9am 0.22 -0.10 0.14 0.12 0.03 0.01 0.10 0.22 -0.14 0.11 -0.01 0.10 -0.01 0.11 13.64 13.58 Essentially, we can correctly “pin” the high/low values at the (four) measured times in the period of interest, and must be VERY cautious about taking things any further than that. My question is technical – how exactly is the Max/Min temperature recorded at older (ie, non electronic type) stations. One could suppose that this method introduces no bias into the trend. time to get some real work done and come back later…. One used to reset it with a magnet, drawing the peg down from the max shown, to the top of the mercury again, each day. Number of instances in which the current 24 hour min is at exactly the same Without more information we do not know how the initial “10 degrees” grid point is arrived at. F, not because of their possible effects on TOB, but because of a concern the first day of the next month. It’s not too different from the adjustment built into my chicken coop automated seasonal light timer: we can turn the light on for a certain period before/after sunrise and sunset. This is even closer to my back-of-the envelope calculation than I had thought! TOBs is a phenomenon concerning the time of day at which measurements are taken, whereby some maximum or minimum temperatures are not recorded; instead, a faulty, but always high (for maxima) or low (for minima), value is recorded from the ‘detritus’ of a more extreme value the previous day. Otherwise, as you have so ably demonstrated, the “inter-day” reading is counted twice, biasing the results. The safe thing would be to regard the first reading after the gap as ambiguous, and not to resume the assumption of 24-hour periods until the second reading after the gap. Then there is the topic of response times. http://www.john-daly.com/tob/TOBSUM.HTM, “Im not convinced on outliers, do you have a link for the tables? We really are making progress, step by step. Fun Facts about the name Tobs. Karl et al’s Min graphs in Fig. “and I thought Johns last post on CRN1,2 vs GISS was very compelling (with one question below) Then. Summer is the worst. 9 Yrs 50.71 -0.49 -0.20 0.13 0.41 1.68 1.30 0.92 0.66 0.49 0.35 Spikes greater than 2 F flattened. Or if today’s max was a little later than Tobs, today’s Tobs-temp will show up as today’s offical max and today’s actual max will show up as tomorrow’s official max. My simple example demonstrates the kind of error that arises. Temp vs Day-Of-Year vs Years. Even if it was every time, then you would still have 15 good data points. Everything name meaning, origin, pronunciation, numerology, popularity and more information about Tobs at NAMEANING.NET Obviously a bad idea to simply connect across the “gap”. temperature at the time of observation. temperature as the 24 hour old 24 hour max: 3314, just under once per I looked at all possible different 24 hour periods (midnight to midnight, 1 AM to 1 AM, etc. a. 2. 2185 instances of 3 occurrences And the hard part to understand, is that we cannot simply switch from a discrete data set containing measurements at specific times, and convert to an assumed infinite-precision timeline linking those data values. and climate. to base the exclusion on. The TOB process needs to be fully documented. Your examples would not get past the Geoff Sherrington’s contributions here are quite interesting to our discussion. If I measure my interior oven temp every second after set it to 400 F and turn it on, I’ll probably get a flat diagonal rising line over time as it heats. Weather OBS abbreviation meaning defined here. No individual moment is in two adjacent days, hours, minutes or seconds. One must treat them as separate trend lines. Thus, the position of the index represented the lowest temperature during the period from the previous reset. BTW, it would seem appropriate that you stop posting false assertions about for JerryB above. 5:00 51.27 #92 Not a problem. Then the add TMIN Select California. For completeness, I’ll respond to this right now: My method estimates monthly, and yearly, TOB based on hourly temperature 3: 30. This adjustment alone is responsible for the majority of the difference between raw and adjusted temperatures reported by NCDC. those data points are RARE events.. like fliping heads 10 times in a row. But in either case, one cannot simply connect the end of the previous trend line to the beginning of the new one. As I said earlier, it’s typically a computer science problem only brought up when creating things like microcode for division algorithms, correctly implemented 2-D path intersections, and so forth. One measures extreme temperatures, the other has the capacity to approximate heat flow. By JerryB’s calculation, the period one hi/lo/avg is 10/10/10, period two hi/lo/avg is 20/10/15, #3 is 30/20/25, and the overall avg for the three periods is 16.7, If we rearrange things, the answer changes for Jerry’s algorithm: A small moveable metal index was embedded in the liquid portion of the column. Average estimated TOB of 190 locations at three times of observation The boundary is not a time period. Tobs and not TOBS, to avoid confusion with TOB, the standard abbreviation for Time of Observation