CHIMPLOT is an easy-to-use data visualization tool driven by an intuitive graphical user interface. It is designed to visualize modelling results in meteorology, air quality, and climate and to compare simulation results with observations. Downloads from more than 220 different IP addresses are registered so far. CHIMPLOT produces 2D and 1D presentation-quality plots resulting from slicing original 2D to 4D data in any combination of dimensions (longitude, latitude, altitude, time). Longitude-latitude slices are drawn on continents map, with a choice of map projections provided by the Basemap library. The user can choose to plot country borders or national administrative boundaries (regions and departments). Vertical cross-sections between two (longitude, latitude) points can have either altitude or time as the vertical coordinate. Several fields can be easily overlapped, e.g., pressure contours + wind vectors + temperature filled contours. Dimension averaging is just a mouse click when configuring Slices. Other operations, like maximum or standard deviation, both on a single Slice and multiple selected Slices, can be performed by just a few mouse clicks. CHIMPLOT can save plotted Slice data to be further processed with Python. It also supports templates that can be used in a command-line mode to automate model post-processing, e.g., for daily model forecasts. CHIMPLOT is based on the a Python class library chimplotclass that can be used alone or together with CHIMPLOT to develop scripts involving more sophisticated data analysis. The Python libraires currently used by CHIMPLOT are numpy, scipy, matplotlib, Basemap, netCDF4, netcdftime, wx, PythonCard, sys, os, math, copy, shapelib.