International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 2 Issue: 8 2184 – 2189 _______________________________________________________________________________________________ 2184 IJRITCC | August 2014, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Data Mining Techniques for Weather Prediction: A Review Divya Chauhan Department of Computer Science Himachal Pradesh University Shimla 5, India dvcherish90@gmail.com Jawahar Thakur Department of Computer Science Himachal Pradesh University Shimla 5, India jawahar.hpu@gmail.com Abstract— Data mining is the computer assisted process of digging through and analysing enormous sets of data and then extracting the meaningful data. Data mining tools predicts behaviours and future trends, allowing businesses to make proactive decisions. It can answer questions that traditionally were very time consuming to resolve. Therefore they can be used to predict meteorological data that is weather prediction. Weather prediction is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems across the world in the last century. Predicting the weather is essential to help preparing for the best and the worst of the climate. Accurate Weather Prediction has been one of the most challenging problems around the world. Many weather predictions like rainfall prediction, thunderstorm prediction, predicting cloud conditions are major challenges for atmospheric research. This paper presents the review of Data Mining Techniques for Weather Prediction and studies the benefit of using it. The paper provides a survey of available literatures of some algorithms employed by different researchers to utilize various data mining techniques, for Weather Prediction. The work that has been done by various researchers in this field has been reviewed and compared in a tabular form. For weather prediction, decision tree and k- mean clustering proves to be good with higher prediction accuracy than other techniques of data mining. Keywords- Data Mining, Decision Trees, Artificial Neural Network, Regression, Clustering. __________________________________________________*****_________________________________________________ I. INTRODUCTION Data mining [13] is a process which finds useful patterns from large amount of data. Data mining can also be defined as the process of extracting implicit, previously unknown and useful information and knowledge from large quantities of noisy, ambiguous, random, incomplete data for practical application. It is a powerful new technology with great potential to help companies focus on the most important information in their databases. It uses machine learning, statistical and visualization technique to discover and predict knowledge in a form which is understandable to the user. Prediction is the most important technique of data mining which employs a set of pre-classified examples to develop a model that can classify the data and discover relationship between independent and dependent data. Weather prediction is the application of science and technology to predict the state of the atmosphere for a given location. It is becoming increasingly vital for scientists, agriculturists, farmers, global food security, disaster management and related organizations to understand the natural phenomena to plan and be prepared for the future [17,37,19,35].The art of weather prediction began with early civilizations using reoccurring astronomical and meteorological events to help them monitor seasonal changes in the weather. Throughout the centuries, attempts have been made to produce forecasts based on weather changes and personal observations. Many meteorological instruments were being refined during the previous centuries. Other related developments that are, theoretical, and technological developments, also contributed to our knowledge of the atmospheric weather conditions. Weather prediction is an important goal of atmospheric research. Hence changes weather condition is risky for human society [3,5,15].It affects the human society in all the possible ways. Weather prediction is usually done using the data gathered by remote sensing satellites. Various weather parameters like temperature, rainfall, and cloud conditions are projected using image taken by meteorological satellites to access future trends. The satellite based systems are expensive and requires complete support systems. The variables defining weather conditions varies continuously with time, prediction model can be developed either statistically or by using some other means like decision tree, artificial neural networks, regression, clustering techniques of data mining. Weather prediction is a form of data mining which is concerned with finding hidden patterns inside largely available meteorological data [31]. Rest of the paper is organized as follows. Section II narrates the background study of data mining and weather prediction. Section III discusses the literature review of various data mining techniques used for predicting weather. Section IV gives the comparison of work done by researchers. Finally, the paper is concluded in section V. II. BACKGROUND STUDY A. Data Mining Data mining is the science and technology of exploring data in order to discover unexplored patterns. Traditionally, data acquisition was considered as one of the most important stages of data analysis [36]. The data had to be collected manually so the quantity was also small. So the decisions were based on limited information. But now, gathering data has become easier and storing it has become inexpensive. Unfortunately, as the amount of information increases, it becomes harder to