{"id":293970,"date":"2024-01-06T14:20:09","date_gmt":"2024-01-06T13:20:09","guid":{"rendered":"https:\/\/climatescience.press\/?p=293970"},"modified":"2024-01-06T14:20:12","modified_gmt":"2024-01-06T13:20:12","slug":"rising-maximum-temperatures","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=293970","title":{"rendered":"Rising Maximum Temperatures"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

<\/p>\n\n\n\n

Watts Up With That?<\/a><\/p>\n\n\n\n

Guest Opinion by Kip Hansen \u2014 5 January 2024 \u2014 2500 words\/15 minutes<\/p>\n\n\n\n

Roger Pielke Jr. recently posted a piece at The Honest Broker <\/em>titled:  \u201cU.S. Climate Extremes: 2023 Year in Review   \u2013 A Very Normal Year<\/a>\u201d \u2013 which was subsequently reposted at WUWT<\/a>.<\/p>\n\n\n\n

In that post, he uses this graphic:<\/p>\n\n\n

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(I have increased the size of the titles for clarity \u2013 kh)<\/figcaption><\/figure>\n<\/div>\n\n\n

It is easy to see that the trends of both the Maximum January temperatures and the Maximum July temperatures have been rising \u2014 more so for January temperatures than July \u2014 though this is somewhat obscured by the different scales of the two graphs.   [Caveat:  The temperature record on which this graph is based is not scientifically reliable before about 1940.] Also, one has to be careful to note what exactly they are really measuring<\/a>. <\/p>\n\n\n\n

This is not the usual average temperature.  Not monthly average temperature. <\/p>\n\n\n\n

It is Contiguous U.S. Maximum<\/strong> Temperature for these two months, January and July \u2013 based on the assumption that these are the coldest and hottest months.    At least we can say they represent a cold month and a hot month.<\/p>\n\n\n\n

So how do we calculate such a record?  Let\u2019s just assume NOAA has done what is usually does \u2013 it took some kind of an average of the maximum temperatures<\/em><\/strong> reported each day by its weather stations in the Contiguous United States<\/a> \u2013 those temperatures reported usually as \u201cTmax<\/strong>\u201d in the daily station records. <\/p>\n\n\n\n

Let\u2019s leave aside all my usual arguments about the inanity of such averages and just accept the idea that they are trying to represent.  (None of this is Roger Pielke Jr.\u2019s  fault \u2013 he is just reporting what they say in the NOAA produced graphics.)<\/p>\n\n\n\n

But rather, consider exactly what they are reporting \u2013 Maximum Daily Temperatures (averaged somehow).\u00a0 But how is this measured?<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

How was this measure in the early 20th century<\/em>?  They used something like this, the Six\u2019s Min-Max Thermometer<\/a>. <\/p>\n\n\n\n

However, the Wiki explains:<\/p>\n\n\n\n

\u201cMMTS (meteorology)<\/em><\/p>\n\n\n\n

A Maximum Minimum Temperature System or MMTS is a temperature recording system that keeps track of the maximum and minimum temperatures that have occurred over some given time period.<\/em><\/p>\n\n\n\n

The earliest, and still perhaps most familiar, form is the Maximum minimum thermometer invented by James Six in 1782.<\/em><\/p>\n\n\n\n

Today a typical MMTS is a thermistor. This may be read locally or can transmit its results electronically.\u201d<\/em><\/strong><\/p>\n\n\n\n

Weather.gov offers this information<\/a>:<\/p>\n\n\n\n

[If you are familiar with weather stations you can skip this section.- kh]<\/p>\n\n\n\n

