Climate classification is a subset of climatology and geography that aims to formalize systems that recognize climatic similarities and differences between geographic areas to further the understanding of climate concerning geography. Many classification schemes rely upon large data sets to detect patterns in geographical areas. These patterns include precipitation, temperature, seasonal patterns, vegetation, and pure observation. Climate classification can either be empirical (quantitative and evidence-based) or genetic (qualitative and observation based). Although climatology is incredibly multi-dimensional, climatologists have attempted to aggregate data to visualize climatic zones on maps. An example of such would be the Köppen-Geiger Climate Classification system, which is a system that uses empirical, evidence-based methods to compare similarities and differences between geographic zones and vegetation zones (biomes). I am curious about the evolution of climate classification maps, their criticisms, and if climate zones can truly and accurately be visualized to represent such a multi-dimensional concept.
I was inspired to research climate classification maps throughout history because of a New York Times visualization on which I did a short critique. This visualization was less about climate and more about water levels concerning California’s draught. Despite the difference in the topic, I couldn’t help but feel that most geospatial visualizations that concern climate in one matter or another are all but related to the Köppen-Geiger climate classification system. There is a clear progression and evolution in geospatial visualizations (mapmaking), especially regarding climatology. Some elements, such as design, color, and the use of keys or legends concerning climate, have their roots in early climatology visualizations.
I used Timeline JS, an open-source tool from Northwestern University Knight Lab, to create my timeline visualization. This resource was incredibly helpful in visualizing information on a chronological line. The timeline was constructed from a Google Spreadsheet template, where an open publication link was required to generate the timeline on Timeline JS. Additionally, I used many resources, such as encyclopedias and open forums, to search for images of original climate map publications dating back to 1884.
I am familiar with climate classification systems and maps, as I have researched and produced geospatial visualizations inspired by the Köppen-Geiger classification system. I did a cursory analysis of all major climate classification maps. I compared them visually and methodologically in how they were created, what they rivaled, and what was created from them. I then determined that there was a timeline from the initial creation of sophisticated climate classification maps in 1884 up to the present day. I determined that there were six major dates in climate classification map history. I then paired the dates with corresponding climate classification maps; almost all are original publications.
I could determine several crucial dates in the timeline of climate classification map history. Starting in 1884 with the first Köppen climate classification map, Köppen based his visualization off of thermal zones and their relation to biomes. He then updated this map two major times, in 1900 and 1918. His schematic in 1900 was his first true climate classification system which based climate zones on precipitation, temperature, and vegetation. In 1918, Köppen published an updated schematic that adjusted for seasonal patterns. I then determined that other climatologists and geographers created climate classification schematics in response to Köppen’s system; some of the reasons included filling gaps in Köppen’s schematic, using entirely different methods or even political reasons. An example of a geopolitical reason for creating a climate classification system was the Cold War. In 1954, Boris P. Alisov, a Soviet climatologist, created a schematic that Soviet scientists would only use.
Moving forward in the timeline, a map created to fill the gaps in Köppen’s schematic, was the Climate classification by Wincenty Okołowicz, a polish climatologist. Okołowicz believed that Köppen had peculiarities in his classification of polar climates. Some climate maps were created using entirely different research methods. Köppen’s map was an empirical, evidence-based map that used statistics and data points aggregated into geographic, climatic zones. A map that rivaled Köppen’s classification was the Trewartha climate classification by American geographer Glenn Thomas Trewartha in 1966. It is a modified version of the Köppen-Geiger climate classification system, created to fill in gaps. The Trewartha system redefined the middle latitudes to be closer to vegetation zoning and genetic climate systems. Genetic climate systems meant more qualitative and observation-based methods were used in creating classifications. Lastly, the Global environmental stratification (GEnS) is based on the statistical aggregation of bioclimate data created by Marc J. Metzger in 2012. A large set of climate variables were used in a quantitative model, which sections geographic zones into bioclimate regions. Metzger’s GEnS would act as the most modern and sophisticated climate classification system. All of these climate classification systems were created as a result of the need for a classification system, a political counter-response to the west, or as a rivaling system.
All major climate classification systems are incredibly important in understanding geospatial data visualization concerning the climate. I think now more than ever, it is pertinent to understand these maps as we face a full-scale climate crisis. Although some of these maps contradict each other, we have much more modern, sophisticated software to observe climate zones. Historical maps are a keystone in the development of visualizing climatology data. Wladimir Köppen updated his classification system every year until he passed in 1940. He updated this system as new research was released, determined new conclusions, and adjusted for newer climate classification systems. These historical maps reinforce the importance of understanding historical data and how we can learn from predefined variables that are well-researched and don’t necessarily need to be changed.
Many climate classification systems exist, and many maps are out there to visualize such data. A limitation of my research would be my limited access to historically published maps. Despite my inability to access all historical climate classification maps, I believe I was able to establish a reliable timeline that illustrates an important progression in map-making and geospatial data visualization. As climate change progresses, climatologists can more effectively visualize the changes in our environment through various methods, many of which are established research methods and perhaps more cutting-edge methods that have not been executed yet. As geospatial visualization software progresses, so will the visualization of climate classification mapping.