c. You must adjust for changes in site location( elevation). Jan 1 hi/lo/avg = 10/0/5 It is 25, not zero. When using point measurement data, if one does not include 24 Actually, come to think of it, it’s not just RC. In these cases TOB can cause a significant discontinuity in the mean temperature record. N samples taken. As Philip_B points out in #29 above, however, even Karl et al admit that there is considerable estimation error in their TOB formula, which could be as high as 0.2deg. I believe this is a basic error in analysis. 2: 20 The discussion at the link in that comment is not about how TOB is adjusted (I have a feeling we’ve covered this on other threads, but I can’t find it. 3) If the 24 hr high is uniquely found at TOB, yesterday or today, we throw out today’s high observation. Barring operational errors, with 24 hour max/min observations, the According to Karl et al, before WWII most stations used to measure in the evening, with 5pm being the most popular time, but an increasing number are moving to the morning, with 7am being the most popular time. As Stephen Mosher has indicated, other issues can easily overwhelm any potential for TOB. To me, that moment is ONLY part of 2007. CRN5 shows ~0.35C more warming than CRN12R and ~0.2C more warming than GISTEMP (likely to increase to ~0.4C after TOBS correction). Figure 1: Recorded time of observation for USHCN stations, from Menne et al 2009. Thanks, Steve, for starting this thread on Time of Observation Bias (TOB). Average estimated TOB of 190 locations at three times of observation The tempeature at the moment between two consecutive time periods is the Depending on your lat/lon and season, generally speaking the AVERAGE of the 7AM will be cooler of what you propose, methodological error. In practice, what I’ve learned is that more data should be invalidated (due to observation-time change)… and there ought to be a whole lot FEWER attempts at micro-adjusting for TOB because it really is not all that predictable. 21:00 52.22 All we can do on the first measurement of the new day is reset our high/low record and begin again. like to have Willis and JeanS and UC and SteveMc and Roman and professional statitiscians those data points are RARE events.. like fliping heads 10 times in a row. If the TOB happens to be near the normal time of minimum (or maximum) daily tempseratures, then these extremes will be counted twice while it’s opposite max (or min) is counted only once. The assumed picture seems to be one of gently sloping land covered by smooth vegetation or desert. It’s always been amazing to me how people assume that it’s ok to just wing it when a data record has not been correctly recorded. 8 show that there is perceptible downward bias from about 9pm to 8am in July. We’ll see that may_nineth is a dataframe with 127 rows and 7 columns including each day’s high (TMAX), low (TMIN), and observed (TOBS) temperature for the day. My method estimates monthly, and yearly, TOB based on hourly temperature I then found the average of these 364 midpoint temperatures for each of the 24 collection times. The 11% of observers who dutifully trudge out to the stations at midnight would be doing everyone a favor if they just took their readings at 9pm and got some sleep instead. If so, what were they? If so, then please explain your statement, and the algorithm that implements it: As I read this, you are saying the moment at the end of the first time period is identical to the moment at the beginning of the second time period. the what happens at one site.. Aurbo (#22) – Thanks! Jan 2 hi/lo/avg = 20/10/15 Even if the exteriors of the sensors were cleaned, would inaccessible soil buildup in the interior not also cause warming? This year-to-year variability [in TOB] is … due to differences in the timing of frontal passages, cloudiness, precipitation, etc. There is a whole new realm of questions when one changes instruments to types that measure hourly temperatures or even less. In sites with good radiational cooling, there can be a very significant difference if temperatures are taken near the time of the min (about 6AM local time) or the time of the max (about 3PM local time). Because those branches allow you to It would seem the correct way to handle TOB is to flag the record when it happens, and then when processing the data for averaging treat it as any other missing measurement (interpolate, substitute average, etc). The USHCN stations were selected for the continuity of their records back in 1999 or so. 3pm 0.21 -0.23 0.68 0.55 0.44 0.46 0.81 0.70 0.41 0.62 0.19 0.58 0.38 0.40 14.05 14.00 Such landscapes do exist of course, but they’re hardly the norm! was probability and statistics. Rats! Since the mins are not affected, this makes the average mean temperature about 1/12 = .08 degree too low, using these hypothetical numbers. The trend is almost identical between the two data sets. Daily rain drains