*Result*: XSLICE: An Efficient Visualization and Diagnosis Tool for Four-Dimensional Climate Dynamics.

*This paper introduces a convenient and fast computer visualization tool for climate data defined on four-dimensional (4D) spatiotemporal coordinates: longitude, latitude, elevation or depth, and time. The tool is named XSLICE, which stands for Cross-Sectional Layers with Interactive Cropping and Exportation. The name also means an anatomy by cross-sectional slices for a 4D climate field. The sliced field is thus visualized on a plane of two variables, such as xy plane for a horizontal cross section, xz plane for a zonal vertical cross section, and yt plane for a latitude-based Hovmöller diagram. As a demonstration, we applied XSLICE to the monthly data from the Global Ocean Data Assimilation System (GODAS). The GODAS dataset is a NOAA real-time ocean analysis and reanalysis consisting of 40 depth layers on a 1/3° × 1° latitude–longitude spatial grid ranging 74.5°S–64.5°N for latitude and 0°–359° for longitude with temporal coverage from January 1980 to the present. The GODAS variables include potential temperature, salinity, u current, υ current, and others. We show that XSLICE can conveniently and quickly display various kinds of climate dynamics patterns, such as El Niño and equatorial upwelling, sliced in different planes at proper locations and displayed with customizable coloring and cropping. As such, XSLICE can serve as an exploratory research tool to gain insight on process dynamics before pursuing further quantitative analysis of observed data or model outputs. XSLICE's easiness to use makes it attractive as an educational and public outreach tool to inspire and engage in climate science or in a broader range of science and engineering fields. Significance Statement: We present a fast and convenient tool to visualize four-dimensional space–time climate data. The tool is named Cross-Sectional Layers with Interactive Cropping and Exportation (XSLICE) and can visualize the gridded space–time data of ocean or atmosphere with six different space–space or space–time cross sections. The easy and efficient use of XSLICE allows to quickly visualize and diagnose climate dynamic patterns or significant anomalies, which can guide further quantitative analysis. XSLICE does not require computer programming training and can be used in classrooms to engage and inspire students in climate science. XSLICE is portable and can be applied to three- or four-dimensional gridded data in any other space–time fields of science and engineering. [ABSTRACT FROM AUTHOR]*