Environmental Science consistently proposes problems with intense complexity and is usually characterized by nonlinear progression dynamics. Systems which are involved in this inquiry makes them complicated due to a lot of interactions from different components. These systems develop under the feat of macroscopic driving as well as modulating agents. The most appropriate example for such a system is the entire climatic system. The Climatic system consists of four closely unified subsystems such as biosphere, cryosphere, atmosphere and hydrosphere. These subsystems get powered by the electromagnetic radiations that are being emitted b the Sun. Such subsystems that form a part of the environment are really complicated and always interact with each other in a nonlinear way.

Some of the applications of Environmental Science and Technology in the present era are as listed below:

• Design, organize and conduct scientific environmental research
• Contribute to the development of innovative technologies for solving environmental problems
• Analyse dynamic interactions in complex human environment systems
• Formulate data requirements and data collection strategies and design
• Apply  conceptual and computational models for a better understanding of these systems
• Provide scientific advice for policy development and decision making.

Weather Forecast

The chore of weather forecast is to give the best depiction of the evolution that has occurred within a short span of time evocative of the state of atmosphere such as pressure, wind, precipitation, temperature, humidity etc. Weather forecast is defined as the prediction of the immediate values of the main atmospheric variables. The time period of the weather forecasts ranges upto the predictability horizon of the atmosphere and it can be clearly estimated within 7 to 10 days.  In order to represent the unavoidable uncertainty of the system, the initial conditions should be selected suitably.

Climate simulation

The simulation of the climate includes a set of statistical properties that can be represented in the time or space domains. The time as well as space domains are used to describe the structure and performance of the different parts of the climatic system.  The climatic models are created to represent and incorporate the statistical properties. The models help in assessing the change of the statistical properties with time when studying about the past or present climatic conditions. The relevant uncertainties are not related to the initial conditions of the system in the case of climate modeling. The ab-initio formulations that are based on the first principle cannot be used here. We can use it along with coarse-grain discretization rather to the very first structure of the model.