The purpose of this page is to share information about the Köppen climate classification, and to provide data and high-resolution figures from the paper Chen and Chen, 2013: Using the Köppen classification to quantify climate variation and change: An example for 1901–2010 (PDF).
Contents
Abstract
The Köppen climate classification was developed based on the empirical relationship between climate and vegetation. This type of climate classification scheme provides an efficient way to describe climatic conditions defined by multiple variables and their seasonalities with a single metric. Compared with a single variable approach, the Köppen classification can add a new dimension to the description of climate variation. Further, it is generally accepted that the climatic combinations identified with the Köppen classification are ecologically relevant. The classification has therefore been widely used to map geographic distribution of long term mean climate and associated ecosystem conditions. Over the recent years, there has also been an increasing interest in using the classification to identify changes in climate and potential changes in vegetation over time. These successful applications point to the potential of using the Köppen classification as a diagnostic tool to monitor changes in the climatic condition over various time scales.
This work used a global temperature and precipitation observation dataset to reveal variations and changes of climate over the period 1901–2010, demonstrating the power of the Köppen classification in describing not only climate change, but also climate variability on various temporal scales. It is concluded that the most significant change over 1901–2010 is a distinct areal increase of the dry climate (B) accompanied by a significant areal decrease of the polar climate (E) since the 1980s. The areas of spatially stable climate regions for interannual and interdecadal variations are also identified, which have practical and theoretical implications.
Permission and copyright
The data are freely available for scientific and educational purposes. If you plan to use the data, feel free to send a message to hans.chen@chalmers.se and tell me about your work.
The figures are owned by the publisher (Elsevier). To obtain rights to reuse the figures, go to the article and click on Get rights and content under the title. Alternatively, you can create your own map from the data, or you can send me a message (hans.chen@chalmers.se) and I will see if I can help you.
If you benefit from this work, please cite the following article:
Citation: Chen, D. and H. W. Chen (2013): Using the Köppen classification to quantify climate variation and change: An example for 1901–2010. Environmental Development, 6, 69-79, doi:10.1016/j.envdev.2013.03.007.
Maps
The plots below show world maps of the Köppen climate classification and time series of the area change for different types (click on the thumbnails to enlarge). Individual images can be saved by right clicking on the thumbnails and choosing "Save Link As", or you can download all images in one zip file.
Long-time average (1901–2010)
These maps show the Köppen classification for the long-term average climate (1901–2010). The data source is a global observational dataset by Kenji Matsuura and Cort J. Willmott, which combines data from several sources (including GHCN2) interpolated onto a 0.5° longitude × 0.5° latitude grid.
Stable and unstable regions
In the maps below, the Köppen classification was applied on temperature and precipitation averaged over shorter time scales, from interannual to decadal and 30 year. The 30 year averages were calculated with an overlap of 20 years between each sub-period, while the interannual and decadal averages did not have overlapping years. Black regions indicate areas where the major Köppen type has changed at least once during 1901–2010 for a given time scale. Thus, the black regions are likely to be sensitive to climate variations, while the colored regions identify spatially stable regions.
Change in areas
A time series for the global area of each Köppen type was obtained using the 30 year classifications. For each time series, the area anomalies were normalized by the mean area for the whole period to yield the relative area change.
Major types
Subtypes
Download data
| Description | File size | Download |
|---|---|---|
| All data and figures | 9.8 MB | Download |
| Data only | 3.0 MB | Download |
| Figures only | 6.8 MB | Download |
See Permissions and copyright for more information about permissions to reuse the data and figures.
How to read
The data are saved in tab delimited ASCII text files with CRLF line endings. The first line contains the header, followed by 85794 lines with centered grid box coordinates and the Köppen type. Each grid box has a size of 0.5° longitude × 0.5° latitude. For the interannual, decadal, and 30 year time scale there are multiple columns for the type, one column for each average period as indicated by the header.
Here is an example of how the data can be read in Python:
# Example of reading the koppen_1901-2010.tsv file in Python
import numpy as np
koppen = np.genfromtxt("koppen_1901-2010.tsv", dtype=None, names=True)
print("The Koppen type at {} latitude and {} longitude is {}".format(
koppen['latitude'][2], koppen['longitude'][2], koppen['p1901_2010'][2]))
And an example for MATLAB:
% Example of reading the koppen_1901-2010.tsv file in MATLAB
koppen = tdfread('koppen_1901-2010.tsv');
disp(['The Koppen type at ' num2str(koppen.latitude(3)) ' latitude and '
num2str(koppen.longitude(3)) ' longitude is ' koppen.p1901_2010(3,:)])
Classification
This work used the same criteria for the Köppen classification as Kottek et al. (2006) and the tables below are largely based on the tables in their paper. The scheme is described in this section.
