Made August 2021/Updated AUG 2023/NOV 2024/FEB 2026/OCT 2026
The purpose of this post is to catalogue counts of monthly records (record high maximums, record high minimums, record low minimums, record low maximums) for Germany coming into the National Centers for Environmental Information’s site and all related charts and graphs produced in my Excel files for those data sets. For example, the highest temperature set during the month of March at Atlanta Hartsville-Jackson Airport was 89F set on 3/23/1995. I continue to update these data as part of my long-term work examining the warm-record/cold-record relationships first studied in the 2009 Meehl et al. paper published in Geophysical Research Letters, research that I helped initiate during 2000–2009. Each individual count could be a report of a tied surface record or one broken by several degrees Fahrenheit. Here is the link to the NCEI site:
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 2016 study from Dr. Jerry Meehl indicates that the daily ratio from year to year will average around 15 to 1 by 2100:
Per one of the authors of both the 2009 and 2016 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 monthly record high maxes to low minimums for the 2010s is higher than any decade since the 1890s:
Germany’s monthly temperature-record statistics reveal a pronounced shift toward record warmth over recent decades. During the 1970s, record cold monthly extremes outnumbered record warm extremes. By the 2010s, warm records exceeded cold records by more than eight to one. During the incomplete 2020s, that ratio has increased to nearly thirty-four to one. Although changes in observing-station coverage must be considered, the magnitude and persistence of this imbalance are consistent with the expected consequences of a warming climate.
Here are the current German monthly record counts per decade (including ties):
Scientific Assessment of Germany’s Monthly Temperature-Record Analysis
Our German analysis reveals a strong and scientifically meaningful relationship between monthly temperature anomalies and the frequency of record-breaking warmth and cold.
Using temperature anomalies relative to the 1961–1990 climatological baseline, grouped into 0.10°C increments, we find that the farther a month departs from its historical average, the more strongly temperature records favor the direction of that departure. This relationship is markedly nonlinear.
The results are particularly striking for the two categories of monthly records:
| Monthly record comparison | Anomalies ≥ +2°C | Anomalies ≤ −2°C |
|---|---|---|
| MHMX / MLMN | ~50 warm records per cold record | ~34 cold records per warm record |
| MHMN / MLMX | ~4.6 warm records per cold record | ~22 cold records per warm record |
These results indicate that exceptionally warm German months are especially favorable to new monthly maximum-temperature records, while exceptionally cold months strongly favor monthly minimum-temperature records. The differences between the two comparisons also suggest that daytime and nighttime temperature extremes do not respond identically to changes in the background climate.
NCEI German Daily Record Count Archive – Guy On Climate.pdf
An important finding is that the imbalance is much smaller near climatological normal. In the accompanying daily-record analysis, months within approximately ±0.5°C of normal produced 25,710 warm records and 25,739 cold records, a nearly equal distribution. This provides a useful internal consistency check.
Across the entire German dataset, warm records outnumber cold records in all four comparisons. For the monthly MHMX/MLMN series, the overall warm-to-cold ratio reaches approximately 3.04 to 1, the largest aggregate imbalance among the four measures examined.
Scientific interpretation
These findings are consistent with the expected statistical consequences of a warming climate. As the temperature distribution shifts toward higher values, the probability of exceeding previous warm extremes increases while opportunities to establish new cold extremes generally diminish.
However, this analysis is observational rather than a formal attribution study. Changing station coverage, record lengths, and the number of record-setting opportunities can affect the counts. Additionally, the very large ratios in extreme anomaly categories should be evaluated alongside sample sizes and uncertainty estimates. The square-root transformation improves graphical readability but does not itself establish statistical significance.
Overall assessment: Germany’s monthly temperature-record analysis provides compelling descriptive evidence that the background thermal state strongly influences the balance between warm and cold records. Its most important contribution is demonstrating how rapidly that imbalance increases as monthly temperature anomalies become more extreme.
The 2020s:
For the following data sets of record of monthly 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. Months and years that are all-time record cold or hot are colored purple. Temperature anomalies greater than +0.5°C are shown in red, while anomalies below −0.5°C are shown in blue. Values within ±0.5°C are shown in black. All-time warmest and coldest months and years are highlighted in purple. Record-count ratios are displayed separately using the established warm-versus-cold comparison.I have opted not to catalogue data prior to 1900 since record counts decrease substantially prior to the decade of the 1910s. 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:
The 1930s:
The 1920s:
The 1910s:
The 1900s:
All of the data listed below is part of this one chart. The ratio of monthly record high minimums to low maximums for the 2020s (so far) is higher than any other decade since the 1900s:
The 2020s:
For the following data sets of record of monthly 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. Months and years that are all-time record cold or hot are colored purple. Temperature anomalies greater than +0.5°C are shown in red, while anomalies below −0.5°C are shown in blue. Values within ±0.5°C are shown in black. All-time warmest and coldest months and years are highlighted in purple. Record-count ratios are displayed separately using the established warm-versus-cold comparison.I have opted not to catalogue data prior to 1900 since record counts decrease substantially prior to the decade of the 1910s. 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:
The 1930s:
The 1920s:
The 1910s:
1900s:
This is all of the NCEI German monthly record count data going back to 1900.
Guy Walton…”The Climate Guy”