The increased availability of daily model output in the latest generation of climate models should allow us a greater understanding of, and an improved ability to predict, future trends in short duration extreme temperature events. We examine the changes in 1, 3, and 5 day averaged annual maximum temperature at the levels of global warming highlighted by the 2016 Paris Agreement, and an additional degree of warming. These events are characterised using daily near surface air temperature output from four large ensemble models in the SSP370 scenario of the Coupled Model Intercomparison Project Phase Six (CMIP6). Bootstrapped distributions of ensemble members are fitted to the generalised extreme value distribution and the changes in location, scale and shape parameters examined at the respective warming levels, compared to the last 10 years of historical model runs. Global trends in location parameter indicate increased warming over land relative to oceans while shape and scale parameters show less globally consistent trends but very clear signals of strong changes over the Arctic sea ice. Risk ratios are determined for extreme temperature events with a return value of 10 years in the historical period, compared to future levels of warming, using the calculated GEV distributions. Risk Ratios increase globally with mean temperature change, with greater increases over the tropics, particularly over the oceans. Longer events are also found to have a greater increase in occurrence than shorter duration temperature extremes.