The vertical resolution of numerical models improved alongside horizontal resolution, such that models today can have more than 50 vertical layers. Many models have the ability to nest finer grids within a coarse grid resulting in a nested grid with much higher resolution. The horizontal distance between the adjacent grids are often known as grid-spacing or resolution. The NWP models in the 1950s had grid points every few hundred kilometers in the horizontal, whereas today, models used in operational forecasting have grid points every 10-100 km. As the number of discrete grid points increases, so increases the representation of the atmosphere. Comparison of the two figures shows how increasing the number of grid points allows the model to better represent the actual wave function. whereas Figure 1b uses a grid spacing of 0.5 in. Figure 1 demonstrates the importance of the number of discrete grid points in order for the model to best represent the atmospheric structures. The atmosphere is represented in a model by a three-dimensional set of points, called grids that cover the region of interest. ĭue to the amount of computer processor time, memory, and disk storage required to run numerical models, the atmosphere cannot be represented perfectly by the model and thereby is approximated by a finite data set. In the mid 20 th century, models evolved from a simple model with a single atmospheric layer to a multi-layer primitive equation model capable of predicting cyclone development. The observed values are then assimilated and used by the model to predict future evolution of the earth’s weather and climate. The models divide the area of interest into a set of grids and then make use of observations of variables such as surface pressure, winds, temperature and humidity at numerous locations throughout the globe. Numerical models are a mathematical representation of the earth’s climate system including the atmosphere, ocean, cryosphere and land, among others. Since then, such models are playing an increasing role in understanding and predicting weather and climate and have been a driving force in the advancement of the meteorological sciences. With the advent of computers, increased observations, and progress in theoretical understanding, numerical models were developed. Since the early 20th century numerical weather prediction (NWP) has increasingly become one of the most important and complicated problems of modern science.
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