caa a22 4500 605473870 CHVBK 20210128100345.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s00382-014-2453-5 doi (NATIONALLICENCE)springer-10.1007/s00382-014-2453-5 Using nudging to improve global-regional dynamic consistency in limited-area climate modeling: What should we nudge? [Elektronische Daten] [Hiba Omrani, Philippe Drobinski, Thomas Dubos] Regional climate modelling sometimes requires that the regional model be nudged towards the large-scale driving data to avoid the development of inconsistencies between them. These inconsistencies are known to produce large surface temperature and rainfall artefacts. Therefore, it is essential to maintain the synoptic circulation within the simulation domain consistent with the synoptic circulation at the domain boundaries. Nudging techniques, initially developed for data assimilation purposes, are increasingly used in regional climate modeling and offer a workaround to this issue. In this context, several questions on the "optimal” use of nudging are still open. In this study we focus on a specific question which is: What variable should we nudge? in order to maintain the consistencies between the regional model and the driving fields as much as possible. For that, a "Big Brother Experiment”, where a reference atmospheric state is known, is conducted using the weather research and forecasting (WRF) model over the Euro-Mediterranean region. A set of 22 3-month simulations is performed with different sets of nudged variables and nudging options (no nudging, indiscriminate nudging, spectral nudging) for summer and winter. The results show that nudging clearly improves the model capacity to reproduce the reference fields. However the skill scores depend on the set of variables used to nudge the regional climate simulations. Nudging the tropospheric horizontal wind is by far the key variable to nudge to simulate correctly surface temperature and wind, and rainfall. To a lesser extent, nudging tropospheric temperature also contributes to significantly improve the simulations. Indeed, nudging tropospheric wind or temperature directly impacts the simulation of the tropospheric geopotential height and thus the synoptic scale atmospheric circulation. Nudging moisture improves the precipitation but the impact on the other fields (wind and temperature) is not significant. As an immediate consequence, nudging tropospheric wind, temperature and moisture in WRF gives by far the best results with respect to the Big-Brother simulation. However, we noticed that a residual bias of the geopotential height persists due to a negative surface pressure anomaly which suggests that surface pressure is the missing quantity to nudge. Nudging the geopotential has no discernible effect. Finally, it should be noted that the proposed strategy ensures a dynamical consistency between the driving field and the simulated small-scale field but it does not ensure the best "observed” fine scale field because of the possible impact of incorrect driving large-scale field. Springer-Verlag Berlin Heidelberg, 2015 Regional climate modeling nationallicence Nudging nationallicence Big Brother Experiment nationallicence WRF model nationallicence Omrani Hiba Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut Drobinski Philippe Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut Dubos Thomas Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut Climate Dynamics Springer Berlin Heidelberg 44/5-6(2015-03-01), 1627-1644 0930-7575 44:5-6<1627 2015 44 382 https://doi.org/10.1007/s00382-014-2453-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-014-2453-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Omrani Hiba Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut NATIONALLICENCE 700 1- Drobinski Philippe Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut NATIONALLICENCE 700 1- Dubos Thomas Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, Ecole Polytechnique, 91128, Palaiseau Cedex, France aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 44/5-6(2015-03-01), 1627-1644 0930-7575 44:5-6<1627 2015 44 382