Summary:
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Q: Was the month cooler or warmer than usual?
A: Colors
show where and by how much the monthly average temperature differed
from the month’s long-term average temperature from 1991-2020. Red areas
were warmer than the 30-year average for the month, and blue areas were
cooler. White and very light areas had temperatures close to the
long-term average.
Q: Where do these measurements come from?
A: Daily
temperature readings come from weather stations in the Global
Historical Climatology Network (GHCN-D). Volunteer observers or
automated instruments collect the highest and lowest temperature of the
day at each station over the entire month, and submit them to the
National Centers for Environmental Information (NCEI). After scientists
check the quality of the data to omit any systematic errors, they
calculate each station’s monthly average of daily mean temperatures,
then plot it on a 5x5 km gridded map. To fill in the grid at locations
without stations, a computer program interpolates (or estimates) values,
accounting for the distribution of stations and various physical
relationships, such as the way temperature changes with elevation. The
resulting product is the NOAA Monthly U.S. Climate Gridded Dataset
(NClimGrid).
To calculate the difference-from-average temperatures shown on these maps—also called temperature anomalies—NCEI
scientists take the average temperature in each 5x5 km grid box for a
single month and year, and subtract its 1991-2020 average for the same
month. If the result is a positive number, the region was warmer than
average. A negative result means the region was cooler than usual.
Q: What do the colors mean?
A: Shades
of blue show places where average monthly temperatures were below their
long-term average for the month. Areas shown in shades of pink to red
had average temperatures that were warmer than usual. The darker the
shade of red or blue, the larger the difference from the long-term
average temperature. White and very light areas show where average
monthly temperature was the same as or very close to the long-term
average.
Q: Why do these data matter?
A: Comparing
an area’s recent temperature to its long-term average can tell how warm
or how cool the area is compared to usual. Temperature anomalies also
give us a frame of reference to better compare locations. For example,
two areas might have each had recent temperatures near 70°F, but 70°F
could be above average for one location while below average for another.
Knowing an area is much warmer or much cooler than usual can encourage
people to pay close attention to on-the-ground conditions that affect
daily life and decisions. People check maps like this to judge crop
progress, estimate energy use, consider snow and lake ice melt; and to
understand impacts on wildfire regimes.
Q: How did you produce these snapshots?
A: Data
Snapshots are derivatives of existing data products: to meet the needs
of a broad audience, we present the source data in a simplified visual
style. This set of snapshots is based on NClimGrid climate data produced
by and available from the National Centers for Environmental
Information (NCEI). To produce our images, we invoke a set of scripts
that access the source data and represent them according to our selected
color ramps on our base maps.
Q: Data Format Description
A: NetCDF (Version: 4)
Additional information
References
Collection Notes:
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Data is divided in to folders by image resolution -- full size (zip), kml (zip), broadcast (png), small (png), and large (png). Occasionally there may be one image missing in a particular size but available in another size.
Data downloaded from climate.gov
full resolution files: 6/14/2025;
small, large, broadcast files: 6/21/2025