off afternoon heat potential and sets up the evening as the high of the day. Here is the same graph for all USHCN stations. See other definitions of TOBS It is the KISS part of engineering school that I didn’t sleep through that makes me think this way. The Balling, Idso paper shows an increasing difference between the RAW and the FILNET data over time which just doesn’t seem right. We can also use it on non-grouped data. TOBS = Time of Observation bias. I just tried it for the first time, and we shall see if it works. Outside of the box take a fictitious site called FT. Hansen, TX. Heads up! As to missing data, that’s a large topic and I don’t think that there are any magic bullets. TOBS is listed in the World's largest and most authoritative dictionary database of abbreviations and acronyms TOBS - What does TOBS … 69 Steve Mosher, if the raw data is indeed raw, trending the data per site should be the most accurate method of building the overall trend, via anomalities (sp) as John V. recommended. How do you correct the TOB adjustments to account for variations between solar time-of-day and wall time-of-day? If you are going to follow a JohnV approach, you might not have to make these adjustments. I would like to get a better idea of it. “I mentioned this once before, but the logical way to check TOBS is through a ( I want to audit that) 1 1 50 50 0 Even if you develop a fantabulous bias correction, it is useless if read times are innaccurate or unreliable. Another way to look at the impact of time of observation changes is to use the “perfect” Climate Reference Network (CRN) hourly data to see exactly what would happen if observation times were systemically changed from afternoon to morning. the TOB differences would be obscured. What we should be seeing is a steady reduction in TOB to zero, rather than the steady increase we do see. In a similar vein, did that old Fortran software incorporate the effect of the International Date Line, where stepping from one station to another on the other side would change times by a whole day? Over at RC The fact of the underlying discrete measurement grid has significant implications on correct management of calculations. My answer is still invisible at WUWT, and the question is still unanswered: https://archive.today/aNInJ#selection-12501.0-12507.54. Suppose as above that the daily highs are always 80 at 2PM and the lows are always 50 at 2AM. My simple example demonstrates the kind of error that arises. . temperature at the time of observation. Definition: A.D. is the Latin abbreviation for Anno Domini, which means 'in the year of our Lord,' or, more fully, anno domini nostri Jesu Christi 'the year of our Lord Jesus Christ.' This is a real worry. Then, I went and flattened the spikes, first those over 9 F, then those [Yeesh. high is 80 at 2PM, and the 5PM temp is 70.”. PRCP = Precipitation (tenths of mm) SNOW = Snowfall (mm) SNWD = Snow depth (mm) TMAX = Maximum temperature (tenths of degrees C) TMIN = Minimum temperature (tenths of degrees C) TOBS = Temperature at the time of observation (tenths of degrees C) Oh, there are no confidence intervals, are there. ” (Jonathan Lowe is saying really) that we should move away from looking at trends NC, divide the 0,15,30 column by 7.5 to get hours. Many long-term sites used the once-a-day max and min temperatures to construct their daily mean temperature record, and then, when replaced by automated recording temperature devices, switched to hourly observations with the means based on the 24-hour averages. In short, I do not believe that Karl and NOAA have presented a convincing case that systematic changes in TOB over the past 80 years require the kind of substantial adjustment they apply. Some stations had recording thermometers, but they were generally not used for climate data. 7. What I have NEVER seen is a corelation between averages derived day after day from an hourly machine, versus the simple average of Tmax and Tmin each day, as we commonly use now. C! Then change The TOBS to 6PM at year 4.5. Numbers of hourly observations of current 24 hour max temperature in 24 But they’re not. You notice that since the start of the period, the yearly average of the min has grown .5 You notice the yearly max has shrunk .5, If a site is measured at the same time throughout its history.. you will get a trend figure. I assumed that such a device was possible (human ingenuity, and an understanding that observors in the 19th and 20th century would want to do a good job of recording max and min). True, but extraneous. 7 instances of 10 occurrences Otherwise, high/low records 24 hours apart will incorporate, in essence, a one-hour overlap of measurements (since the measurements are hourly). hour old point measurements, one can get gaps between consecutive day 1 hi/lo/avg = 30/30/30, 2 = 30/20/25, 3=20/10/15, overall avg = 23.3. QED. That discussion majors on interpolation due to geolocation, and minors on time-based interpolation. 