Lossy compression of climate data using principal component analysis

Enormous size of climate data has posed a difficulty in terms of storage since a long time. Principal Component Analysis is a well known method used for data compression. This paper gives a brief idea about the compression of climate data using Principal Component Analysis by modifying the data obtained from the weather station. A minor modification in handling data led to a high compression ratio. This compressed file can then be processed to retrieve the data again with a significant accuracy. The data obtained from the retrieval using compressed file almost matched the real time data.