were sampled by both the satellite and the radiosonde dataset. Note that this results in multiple versions of the subsampled satellite data, one for each radiosonde dataset.

Here we plot 5 time series for globally averaged HadAT data, the "raw" RSS and UAH time series, and the HadAT-subsampled RSS and UAH time series. In this case, differences between HadAT and both satellite datasets are reduced significantly by subsampling. This occurs for both the long-term trends and the short time scale differences.

It depends. If the cool bias isn't changing with time, it by definition won't affect the trendline.

They didn't just abruptly switch from LKS to IGRA after 1997. They had to correct for the inhomogeneity between the two datasets during the transition, and the IGRA dataset was/is warmer than LKS. The last adjustment to the LKS data was in 2004, which did not sufficiently correct for the cold bias noted in the literature, which finds a cold bias in the RATPAC data through 2006.

The IGRA data doesn't have this problem, and it matches the satellite data more closely than either RATPAC-A or RATPAC-B.

OK now that that is over, we can move on to the peer-reviewed studies you posted. Again, I find this above post to be misleading as well.

Fu/Randel found there were some cool biases remaining in LKS 1979-2004. First of all, RATPAC may have corrected for some of these biases since RATPAC is a bit warmer than LKS.

The majority of the divergence between the satellite data and the radiosondes can actually be attributed to the lack of spatial coverage in the radiosonde data

http://www.remss.com/measurements/upper-air-temperature/validation.

That said, you're referring to RATPAC-A, which matches the satellite data more closely than RATPAC-B (though the IGRA data is probably preferable). The RATPAC-B dataset runs warmer after 1997 due to the transition off LKS and onto IGRA station data from 1997-2005, as the two are relatively inhomogeneous. There have (so far) been no adjustments to account for the noted bias in the LKS data.

When RATPAC switched their primary radiosonde dataset, they needed to homogenize it for continuity. The problem is the cool bias in the earlier data was left uncorrected for, so the smoothed final product depicts a somewhat unrepresentative trendline in the timeframe of interest.

Second, the fact that there were cool biases 1979-2004 does NOT imply there are warm biases 2004-2015. You have provided no evidence of such. Your conclusion drawn from Fu/Randel is pure assumption and quite misleading.

It's not that there are warm biases now, it's that they have yet to correct for the cool biases in the data through 2005. Do you not think that cooler biases in the data through 2005 will affect the trendline?

There is considered to be moderate uncertainty associated with radiosonde data which could be in either the warm or cool direction. This does not limit the utility of radiosonde data vs MSU data, because MSU data is also considered to have comparable if not higher uncertainty.

The RSS team investigated the reasons for the differences between the satellite data and the radiosondes, and determined that over 80% of the divergence is due to the lack of spatial coverage in the radiosonde data. By sub-sampling the RSS data only in the regions where the radiosonde data measures, the trendline swerve brought back into relative agreement.

http://www.remss.com/measurements/upper-air-temperature/validation

In the long term, the radiosonde datasets and satellites have equal uncertainty estimates, according to AR5.

This is progress.

I'd also like an apology for all the names you called me when I pointed this out and an apology for de-railing the thread for a week because you couldn't admit this until now.

I'm sorry if I called you any names. Personal attacks are unproductive and uncalled for.

That said, I'm sticking with the consensus of the peer reviewed literature regarding the error potential in the radiosonde data. In the shorter term (<15yrs), most of the divergence between the two can be attributed to inhomogeneities in the radiosonde data.

Obviously this is all debatable still, and I'm sure you disagree, so I hope we can end this on a positive note.

Fine. I had a bizarre change of mind that lasted 15 minutes. The sentence in reference was wrong. I was wrong. Is that an adequate admission?

Getting back on topic, my initial argument still stands. The shorter term divergence between the satellite and radiosonde data can be largely attributed to inhomogeneities in the radiosonde data. The majority of the peer reviewed literature comparing the two reaches the same conclusion.

First, this is a butchering of the english language and I have a hard time that when writing the first version you could possibly have been intending the second version.

That's fine. You don't have to believe me, but I can tell you exactly what it is I meant.

Second, this is still inconsistent with previous posts which you described as mistaken.

There's nothing inconsistent about my re-worded quote. That's what I have and continue to imply regarding the extrapolation process, if that's what you're referring to.

