Atmospheric Moisture and Cloud Cover Characteristics Forecast by AMPS*

• Main Authors: Ryan L. Fogt, David, H. Bromwich
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Published: 2006
• Subjects: Amundsen Scott South Pole Station; Amundsen-Scott; Amundsen-Scott South Pole Station; Antarctic; South Pole; Antarc*; Antarctica; South pole
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.3252; http://polarmet.osu.edu/PMG_publications/fogt_bromwich_wf_2008.pdf

Antarctic Mesoscale Prediction System (AMPS) forecasts of atmospheric moisture and cloud fraction (CF) are compared with observations at McMurdo and Amundsen–Scott South Pole station (hereafter, South Pole station) in Antarctica. Overall, it is found that the model produces excessive moisture at both sites in the mid- to upper troposphere because of a weaker vertical decrease of moisture in AMPS than observed. Correlations with observations suggest AMPS does a reasonable job of capturing the low-level moisture variability at McMurdo and the upper-level moisture variability at South Pole station. The model underpredicts the cloud cover at both locations, but changes to the AMPS empirical CF algorithm remove this negative bias by more than doubling the weight given to the cloud ice path. A “pseudosatellite ” product based on the microphysical quantities of cloud ice and cloud liquid water within AMPS is preliminarily evaluated against Defense Meteorological Satellite Program (DMSP) imagery during summer to examine the broader performance of cloud variability in AMPS. These comparisons reveal that the model predicts high-level cloud cover and movement with fidelity, which explains the good agreement between the modified CF algorithm and the observed CF. However, this product also demon-strates deficiencies in capturing low-level cloudiness over cold ice surfaces primarily related to insufficient supercooled liquid water produced by the microphysics scheme, which also reduces the CF correlation with observations. The results suggest that AMPS predicts the overall CF amount and high cloud variability notably well, making it a reliable tool for longer-term climate studies of these fields in Antarctica. 1.