There are many ways to describe the climate of a place. The descriptions can range from quite technical to quite informal. Earlier this year we discussed the venerable Köppen Climate Classification System that is described in every climate textbook written in the last 100 years. The system uses monthly and annual temperature and precipitation to classify all portions of the earth into one of 5 major categories and 30 minor categories. There are many critics of the system and many alternative classification systems have been developed but nothing has come close to the widespread acceptance of the Köppen Climate Classification System. Therefore, we will utilize this well established system.
The five main categories of the Köppen Climate Classification System as as follows:
A – Topical climate: All months have a temperature greater than 64.4°F.
B – Dry, arid, or semiarid climate: Potential evapotranspiration exceeds precipitation. Criteria on a sliding scale based on average annual temperature.
C – Mesothermal climate: Warmest month above 50°F and all months between 32°F and 64.4°F.
D – Microthermal climate: Warmest month above 50°F, all months below 64.4°F, and at least one month less than 32°F.
E – Tundra climate: All months below 50°F.
There are many subcategories based on a variety of temperature and precipitation factors. The Encyclopedia Britannica entry for the Köppen Climate Classification System has an excellent description of the major and sub categories. (Note: they use 26.6°F as the cutoff between C and D climate types whereas the traditional cutoff is 32°F).
A recent paper by Chen and Chen (2013) looked at the change in spatial coverage of the major and minor Köppen categories across the entire earth as a metric for measuring climate change between 1900 and 2010. They combined all station data within 0.5° grid cells to determine a Köppen category for those cells. My methodology is similar to the Chen and Chen methodology except that the focus is on individual stations and not a continuous surface.
Using the Global Historical Climate Network (GHCN) database, we extracted daily temperatures and precipitation for over 1,000 stations across the U.S. Only "WBAN" stations were utilized for this analysis. These are frequently referred to as "first-order" stations.
Data were obtained by decade (e.g., 1901-1910, 1911-1920, etc.) and only those stations with valid observations for at least 75% of the days during the decade were included. Unlike Chen and Chen, data are non-overlapping in consecutive decades. For example, data for the 2001-2010 period only utilize data during those 10 years. The traditional method is to use 30-years of data to compute normal for a 10-year period. However, I decided that to map the changing patterns effectively, overlapping data were to be eliminated.
Monthly and annual averages were computed for all stations meeting the selection criteria using a Java parsing routine. A decision tree was constructed in the Java program to assign each station into a major Köppen category and a minor Köppen subcategory or subcategories.
This YouTube video shows the results of the analysis for each 10-year period. The 5 major Köppen types are represented by different colors. The minor Köppen subcategories are represented by different shapes and shades of the major category color. Early time periods have relatively few stations meeting the selection criteria, so meaningful analysis is limited. To view the video clearly, expand it into full screen mode and make sure the resolution is set to 1080p HD from the settings (gear-shaped) button. This is the only way to read the text in the legend.
Other than the total number of stations, the two most discernible patterns are: 1) the changing C/D line, and 2) the dramatic expansion of stations meeting the B criteria.
1) The C/D line marks the limit of stations recording at least one month a year with a below freezing average monthly temperature. Inspecting the corridor between Boston and Washington D.C. is especially interesting.
2) Since the B climate type supersedes all other types, an increase in temperature or decrease in precipitation will affect the evapotranspiration regime thereby moving marginal C/D stations into the B category. This is not surprising given the increase in temperatures during the last 50 years. On a global scale, Chen and Chen computed the relative change in percentage of Köppen type throughout a 100-year period (see Figure 1).
Figure 1. Global change in major Köppen types from 1915 to 1995. Figure taken from Chen and Chen (2013).
Why should anyone care what the climates type are for a collection of stations? It is not an overstatement to say that the climate of an area is the single most important variable in describing the ecological regime, the agricultural potential, and the geomorphological processes of a region. Measuring shifting climate patterns will give politicians and the public an additional tool for developing public policy adaptations for the benefit of all.
Due to limited computing power, I was not able to assess the many thousands of Cooperative stations for which data exists. Having these data in the analysis would significantly enhance the analysis.
© Brian Brettschneider, 2014