Changes in Antarctic net precipitation in the 21st century based on Intergovernmental Panel on Climate Change (IPCC) model scenarios

Projections from 15 global climate models and 2 reanalysis products (National Center for Environmental Prediction (NCEP)/National Center for Atmospheric and Climate Research (NCAR) reanalysis (NNR) and European Centre for Medium‐Range Weather Forecasts (ECMWF) 40‐year reanalysis (ERA40)) were utilized to project changes in the net precipitation ( P − E ) over the Southern Ocean and Antarctica during the 21st century. Three time periods, 1979–2000, 2046–2055, and 2091–2100, of data were compared. The P − E was related to a classification of synoptic circulation patterns obtained using a neural network algorithm known as self‐organizing maps (SOMs). SOM classification was successfully used as a quality control tool to assess the simulated atmospheric circulation and model performance in P − E . The models predicted an increase of Antarctic P − E that averages 0.42 ± 0.01 mm year −1 for the coming hundred years based on the difference between 1979–2000 and 2091–2100. P − E changes of individual models ranged from 0.02 to 0.71 mm year −1 . P − E integrated over the entire Antarctic ice sheet was forecast to increase more quickly from the end of the twentieth century until 2046–2055 than from 2046–2055 until 2091–2100. Contributions to the predicted change in P − E were evaluated for both thermodynamic and dynamic processes. The projected change in Antarctic P − E was primarily due to thermodynamic changes rather than circulation changes. The dynamic component of P − E change, associated with the circulation, was important at subcontinental scales, especially over the coastal regions. The role of dynamic changes was maintained until the end of the 21st century. Intermodel variation in predicted P − E changes and differences between models and reanalyses in the twentieth‐century simulations severely restrict the reliability of these projections and highlight the need for improved polar simulations in climate models.