Value added in regional climate modeling: Should one aim to improve on the large scales as well?

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Abstract

Expectations various regional climate modelers have expressed as to the impact on large scales are recalled. While some authors do mention the possibility of improvement also at large scales (e.g., Giorgi, J Phys IV France 139:101–118, 2006), the majority clearly accepts the view of “downscaling” as an effort in which the driver global model large scales are hoped to be preserved as much as possible and only small scales improved compared to those of the driver model. Many authors find it even desirable to use the so-called “large-scale nudging” in order to help achieve this objective. Mesinger et al. (Limited area predictability: can “upscaling” also take place? Research activities in atmospheric and oceanic modeling, WMO, Geneva, CAS/JSC WGNE Rep. No. 32, 5.30-5.31, 2002; see also Mesinger, The Eta model: design, history, performance, what lessons have we learned? In: Symposium on the 50th anniversary of operational numerical weather prediction, University of Maryland, College Park, MD, 14–17 June 2004, Preprints CD-ROM, 20pp, 2004) have however argued that various NWP results of the Eta model at NCEP strongly suggest that improvements in the large scales of the global driver model have been taking place more often than not. In addition, there was a four-month nine-member ensemble result of Fennessy and Altshuler in the early 2000s, published recently (Veljovic et al. Meteorol Z 19:237–246, 2010), in which an RCM achieved a dramatic improvement over its driver AGCM in hindcasting the precipitation difference over the central United States between the “flood year” of 1993 and the “drought year” of 1988; which we do not believe could have been possible without a significant improvement in the large scales. If this indeed is so and could be generalized, then large-scale nudging would not only be unnecessary but may also be harmful to the result. It could however be that this holds for some models while not for others. In that case, why so is a question of obvious importance. Given however that claims have even been made that improvements in large scales in regional climate modeling may be impossible for any models, hard evidence of specific large-scale improvements achieved are desirable. The preceding and additional points are discussed as well as more detail given, summarizing the results of perhaps the first comprehensive direct tests of the issue (Veljovic et al. Meteorol Z 19:237–246, 2010). Additional results are shown regarding the impact of the choice of the lateral boundary conditions (LBC) scheme, pointing to the advantage of the Eta (Mesinger, Contrib Atmos Phys 50:200–210, 1977) over the conventional and costlier relaxation scheme. As to the large scales question posed, the results summarized show that driving the Eta by ECMWF 32-day ensemble members the driver model large scales tended to be improved more often than not, giving support for our tenet that improving large scales as well in RCM efforts is possible. We furthermore argue that pursuing this objective should be beneficial for the improvement in smaller scales as well.

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Mesinger, F., Veljovic, K., Fennessy, M. J., & Altshuler, E. L. (2012). Value added in regional climate modeling: Should one aim to improve on the large scales as well? In Climate Change: Inferences from Paleoclimate and Regional Aspects (pp. 201–214). Springer-Verlag Vienna. https://doi.org/10.1007/978-3-7091-0973-1_15

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