Third, this is certainly inconsistent with your statement in the same post saying it is "merely an average of 85 stations"

That post is correct. A simple extrapolation with no interpolation between grids is a gridded average.

Every dataset is essentially a tuned conglomerate average. What RATPAC does is put the data into equally sized grids to account for areal bias, then extrapolates the data from these stations through the grid boxes they belong to. When there are multiple stations in a grid box, an interpolation procedure is done. When there is only only station in a grid box, no interpolation is done.

Here, I'll post my original quote, then I'll edit it to reflect what I was intending to convey.

Original quote:

Actually, I made a mistake. RATPAC does nothing in the way of gridding or spatial homogenization at all.

Re-organized quote:

Actually, I made a mistake. RATPAC does no spatial/gridding homogenization at all.

Is that better? I'll concede that the first quote was worded poorly, but I never believed they did no gridding. That would be ludicrous.

It's not just a matter of grammar either. The post began with "Actually I was mistaken" referring to his previous post where he talks about gridding. The following post is clearly, in context, a reversal in which he claims there isn't any gridding or spatial homogenization.

Maybe you interpreted it that way, but that's definitely not was I was trying to say. See my post below, I was referring to the idea that macroscale homogenization was taking place.

If you won't let this go, this roundabout will continue forever.

You were wrong, I'm not sure why you can't just drop it. Posting peer reviewed papers doesn't change what was said. The reason you're aggravating lots of people in here is because you can't drop it.

What was I wrong about? Everything I've said regarding the inhomogeneities in the radiosonde datasets is accurate, and can be verified with numerous peer reviewed analyses.

If you disagree or would like to discuss the issue, I'm happy to have a respectful, open-minded conversation with you about it. However, if you'd rather mischaracterize one of my posts in order build a strawman, please don't waste my time.

Pretty much this, I'm all for second chances but jesus....

For christ's sake, I never said they don't do gridding. I've explained what I was intending to say several times now. You don't have to believe me, but continuing this accusatory roundabout is pointless. Let it go.

Instead of continuing this pointless back and forth, let's have a scientific discussion regarding the inhomogeneities and uncertainties in the radiosonde data. I have more than 10 peer reviewed papers that I'm ready to post and discuss, should anyone be interested.

Mears et al 2012

http://images.remss.com/papers/Mears_JGR_2012.pdf

Multidecadal-scale changes in atmospheric temperature have been measured by both radiosondes and the satellite-borne microwave sounding unit (MSU). Both measurement systems exhibit substantial time varying biases that need to removed to the extent possible from the raw data before they can be used to assess climate trends. A number of methods have been developed for each measurement system, leading to the creation of several homogenized data sets. In this work, we evaluate the agreement between MSU and homogenized radiosonde data sets on multiyear (predominantly 5-year) time scales and find that MSU data sets are often more similar to each other than to radiosonde data sets and vice versa. Furthermore, on these times scales the differences between MSU data sets are often not larger than published internal uncertainty estimates for the RSS product alone and therefore may not be statistically significant when the internal uncertainty in each data set is taken into account. Given the data limitations it is concluded that using radiosondes to validate multidecadal-scale trends in MSU data, or vice versa, or trying to use such metrics alone to pick a ‘winner’ is an ill-conditioned approach and has limited utility without one or more of additional independent measurements, or methodological, or physical analysis.

So, saying "that's ridiculous" is unhelpful here. It's not ridiculous, as skier and I (and many others) interpreted your post exactly the same way. If you really did mean something else, then you chose one of the most poorly worded means to express yourself I've ever seen. To me, the grammar of your post so obviously meant exactly what skier is suggesting, that it is actually easier for me to believe that you were wrong and didn't like being called out, than that you honestly just worded your statement poorly and meant something that no reasonable person would interpret your post to have meant. And that's why skier is so combative with you.

Does that all make sense?

I understand why that post could be taken out of context. The use of the word "or" was a bad idea on my part because it creates a mutually exclusive appearance between "gridding" and "spatial homogenization".

However, I honestly did not intend for that to be the interpretation. I want to make that abundantly clear.

Another good paper by McCarthy et al 2008.

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.524.608

Abstract

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from tem-perature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quan-tifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combi-nation of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homog-enization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radio-sondes. 1.