Temperature Sensors \u2013 Liquid<\/u><\/em><\/p>\n\n\n\n

Thermometers used in a CRS\u00a0<\/em>[Cotton Region Shelter]\u00a0are Liquid In Glass (LIG) and are either alcohol or mercury.\u00a0\u00a0 Alcohol thermometers are employed in the colder climates where winter temperatures drop below -40 degrees, the freezing point of mercury.\u00a0\u00a0 Minimum temperature thermometers have a small bar embedded in the liquid that is pulled down the tube as the temperature falls.\u00a0\u00a0 As the temperature warms again and the liquid moves back up the tube, the bar remains at the minimum temperature.\u00a0\u00a0 This allows the observer to read the lowest temperature.\u00a0\u00a0 Maximum thermometers have a small break near the base of the well of liquid at the bottom of the thermometer.\u00a0\u00a0 As the temperature falls from the maximum, this break in the liquid keeps the liquid in place at its high point.\u00a0\u00a0 The maximum and minimum thermometers are mounted on a rack.\u00a0\u00a0 After noting the highest and lowest temperatures, the observer then tilts the rack.\u00a0\u00a0 This resets the thermometers by rejoining the liquid in the \u201cmaximum\u201d thermometer and sending the bar back to the top of the liquid in the \u201cminimum\u201d thermometer.\u00a0\u00a0 The thermometers are now reset, allowing observation of the highest and lowest temperatures for the next day.<\/em><\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

Temperature Sensor \u2013 Electronic<\/u><\/em><\/p>\n\n\n\n

[The newer electronic MMTS can look like the one picture here.)<\/p>\n\n\n\n

Another and newer type of thermometer is the Maximum Minimum Temperature System (MMTS).\u00a0\u00a0 An MMTS is an electronic thermometer, not too different from the type one might buy at a local electronics store.\u00a0\u00a0 The MMTS is a thermistor.\u00a0\u00a0 This thermistor is housed in a shelter similar in appearance to a bee hive.\u00a0\u00a0 This design is similar in functionality to the CRS.\u00a0\u00a0 Currently, the MMTS requires a cable to connect the sensor with a display.\u00a0\u00a0 Future plans are for wireless displays.\u00a0\u00a0 This would eliminate many of the problems associated with cabled systems.<\/em><\/p>\n\n\n\n

In the 1980s, thermistor MMTS units began to be introduced into the NOAA and NWS systems.  [ source<\/a> ]<\/p>\n\n\n\n

In a larger application, such as the\u00a0NY State Mesonet<\/a>, a typical station looks like this:<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

This is a Mesonet station<\/a> high in the Catskill Mountains, I took this photo a couple of weeks ago.  Circled is the 6-foot temperature sensor.  It is specifically a RM Young 41342<\/a>  [spec sheet<\/a>] in a RM Young 43502 \u2013 Aspirated Radiation Shield<\/a>.  The standard version has an accuracy (at 23\u00b0C ) of \u00b10.3\u00b0C (about 0.5\u00b0F), with a 10 second response time. <\/p>\n\n\n\n

Why do we need to know the response time when measuring 6-foot (2 m) air temperature?   Well, when you were a child (most of us, anyway) the doctor and your mother took your temperature with \u201cliquid-in-glass\u201d oral thermometer (for me, a mercury-in-glass then later alcohol-in-glass) which you were required to hold \u201cunder your tongue\u201d  for how long?  \u201cfor 3 minutes<\/a>.\u201d  That\u2019s how long it took to get a \u201cliquid-in-glass\u201d [LIG] thermometer to reliably change and record temperature.   Our original Six\u2019s Min-Max Thermometer<\/a>-style thermometers, used for many years and still in use in some places today, had a similar response time to changes in temperature measured in minutes \u2013 not seconds<\/em>.<\/p>\n\n\n\n

This becomes important when looking at the Maximum Temperature record for any weather station.  For a properly sited<\/em><\/strong> weather station, which would look something like the Mesonet station pictured above in many ways, there is little chance of spurious very-short-term temperature changes being recorded by an electronic MMTS.  There are no parking lots, no air conditioners, no jet exhaust, no delivery trucks, no buildings reflecting heat, no odd little shifts of blowing a stream of uncharacteristic hotter air over the sensor for a minute, etc.<\/p>\n\n\n\n

