The process typically involves the following steps:

1. Identify and quantify any biases in the data. Scientists initially analyze the data from all the weather stations available in a region or on a global scale, comparing the data to that of neighboring stations to identify any inconsistencies or outliers.

2. Determine the cause of biases. Once biases are identified, researchers must determine whether these biases result from factors such as changes in instrumentation, aging paint, or other reasons. This may involve analyzing station metadata, information about instrumentation changes, or even conducting site visits to inspect the specific weather station.

3. Apply homogenization algorithms. Several techniques and algorithms exist for homogenizing climate data. One such commonly used method is the "Relative Homogenization Algorithm