Software models on prediction and forecasting of climate change are already available on both national and international levels. Here are some resources about. "Climate prediction is similar to numerical weather prediction, but the forecasts are for longer periods. Special numerical models are used to alter trace atmospheric gases (carbon dioxide and methane, for example), sea ice and glacier cover, changes in incoming solar radiation, and a host of other parameters."
The issue of reliability of such models is important.
Software models on prediction and forecasting of climate change are already available on both national and international levels. Here are some resources about. "Climate prediction is similar to numerical weather prediction, but the forecasts are for longer periods. Special numerical models are used to alter trace atmospheric gases (carbon dioxide and methane, for example), sea ice and glacier cover, changes in incoming solar radiation, and a host of other parameters."
The issue of reliability of such models is important.
Climate models are based on well-established physical principles and have been demonstrated to reproduce observed features of recent climate and past climate changes. There is considerable confidence that Atmosphere-Ocean General Circulation Models (AOGCMs) provide credible quantitative estimates of future climate change, particularly at continental and larger scales. Confidence in these estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation).
Research has demonstrated that multi-model ensemble forecasts perform better than any single GCM in simulating observed conditions at a global scale.
Climate models are based on well-established physical principles and have been demonstrated to reproduce observed features of recent climate and past climate changes. There is considerable confidence that Atmosphere-Ocean General Circulation Models (AOGCMs) provide credible quantitative estimates of future climate change, particularly at continental and larger scales. Confidence in these estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation).
Research has demonstrated that multi-model ensemble forecasts perform better than any single GCM in simulating observed conditions at a global scale.
Please go through this, where Dr. Gahul and Dr. Sahid have given their inputs on LOTUS forecasting. Basically ARIMA is a good and realistic (relatively) programme to take care of his issue.
Software applications on forecasting climate changes follow algorithm which is dependent on various factors affecting climate. They patternise and trend with the past so as to assure a reliable information. Prediction with sattelite images give accurate data on 'hard to access' information.
Nature has uncertainty, to read has its own unpredictableness
Software modelings on prediction and forecasting on climate change is especially important for so called 'Precision Agriculture', where novel technologies such as satellites are used for collecting data, softwares are developed for analyzing and predicting the needs of specific farms for farmers. Precision Agriculture will be the future trend of farming practice. Private companies (see below example link) and public sectors for Precision Agriculture have set up to provide the references from those analyzed data to farmers to let them know, for example, (1) what type of weather change around the area, (2) how many seeds need to be used, (3) how to handle the soil type, and (4) how much fertilizer is needed, ------etc., all for the purpose of the best performance of the crops chosen by the farmers and reduce the waste of farmlands and resources.