The Köppen climate classification uses monthly temperature and precipitation for the twelve months, usually averaged over a long period of time (30 years or more). Climate types are represented by a two or three letter combination in which the first letter defines the major type. The major types can be further divided into subtypes based on the precipitation pattern (second letter, except for the E type) and the temperature (third letter).
Subtypes satisfy the criterion of their parent type(s). There can only be one climate type in a region and is decided in the following order: E is determined first, followed by B, A, C, and D. The second and third letters are decided in the order they are listed in the tables below (for example, if the climate satisfies both Af and Am, it is classified as Af).
Summer is defined as April through September and winter as October through March in the Northern Hemisphere, and vice versa for the Southern Hemisphere.
Example code for implementing the scheme in MATLAB can be found inclassKoppen.m from the MeteoLab toolbox.
First and second letter
| Type | Description |
Criteria |
|---|---|---|
| A | Tropical climates | Coldest month temperature is greater than or equal to +18 °C |
| Af | Tropical rain forest | Driest month precipitation is greater than or equal to 60 mm |
| Am | Tropical monsoons | Driest month precipitation is greater than or equal to 100 - (total annual precipitation in mm/25) mm |
| As | Tropical savanna with dry summer | Driest month precipitation in summer is less than 60 mm |
| Aw | Tropical savanna with dry winter | Driest month precipitation in winter is less than 60 mm |
| B | Dry climates | Total annual is less than 10 times the dryness threshold1 |
| BW | Desert (arid) | Total annual precipitation is less than or equal to 5 times the dryness threshold1 |
| BS | Steppe (semi-arid) | Total annual precipitation is greater than 5 times the dryness threshold1 |
| C | Mild temperate | Coldest month temperature is greater than -3 °C and less than +18 °C |
| Cs | Mild temperate with dry summer | Driest month precipitation in summer is less than driest month in winter, wettest month precipitation in winter is more than 3 times the driest month precipitation in summer, and driest month precipitation in summer is less than 40 mm |
| Cw | Mild temperate with dry winter | Wettest month precipitation in summer is more than 10 times the driest month precipitation in winter, driest month precipitation in winter is less than wettest month precipitation in summer |
| Cf | Mild temperate, fully humid | Not Cs or Cw |
| D | Snow | Coldest month temperature is less than or equal to -3 °C |
| Ds | Snow with dry summer | Driest month precipitation in summer is less than driest month in winter, wettest month precipitation in winter is more than 3 times the driest month precipitation in summer, and driest month precipitation in summer is less than 40 mm |
| Dw | Snow with dry winter | Wettest month precipitation in summer is more than 10 times the driest month precipitation in winter, driest month precipitation in winter is less than wettest month precipitation in summer |
| Df | Snow, fully humid | Not Ds or Dw |
| E | Polar | Warmest month temperature is less than +10 °C |
| ET | Tundra | Warmest month temperature is greater than or equal to 0 °C |
| EF | Frost | Warmest month temperature is less than 0 °C |
1 The dryness threshold is given in mm and depends on the annual mean temperature (Tann) in °C. It is calculated as follows: if at least 2/3 of the annual precipitation occurs in winter, then the dryness threshold is 2×Tann; if at least 2/3 of the annual precipitation occurs in summer, then the dryness threshold is 2×Tann + 28; otherwise the dryness threshold is 2×Tann + 14.
Third letter
| Type | Description |
Criteria |
|---|---|---|
| h | Hot arid | Annual mean temperature is greater than or equal to +18 °C |
| k | Cold arid | Annual mean temperature is less than +18 °C |
| a | Hot summer | Warmest month temperature is greater than or equal to +22 °C |
| b | Warm summer | Warmest month temperature is less than +22 °C and at least 4 months with temperatures greater than or equal to +10 °C |
| c | Cool summer | Warmest month temperature is less than +22 °C, at least 4 months with temperatures less than +10 °C, and coldest month temperature is greater than -38 °C |
| d | Cold summer | Warmest month temperature is less than +22 °C, at least 4 months with temperatures less than +10 °C, and coldest month temperature is less than or equal to -38 °C |
Contact
Feel free to contact us if you have any comments or questions.
- Hans Chen
- Email: hans.chen@chalmers.se
- Website: http://hanschen.org
- Deliang Chen
- Email: deliang@gvc.gu.se
- Website: http://rcg.gvc.gu.se/dc