摘要: The DOE's Atmospheric Radiation Measurement (ARM) Program employs both upward- and downward-looking remote-sensing instruments to measure the horizontal and vertical distributions of clouds across its Southern Great Plains (SGP) s... 展开 The DOE's Atmospheric Radiation Measurement (ARM) Program employs both upward- and downward-looking remote-sensing instruments to measure the horizontal and vertical distributions of clouds across its Southern Great Plains (SGP) site. No single instrument is capable of completely determining these distributions over the scales of interest to ARM's Single Column Modeling (SCM) and Instantaneous Radiative Flux (IRF) groups; these groups embody the primary strategies through which ARM expects to achieve its objectives of developing and testing cloud formation (USDOE, 1996). Collectively, however, the data from ARM's cloud-detecting instruments offer the potential for such a three-dimensional characterization. Data intercomparisons, like the ones illustrated here, are steps in this direction. Specifically, they are valuable because they help: provide a measure of uncertainty in ARM's measurement capabilities, calibrate retrieval methods and refine algorithms and concepts. In the process, we are forced to think of meaningful ways in which measurements from different instruments can be compared and, perhaps, combined. While the ultimate goal of this particular effort is to develop the ability to accurately characterize cloud fields in three dimensions over time at the SGP site, along the way we will address such questions as which source, or combination of cloud data sources, offers a best estimate product and how can cloud observations be used to evaluate the representation of clouds in numerical models. Examples of some initial comparisons, involving satellite, millimeter cloud radar, whole sky imager and ceilometer data, are provided herein. 收起