Bias. TEMPERATURE (-F). Second if you have trouble with JerryBs description download one of his data files Using about 6.5 years of hourly observations from the Columbus, GA airport (a data file I just happened to have handy I took the min/max temperatures at each hour of the day. 18 instances of 10 occurrences It wasn’t short, it was in fact past her knees. …and imagine that the value for 2005 should somehow be selected as any of 110, 100 or 80. Yes, we can draw an imaginary continuous line between our measurements, but when we want to fix a given temp/time estimate along that curve, we recognize it will resolve to a spot on the grid, never in between grid points. The TIME of this observation is supposed to be midnight. The bias results from an accumulation of differences in temperatures of If you measure the max temperature near the afternoon average temperature peak, on a day that is warmer than both its neighbors, there is a good chance that the temperature near the observation time will also be recorded as the peak for one of the adjacent days. RE 137. in mind. Furthermore, nearly all the MD stations observed at midnight. years of hourly temperature data. In the horizontal (time) axis, the two lines are discontinuous: either there’s a time gap or a time overlap. Has anyone tried applying the TOBS correction they use to the 7am data you used to see if you get the MIdnight values and/or the correct trend? As the period moves such that one of the end points approaches one of the peaks, you no longer capture the peak of every period. When using point measurement data, if one does not include 24 Proper management of high/low readings must be designed to avoid incorrect outcomes. By the way, glad you got round to naming the databases. 14:00 52.10 In a climate audit, we are supposed to discern the possible errors then uncover methodology “adjustments” by audit to see if they are valid or not. one hour earlier for hourly measurements. If observer reads “late” by two hours, then a high/low occuring in the final two hours of the previous day, larger than today’s high/low, will overwhelm today’s data. the temperature at the end of the first time period, and it is also the 3 1 100 100 0 Green line shows the data with a lowers smoother applied. Ummm… I finally woke up and found JerryB’s data links ;)… THANK YOU Jerry for going to all that trouble! Free the code is my watchword no matter what the outcome. The AM category included observers who ended their climatological day between 3 AM and 11 AM; the PM category between noon and 9 PM; and the MD category between 10 PM and 2 AM; all local standard time. The only explanation is increasing minimums are caused by increasing daytime warming and therefore unchanged nighttime temperatures result from increased nighttime cooling. See? I respectfully disagree that it is correct to incorporate 25 measurements into the high/low of a 24 hour day. Hmmm: R users ( and people who know how to use Excel) should avert their eyes now, I think. Also, while the operator made the change on the 18th, the Does an hourly instrument average point temperatures over that last hour and record the mean? When the time of observation is systematically changed from afternoon to morning in the Climate Reference Network, a clear cooling bias emerges. Thanks for that reference, Steven! This will require some thought. Of the 8,756 hourly readings, twelve were missing and replaced using a linear approximation based on the surrounding temperatures. It cannot be in both.. Midnight: .146 F per year 6 PM 0.48 C 0.87 F. Thirty seconds are up? above; they were seperately derived from data in F. Suppose that every day in July the low is 50 at 2AM, the 7AM temp is 60, the How fast are thermocouple devices designed to respond or smooth? Synthetic observation times applied to hourly CRN data. It looks to me like when temp at time of observation is lower than the min temp, they select the temp that looks more in line with surrounding days. 9 instances of 8 occurrences What about the jiffie? I believe this is a basic error in analysis. True, but extraneous. Also, the second two of them are error does not invalidate that recognition. #34 I believe I have what you’ve suggested, but I don’t have a place to upload the image. Can you tell when Whatever TOB adjustment that was required with manual recording should have steadily declined toward zero as the proportion of automated stations increased. what my method, or algorithm, or calculation, would do with your simple examples. Thoughtful contributions most welcome! C). I mostly see attempts at “correction” for duplicate/missing data! Is it a discussion of sampling interval? I suppose it’s everywhere, just seems more so on ‘the alarmist’ sites than on ‘the denier’ sites. It is dangerous to presume high/low values on the basis of presumed data, unless one knows something about the inter-measurement data curve… in which case there’s really more data available than meets the eye. Differences between the Mohonk Lake record of mean annual temperatures and those of nearby stations in the USHCN (see map in Fig. but Im not as convinced with his CRN 5 analysis. An observer can make a reading error there just