Near real-time observation of sea temperature is an important management tool for monitoring the impacts associated with a changing climate on a range of marine communities particularly within marine protected areas. However, limitations exist when using data derived from satellite remote sensing as virtual stations are usually distant from areas of interest for management. Modelled sea surface temperature will, in most cases, provide a general over a large spatial scale rather than a specific prediction. Understanding the relationship between remotely sensed sea temperature and in situ temperature enables real-time management responses to sea temperature, in relation to both long-term changes and short-term anomalies, and their biological implications. Historically, the effects of most thermal stress events on marine communities have been observed opportunistically or realised well after the event, due to the use of in situ loggers and the associated time-lag between the event, logger retrieval and data interpretation. Understanding the susceptibility of marine communities to, and recovery from, thermal stress events requires reliable estimation of the events in real time at local spatial scales. To further understand the relationship between in situ and satellite derived sea temperatures, and develop a real-time monitoring tool, a simple linear interpolation was undertaken to estimate local in situ temperature, at depth, using near real-time satellite derived sea surface temperatures. The US National Oceanic and Atmospheric Administration's (NOAA) Coral Reef Watch 50 km sea surface temperature (SST) data was selected because of its readily available and continual near real-time update of sea surface temperatures worldwide. In situ temperature logger data from four Western Australian marine protected areas (MPAs) were used to develop and test the linear interpolation. Utilising the model, we were able to successfully estimate the in situ temperature to within ±1 °C, at least 78% of the time, including temperature anomalies experienced in February 2011, at sites of interest across the four MPAs. This simple linear interpolation model will be used to improve near real-time estimates of temperature for broadscale monitoring of MPAs throughout Western Australia, allowing greater understanding and informed management response to long-term changes and short-term temperature anomalies. Future expansion of the sites monitored, improved satellites resolution and an annual review of data sources will ensure that the data used for management of this threat to water quality remains at the highest level of accuracy possible with the available data.