Made May 2022/Updated FEB 2025/JUN 2026
The purpose of this post is merely to catalogue counts of all-time record high maximums, high minimums, low minimums and low maximums coming into the National Center for Environmental Information’s site and all related charts and graphs produced in my Excel files for those data sets for Russia. All-time records are the highest or lowest temperatures recorded over the entire time a station has been recording data. For example, the all-time record for Atlanta Hartsville-Jackson Airport was 106°F set on 6/30/2012. I am in the process of constantly updating this data verifying the 2009 Meehl et. all surface Records published in geophysical Science that I initiated from the year 2000. Each individual count could be a tied surface record or one broken by several degrees Fahrenheit.
Here is the link to the NCEI site:
https://www.ncdc.noaa.gov/cdo-web/datatools/records
More from NCEI:
The daily records summarized here are compiled from a subset of stations in the Global Historical Climatological Network. A station is defined as the complete daily weather records at a particular location, having a unique identifier in the GHCN-Daily dataset.
For a station to be considered for any parameter, it must have a minimum of 30 years of data with more than 182 days complete each year. This is effectively a “30-year record of service” requirement, but allows for inclusion of some stations which routinely shut down during certain seasons. Small station moves, such as a move from one property to an adjacent property, may occur within a station history. However, larger moves, such as a station moving from downtown to the city airport, generally result in the commissioning of a new station identifier. This tool treats each of these histories as a different station. In this way, it does not “thread” the separate histories into one record for a city.
This tool provides simplistic counts of records to provide insight into recent climate behavior, but is not a definitive way to identify trends in the number of records set over time. This is particularly true outside the United States, where the number of records may be strongly influenced by station density from country to country and from year to year. These data are raw and have not been assessed for the effects of changing station instrumentation and time of observation.
An updated 2015 study from Dr. Jerry Meehl indicates that the ratio of daily records from year to year will average around 15 to 1 by 2100:
Per one of the authors of both the 2009 and 2015 studies, Claudia Tebaldi said “This climate is on a trajectory that goes somewhere we’ve never been. And records are a very easy measure of that.”
All of the data listed below is part of this one chart. The ratio of all-time record maxes to low time minimums is highest for the 2010s than any other decade since the 1920s:
Here are the current all-time record counts of high maximums and low minimums per decade:
Formula Notes
R = DHMX / DLMN
If R >= 1, then T = R
If R < 1, then T = -(1/R)
From our recent research on AHMX/ALMN (all-time monthly high maximum vs. all-time monthly low minimum records), several broad findings emerged:
- Warm all-time records strongly dominate during positive temperature anomalies.
- As monthly or annual temperature anomalies become warmer, the ratio of AHMX (all-time warm maximum records) to ALMN (all-time cold minimum records) rises rapidly.
- The relationship is highly nonlinear. Small amounts of warming produce disproportionately large increases in warm records.
- Cold all-time records become increasingly rare in warm climates.
- During strongly positive anomaly periods, ALMN occurrences collapse toward zero in many bins.
- Once anomalies become sufficiently positive, new all-time cold records are almost absent.
- The response is stronger than for ordinary daily records.
- All-time records are rare events, but when they occur in a warming climate, they are overwhelmingly warm rather than cold.
- This indicates a systematic shift of the entire temperature distribution, not merely year-to-year variability.
- The anomaly-bin curves show threshold behavior.
- Near neutral anomalies, warm and cold all-time records can still occur together.
- Beyond roughly moderate positive anomalies, warm all-time records increasingly dominate and the transformed warm/cold ratios climb sharply.
- Data sparsity introduces noise.
- Because all-time records are infrequent, especially in countries with short records or limited station coverage, individual bins can be noisy.
- Nevertheless, the long-term signal remains clear: warming greatly favors the occurrence of new all-time heat records while suppressing new all-time cold records.
- Physical interpretation.
- The AHMX/ALMN results support the conclusion that ongoing climate warming is shifting the probability distribution toward higher temperatures.
- The climate system is producing many more opportunities for unprecedented heat than for unprecedented cold.
In short, our AHMX/ALMN work indicates that:
A warmer climate produces a rapidly increasing excess of all-time heat records and an increasingly severe deficit of all-time cold records, with the imbalance becoming extreme during the warmest anomaly regimes.
This behavior was consistent with our findings from the broader DHMX/DLMN, DHMN/DLMX, and AHMN/ALMX analyses, although the all-time record datasets are much noisier because of their rarity.