A paper by Free/Siedel (2007) expanding on Fu/Randel (2005).

http://www.researchgate.net/profile/Dian_Seidel/publication/241620702_Comments_on_Biases_in_Stratospheric_and_Tropospheric_Temperature_Trends_Derived_from_Historical_Radiosonde_Data''/links/004635331e6260eb33000000.pdf

We have examined data from some of the stations used in RW as examples of inhomogeneities and found two possible reasons.

At several stations in the western tropical Pacific (e.g., Majuro and Truk), shifts in the sonde–satellite difference series occur around 1989–90, coinciding with changes in ground equipment and, at some stations, with the resumption of regular nighttime soundings, which had been sparse or nonexistent since the 1970s. These coincident changes, although not providing a clear reason for a shift, suggest that the shift in the differences could have come from a change in radiosonde observations. As RW pointed out, radiosonde temperatures do not shift noticeably around this time (top of Fig. 1). Since night observations were not avail- able, and since day–night differences were an important aspect of the LKS analysis method, the LKS team had no reason to suspect an inhomogeneity. Furthermore, because the adjustment method depends on differenc- ing the temperatures before and after a change point, it cannot adjust effectively for discontinuities that are masked by natural changes. Without a reference time series, there is no way to reconstruct the true temperature history when a change point coincides with a real

FIG. 1. MSU channel-4 equivalent temperature anomalies (K) at (top) Majuro from RATPAC radiosonde data and (bottom) Hong Kong from RATPAC radiosonde data (0000 and 1200 UTC combined). Only daytime data were used for LKS at Majuro. Arrow shows time of apparent downward shift in the satellite– sonde difference series shown in Randel and Wu (2006).

change in temperature. LKS deliberately chose not to use the satellite data as a reference so as to produce an independent time series that could be compared to the satellite temperature series, but this choice may have made it harder to detect or adjust for some changes. The shifts in LS satellite–sonde difference series around 1988 shown in RW at Singapore, Antofagasta, and Ascensio, similarly show no obvious changes in the LKS time series (not shown). Again, there were little or no night data for comparison.

As skierinvermont says, it's impossible to debate with someone who claims he didn't say one of his own direct quotes. Or someone who contradicts himself completely as in "RATPAC has no gridding" then "I never said RATPAC wasn't gridded." Just a total deceit in order not to admit being wrong.

Also, individuals who are banned aren't supposed to make new accounts in order to post under a different name. Admins need to track the IP address in this case. Also, SOC should be on a very short leash as a previously banned poster. How he can create another disruption (and the broad consensus was that SOC was the party responsible) and then not be permanently banned is a shock to me.

I didn't create any disruption. My words were clearly out of context.

The peer reviewed literature supports my point of view. This is Fu/Randel et al 2005, back when the radiosonde data was running colder than the satellite data, for the same reason(s) it's now running warmer.

http://acd.ucar.edu/~randel/JCli_2006.pdf

ABSTRACT

Temperature trends derived from historical radiosonde data often show substantial differences compared to satellite measurements. These differences are especially large for stratospheric levels, and for data in the Tropics, where results are based on relatively few stations. Detailed comparisons of one radiosonde dataset with collocated satellite measurements from the Microwave Sounding Unit reveal time series differences that occur as step functions or jumps at many stations. These jumps occur at different times for different stations, suggesting that the differences are primarily related to problems in the radiosonde data, rather than in the satellite record.

As a result of these jumps, the radiosondes exhibit systematic cooling biases relative to the satellites. A large number of the radiosonde stations in the Tropics are influenced by these biases, suggesting that cooling in the tropical lower stratosphere is substantially overestimated in these radiosonde data. Comparison of trends from stations with larger and smaller biases suggests the cooling bias extends into the tropical upper troposphere. Significant biases are observed in both daytime and nighttime radio- sonde measurements.

RATPAC has already been proven to be usable and highly accurate on 30+ year baselines. The one thing I don't trust is UAH at this point until I have 10+ years of more data. Global surface datasets continue to tick up quite strongly.

I agree with that. The problem is it's less reliable on <15yr baselines, due to regional differences in the magnitude of warming over time. Eventually, these differences smooth out, but a lot of the periodic divergence can be chalked up to a simple lack of coverage over the Southern Hemisphere and Pacific Ocean.