Many NOAA weather stations consist of a MMTS alone, on a pole. (see Anthony Watts\u2019 Surface Station Project reports<\/a>.)<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

[Interesting note:  The NYS Mesonet<\/a> station TANN, pictured here with a UFO (unidentified finger object) in the upper left, looked to me, when I visited it on a cold snowy morning, to be a very well sited weather station.  But on its site data page<\/a> it gives a siting rating for various measurements according to WMO SITING CLASSIFICATIONS FOR SURFACE OBSERVING STATIONS ON LAND<\/a> [required reading<\/em> for anyone concerned about station siting and the temperature\/weather record] in which \u201cWMO guidelines give different variables a classification number, with 1 being the best [on a scale of 1-5]. Higher-numbered classifications indicate that the site\u2019s surrounding environment may cause uncertainty in the data.\u201d  Of the three categories rated for this station, it received a \u201c4\u201d for Temperature\/Humidity and a \u201c5\u201ds for Surface Wind and Precipitation.]<\/p>\n\n\n\n

Back to response time:  Why would this make a difference?<\/p>\n\n\n\n

I didn\u2019t know but I had suspicions\u2026.so, naturally, I asked Anthony Watts, probably the man most knowledgeable about how temperatures are measured inside of Stevenson Screens<\/a>, in the somewhat similar Cotton Region Shelters (CRS),<\/a> and in modern electronic weather stations, this question:<\/p>\n\n\n\n

\u201cPielke Jr has published these graphs of January and July Maximum temperatures.\u00a0 (his substack and\u00a0<\/em>at WUWT<\/em><\/a>.)<\/em><\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

What are the chances that some of the rise<\/strong> is due to the use of electronic weather stations which report INSTANTANEOUS highs and lows?\u201d<\/em><\/p>\n\n\n\n

With Anthony\u2019s permission, I quote his answer:<\/p>\n\n\n\n

\u201cAbsolutely, I\u2019m convinced that short, local events, such as a wind shift bringing heat from pavement can contribute to a high that is spurious. The MMTS system as well as the ASOS system logs the Tmax \u2013 it does not log the duration.<\/em><\/em><\/p>\n\n\n\n

The response\u00a0time of a mercury or alcohol\u00a0max\/min\u00a0thermometer basically makes it a low pass filter, and such spurious events don\u2019t get recorded.

The solution is to install a \u201cmass hat\u201d on an electronic thermometer sensor to get its response\u00a0time down to that of\u00a0a mercury or\u00a0alcohol\u00a0max\/min\u00a0thermometer.\u201d<\/em>\u00a0\u2014 Anthony Watts (personal communication)<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

[\u201cMass hat\u201d \u2013 this would be something like a sleeve that slips over the\u00a0thermistor<\/em>, which is the long skinny probe seen in this image, with sufficient\u00a0mass\u00a0<\/em><\/strong>that has to change temperature before the thermistor is affected \u2013 thus slowing the response time of the thermistor to more closely match that of liquid-in-glass max\/min thermometers.]<\/p>\n\n\n\n

<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

How\u2019s that, you say?\u00a0 It is a result of exactly what they are measuring and recording: the\u00a0Maximum<\/strong>\u00a0temperature reading.\u00a0 Here are the hourly Maximums from an imaginary weather station:<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

We can see the usual diurnal shape, warming to midday, cooling overnight.\u00a0 But, hey, what\u2019s that sticking up in the middle? At 1000 hrs?\u00a0 That, my friends, is a\u00a0spurious instantaneous temperature reading<\/em>.\u00a0 You see, this below is the imaginary Anywhere, U.S.A. station:<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

