Open AccessWeather systems occurring over Fort Simpson, Northwest Territories, Canada, during three seasons of 1998–1999: 1. Cloud features
Author(s) -
Hudak D.,
Currie B.,
Stewart R.,
Rodriguez P.,
Burford J.,
Bussières N.,
Kochtubajda B.
Publication year - 2004
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2004jd004876
Subject(s) - environmental science , cloud top , cloud computing , radar , cloud fraction , cloud height , climatology , meteorology , satellite , cloud cover , atmospheric sciences , latitude , remote sensing , geology , geography , computer science , telecommunications , engineering , geodesy , aerospace engineering , operating system
An investigation of high‐latitude continental cloud systems was carried out in the interior of the Northwest Territories of Canada during three multiweek periods during the fall, winter, and spring of 1998–1999 as part of the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study. Radar data supplemented by satellite, upper air, and surface observations were used to determine the seasonal behavior of cloud macroscopic properties and compare these with similar observations elsewhere. Unique features included the prevalence of multilayered systems, the cold temperatures of low clouds, and a significant diurnal trend in cloud properties in the winter. A synoptic classification was developed and shown to be an important factor in explaining the variability of cloud properties. A consistent picture emerges of the upslope component and wind shear aloft contributing to the cloud structure in five synoptic classes. Vertically resolved cloud properties highlighted the importance of the ice process in these cloud systems. The cloud system reflectivity and temperature dependencies further supported the synoptic characterizations and highlighted the significance of using seasonally based relationships in automated cloud identification algorithms. The implication of the cloud system variability for radiation measurements was also shown. The radar reflectivity data, degraded to match CloudSat resolution and sensitivity, showed that cloud detection was reliable but that there was a positive bias with cloud thickness. Negative biases in cloud top retrievals based on advanced very high resolution radiometer data were also identified. The Global Environmental Multiscale model illustrated some degree of bias in the occurrence and vertical distribution of these cloud systems. Winter situations in general and midclouds situations in particular were the most poorly handled in both the satellite applications and the model simulations.