Conventional experiments are characterized by conducting test to measure changes which follows basic scientific methods. Usually variables are subjected to treatments and replications using a randomly selected subjects. The scientific methods involve processes of “systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses” (Oxford Dictionaries).
A general theory may be developed from a well supported hypothesis (Garland, 2015).On the other hand, numerical simulation contains algorithms and equations used to capture behaviors in creating computer system models. The models that are then run in the program that contains these algorithms and equations is known as computer simulation. Simulation of a system is represented as the running of the system’s model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions (Strogatz in Brockman, 2007).
At present, mathematical modeling of many natural systems in physics (computational physics), astrophysics, climate science, chemistry, biology, ecology, human systems in psychology, social science, and engineering are using computer simulations as a tool to visualize predictive spatial and temporal scales of system behaviors. Digital computer simulation helps study phenomena of great complexity ( Winsberg, 2010) such as weather and climate. Although there is an argument between experimentation and theoretical numerical simulation (computer simulation) which of them is most reliable and valid in the light of environmental science problems especially that variables are subject to dynamic variations and fluctuations, simulation is prone to “representation that fails to represent exactly” (Winsberg, 2010 reviewed by Jerkert, 2012).
The bridge between conventional experiments and numerical simulation is that the experiment results are used as the input to the creation of system model simulations. Simulation worked to build good models of the target system, on the other hand, experiment is based on the object and the target that belong to the system itself (Winsberg, 2010 reviewed by Jerkert, 2012). In a way, both experiment and simulation can be a part of each other, the later as the larger and bigger scale of the other. Simulation model can be always compared with experimental results for validation and calibration to appreciate the real-time representations in 3 dimensional aspects of a system.