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9998-revision-ecmwf-humidity-analysis-construction-gaussian-control-variable.pdf
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Summary

The ECMWF is revising its humidity analysis by constructing a Gaussian control variable, aiming for simpler error characteristics. Currently, specific humidity q is used, but its background error covariances are partly statistical and partly empirical. The goal is to find a control variable with close to Gaussian error statistics, which can be accurately modeled within the least square formulation of the analysis system.

The study analyzes probability distributions of humidity forecast differences, finding that forecast differences for q, logq, and RH show exponential-like error distributions, rather than Gaussian. However, for a limited geographical region and/or similar background values, the distributions are easier to approximate with a Gaussian.

To find a Gaussian control variable, the study determines the bias and standard deviation of forecast differences as a function of a variable Φ, normalizing forecast differences by the bias and standard deviation. The result is a uniformly Gaussian distribution for all levels, with zero bias and a standard deviation of 1.

Relative humidity RH is found to have reasonably homogeneous statistics, and a linear transformation of RH is proposed as a control variable. The transformation involves normalizing RH by its standard deviation and bias, resulting in a Gaussian distribution. This new control variable can be used in the analysis system, potentially improving the accuracy of humidity analysis.

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Description

The ECMWF is revising its humidity analysis by constructing a Gaussian control variable, aiming for simpler error characteristics.

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  • Language: EN
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