Climate classification for the earth's oceanic areas using the KӦppen System

Abstract

The objective of this thesis is classify climate for the Earth’s ocean areas. The classifica-tion task is accomplished in part by using monthly average sea surface temperature and precipita-tion data from 1980-2008. Coast-to-coast coverage of the needed data were obtained from the reanalysis product produced by the National Centers for Environmental Prediction and the National Center for Atmospheric Research. Köppen’s classification scheme was implemented in the ArcGIS suite of software, which was used to analyze and display all of the classified map products. Russell’s ‘climatic years’ concept was used and separate classifications were produce for each year of available data. Findings indicate that the oceans are very different from land areas when it comes to the location and extent of varying climate types. Some main findings include the idea that A, C, and E climates dominate the geography of the oceans and that there are zero continental, or D, climates. Also, the Southern Oscillation plays an important part in tropical ocean dynamics and climate, but summarizing twenty nine years of mapped patterns into a summary product removes any major effect from yearly climate system anomalies. A key finding is an argument that supports the establishment of a unique Southern Ocean surrounding Antarctica. There are polar, ET and EF, climate subtypes surrounding both the Arctic and Antarctic poles, but only the north has the well established Arctic Ocean. Oceanic E climate areas are more pronounced in the Southern Hemisphere with circumpolar rings around the Antarctic continent. Classification results support the idea of a Southern Ocean based on the spatial pattern of climate types and in view of the fact that that the climate of the Southern Ocean area is so different from the temperate, or C, climate and its subtypes. This research is important for many reasons, the primary being that climate classification helps us better understand the world around us. It is difficult to see change in the environment without first knowing what the state of the system used to be. Classification will also help depict the changes that have happened, when these shifts in climate occurred, and with that information we can better predict what the future will hold.