tag:blogger.com,1999:blog-9093436161326155359.post1972673316954778151..comments2024-03-28T06:43:02.954+00:00Comments on Variable Variability: Anthony Watts at AGU2015: Comparison of Temperature Trends Using an Unperturbed Subset of The U.S. Historical Climatology NetworkVictor Venemahttp://www.blogger.com/profile/02842816166712285801noreply@blogger.comBlogger254125tag:blogger.com,1999:blog-9093436161326155359.post-9735559682662838992016-06-20T03:29:22.311+01:002016-06-20T03:29:22.311+01:00Finally finished my end of the draft. Those equipm...Finally finished my end of the draft. Those equipment adjustments take time.<br /><br />Eventually, I'll do up a set of individual station graphs with MMTS/ASOS/CRS-adjusted data to show the effects -- yet more followup.<br /><br />This paper is a first step. "Further work is necessary."<br /><br />One thing's fer sher: I would never have been prodded into tackling equipment head-on were it not for the discussion that occurred above. Working out the methods and then applying them was both exiting (and a little hair-raising).<br /><br /><br />So I want to personally thank you all for your kind assistance and stimulating criticisms, and especially my dear VeeV who has provided this forum. Homogenization is a potentially very powerful tool, but, as you must know, it is tricky, particularly prone to systematic artifacts.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-26544349046635856742016-03-08T23:41:15.189+00:002016-03-08T23:41:15.189+00:00The mechanism is as follows:
Jp = 5Yb - 5ya (regi...<i>The mechanism is as follows:<br /><br />Jp = 5Yb - 5ya (regional)<br />Js = 5Yb - 5ya (subject station)</i> <br /><br />Aack! Typo. make that:<br /><br />Jp = 5Ya - 5yb (regional)<br />Js = 5Ya - 5yb (subject station) Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-2411980619437123022016-03-06T23:22:33.123+00:002016-03-06T23:22:33.123+00:00Sorry, slipped a decial point. -0.240 UAH6 (compar...Sorry, slipped a decial point. -0.240 UAH6 (compared with -0.270 USHCN).Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-31073475369455931202016-03-06T19:32:33.138+00:002016-03-06T19:32:33.138+00:00Evan Jones writes: "Trend UAH6.0 CONUS: Tmean...Evan Jones writes: "Trend UAH6.0 CONUS: Tmean -2.40"<br /><br />And vs RSS V4?<br /><br />Or STAR?Kevin O'Neillhttps://www.blogger.com/profile/06692943768484857724noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-34934114054135013712016-03-06T19:32:10.411+00:002016-03-06T19:32:10.411+00:00In order to improve accuracy on the individual sta...In order to improve accuracy on the individual station reliability level, one might well correct station change by running the above process through multiple iterations, a sort of crude homogenization process. Won't shake the regionals much, and it would rope the mavericks. Sans systematic error, it is to be hoped. #B^)<br /><br />Maybe I'll do it for followup. (Via the Excel hand crank.)Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-52621836948467285092016-03-06T18:20:19.118+00:002016-03-06T18:20:19.118+00:00Yes, of course.
Trend CRN 2005 - 2014 (C/decade):...Yes, of course.<br /><br />Trend CRN 2005 - 2014 (C/decade): Tmean -0.270, Tmax -0.221, Tmin:-0.318<br /><br />Trend USHCN (TOBS data):<br />TMEAN Class 1\2: -0.360, 3\4\5: -0.408 <br />TMAX Class 1\2: -0.448, Class 3\4\5: -0.492<br />TMIN Class 1\2: -0.248, Class 3\4\5: -0.336<br />TMEAN CRS-only, all classes: -0.551<br /><br />Trend UAH6.0 CONUS: Tmean -2.40<br /><br /><br />That CRS is a headbanger. Both on the way up from 1979 and on the way down from 2005.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-52089133371903885472016-03-06T14:58:11.631+00:002016-03-06T14:58:11.631+00:00Okay, here is the method for determining equipment...Okay, here is the method for determining equipment jumps:<br /><br />Compare the jump in each station within each of the 9 Climate regions with the average of the jump of the average of all eligible stations within the region.<br /><br />The interval for determining the jumps is five years in either direction, and applied starting the year after conversion. This is necessary as the jumps are not instantaneous and to calculate the jumps from the month of conversion would reduce the jump. A jump takes ~2 years to manifest itself fully, so applying the full results a year later balances the equation very nicely.