You can see the MMTS there on the left-hand side, on the lawn, and the five air conditioning units 6 to 8 feet away.  Maybe, around 10 o\u2019clock, the buildings air conditions all started up, timer controlled, and kicked out lots of heat just as an errant puff of wind came around the corner from the building on the right, blowing all that extra heat over the MMTS for a minute.  The MMTS dutifully records a new Maximum Temperature.  That little spike would be reported as the Maximum for the day, averaged into the Monthly Maximum.  As more and more MMTS are added to the network, the more spurious instantaneous Maximums can be recorded, slowly driving the Contiguous U.S. Maximum Temperature of January or July up a bit each year, as the number of MMTS units increase the number of spurious readings.<\/p>\n\n\n\n

These types of spurious Tmax readings can be caused by all sorts of things.  See Anthony\u2019s two Surface Station reports [2009 here<\/a> and 2022 here<\/a>].  At airports, a badly sited MMTS can be influenced by passing or turning jet airplanes on the runway, taking off or landing. For parking lot sited stations, a UPS or Amazon truck parked right next to the MMTS can reflect extra heat onto the MMTS for a minute or two.  An odd little puff of wind picks up the hottest air six inches above the black asphalt and wafts it up over the MMTS.  The point is that it doesn\u2019t have to last long \u2013 10 second response time<\/em>!  New Tmax!<\/p>\n\n\n\n

Let me provide a real-time, real-life example from a weather station I have visited many times:\u00a0\u00a0C \u2013 Turkey Point Hudson River NERRS, NY (NOS 8518962)<\/a>.\u00a0\u00a0 We can find the\u00a0real time standard meteorological data for last 45 days from this page<\/a>.\u00a0 Temperatures are recorded at six-minute intervals (which are averaged instantaneous measurements).\u00a0 [Note:\u00a0 ASOS stations, on the other hand, \u00a0use five-minute intervals.] Looking closely at the data for examples, we find this 30 minute period on December 18th<\/sup>\u00a02023 from 1436 to 1500 \u2013 five six minute records:<\/p>\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n

A temperature jump of 4.2\u00b0C  (or 7.6\u00b0F)  in six minutes?   For over 20 minutes, the recorded temperature remains higher, and then is aback at 10-11\u00b0C. [See note<\/em> just below]  There are lots of instances of these types of oddities in the record of this station.  In this case, we have a 10-11\u00b0C (about 50\u00b0F) day suddenly transformed into a 15\u00b0C (60\u00b0F) day  \u2014 for 15 minutes.  That 15\u00b0C is a Tmax for the day \u2013 almost 4\u00b0C higher than the rest of the day.  The average temp (including the spurious reading)  for the hour (all six-minute records) in which this oddity occurs is 12.7\u00b0C.<\/em><\/p>\n\n\n\n

Note :<\/em>  \u201cOnce each minute the ACU [which is the central processing unit for the ASOS] calculates the 5-minute average ambient temperature and dew point temperature from the 1-minute average observations (provided at least 4 valid 1-minute averages are available). These 5-minute averages are rounded to the nearest degree Fahrenheit, converted to the nearest 0.1 degree Celsius, and reported once each minute as the 5-minute average ambient and dew point temperatures. All mid-point temperature values are rounded up (e.g., +3.5\u00b0F rounds up to +4.0\u00b0F; -3.5\u00b0F rounds up to \u2013 3.0\u00b0F; while -3.6 \u00b0F rounds to -4.0 \u00b0F).\u201d  <\/em>[source:  ASOS Users Guide, 1998<\/a>]  The station illustrated is a NERRS station and uses 6 minute intervals, but the algorithm is similar \u2013 kh.<\/p>\n\n\n\n

Here is how that works to bias the temperature record \u2013 both the Tmax record and the Tavg record:<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

The five latest 1-minute values are averaged, giving a new 5-minute-average every minute.  In the NERRS network,  1-minute values are averaged every five minutes to created the Recorded 5-minute Temperature record<\/a>.  [Note: different agencies use slightly differing algorithms and timings \u2013 NERRS uses six minute averages, while ASOS uses five minutes.]  A single 1-minute spurious temperature causes five spuriously high 5-minute averages in the \u201caveraged every minute\u201d system used in ASOS (the orange trace in the graphs above) .  In the NERRS network, 1 spurious reading creates at least two spuriously high Recorded 5-minute values (red trace and stars). <\/p>\n\n\n\n

