51 Applying a General Nonlinear Transformation to the Analysis of Surface Visibility and Cloud Ceiling Height

Thursday, 7 June 2018
Aspen Ballroom (Grand Hyatt Denver)
Runhua Yang, IMSG and NOAA/NCEP/EMC, College Park, MD; and R. J. Purser, J. R. Carley, M. Pondeca, Y. Zhu, and W. S. Wu

The current version of NOAA’s Real-Time and UnRestricted Mesoscale Analysis (RTMA and URMA, respectively) provides routine analyses of surface visibility and cloud ceiling height (hereafter C and V). In this talk we present the application of a general nonlinear transformation to C and V, through the application of new analysis control variables, to further improve the C and V analysis.

The challenges in analyzing C and V are mainly due to the highly discontinuous spatial and temporal nature of these respective variables, as well as their non-Gaussian distributions. Statistically, the situations with low visibility and cloud ceiling height occur much less often than the clear situations. But the analysis is expected to catch these rare events that are of highest practical impact to the aviation community.

Using the new analysis control variables is expected to avoid complications associated with the non-linear analysis variable transform inside the cost function minimization, which may produce non-physical features in the resulting analysis when the innovations are large. Furthermore, the application of a general nonlinear transform to the analysis control variables is expected to provide a reasonable Gaussian distribution.

We will present work on the estimation of the parameter for the nonlinear transformation formula, via examining and comparing numerous histograms in two regimes: one with low visibility/ceiling values and another with high visibility/ceiling values. Further, we will describe results on the estimation of statistical errors obtained by performing single observation testing and by analyzing innovation statistics. Finally, we will show the impact of the new control variables on C and V analyses from long term and real-time runs of the RTMA/URMA.

Disclaimer: This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.

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