The depth of seasonal thaw (the active layer depth) integrates a range of soil and atmospheric climate variables and has potential to provide a clear signal of a changing climate. Nine soil climate monitoring stations (SCS) were established between 1999 and 2012 and are currently operating in the Ross Sea Region of Antarctica. At each monitoring station soil temperature and moisture are measured at a range of depths down to 120 cm. Atmospheric variables measured include; air temperature, relative humidity, solar radiation, and windspeed and direction. Data validation has been carried out through the comparison of multiple sensors and has given confidence in the dataset. The objectives of this thesis were to; describe the active layer, assess the dataset for significant long-term trends, investigate the link between large scale climate systems and permafrost temperature, to test the model of Adlam et al. (2010), and develop a predictive model suitable for modelling all ice free areas in Antarctica. Active layer depth (ALD) showed marked between-year variation, and between the SCS establishment and 2018. The mean ALD was 7.5 cm at Mt Fleming, 38 cm at the Wright Valley South Wall, 37 cm at the Wright Valley North Wall, 23 cm at Victoria Valley, 49 cm at the Wright Valley floor, 50 cm on the coast at Marble Point, 29 cm at Minna Bluff, 33 cm at Scott Base, and >90 cm at Granite Harbour. There were no significant trends of warming or cooling in either ALD or in temperature at top of the permafrost. Relationships between ALD and altitude (R²=0.71), and with latitude (R²= 0.66) were identified. Wavelet analysis showed that both global and regional climate systems were significant drivers of de-seasonalised permafrost temperature (p <0.05). The Southern Annular Mode showed relationships at both annual and biannual timescales; the Southern Oscillation Index had a relationship at a two to three year timescale; and the Amundsen Sea Low had an annual signal and some between season signals with de-seasonalised permafrost temperature, at the Wright Valley Floor, Victoria Valley, Marble Point and at Mt Fleming. Nineteen potential models were developed using stepwise analysis and compared to the previous work of Adlam et al. (2010). Model 8 (Adj R² = 0.75) accounted for more variation in the data than the Adlam et al. (2010) model (Adj R² = 0.69) and predicted the ALD within ±10 cm at the five low altitude sites, using mean summer air temperature, mean winter air temperature, altitude and mean summer surface temperature. Model 14 (Adj R² = 0.49) was developed using data from all eight SCS sites, and was able to predict the ALD at high altitude sites within < ±11 cm, and the low altitude sites within < ±20 cm. Model 14 did not capture the between year variation with detail. Future testing of model 8 and 14 is recommended using data from other parts of Antarctica, and both models could also be used to explore the use of satellite remote sensed surface temperature data in predicting ALD. The database comprises approximately 87,000,000 data points, collected from both soil and atmospheric sensors, and becomes more valuable with time as the record gets longer. This thesis did not use all the available data in the network, and further research is recommended. The SCS network provides a robust baseline to predict future change and understand how Antarctica is impacted by the changing global climate.