The graph at the top of this essay \u2013 Contiguous U.S. Maximum Temperature \u2013 is created by this process:  \u201cOnce each day (at 23:59 LST), the highest and lowest ambient temperatures for the current month, along with the date(s) of occurrence, are computed and stored in memory until the end of the following month. On the first day of the following month, ASOS outputs the Monthly Maximum Temperature and date(s) of occurrence, plus the Monthly Minimum Temperature and date(s) of occurrence.\u201d  <\/em>It logically follows that spuriously high instantaneous readings can easily make that monthly Maximum Temperature listing and thus create the graph from NOAA highlighted by Pielke Jr.<\/p>\n\n\n\n

Yes, it can be confusing, but:  The NERRS network does not record each 1 minute temperature, only an average every six minutes.  ASOS and MMTS record a new 5-minute average<\/em> every minute, which are also not a record of the 1-miute temperature measurements themselves.
These are examples of spurious instantaneous MMTS\/ASOS<\/em> temperature readings<\/em> and their effects \u2013 and lead to the bottom line:<\/p>\n\n\n\n

Bottom Line:<\/strong><\/p>\n\n\n\n

There is a reasonable hypothesis that could or should be investigated:<\/p>\n\n\n\n

With the widespread introduction of MMTS and ASOS weather stations over time since 1980, which record instantaneous temperatures every minute with a 10 second response time, spurious instantaneous high temperatures can be recorded as Tmax driving up both the daily temperature average (Tavg) and the daily, weekly monthly and annual Tmax records.<\/p>\n\n\n\n

# # # # #<\/strong><\/p>\n\n\n\n

Author\u2019s Comment:<\/strong><\/p>\n\n\n\n

A good question based on curiosity about an observation of something (anomalous or not) is the basis of all good science and research.<\/p>\n\n\n\n

This topic could be important \u2013 as all the temperature records (local, US Contiguous, Regional, Global)  are based on the record of Tavg \u2013 the daily \u201caverage\u201d temperature of a weather station.  That \u201caverage\u201d is not the average of all the temperature measurements for a 24 hour period, but rather the \u201caverage\u201d of the Tmin and Tmax  <\/sub>of that 24 hour period.  Thus, Daily\/Weekly\/Monthly Average Temperatures are highly influenced by Tmax.  [for details, see this document<\/a><\/a> from the National Centers for Environmental Information]<\/p>\n\n\n\n

It is not just the Tmax record that can be nudged higher by anomalous instantaneous affects all of the subsequent  temperature metrics.<\/p>\n\n\n\n

Nearly 20 years ago, K. G. Hubbard et al. produce a paper titled \u201cAir Temperature Comparison between the MMTS and the USCRN Temperature Systems<\/a>\u201d which found MMTS systems biased Tmax high and Tmin low. It was based on a single year\u2019s worth of data but claims that MMTS data was or maybe still is being \u201ccorrected\u201d.<\/p>\n\n\n\n

Just to be clear:  This Opinion piece represents my personal investigation and  opinion on the topic \u2013 I have quoted Anthony Watts\u2019 response<\/em> to my emailed question.  Everything else, every word, is my responsibility and does not necessarily represent his viewpoint.<\/p>\n\n\n\n