<br /><br />Tmax and Tmin are calculated separately. Mean is problematic: For a station with little trend in either max or min will be<br /><br />Eligibility is determined as follows: Unperturbed stations are used. A station can be any sort of equipment (CRS, MMTS, or ASOS), however, there must be no equipment change within 5 years prior or within five years subsequent, or station being used for pairwise will be contaminated by equipment change, itself.<br /><br />As with both Q-91 and H&L-06, USHCN metadata is used. (However, to NOAA's credit, there has been a vast improvement in metadata since 2006.)<br /><br />This allows us a much larger station base than H&L-06 or Q-91, with at least 10 stations used for each pairwise, and in many cases, more than 30.<br /><br />The mechanism is as follows:<br /><br />Jp = 5Yb - 5ya (regional)<br />Js = 5Yb - 5ya (subject station) <br /><br />Jf = Js - Jp<br /><br />Where:<br />Js = Jump (subject station)<br />Jp = Jump (regional)<br />Jf = Final jump (to be applied to each month starting 1 year after conversion).<br />5Yb = Average of 5 years prior to jump<br />5Ya = Average of five years subsequent to the jump<br /><br />Jumps are applied before CRS-bias adjustment or else the jumps would be a lot smaller. I round this against our hypothesis for the nonce. <br /><br />Also, raw data shows greater jumps than anomalized. So we use raw. Despite its drawbacks, raw data must be used, as we do not want the 10-year comparison interval to be contaminated by events outside the 10-year comparison span. They must be strictly separated.<br /><br />We use all classes station to determine pairwise owing to the relative dearth of Class 1\2 stations. This skews the results somewhat against the Class 1\2s.<br /><br />And indeed, the resulting jumps net out at near-zero for Class 3\4\5s, and falls exclusively on the Class 1\2s, raising Tmean trend by ~0.04 (prior to CRS trend adjustment), which is close to the findings in Menne (2010).<br /><br />My results suggest is indeed possible that there is an overlap effect of microsite effect and jump effect in the Class 3\4\5 stations. However, we are concerned more with the results of the Class 1\2s, because that more closely resembles the "real-life" trend.<br /><br />Jumps for individual stations of all classes have wide variation, consistent with the findings of both Q-91 and H&L-06. In any case, one cannot reliably apply the same jump to all stations within a region. It must be worked out individually, as above, and even so, there is some risk of conflation with unrelated events concerning individual stations. But that is a vital first step. <br /><br />In followup, I plan to expand the pairwise sample to include stations with "partial" unperturbed records. This would not only make the pairwise yet more robust, but also our basic trend findings, as well, in regions with lower coverage. But as that involves varying baselines for varying start-points, it will be dealt with in followup.<br /><br />If anyone has any questions as to the above methods, please feel free to ask (shout, tear out hair, whatever), and I will be happy to answer.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-75197520575216978832016-03-06T13:51:37.155+00:002016-03-06T13:51:37.155+00:00Evan, could you express these percentages in °C? T...Evan, could you express these percentages in °C? That would make it clear to the reader how small the numbers are that you are interpreting as real. For example, the differences in trend between USHCN and USCRN. <a href="http://variable-variability.blogspot.com/2015/06/COOP-United-States-Climate-Reference-Network-USCRN-stations.html" rel="nofollow">I did not dare to interpret them.</a><br /><br />USCRN is not "official ongoing record". It is much too short to be climatologically useful yet. <br /><br />Didn't the mitigation skeptical movement learn anything from their "hiatus" debacle? I know Anthony Watts like to cover up his mistake by calling it "Karlisation", what it actually is is another case of excessive (proclaimed) convinced in minute deviations. If there is anything Karl et al. (2015) showed it was how enormously fragile that deviation WUWT & Co. likes so much was. And how stupid it is not to consider the arguments of experts trying to help you and avoid making a fool of your movement. <br /><br />Why don't you tell the people you real reasons to be against mitigation. (Not here. This is a science blog.) These reasons convinced you, why wouldn't these reasons convince others as well?Victor Venemahttps://www.blogger.com/profile/02842816166712285801noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-9743418593490545032016-03-06T13:29:36.801+00:002016-03-06T13:29:36.801+00:00As for sats, compare UAH6.0 and USHCN trends with ...As for sats, compare UAH6.0 and USHCN trends with CRN trends from 2005 - 2014.