as easily as at a CRN5 site. The temperature persists through The fraction of observers in these categories was calculated, and it was assumed the 7 AM observation time best represented the AM category; the 5 PM observation time, the PM category; and midnight for the MD category. Heads up! 2 instances of 11 occurrences day to the next, and common, ordinary, differences of low temperatures 2pm 0.11 0.04 0.56 0.34 0.22 0.26 0.75 0.69 0.37 0.60 0.37 0.36 0.46 0.35 14.00 13.95 79 to create the model 28 held The net effect of adjustments to correct for time of observation changes is shown in Figue 2. How did I misuse that? over 5 F, then 3 F, and then 2 F, and after each successive flattening, OK but I am pointing to something else entirely. In practical terms this means while monthly TOBs can be significant (as much as 1C) around the equinoxes, over the year monthly TOBs tend to cancel out and are much smaller over a year. IF you are going to follow the ‘peterson, easterling, hansen” method of The trend is almost identical between the two data sets. However, when times of observation are other than The fact is that GISTEMP agrees well with the temperature trends from the best stations (CRN12R). “The observer has to report 85 because it was the temperature at the time of If you are interested in statements such as x degrees/century, the method used to correct TOBS is wrong wrong wrong. Is “10” used for an underlying (continuous) range of 10.0 to 10.999…, or 9.000…001 to 10.0, or 9.5 to 10.4999…? Between 1960 and today, the majority of stations switched from a late afternoon to an early morning observation time, resulting a systemic change (and resulting bias) in temperature observations. The fact of the underlying discrete measurement grid has significant implications on correct management of calculations. I think I’m seeing a basic methodological error. The only place I can see TOBS being important for annual averages is if you are trying to compare different stations on the same day to weed out typographical errors. The fact that hourly, much less six hourly, point temperature to my IQ: At either page linked by this page you can see The documentation and data sets say Below is the station list used in the top graph. CRN12 describes the physical being of the site. “During this period there would have been a changeover from mostly manual My guess: it is embarrassing to leave blank spots in the record, and we assume that we just “know” what the missing value ought to be. 1 1 50 50 0 Heres the link. #128. Figure 5. These last 4 columns want a name putting above the info and then you can drag over them all (included the name) and create a pivot table&chart. Once this has been correctly implemented, any given time of observation will show no trend compared to any other time of observation…assuming changes in time of observation are treated as beginning a new, unrelated, series. 2:00 51.67 In the former Delaware OH USHCN station, for example, an intriguing pattern of every 7th day missing develops in 1999. Here is the same graph for all USHCN stations. Minneapolis can be freezing in May! You have a thermometer that’s way off but it stays in the same condition over 100 years. At high latitudes, 1000 km can mean midnight at one station and midday at another 1000 km east or west. But now Kristin has dug out the original data forms, and as Andrew notes, there’s already a LOT of missing data. Unlike Mann and hansen and others I would which may relate to discussions of “double counting” and “under This is attributed to the preponderance of AM observation times falling between 6 AM and 9 AM, and PM observation times falling between 4 PM and 7 PM. I’ve been noodling over the challenge of how to convert the record to unbiased/TOB-free data. Impact of adjustments on U.S. temperatures relative to the 1900-1910 period, following the … Switching from an afternoon time of observation to a morning time of observation would result in minimum, maximum, and mean temperatures around 0.6 C colder previously measured. This is pretty much along the lines of #14’s examples. FILNET is not needed for JohnVs approach. But I guess the right people liked the result, so it lives on. one considers the afternoon of day 1 of the Peoria sample, “No individual moment is in two adjacent days, hours, minutes or seconds.”. However, it appears it’s not and the Tobs is estimated, bizarely IMO to save a small amount of money. Well he is, I was. You can almost watch it happen by visiting here and following No individual moment is in two adjacent days, hours, minutes or seconds.. There are two specific changes to the U.S. temperature observation network over the last century that have resulted in systemic cooling biases: time of observation changes at most of the stations from late afternoon to early morning, and a change in most of the instruments from liquid in glass thermometers to MMTS electronic instruments. See other definitions of TOBS count, but only #16 in the 3 F or more, not because it didn’t have its Period. rather than the way they do work. cool stuff. If a puff of hot air floats through the instrument chamber, is this recorded as the daily max, or are the instruments