Uncertainty Management in Remote Sensing of Climate Data Summary of a Workshop (2009) / Chapter Skim
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3 Concluding Thoughts
3 Concluding Thoughts
Pages 24-25
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From page 24... ...
For example, the importance of climate models for policy making suggests that improved statistical techniques for improving their parameterizations and analyzing their output could have substantial benefits for both the scientific community and society as a whole. There are historical precedents for this type of progress; for example, in the 1970s and 1980s the community recognized that it was critical to gain a better understanding of how clouds affect the earth's radiation budget.
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From page 25... ...
Examples might include the advancement of statistical techniques to address spatial and temporal autocorrelation in large datasets and methods to incorporate more physical knowledge and physical modeling into the statistical models that will help improve calibration and validation studies. With the rich collection of remotely sensed data, the workshop participants discussed that considerable progress could be made by going beyond simple monthly and annual averages to describe the climate system, and that modern statistical methods had much to offer in the area of representing the physical processes that make up the climate system.
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