New Paper Published “Errors of Interannual Variability and Trend in Dynamical Downscaling of Reanalysis” By Kanamitsu Et Al 2010

An important new paper has appeared on the issue of dynamic downscaling. It is

Kanamitsu, M., K. Yoshimura, Y. Yhang, and S. Hong (2010), Errors of Interannual Variability and Trend in Dynamical Downscaling of Reanalysis, J. Geophys. Res., 115, D17115, doi:10.1029/2009JD013511.

This scientific contribution is with respect to Type II downscaling as we define in

Castro, C.L., R.A. Pielke Sr., and G. Leoncini, 2005: Dynamical downscaling: Assessment of value retained and added using the Regional Atmospheric Modeling System (RAMS). J. Geophys. Res. – Atmospheres, 110, No. D5, D05108, doi:10.1029/2004JD004721.

The abstract reads

The interannual variability of dynamically downscaled analysis and its error relative to global coarse resolution analysis is examined in this paper. The regional model error is shown to significantly contaminate the interannual variability of the seasonal mean. The error occupies a significant part of the interannual variability, particularly during the summer season. Accordingly, the leading modes of empirical orthogonal functions (EOFs) of 500 hPa height in the region differ greatly from those of global analysis. In this paper a variant of spectral nudging, the scale selective bias correction (SSBC) method, is refined to further reduce the error within the observational error. Application of this method in dynamical downscaling reduced the error of the interannual variability of analysis fields (namely, height, temperature, and winds), and made the EOFs of seasonal mean at 500 hPa height agree well with those of the global analysis. Application of the SSBC had a modest impact on model‐derived fields, such as precipitation and near‐surface air temperature. The improvements in these fields are not as dramatic as those in the analysis fields, but the increased simulation skill is evident. A possible cause of the error in the interannual variability is discussed. No apparent systematic reduction in high‐frequency variability is found, and the error in interannual variability is more likely due to excitation of the stationary computational mode by the lateral boundary forcing and ill‐posed lateral boundary condition.

A valuable next step is recommend in this paper. It reads

“The question that needs to be answered next is whether spectral nudging should be applied to the downscaling of seasonal forecast and global change simulations, for which no observation is available but the large‐scale features are unquestionably contaminated by model errors. Answering this question requires discussion of the following somewhat controversial issues: (1) Can regional models make better forecasts or simulations of synoptic‐ to planetary‐scale features? and (2) How should the chaotic nature of the atmosphere and model be treated? The first question is connected to how much the synoptic‐ to planetary‐scale motion in the regional domain is trusted, and the second question is how to deal with the situation where no single truth exists. We will hopefully answer these questions in the future, as a continuation of this work.”

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