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. These are not in the Glossary and they definitely should be. The Karl paper is a wonderful presentation of certain analyses. FWIW, this post was prompted by your post at ATMOZ. The link form Jerry B in # 14 is useful, but the logic therein is hard to follow. Briefly, no. The charts for the minimum tend to have a high plateau from around 10am to 9pm, with a big dip from 9pm to 10am. Impact of adjustments on U.S. temperatures relative to the 1900-1910 period, following the … For that day, starting at 9 am, the Tmax comes at 2 pm (say) and the Tmin comes next morning on the same day at 8 am (say). Discrete measurements are points on a grid. Guess at cloud/wind/rain modulating half of the effect. or do you think the coin is biased? This may Heads up! Figure 5. It is an aspirated electronic device, originally using a thermistor as the temperature element. temperature ranges, which imply either operational error, or in the case This is all a matter of properly envisioning the two dimensional space, in this case of temperature vs time, with respect to the discrete point measurements. That might explain why I found no “.” flags in data from source 0: (from NDP019.PDF: (JAN-DEC)FLAG2 is the data source code. * Does R have good tools for dealing with sparse datasets? So, when they look through the records they are throwing out extremely rare EVENTS. Try 1,840,000 station/months, give or take a few thousand. Thus, high maxes tend to get double counted. “TOB is not an issue for me, I think it’s probably pretty close. I wonder what Karl et all think about how their numbers have been applied to the data. My method: average remains the same at 160.0 degrees. time to get some real work done and come back later…. A problem with that currently is that CEN is only a few years old. For that station then, the trend recorded is a valid daily trend. “period of record” of the data may be too short to be sufficient for such a Climate data and weather averages in Lansing. Many time zones are an hour wide, so a time at the borders can change by an hour as you cross the line from one station to another nearby. ), and calculated the maximum, minimum, and mean temperatures for all of the 24 hours periods in the CRN data. You bring up another important area: determining what time the thermometers were actually read and reset. A plot of temperatures taken every minute can produce a skinny curve or a fat one depending on how long the heat hung round before a cool breeze set in – but sill give the same Tmax and Tmin as before. The fraction of observers recording at various hours of the day was calculated and interpolated for intervening years (extrapolated for subsequent years). She/he says “I won’t reset the thermometer until this cold snap passes otherwise it might show up tomorrow too. The maximum (MAX.) TMAX and TMIN. They compare the Kingston USHCN station to a nearby pristinely sited USCRN station. Click next. In fact the best way to reconstruct a temperature series (IMO) would be to do the slopes and then pick a calibration period and integrate the slopes to find actual temps. measurements do not tell us what temperatures occurred between those In other seasons, the weather is more turbulent, making the bias period is somewhat longer, so that there is no perfect observation time from the point of view of both max bias and min bias. We’ll John Needs to build an expectation ( a model of what he will see) in order to do a PROPER If I do that again in a year, unless at that time there’s some weather event different than the year before, I’ll probably get pretty much the same numbers. I hope my brain doesn’t burn out along the way! One more time — the lower temperatures in CRN5 relative to CRN12R and GISTEMP prior to ~1970 are caused by normalization to the 1951-1980 reference period. interpreted. 3) It’s assumed that measurement at certain times of day will record duplicate high or low values over time, Yes, if the daily high/low observation is recorded and reset at the exact moment of the daily high/low, that high/low will affect both the prior and next day (if it happens to be the actual high/low of both 24 hour periods.). A mistake. However, either 9am or 9pm would be a big improvement over either 7am or 5pm, or midnight for that matter! 1: 10 on the barbie mate. Just two days of data may, or may not, indicate the Okay, I’m obviously not so good at this. Throwing a lot of data at the problem is not helpful for understanding. My gut keeps telling me the uncertainties are larger than the supposedly accurate “corrections.” But I don’t suppose the media care. The referencing between the posts is broken. I may have missed a few, but a good start would be #305, 376, 400, 402, 403, 413, 418, 419, 420, 424, 455, 458, 460, 462, 464, 468, 484, 488, and 493. If you keep the time of observation constant over time, this won’t make any different to the long-term station trends. 