<br /><br />You will find that HCN exaggerates the cooling trend by ~50%. <br /><br />As USHCN was discontinued as the official ongoing record in 2014, it seems that NOAA is happy to ride HCN trend exaggeration up -- but not ride it down. Instead, it changes the bus to CRN. You will also find the CRS bias demonstrated: MMTS cools over 20% faster than MMTS -- and this is for all Classes of stations (1 to 5).<br /><br />UAH is much closer in terms of trend to CRN than is USHCN. <br /><br />UAH6.0 shows ~13% less cooling from 2005 - 2014 than CRN, which suggests that during a warming trend, UAH will show ~13% less warming than is actually occurring on the ground. So surface should be a somewhat higher trend than sats during our study period.<br /><br />So when adjusting for CRS bias we do not baseline the CRS record to UAH, but to 13% higher than UAH.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-88845909483517107312016-03-02T16:21:09.945+00:002016-03-02T16:21:09.945+00:00Evan - I'll ask again regarding your statement...Evan - I'll ask again regarding your statement: ""The adjustments made to sat data are large but fairly simple."<br /><br />My response was: "LOL. You can't make this up. Has any layman ever actually taken the raw satellite data and duplicated any satellite temperature series? Anyone?"<br /><br />Well, has any layman ever reproduced a satellite temperature series from raw data? Anyone? Ever? <br /><br />The satellite series are just one 'blackbox' after another per your interpretation. Kevin O'Neillhttps://www.blogger.com/profile/06692943768484857724noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-88784525473492302282016-02-28T20:18:51.312+00:002016-02-28T20:18:51.312+00:00Yes, quite. A sine qua non. I am currently checkin...Yes, quite. A sine qua non. I am currently checking my results (I'll report any changes) and fill y'all in on the method.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-83443579955972484282016-02-27T23:08:32.820+00:002016-02-27T23:08:32.820+00:00Any questions?
Yes, how did you compute these adj...<i>Any questions?</i><br /><br />Yes, how did you compute these adjustments? The methods section of a paper is normally the most important one.Victor Venemahttps://www.blogger.com/profile/02842816166712285801noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-69116033782273035312016-02-27T23:07:04.092+00:002016-02-27T23:07:04.092+00:00UAH6.0 is closer.
Hard to believe UAHv6.0 has a b...<i>UAH6.0 is closer.</i><br /><br />Hard to believe UAHv6.0 has a better fit with USCRN than the fit of USHCN with the USCRN. <a href="http://www.theguardian.com/environment/climate-consensus-97-per-cent/2016/feb/08/no-climate-conspiracy-noaa-temperature-adjustments-bring-data-closer-to-pristine" rel="nofollow">The fit of the USHCN is very close.</a> <br /><br />I guess it really has to be version 6.0, right? Given the large differences between the versions. Do you have computation that actually shows this closer fit?Victor Venemahttps://www.blogger.com/profile/02842816166712285801noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-13763432138759682312016-02-27T23:00:52.150+00:002016-02-27T23:00:52.150+00:00And, as I have said, it will work -- provided alwa...<i>And, as I have said, it will work -- provided always there is not a systematic bias in the data.</i><br /><br />The validation with simulated data by Claude Williams and colleagues (2012) shows that the homogenization algorithm of NOAA can remove temperature trend biases. The Time of Observation bias is also a cause of a trend bias in the USA. If you do not explicitly correct this bias, the homogenization method of NOAA does it. Clearly it can remove biases.<br /><br />Claude Williams Jr, Matthew J. Menne, and Peter W. Thorne, 2012: <a href="ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/v2/monthly/algorithm-uncertainty/williams-menne-thorne-2012.pdf" rel="nofollow">Benchmarking the performance of pairwise homogenization of surface temperatures in the United States</a>. <i>Journal Geophysical Research</i>, <b>26</b>, no. 3, pp. 345–381, doi: <a href="http://dx.doi.org/10.1029/2011JD016761" rel="nofollow">10.1029/2011JD016761</a>.