Why study the uncertainty?

Without realistic uncertainty estimates we are not doing science!
In the past, numerous conclusions have been drawn from MSU/AMSU data with little regard to the long term uncertainty in the data.
Most previous error analyses for MSU/AMSU data sets have focused on decadal-scale trends in global-scale means, while in contrast, many applications are focused on shorter time scales and smaller spatial scales.
Here we describe a comprehensive analysis of the uncertainty in the RSS MSU/AMSU products. The results can be used to evaluate the estimated uncertainty on all relevant temporal and spatial scales.

Issues

Our MSU/AMSU products use data from 14 different satellites. The data need to be intercalibrated before being merged together. This is a complex process, as shown in the flow chart below.

First, adjustments are made for changes in local measurement time (diurnal adjustment) and Earth incidence angle.
Then, intercalibration is performed by comparing measurements from co-orbiting satellites, yielding a set of “merging parameters”.
Uncertainty that arises earlier in the process (e.g. from the adjustments for local measurement time) can cause uncertainty in the merging parameters, which adds to the uncertainty in the final results.

Because of the complex nature of the errors, they are difficult to calculate and describe using simple statistical methods. Instead, we use a Monte Carlo technique to produce a large number of possible realizations of the errors that are consistent with the sources of error that we have studied.

Available Uncertainty Information and Recommendations

We have constructed a 400 error ensemble for each of the MSU/AMSU products we produce. (No uncertainty analysis has yet been performed on the AMSU only stratospheric channels.) These uncertainty realizations are available in netCDF, with exactly the same form as the baseline temperature data.

Acknowledgement

MSU/AMSU data are produced by Remote Sensing Systems. Over the years, we have received support for the development of this dataset from a number of sources, including NOAA's Office of Global Programs, NOAA's Climate Program Office, and NOAA's Climate Data Record Program. Production of the current dataset (version 3.3) is supported by NOAA's Climate Data Record Program, while improvements to the methods used to produce the dataset are currently supported by NASA's Earth Science Division, which is part of the Science Mission Directorate.

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