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. It’s already quite complete enough. Depending on what 24-hour periods you use, you can get some very interesting distortions of the data. 25% of the year. What means TOBS, SHAP, FILNET ? 16:00 52.61 http://www.isixsigma.com/library/content/zdistribution.asp. My background is heat transfer, and I taught graduate lab courses, including issues dealing with psychromatic ratios (ie, mass transfer). – Late 1940s into early 1950s You must adjust for Instrument changes at that site. But what about hot days? JohnV and I are engineers. 4. Does anyone know whether Jonathan’s findings extend to other locations eg the US? Or the thermemter breaks. However, being a power station engineer, I have access to a lot of high quality monitoring data done to a lot higher accuracy than usual temperature measurements Processing that data, shows TOBS is real – as the summary below shows: Average ((min+max)/2) Temperature Data It is a sneaky bias. A lot of effort has gone into analysis (and display) of station data based on the assumption that the data can be treated as a valid time series, with data points that (for the most part) describe a temperature “line” through time. It’s already quite complete enough. TOB impacts the means. 107 sites. Hmmmm, what a novel concept! 1. That’s what this is for) The moment at the beginning of the second time period, M2007b, The temperature at the end of the first time period, T2006e Let me try a thirty second introduction to TOB, and why it matters: It does not depend on passing warm, or cold, fronts, or storms. In this case, the “vertical” axis of the grid is typically “snapped” (in graphics/drawing parlance) to whole degree units. We’re dealing with a subtle boundary condition that’s best understood under simplified conditions. Here is recipe for creating the TOB for a simple sine wave day, in Excel: Rounds up 5/9 of the time (5,6,7,8,9) and down 4/9 of the time (1,2,3,4). Suppose the min/max is read and reset at midnight each day. The temperature at that moment is either in one period or in the other. How can one comment on TOB when there is so much confusion about it? Doesn’t matter. Dangerous assumption. the temperature, not the The AT OBSN temperature is the temperature at the time you take your observation. If the object is to proxy the 24-hour average temperature with the average of a 24-hour min and max, the ideal time to take the reading would be at the intersection of the two plateaus. Why introduce another bias, if it is only 1 day or so a month? 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. The TOBS adjustments have a point, but they are very large relative to measured warming and this sort of spot check would be worth doing on some stations where it can be done. The model (like most GCN models) is based on an assumption of well-sited observing stations placed in open areas. Between 1-3 and 2-0, the temperature could have been anything in a wide range, certainly enough to impact the high/low for either day. The MEAN goes to 69.0 The trend goes to .0001F day. Weather Information Applications Branch: WMO: World Meteorological Organization: WOU: Watch Outline Update: WPC: Weather Prediction Center (formerly HPC) WPDN: Wind Profiler Demonstration Network: WR: Western Region: WSFO: Weather Service Forecast Office: WSO: Weather Service Office: WSR-88D: Weather Surveillance Radar 1988, Doppler: WSW Why not assume that NASA GISS shows lower temperatures for CRN5 (urban heat island)than CRN12 (see your own graph), and that therefore the NASA GISS files are FUBAR? The graph shows the opposite, a steadily increasing TOB adjustment since 1970. Jan 1 2007: 24 samples, 10 degrees. TOBS = Time of Observation bias. Nor am I suggesting that time stops. C). A question that someone raised in one of my email spools about TOBS: If MMTS is an automated system that automatically records temperature then why would the TOBS trend increase as the amount of MMTS increased? 107 sites were used. 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…? I realize this is not easy to grasp. It does recognize that that Our interactive map allows you to see the local & national weather 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. With the exception of the MMTS that requires correction because it sucks, you just have trends with variations above and below each trend’s average. I’ve been noodling over the challenge of how to convert the record to unbiased/TOB-free data. (It’s easy to understand when the readings are not at the edge of the day. But it is a 24 hour high/low. that some things that I had not counted in the hourly data might be of Here is an example. Now we are at .6C.. simply the microsite bias works at night in the summer.

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