The quality of discussion in this forum has decreased dramatically recently, not because of SOC, but due to certain individuals who apparently have something personally against SOC, and thus are trying desperately to discredit him / run him off the board. Meanwhile, I've seen nothing from him that necessitates a banning (however, a ban could be argued for those responsible for the verbal attacks). As I said before, it's unprofessional, inappropriate, and speaks volumes of the characters' of the people engaging in this behavior.

I'm not sure why a discussion on climate needs to devolve into something nasty (actually I do: it's because people cannot separate their emotional instinctive response from their more emotionally detached intellectual response, and the way to accomplish this is through simple discipline).

I hope this forum improves in the future, as climate is an important subject that deserves attention. But productive discourse cannot occur if there are folks constantly attempting to derail the threads with personal attacks.

Thank you. I see it basically the same way.

I don't think skierinvermont has any personal vendetta against me, and frankly he doesn't sound like the kind of guy that would take things personally on an internet forum. He just doesn't trust me.

How can the level of discussion improve when you quote something SOC says and he responds saying he never said that? In my last post before Mallow closed the thread I quoted him and he responded by saying "I didn't say that." Well, it's a direct quote. It's just impossible to have a discussion when even the most basic facts are denied.

There was nothing "direct" about that quote, and you were clearly taking it out of context. You resorted to throwing personal attacks at me because, I believe, you realized your mistake but didn't want to admit it. I don't know, but I can tell you that I certainly did not intend to imply what you think I was implying.

Literally it's impossible for anybody to interact with him unless they are just agreeing with everything he says. You pretty much have to let him have his way with the whole forum if you want to avoid conflict. Good posters come in like Don and make an informative post and SOC responds with a bunch of mis-information clogging up the forum and it's impossible to correct that because SOC will go to the end of the earth to not admit anything he said was mistaken. If he posts lies or misinformation I will continue to point it out. If that clogs up the thread, we should be looking at the source of the lies and misinformation.

There was no misinformation posted in that discussion, and I think you know it. Everything I post here is based on peer reviewed literature and common sense. You don't have to agree with me, and I make mistakes sometimes just like everyone here, including you. That said, all I care about is objective science and honest debate. So, when I'm being unfairly called out, I'm going to respond to that.

And yet you're at the center of most of the discourse. How much do you donate? Serious question.

I have a sketchy history with a few posters here, unfortunately, most of it being my fault. That's the main issue and I think it's going to take time to heal. That being said, I make sure never to throw deragatory names and personal attacks around, because it's unproductive and hypocritical to do so.

Regarding the "donation" rumor, all I did was purchase a model subscription package. I have no idea where the mega-donor rumor originated, but it's not true.

Good god, I hope SOC donates a lot for the mods to look the other way. He IMO makes threads he posts in unreadable.

I'm not the problem this go around. I don't take anything personally here, but honestly I'm surprised at the low level of discourse displayed recently.

I've been trying to have a scientific-minded discussion with posters who deliberately take my statements out of context, attack my character, and call me names. I've tried to get the entire discussion moved into PM, to no avail. I've tried to provide peer reviewed literature a to better elaborate on my positions, to no avail.

So yeah, I'm at a loss as for what to do here.

Don't go there Nzucker. He hasn't done anything wrong otherwise and is entitled to his opinion. SOC is not the only one with a second account. I don't think anyone takes the TOS seriously unfortunately.

You've always been a passive-aggressive poster even after you moved into the warmer camp. You should have realized AGW was legitimate way back.

Thank you, very much appreciated. I've done my best to conduct myself professionally since I've been back.

If you're banned, you're not allowed to come back under a different username. This is a violation of the terms of service.

Mods, I suggest StudentofClimatology's account be suspended or deleted as he has admitted activity in violation of forum rules.

Don't assume what you don't know. After the model site was paywalled, I contacted the administrative team, explained who I was, and was given the okay to make a new account. I'm very thankful for that.

I was banned 4 years ago (as a teenager struggling with substance abuse). After the layoff, completing rehabilitation, and returning to finish my education, I was given a second chance to participate here. I've really enjoyed my time here since I've been back, and I hope to continue to improve as a poster.