Thanks for reading.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

It is Contiguous U.S.\u00a0Maximum\u00a0Temperature for these two months, January and July \u2013 based on the assumption that these are the coldest and hottest months. \u00a0\u00a0\u00a0At least we can say they represent a cold month and a hot month.<\/p>\n","protected":false},"author":121246920,"featured_media":293991,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_crdt_document":"","advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"It is Contiguous U.S.\u00a0Maximum\u00a0Temperature for these two months, January and July \u2013 based on the assumption that these are the coldest and hottest months. \u00a0\u00a0\u00a0At least we can say they represent a cold month and a hot month.","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[691826010,691826009,691826012,691818765,691826013,691826011],"class_list":{"0":"post-293970","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-uncategorized","8":"tag-coldest-and-hottest-months","9":"tag-maximum-temperatures","10":"tag-mmts","11":"tag-noaa-national-weather-service","12":"tag-thermometers","13":"tag-tmax","15":"fallback-thumbnail"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/01\/0AWS.jpg?fit=1366%2C853&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-1ets","jetpack-related-posts":[{"id":202465,"url":"https:\/\/climatescience.press\/?p=202465","url_meta":{"origin":293970,"position":0},"title":"Plummeting US Temperatures","author":"uwe.roland.gross","date":"06\/01\/2022","format":false,"excerpt":"Ten years ago the US had a very warm winter and spring, which was widely attributed to \u201cglobal warming\u201c. Tropical storm Sandy made landfall at the end of October, 2012 and may have won the election for Obama and Biden. Since then US temperatures have plummeted with the first five\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2022\/06\/0January-1-To-May-31-Average-Mean-Temperature-Vs-Year-1895-2022-At-All-US-Historical-Climatology-Network-Stations-Red-Line-Is-10-Year-Mean.png?fit=1200%2C1158&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2022\/06\/0January-1-To-May-31-Average-Mean-Temperature-Vs-Year-1895-2022-At-All-US-Historical-Climatology-Network-Stations-Red-Line-Is-10-Year-Mean.png?fit=1200%2C1158&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2022\/06\/0January-1-To-May-31-Average-Mean-Temperature-Vs-Year-1895-2022-At-All-US-Historical-Climatology-Network-Stations-Red-Line-Is-10-Year-Mean.png?fit=1200%2C1158&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2022\/06\/0January-1-To-May-31-Average-Mean-Temperature-Vs-Year-1895-2022-At-All-US-Historical-Climatology-Network-Stations-Red-Line-Is-10-Year-Mean.png?fit=1200%2C1158&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2022\/06\/0January-1-To-May-31-Average-Mean-Temperature-Vs-Year-1895-2022-At-All-US-Historical-Climatology-Network-Stations-Red-Line-Is-10-Year-Mean.png?fit=1200%2C1158&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":287853,"url":"https:\/\/climatescience.press\/?p=287853","url_meta":{"origin":293970,"position":1},"title":"L A Times Fails to Comprehend the Difference between \u201cAverage Temperature Anomaly\u201d & \u201cAbsolute Maximum Temperature\u201d Climate Data","author":"uwe.roland.gross","date":"11\/13\/2023","format":false,"excerpt":"From Watts Up With That? Essay by Larry Hamlin In the most recent L A Times\u00a0article\u00a0hyping \u201cthe hottest October on record\u201d the Times can\u2019t seem to get it right in understanding the critical differences between\u00a0\u201caverage temperature anomaly\u201d\u00a0and\u00a0\u201cmaximum absolute temperature\u201d\u00a0data. The Times article references the global\u00a0average temperature anomaly\u00a0graphic noted below which\u2026","rel":"","context":"In \"average temperature anomaly\"","block_context":{"text":"average temperature anomaly","link":"https:\/\/climatescience.press\/?tag=average-temperature-anomaly"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/image-391.png?fit=1024%2C1024&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/image-391.png?fit=1024%2C1024&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/image-391.png?fit=1024%2C1024&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/image-391.png?fit=1024%2C1024&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":291766,"url":"https:\/\/climatescience.press\/?p=291766","url_meta":{"origin":293970,"position":2},"title":"NASA GISS Data Shows 2023 EL Nino Driving Global Temperature Anomaly Increases; NOAA Data Shows U.S. Nov. 2023 Temperature Anomaly Declining","author":"uwe.roland.gross","date":"12\/18\/2023","format":false,"excerpt":"The NASA GISS global average temperature anomaly for