What is this project?
This project is a personal undertaking to (1) understand climate data and (2) to hopefully spread this understanding. All code to generate this visualization from its raw form on the NOAA FTP server to this current visualization is available in this repository.
Special thanks to the NOAA and all their scientists for their unrelenting work, and the Google Data Arts Team for this nifty globe visualization.
What is a temperature anomaly?
The term temperature anomaly means a departure from a reference value or long-term average. A positive anomaly indicates that the observed temperature was warmer than the reference value, while a negative anomaly indicates that the observed temperature was cooler than the reference value.
How can I make sense of this visualization?
Red coordinates indicate a geographic location where the yearly average anomalies were warmer than usual. Blue coordinates indicate a geographic location where the yearly average anomalies were cooler than usual. Both the height and color saturation of the geographic coordinate relate to the magnitude of the average anomaly. The higher the magnitude of the anomaly average, the higher the bar and the more saturated the color.
Note: black values indicate maximum saturation. This occurs for average anomalies greater than than 10.0° Celsius in magnitude (seen in 2017 and 2019).
What is the big picture here?
Above is a linear regression on the average anomalies grouped by year. As we can see, there is about an equal breakdown between cold and hot years until 1980. After this, yearly average anomaly temperatures increase steadily.
TL;DR: the earth is warming (and it's speeding up).
FAQ Source (NOAA)
TL;DR on the dataset visualized?
HadGHCND is output into annual maximum temperature anomaly and annual minimum temperature anomaly files. The anomalies were calculated with respect to the following base period: 1961 to 1990.
The GHCND gridded dataset (HadGHCND) is produced through a joint effort between the United States National Oceanic and Atmospheric Administration (National Climatic Data Center) and the United Kingdom's Hadley Centre.
What can the mean global temperature anomaly be used for?
This product is a global-scale climate diagnostic tool and provides a big picture overview of average global temperatures compared to a reference value.
What datasets are used in calculating the average global temperature anomaly?
Land surface temperatures are available from the Global Historical Climate Network-Monthly (GHCN-M). Sea surface temperatures are determined using the extended reconstructed sea surface temperature (ERSST) analysis. ERSST uses the most recently available International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and statistical methods that allow stable reconstruction using sparse data. The monthly analysis begins January 1854, but due to very sparse data, no global averages are computed before 1880. With more observations after 1880, the signal is stronger and more consistent over time.
FAQ Source (NOAA)
Why use temperature anomalies (departure from average) and not absolute temperature measurements?
Absolute estimates of global average surface temperature are difficult to compile for several reasons. Some regions have few temperature measurement stations (e.g., the Sahara Desert) and interpolation must be made over large, data-sparse regions. In mountainous areas, most observations come from the inhabited valleys, so the effect of elevation on a region's average temperature must be considered as well. For example, a summer month over an area may be cooler than average, both at a mountain top and in a nearby valley, but the absolute temperatures will be quite different at the two locations. The use of anomalies in this case will show that temperatures for both locations were below average.
Using reference values computed on smaller [more local] scales over the same time period establishes a baseline from which anomalies are calculated. This effectively normalizes the data so they can be compared and combined to more accurately represent temperature patterns with respect to what is normal for different places within a region.
For these reasons, large-area summaries incorporate anomalies, not the temperature itself. Anomalies more accurately describe climate variability over larger areas than absolute temperatures do, and they give a frame of reference that allows more meaningful comparisons between locations and more accurate calculations of temperature trends.
FAQ Source (NOAA)
How is the average global temperature anomaly time-series calculated?
The global time series is produced from the Smith and Reynolds blended land and ocean data set (Smith et al., 2008). This data set consists of monthly average temperature anomalies on a 5° x 5° grid across land and ocean surfaces. These grid boxes are then averaged to provide an average global temperature anomaly. An area-weighted scheme is used to reflect the reality that the boxes are smaller near the poles and larger near the equator. Global-average anomalies are calculated on a monthly and annual time scale. Average temperature anomalies are also available for land and ocean surfaces separately, and the Northern and Southern Hemispheres separately. The global and hemispheric anomalies are provided with respect to the period 1901-2000, the 20th century average.
How often and when is the global average temperature dataset updated?
The dataset is updated every month. Data for a month are typically made available by the 15th of the following month.