How do weather observations become climate data?
Observations of Weather are the Foundation of Climate Products
Around the globe, millions of weather observations are recorded each day, by both human observers and automated instruments. In the United States, daily observations at stations that meet specified criteria, methodically collected by volunteer observers and automated weather stations, are used to document our weather and climate. One volunteer weather observer program in the United States is the Cooperative Observer Program (COOP). This program, which includes more than 11,000 stations, is key to obtaining accurate observations across the country. Started in 1890, the COOP network now spans all corners of our nation: from mountaintops to meadows, urban to rural regions, and from seashores to suburbs.
Each COOP weather station has a set of precise scientific instruments to measure climate variables including temperature, precipitation, evaporation, and snow depth. Every day COOP observers follow a consistent and prescribed procedure to check (validate) their instruments and record their data. In some cases, observers record their data on handwritten forms, while in other cases, digital automated instruments record the data. At a minimum, each station records the minimum and maximum temperature of the day and the amount of any precipitation that fell.
Data Processing Begins with Quality Control
Right after making their observations, observers check the records for quality and accuracy themselves. If they notice something amiss, they can recheck their instrument or discuss the issue they notice with an expert at their local National Weather Service office.
Observers submit their raw data to NOAA’s National Center for Environmental Information (NCEI) on a daily or monthly schedule for further quality checks. Meteorologists at NCEI use computers to perform a basic check of all incoming data. The computer checks patterns in each record for issues such as spikes, flatliners, outliers, excessive ranges, and change points.
Weather data are also checked for consistency across a region. Scientists observe data sets from comparable stations to see if the data makes sense for the region and time of year. For example: does one station report sunshine and warm temperatures in December, while a neighboring station shows windy sub-zero temperatures and snow? If they find inconsistencies, meteorologists methodically track down the source of the inconsistent data. At this point, original data values may be flagged as incorrect, and excluded from further processing, but they are never changed or edited, unless the error was due to incorrect transcriptions by volunteers.
Once the COOP data has passed quality control, it becomes part of the larger data record known as the Global Historical Climate Network-Daily (GHCN-D) database. The data can then be processed to generate climate products such as maps and graphs.
From Raw Data to Finished Products
The most common processing steps used to turn daily weather data into climate data products involve straightforward mathematical operations such as averaging or adding measurements. For instance, a station's daily average (mean) temperature is calculated by averaging the minimum and maximum temperatures for the day: daily average = (minimum + maximum) / 2. As another example, a station's average monthly maximum temperature is calculated by averaging all the daily maximum temperatures observed during the month. For precipitation data, the most common processing step is adding: for instance, monthly precipitation values are calculated by adding the depths of precipitation from each day over the entire month.
To understand climate on larger scales, climatologists average data from individual stations with data from other stations in the area. When combining observations, the values for each station are mathematically weighted to account for the fraction of the averaging area they represent. This keeps areas with many weather stations from being overrepresented compared to areas with fewer stations.
Climate products produced from the GHCN-D database include reports, maps, and graphics such as monthly State of the Climate reports. These data also serve as input for computer models to help generate future climate outlooks and weather forecasts.
Data for Decisions
Current weather and climate data are used in many ways. People who make decisions for cities and towns rely on accurate and easy-to-understand graphs and maps to assist them in planning for energy needs, water management, and extreme weather events. Local climate data are also used to determine city budgets for maintaining roads, bridges, and other infrastructure.
Climate data are used by people across many sectors of our economy. For example, farmers use climate data to select which crops to grow, while water managers use climate data to know when to release water from reservoirs. Read more about how climate data are used in various sectors »
Following consistent procedures at every step—from making weather observations to publishing climate products—ensures that NOAA’s climate information is accurate and reliable.
References: Dr. Karsten Shein “Interactive Quality Assurance Practices” PPT presentation AMS 2008