November 2023 was released (provided below) which shows an El Ni\u00f1o driven value of 1.44 degrees C (2.592 degrees F) with the November outcome hyped in an\u00a0L A Times article\u00a0as being \u201ca new monthly record for heat\u201d and the \u201chottest November\u201d.","rel":"","context":"In \"Climate Alarmists\"","block_context":{"text":"Climate Alarmists","link":"https:\/\/climatescience.press\/?tag=climate-alarmists"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/OIG-2023-07-29T140641.234.jpeg?fit=1024%2C1024&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/OIG-2023-07-29T140641.234.jpeg?fit=1024%2C1024&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/OIG-2023-07-29T140641.234.jpeg?fit=1024%2C1024&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/OIG-2023-07-29T140641.234.jpeg?fit=1024%2C1024&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":263475,"url":"https:\/\/climatescience.press\/?p=263475","url_meta":{"origin":293970,"position":3},"title":"BBC Ignore Cold Weather In\u00a0India","author":"uwe.roland.gross","date":"06\/23\/2023","format":false,"excerpt":"But there has been much less discussion by the BBC about the extremely cold weather there in May this year. Indeed it is the third coldest on record","rel":"","context":"In \"BBC\"","block_context":{"text":"BBC","link":"https:\/\/climatescience.press\/?tag=bbc"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/06\/0Winter.webp?fit=1000%2C567&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/06\/0Winter.webp?fit=1000%2C567&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/06\/0Winter.webp?fit=1000%2C567&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/06\/0Winter.webp?fit=1000%2C567&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":257779,"url":"https:\/\/climatescience.press\/?p=257779","url_meta":{"origin":293970,"position":4},"title":"Media Ignore Delhi\u2019s Coldest May Since 1901","author":"uwe.roland.gross","date":"05\/17\/2023","format":false,"excerpt":"On May 4, India\u2019s capital of New Delhi recorded the third coldest May morning since 1901. At 16 degree Celsius (60 Fahrenheit), the region\u2019s 32 million residents woke up to a relatively cold morning in what is usually the hottest month of the year.","rel":"","context":"In \"Climate change\"","block_context":{"text":"Climate change","link":"https:\/\/climatescience.press\/?tag=climate-change"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/073008865.webp?fit=1070%2C580&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/073008865.webp?fit=1070%2C580&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/073008865.webp?fit=1070%2C580&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/073008865.webp?fit=1070%2C580&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/073008865.webp?fit=1070%2C580&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":283619,"url":"https:\/\/climatescience.press\/?p=283619","url_meta":{"origin":293970,"position":5},"title":"Major Climate Alarmist Fail: \u201cThe Hottest Summer Ever\u201d that Never Was","author":"uwe.roland.gross","date":"10\/17\/2023","format":false,"excerpt":"The \u201chottest summer ever\u201d is a failure by climate alarmist and the climate boogeyman media. Use your mind and don\u00b4t follow the climate propaganda. From Watts Up With That? Guest essay by Larry Hamlin A recent WUWT\u00a0article\u00a0addresses the failure by climate alarmist media and scientists to utilize NOAA\u2019s July through\u2026","rel":"","context":"In \"climate alarmist\"","block_context":{"text":"climate alarmist","link":"https:\/\/climatescience.press\/?tag=climate-alarmist"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/image-433.png?fit=1024%2C1024&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/image-433.png?fit=1024%2C1024&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/image-433.png?fit=1024%2C1024&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/image-433.png?fit=1024%2C1024&ssl=1&resize=700%2C400 2x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/293970","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/users\/121246920"}],"replies":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=293970"}],"version-history":[{"count":10,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/293970\/revisions"}],"predecessor-version":[{"id":293993,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/293970\/revisions\/293993"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/media\/293991"}],"wp:attachment":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=293970"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=293970"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=293970"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}