Measurements of Earth's energy budget with sufficient accuracy for climate studies began about 1985 with the Earth Radiation Budget Experiment. Measurements of water vapor and upper tropospheric temperature need to be improved in both accuracy and sampling. At the present time cloud data come from two sources: surface visual observations (Hahn and Warren, 1999) and meteorological imaging instruments on operational satellites (Rossow and Schiffer, 1999). The International Satellite Cloud Climatology Project (ISCCP) data provide estimates of cloud-top temperature and visible optical depth on spatial scales of tens of kilometers. These data have seen only limited use in climate model validation (e.g., Klein and Jakob 1999; Webb et al., 2001). More of this kind of analysis is needed. In addition, more detailed global observations of clouds, including such things as vertical structure and cloud particle size, are needed to test climate model parameterizations and their relationship with precipitation, water vapor, and air temperature.
Current satellite data give only rather crude estimates of cloud particle size and cannot readily distinguish cloud water from cloud ice. Passive infrared sensing of cloud-top height is imprecise when the clouds are not optically thick, which is an important constraint when studying high, thin clouds in the tropics and elsewhere. New cloud data are becoming available from instruments on satellites that use polarization of reflected sunlight and active scanning with cloud radars and lidars to probe the vertical structure and particle size of clouds. These data will provide an important new source of data on the global distribution of clouds that should be used to further constrain and test the simulation of clouds in climate models.
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