The MM5 (short for Fifth-Generation Penn State/NCAR Mesoscale Model) is a regional mesoscale model used for creating weather forecasts and climate projections. It is a community model maintained by Penn State University and the National Center for Atmospheric Research. The MM5 is a limited-area, terrain-following sigma coordinate model that is used to replicate or forecast mesoscale and regional scale atmospheric circulation. It has been updated many times since the 1970s to fix bugs, adapt to new technologies, and work on different types of computers and software. It is used in many different ways: for research and for weather prediction. In research, it is used to compare it to other models, to see what works and what does not work. It is also used for air quality models. Active development on the model ended with version 3.7.2 in 2005, and it has been largely superseded by the Weather Research and Forecasting (WRF) model. Features MM5 is globally relocatable, which helps support different latitudes, terrain types, elevations, soil types, etc. . The model can be either hydrostatic or non-hydrostatic, depending on the desired outcome. The fact that the model is regional implies that it requires initial conditions and lateral boundary conditions. This means that each boundary (there are four) has initialized wind speeds, temperatures, pressure and moisture fields. Thus, gridded data is needed for this program. This model takes and then analyzes its data based on pressure surfaces. However, these surfaces must first be interpolated by a specific vertical coordinate before it can be analyzed. This vertical coordinate, sigma, is computed and then used throughout the program. Σ is defined as: Σ = (p-pt)/p*, p* = ps-pt, Where p is pressure, ps is surface pressure, and pt is the pressure at the top of the model. When Σ is close to the ground, the program follows the actual terrain, but when Σ is higher up, the program looks at isobaric surfaces. Σ ranges from 0 to 1. It has adaptable and multiple nesting capabilities, which allows multiple programs to run at once, while utilizing 2-way nesting. MM5 features inputs from actual data, which is helpful because routine observations can be used. Then, data can be compared and used in context with other models. MM5 also features terrain-following vertical coordinates and four-dimensional data assimilation (FDDA) . FDDA is used when there is a lot of data that was taken over a longer period