Made August 2023/Updated OCT 2026/SEP 2024/SEP 2025
The purpose of this post is to catalogue counts of daily records (high maximums, high minimums, low minimums, low maximums) for China 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. I am in the process of constantly updating these data verifying the 2009 Meehl et al surface Records published in Geophysical Research Letters that I initiated from 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 that I glean data from:
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 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. Prior to 1970 there were very few reports of records, so I have opted not to catalog data prior to that year. The ratio of daily record high maximums to low minimums for the 2020s (so far) is higher than any decade since the 1970s:
Here are the current daily record counts per decade, which have gone into the prior chart:
Chinese Temperature Anomalies and Daily Record Counts: A Strong Nonlinear Relationship
I have matched Chinese monthly temperature anomalies with NCEI daily record counts to examine how the background climate state influences the balance between record warmth and record cold. The relationship is strongly nonlinear: months with temperatures close to the 1961–1990 average produce a more balanced mix of warm and cold records, while increasingly warm anomalies strongly favor daily warm records and increasingly cold anomalies favor daily cold records. This relationship is consistent with the patterns found in Australia, Germany, Canada, the United States, and the other countries examined in this investigation.
Chinese daily record counts show a particularly pronounced relationship between monthly temperature anomalies and the balance between record warmth and record cold. When monthly temperatures are relatively close to the 1961–1990 average, daily warm and cold records are much closer to balance. As monthly anomalies climb above +1°C, warm records increasingly dominate. For months with anomalies of +2.0°C or greater, daily record high maximums outnumber daily record low minimums by approximately 18 to 1, while daily record high minimums outnumber daily record low maximums by approximately 12.6 to 1. At −1.0°C and colder, the relationship reverses: daily record low minimums outnumber daily record high maximums by approximately 3.0 to 1, while daily record low maximums outnumber daily record high minimums by approximately 3.5 to 1. These results demonstrate a pronounced nonlinear relationship in which increasingly warm background conditions strongly favor record warmth, while colder conditions favor record cold. The ratios describe the available Chinese record-count data rather than establishing a causal relationship.
One especially notable feature of this analysis is that the daily record counts and monthly temperature anomalies come from independent datasets with different origins and processing methods. Despite that independence, they exhibit a strong and coherent relationship: increasingly warm monthly anomalies are associated with increasingly large imbalances toward daily warm records, while negative anomalies favor daily cold records. This agreement strengthens confidence that the observed pattern reflects a genuine climate signal rather than an artifact of a single dataset. China’s usable NCEI record-count history is considerably shorter than that of several other countries examined, beginning primarily in the 1970s. Furthermore, reporting delays of approximately 18 months can leave recent records incomplete, particularly those for 2025 and 2026. Consequently, the most recent record counts should be treated as provisional, and comparisons with countries having longer and more complete observational histories should account for differences in record length, station density, and observing-network coverage.
To better quantify the relationship, monthly anomalies were grouped into 0.10°C bins. Within each bin, warm-record and cold-record counts were compared using a signed ratio, then square-root scaled for display so that both large warm and cold imbalances remain readable on the same graph.
The 2020s:
Red indicates anomalies warmer than +0.5°C, blue indicates anomalies colder than −0.5°C, black indicates months or years within ±0.5°C of the 1961–1990 average, and purple marks all-time warmest or coldest months and years. Time stamps for when record totals were last updated are located on the upper left corner of each chart
The 2010s:
The 2000s:
The 1990s:
The 1980s:
The 1970s:
All of the data listed below is part of this one chart. The ratio of daily record high minimums to low maximums for the 2020s (so far) is higher than any decade since the 1970s (For China):
Here are the current daily record counts per decade, which have gone into the prior chart:
And more data:
The 2020s:
The 2010s:
The 2000s:
The 1990s:
The 1980s:
The 1970s:
These are all of the counts of daily record reports in the NCEI database from China since 1970.
The Climate Guy