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The mechanisms and geographic distribution of global tidal dissipation in barotropic tidal models are examined using a high resolution unstructured mesh finite element model. Mesh resolution varies between 2 and 25 km and is especially focused on inner shelves and steep bathymetric gradients. Tidal response sensitivities to bathymetric changes are examined to put into context response sensitivities to frictional processes. We confirm that the Ronne Ice Shelf dramatically affects Atlantic tides but also find that bathymetry in the Hudson Bay system is a critical control. We follow a sequential frictional parameter optimization process and use TPXO9 data‐assimilated tidal elevations as a reference solution. From simulated velocities and depths, dissipation within the global model is estimated and allows us to pinpoint dissipation at high resolution. Boundary layer dissipation is extremely focused with 1.4% of the ocean accounting for 90% of the total. Internal tide friction is much more distributed with 16.7% of the ocean accounting for 90% of the total. Often highly regional dissipation can impact basin‐scale and even ocean wide tides. Optimized boundary layer friction parameters correlate very well with the physical characteristics of the locality with high friction factors associated with energetic tidal regions, deep ocean island chains, and ice covered areas. Global complex M2tide errors are 1.94 cm in deep waters. Total global boundary layer and internal tide dissipation are estimated, respectively, at 1.83 and 1.49 TW. This continues the trend in the literature toward attributing more dissipation to internal tides. This study studies how and where tides dissipate energy in the ocean. Using current speeds and water levels, it is possible to estimate how much energy the ocean dissipates and find areas that are particularly energetic. An important aspect of tidal modeling is accurately setting the depth of the ocean. We identify areas of the ocean where it is very important to have accurate water depths for accurate results by using different bathymetric databases. Additionally, we find what areas of the ocean are sensitive to changes in energy dissipation. This is done via altering frictional coefficients in our model for both friction between the ocean floor and the bottom of the water column, and for internal waves that are generated near steep topography with strong vertical density gradients. With this information, we determine optimal friction coefficients, improving the tides in our model. We find that the friction coefficients obtained through the optimization process correlate well to the physical characteristics of the assigned regions. We also determine where and how energy is dissipated enabling us to pinpoint the most significant dissipation regions. Boundary layer dissipation is concentrated in a small portion of the ocean while baroclinic conversion is more distributedBoundary layer dissipation on certain shelves controls basin‐scale tidesFrictional coefficients derived via optimization methods are consistent with regional physical and hydrodynamic characteristics Boundary layer dissipation is concentrated in a small portion of the ocean while baroclinic conversion is more distributed Boundary layer dissipation on certain shelves controls basin‐scale tides Frictional coefficients derived via optimization methods are consistent with regional physical and hydrodynamic characteristics