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forcing dataset is only available during this period. To have cloud information at the ARM SGP site, surface observations from a vertically pointing cloud radar and micropulse lidar pair have also been collected along with Geostationary Operational Environmental Satellite (GOES) observations. All forcing and reanalyses have been processed to identical temporal and spatial resolutions for comparison in sections 3 and 4 . For example, the results from the two reanalyses are averaged in space to the
forcing dataset is only available during this period. To have cloud information at the ARM SGP site, surface observations from a vertically pointing cloud radar and micropulse lidar pair have also been collected along with Geostationary Operational Environmental Satellite (GOES) observations. All forcing and reanalyses have been processed to identical temporal and spatial resolutions for comparison in sections 3 and 4 . For example, the results from the two reanalyses are averaged in space to the
1. Introduction Over the past few decades, atmospheric reanalysis datasets have provided a long-term, gridded representation of the state of the atmosphere while offering a resource for investigating climate processes and predictability. Reanalyses utilize observations through state-of-the-art data assimilation systems. Combined with underlying models, they provide a continuous data record that consists of various atmospheric variables describing (diagnosing) past weather conditions. Reanalyses
1. Introduction Over the past few decades, atmospheric reanalysis datasets have provided a long-term, gridded representation of the state of the atmosphere while offering a resource for investigating climate processes and predictability. Reanalyses utilize observations through state-of-the-art data assimilation systems. Combined with underlying models, they provide a continuous data record that consists of various atmospheric variables describing (diagnosing) past weather conditions. Reanalyses