<br />Victor Venemahttps://www.blogger.com/profile/02842816166712285801noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-77307514461618973382016-02-27T22:05:48.842+00:002016-02-27T22:05:48.842+00:00Obviously Evan Jones hasn't shown up to tell u...<i>Obviously Evan Jones hasn't shown up to tell us the results of latest adjustments</i><br /><br />Just finished. Results are not far from Quayle (1993).<br /><br />All: Tmax -0.29, Tmin:+0.26 (Quayle is -0.4, +0.3)<br />Class 1\2: Tmax -0.20, Tmin: +0.09<br />Class 3\4\5: Tmax +0.30, Tmin +0.30<br /><br />This varies by region, obviously, but that's the average for all unperturbed stations.<br /><br />As you can see, the Class 1\2 trends are increased by the jump and Class 3\4\5s are largely unaffected. So the full brunt of the jump adjustments fall upon the well sited stations.<br /><br />And, to maximize the jumps I applied the results <i>before</i> adjusting for CRS, not after.<br /><br />As with both Quayle and H&L, results can be large for individual stations and in either direction. They got that right.<br /><br />The results will be applied immediately, as indicated in my posts above.<br /><br />Any questions?Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-83974862839071182402016-02-27T21:49:33.005+00:002016-02-27T21:49:33.005+00:00Empirical demonstration that adjusted historic tem...Empirical demonstration that adjusted historic temperature station measurements are correct, because they match the pristine reference network<br /><br /><br />I ran 'em myself (2005 - 2014). They don't. UAH6.0 is closer.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-43867676837769793692016-02-27T21:47:06.759+00:002016-02-27T21:47:06.759+00:00I ticked off the results of homogenization. You ma...I ticked off the results of homogenization. You made your own list. It's quite clear what is going on, writ large.<br /><br />And, as I have said, it will work -- provided always there is not a systematic bias in the data. There is. And the results are just as expected and rather easily explained. But it can be fixed, if you are willing to do it. Account for Microsite bias. Account for CRS Tmax bias. Then you're golden. Not until.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-44588262752317563752016-02-27T19:25:24.860+00:002016-02-27T19:25:24.860+00:00Hilarious. Homogenization a black box??? Just beca...Hilarious. Homogenization a black box??? Just because they refuse to look into it?<br /><br /><a href="http://www.meteobal.com/climatol/DARE/#Homogenization_packages" rel="nofollow">The homogenization algorithm of NOAA, they keep on fretting about, is open source software.</a> <br /><br />If that is too complicated for them, they can have a look at the method of Kevin Cowtan, who <a href="http://www-users.york.ac.uk/~kdc3/papers/homogenization2015/homog.pdf" rel="nofollow">only needed 150 lines of code for a basic homogenization method</a>. <br /><br />If something is a black box, it is all the computations WUWT makes for their press releases on their manuscripts that are always about to be submitted. Since 2012.Victor Venemahttps://www.blogger.com/profile/02842816166712285801noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-29459442477939753472016-02-27T18:45:14.099+00:002016-02-27T18:45:14.099+00:00Obviously Evan Jones hasn't shown up to tell u...Obviously Evan Jones hasn't shown up to tell us the results of latest adjustments, but it's quite instructive to read his <a href="http://wattsupwiththat.com/2016/02/17/how-not-to-measure-temperature-or-climate-change-96/" rel="nofollow">most recent comments in his safe haven at WUWT</a> on Feb. 17-19.<br /><br />"<i>All surface station data (arguably other than CRN) is bad data.</i>"<br />Yes, so let's discuss Hausfather et al 2016.<br /><br />"<i>One cannot achieve perfection. But sometimes one can identify issues and improve otherwise downright incorrect data to the level of usefulness.<br /><br />Or, as in the case of NOAA, make it worse."</i><br />Disregarding every piece of research ever done on the topic.