designed to smooth transients? To consider this in a bit more detail, consider the case where the precision of our timing is to the second, and our measurements are made hourly. Yes, the temperature persists. their procedures at the time that I initially wrote my code (summer 2002). Do it the right way. 6pm -0.11 0.14 0.43 0.34 0.32 0.28 0.33 0.35 0.11 0.30 0.25 0.20 0.42 0.34 13.88 13.83 I’ve beat the rounding drum before but no Indians came running to help. Geography impacts climate! variations of temperatures. The total bias caused by afternoon TOBS is a little more than 0.1C (0.2F) This is much less than the bloated adjustment used by USHCN. My gut keeps telling me the uncertainties are larger than the supposedly accurate “corrections.” But I don’t suppose the media care. So I’ll come back at 11 am and read and reset the min thermometer”. The same is true for low minima if the recording time is near the early morning average temperature min.” (and reset) is during usually relatively warm evening hours, there will Rainy days cut the effect Recorded + .05F fater introduction of MMTS. And the sensor records in 25 degree increments: D M T Hi Lo * Any bids on good/proper/best ways to “bin” sparse data collections, so as to properly recognize trends? This is optional. period is identical to the moment at the beginning of the second time C. net upward adjustment shown in the Stepwise Differences graph linked by John V in #376 of the A Second Look thread. A.D. is used with dates in the current era , which is considered the era since the birth of Christ. OK, just a few more. lastly ;level with the first row of your 24 hours max and min columns copy the time of day column across. The Karl method of estimating TOB has a significant error and is intended to adjust monthly data. The value for 2004 and the value for 2006 are immaterial. So if you look at the last table for 3.49 Sigma, you will see this. Don't miss out on the promotions for Tobs Wicker, buy Tobs Wicker directly online and enjoy big saving on your purchases. ), True. simply from curiosity, but did not attempt to quantify their effects on : While considering some of Hu’s and Jon’s recent comments, it seemed to me For reasons discussed below, I believe attempts to apply such calculations to specific stations and/or for climatic trend analysis, are misguided. The Karl paper is a wonderful presentation of certain analyses. Recognize that the “day boundaries” do not lie ON the grid but between grid points: every point on the grid lies inside a single “box.”, If we have a need to “connect the dots” (such as for curve estimation between measurements), we can’t just forget the grid. Mrpete, you suggest a methodology that has much to reccommend it. We don’t know. I think that’s why I called it an RC type discussion, they seem to go around in circles a lot there with nobody understanding they’re not really having a discussion on the same topic! Impact of observation time on resulting temperatures (relative to midnight) based on 2004-2014 USCRN hourly data.Shaded areas reflect most common morning and afternoon observation times. C. This is at least close to the approximately +.35 deg. Correct? There is NO justification for spreading TOBs adjustments over every day for months or years. Weather data can serve many business applications, such as evaluating the impact of weather on insurance claims, heating oil consumption, electricity load during summer months in hot weather areas, agricultural output, and clothing items purchased from retail outlets. And I don’t just mean in climate science. hour old point measurements, one can get gaps between consecutive day This would tend to increase the true standard error of the US average toward the end of the data. In fact, the “Stepwise differences” graph linked by John V shows approximately +.35 deg. Thus, high maxes tend to get double counted. I just read Karl, Williams, Young, and Wendland (J. – AND in any case, the actual missing data is of course not filled in. So my next thought-experiment question becomes… How do we perform the reverse conversion? Jerry One thing I was thinking of doing was a simple Graph. That’s true. 3 2 25 100 0 The first step of my method is to find sets of several OK, now let’s specify that a bit more completely. One thought experiment: imagine a sine wave, sampled at regular intervals. The example you provide does not shed any light on the problem at hand, which is: Given hourly measurements of temperature, what method best emulates the results that would be produced by daily observations recorded on a min/max thermometer so that time-of-observation bias in a min/max regime can be measured? Such thermometers as above, if used, would record the same max for several days in a row (unless mathematically corrected by guessing). Yes. It depends on common, ordinary, differences of high temperatures from one Each reading exists in only one time period, never two. hour periods.)”. Rounds up 5/9 of the time (5,6,7,8,9) and down 4/9 of the time (1,2,3,4). Then I think we would have a historical fact 13:00 51.89 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Nov year Oct year
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