The 2020s:
Blue colors represent cold months and red warm. Those months with counts close to a 1 to 1 ratio of highs to lows are colored black. I have opted not to catalogue data prior to 1920 since record counts decrease substantially prior to 1930. Time stamps for when I last updated counts are located in the upper left-hand corner of each chart. Drop me a note if you see an error or if you have suggestions for improvements.
The 2010s:
The 2000s:
The 1990s:
The 1980s:
The 1970s:
The 1960s:
The 1950s:
The 1940s:
1930s:
1920s:
For the following data sets of all-time record high minimums and low maximums I have opted not to boldly highlight ratios greater than 10 to 1. Blue colors represent cold months and red warm. Those months with counts close to a 1 to 1 ratio of highs to lows are colored black. I have decided not to catalogue data prior to 1920 since record counts decrease substantially prior to 1930. Time stamps for when I last updated counts are located in the upper left-hand corner of each chart. Drop me a note if you see an error or if you have suggestions for improvements.
All of the data listed below is part of this one chart. The ratio of all-time record high minimums to low maximums for the 21st century is higher for the 2010s than any other decade since the 1920s, so far:
Here are the current all-time record counts per decade, which have gone into the prior chart:
Our AHMN/ALMX anomaly-bin analysis (all-time high minima versus all-time low maxima) produced perhaps the strongest warming signal of all the all-time record datasets.
Summary of AHMN/ALMX Ratios vs. Temperature Anomalies
- Warm nighttime all-time records increase dramatically with warming.
- As temperature anomalies become increasingly positive, the ratio of AHMN (all-time warm minimum records) to ALMX (all-time cold maximum records) rises rapidly.
- The increase is highly nonlinear, with the warmest anomaly bins showing overwhelming dominance of AHMN records.
- The relationship is stronger than AHMX/ALMN.
- The AHMN/ALMX transformed-ratio curves generally rise more steeply than the AHMX/ALMN curves.
- This indicates that warming is being expressed especially strongly through increasing nighttime temperatures.
- ALMX records become exceptionally rare during warm anomalies.
- As anomalies move into positive territory, all-time cold daytime maxima decline sharply.
- In many strongly positive anomaly bins, ALMX records nearly disappear altogether.
- Warm anomalies favor warm minima much more strongly than cold anomalies favor cold maxima.
- Negative anomalies do produce more ALMX records.
- However, positive anomalies generate a much larger increase in AHMN records than the corresponding increase in ALMX records during cold periods.
- This asymmetry is one of the clearest signatures of long-term climatic warming.
- The curves exhibit threshold behavior.
- Near neutral anomalies, AHMN and ALMX records can still occur together.
- Beyond modest positive anomalies, the warm/cold ratio accelerates rapidly upward as warm nighttime records begin to dominate.
- Statistical noise remains significant because all-time records are rare.
- Individual anomaly bins often contain relatively few observations.
- Consequently, the AHMN/ALMX curves show substantial scatter.
- Despite this noise, the underlying warming signal remains unmistakable.
Comparison with AHMX/ALMN
| Metric | Dominant Signal |
|---|---|
| AHMX/ALMN | More unprecedented daytime heat and fewer unprecedented cold nights |
| AHMN/ALMX | Much stronger increase in unprecedented warm nights and disappearance of cold daytime extremes |
The AHMN/ALMX dataset generally displays:
- Steeper transformed-ratio increases.
- Stronger warm-record dominance.
- Greater sensitivity to positive anomalies.
Physical Interpretation
The AHMN/ALMX findings suggest that:
Climate warming is increasing nighttime heat more rapidly than daytime heat, causing unprecedented warm nights to become much more common while unprecedented cool daytime extremes become increasingly rare.
In practical terms:
As anomalies become warmer, the climate system retains heat overnight far more efficiently, producing a rapid increase in all-time warm minimum records and a near disappearance of all-time cold maximum records.
Taken together with the DHMN/DLMX results, the AHMN/ALMX analysis provides strong evidence that:
Nighttime warming is one of the most pronounced and robust signatures of modern climate change.
The 2020s:
The 2010s:
The 2000s:
The 1990s:
The 1980s:
The 1970s:
The 1960s:
The 1950s:
The 1940s:
The 1930s:
The 1920s:
These are all of the NCEI all-time Russian record report counts back through 1920.
Guy Walton…”The Climate Guy”