<br /><br /><i>"When VeeV wants me to feed my stuff into his black box, my impulse is to infer (from the results) what is going into the black box and create on my own a cruder, but entirely transparent and understandable box that can be understood and discussed — positively or negatively — by anyone."</i><br />So, homogenization is a blackbox? <br /><br />"<i>The best way to ensure the best result is complete transparency of method. No black boxes need apply."</i> <br />I really don't think Evan understands the concept of 'blackbox.' <br /><br />"<i>The adjustments made to sat data are large but fairly simple."</i><br />LOL. You can't make this up. Has any layman ever actually taken the raw satellite data and duplicated any satellite temperature series? Anyone? <br /><br />There's no indication Evan and company have really changed at all. They have a hypothesis and *every* new piece of data confirms it. The 2012 "pre-release" paper had an uncounted number of errors, but none of them changed the conclusion. Every piece of research shows that hommogenization works, but it doesn't change their conclusion. USCRN matches USHCN, but that doesn't change their conclusion.<br /><br />Basically, there is *zero* evidence that can ever change their conclusion.Kevin O'Neillhttps://www.blogger.com/profile/15751040367339659805noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-14204327032577953052016-02-08T23:52:05.037+00:002016-02-08T23:52:05.037+00:00How strange that Evan has not 'splained in res...How strange that Evan has not 'splained in response to my most recent comment. Maybe he does not understand the issue, so I'll be explicit: <br /><br />Watts's and Evan's entire endeavor's sole nominal purpose is to create a semblance of a "pure" surface station temperature record--a record that is unsullied by microsite influences. They are attempting to approximate the record that would have resulted from stations lacking microsite "problems." Their attempt involves sampling and adjustments that they admit are destined to result in a record less pure than what would be gotten from physical stations that always lacked microsite "problems."<br /><br />But there is in fact such a "pure" set of physical stations--the Reference Network. Watts's and Evan's constructed record can only be hoped to be nearly as pure as that one.<br /><br />The new paper by Hausfather, Cowtan, Menne, and Williams shows unequivocally and more thoroughly than any efforts before, that the current homogenization scheme already succeeds in making the record indistinguishable from the reference network. So the existing homogenization scheme already accomplishes what Watts and Evan nominally are struggling to accomplish.<br /><br />So Watts and Evan are wasting their time. Their nominal goal already has been met by other people. <br /><br />But of course their <b><i>real</i></b> goal is to show that the current homogenization scheme does <b><i>not</i></b> produce a record nearly identical to the reference network. So they have failed to meet their real goal, and there is no hope of them meeting that goal--ever. Ever. Really. <br /><br />It would be genteel for them to admit they were wrong.Tom Daytonhttps://www.blogger.com/profile/14033524810322903771noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-68047149803278930972016-02-07T18:21:35.173+00:002016-02-07T18:21:35.173+00:00Empirical demonstration that adjusted historic tem...Empirical demonstration that adjusted historic temperature station measurements are correct, because they match the pristine reference network: Evaluating the Impact of Historical Climate Network Homogenization Using the Climate Reference Network, 2016, Hausfather, Cowtan, Menne, and Williams. http://www-users.york.ac.uk/~kdc3/papers/crn2016/background.html<br /><br />Evan, you got some splainin to do.Tom Daytonhttps://www.blogger.com/profile/14033524810322903771noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-77032744418464625372016-02-07T15:08:24.389+00:002016-02-07T15:08:24.389+00:00Over at Nick Stokes Olof commented:"The lates...Over <a href="http://moyhu.blogspot.com/2016/02/satellites-surface-temperatures-up-in.html?showComment=1454842518363#c3093803451423687897" rel="nofollow">at Nick Stokes Olof commented:</a>"<i>The latest Ratpac A data is out now. The troposphere temperature 850-300 mbar is skyrocketing, winter (2 months of 3) is up by 0.25 C from autumn.<br /><br />At the peak of the 1998 el Nino (spring season), Ratpac and UAH v6 were quite similar in 1981-2010 anomalies. Now,in the present winter season Ratpac leads by 0.4 C...