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Sea ice forecasts for the Arctic are investigated. Sea ice forecasts are generated for 6 hours to 9 days using the Marginal Ice Zone Modelling and Assimilation System (MIZMAS) driven with 6 hourly forecasts of atmospheric forcing variables from the NOAA Climate Forecast System (CFSv2). Forecast sea ice drift speed is compared to observations from drifting buoys and other observation platforms. Forecast buoy positions are compared with observed positions at 24 hours to 9 days from the initial forecast. The initial thickness fields are compared to aircraft remote sensing data from Operation IceBridge (OIB). Forecast Ice concentrations and ice edge positions are compared to passive microwave products. Forecast skill is assessed relative to reference forecasts based on climatology or persistence. RMS errors for ice speed are found in the order of 5 km/day for 24 h to 48 h using the sea ice model vs. 12 km/day using climatology. Following adjustments in the sea ice model to remove systematic biases in direction and speed, predicted buoy position RMS errors are 6.5 km for 24 hour forecasts and 15 km after 72 hours. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10x10 km sized image to 95% vs. 50% using climatology. Initial ice thickness computed by MIZMAS compares well with OIB data. Skill assessment of ice edge position forecasts faces challenges due to observational uncertainty and shows room for improvement. The results are generated in the context of planning and scheduling the acquisition of high resolution images which need to follow buoys or research platforms for scientific research but additional applications such as navigation in the Arctic waters may benefit from this accuracy assessment. Ideas for future improvement of short term sea ice forecasts are explored. Implications for intra-seasonal forecasts are considered.