</i>"<br /><br />Someone will need to analyze microsite on those radiosondes - I'm sure that must be the problem.Kevin O'Neillhttps://www.blogger.com/profile/15751040367339659805noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-78891885615510066292016-01-30T02:50:05.649+00:002016-01-30T02:50:05.649+00:00Well, for our MMTS issue, here's how the proce...Well, for our MMTS issue, here's how the procedure needs to occur.<br /><br />We do need to address CRS. L&H-06 gives us his 2006-metadata version of jumps for CRS vs. MMTS. But he also says CRS looks wonky and needs to be adjusted. (I'll provide data with both CRS adjusted and CRS not adjusted, for discussion).<br /><br />So first, CRS must be adjusted for trend. How to do this? We don't want to simply match to sats. That reduces the argument to surface vs. sats. We want to connect it to CRN, which doesn't go back that far or this whole issue would be moot.<br /><br />But what we can do is:<br />First compare the magnitude of the trend of UAH6(latest) with CRN (2005 - 2014). See how well it tracks is it closer to CRN than USHCN. There is 15% less trend for UAH (less cooling, in the 2005-1014 case). That suggests a baseline for CRS adjustment at 15% higher than UAH. So that's what we shoot for. (This is applied to the anomalies, not the raw data, because we want to reduce the cooling as well as the warming.) To support this, CRS cooled at a rate just about as great (as CRN percentage) during the cooling as it warmed from 79-08, another support for heat sing hypothesis.<br /><br />So anyway, then we pairwise (5 years forward and back) to calculate our jumps. An MMTS can be used for comparison, but any station included in the pairwise must not have equipment conversion within 5 years of its inclusion in either direction. All such eligible stations in a region will be used. I'd like to do it Class 1\2 to Class 1\2, but there are simply not enough of them. So I will do it all-to-all, even though this will work against the class 1\2s.<br /><br />Short version:<br />1.) Adjust CRS trend.<br />2.) Do pairwise.<br />Note both jumps for both the CRS adjusted and non-adjusted.<br /><br />We will see if that wipes out the difference between the Class 1\2s and the adjusted record as you say it will. I don't know what the results will be, so it is exciting. This is taking L&H06 to its conclusion (individuals for each station and CRS accounted for).<br /><br />(Anyone who thinks these discussions are without value needs to re-evaluate.)<br /><br />Results pending.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-51620598105352294712016-01-26T17:59:03.825+00:002016-01-26T17:59:03.825+00:00As Hubbard & Lin wrote, you cannot apply the M...As Hubbard & Lin wrote, you cannot apply the MMTS Bias corrections globally.<br /><br />I am looking at using his own methods, pairwising with stations in the same region. Pretty much the same as H&L (but with some differences I'll explain later).<br /><br />Interesting to note that PRT shows an even greater absolute-value trend sensitivity than MMTS (and especially) CRS using non-converted MMTS & CRS stations from 2005 - 2014.Anonymoushttps://www.blogger.com/profile/04487574293471850518noreply@blogger.comtag:blogger.com,1999:blog-9093436161326155359.post-38543263466497798072016-01-19T01:26:41.721+00:002016-01-19T01:26:41.721+00:00Evan Jones writes: "The trend disparity would...Evan Jones writes: "<i>The trend disparity would not disappear. It would increase. There is a higher percentage of Class 2\4\5 that converted to MMTS than there are Class 1\2s. I will no doubt up the ante on MMTS in any case, come what will -- but watch for the CRS side of life.</i>"<br /><br />As Hubbard & Lin wrote, you cannot apply the MMTS Bias corrections globally - they require individual site adjustment based on specific temperatures, solar radiance, and wind. Your supposition is due to thinking you can apply a *global* offset - you can't. Unless you believe that your two subsets are homogeneous already, per the aforementioned criteria, any suppositions about the effect of the MMTS Bias adjustment are just a WAG. And your whole point has been the two sets are *not* homogeneous.<br /><br />You also forget that the Hubbard and Lin MMTS Bias adjustments are *not* linear. Kevin O'Neillhttps://www.blogger.com/profile/15751040367339659805noreply@blogger.com