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The Influence of Spectral Nudging on Typhoon Formation in Regional Climate Models

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The Influence of Spectral Nudging on Typhoon Formation in Regional Climate Models Home Search Collections Journals About Contact us My IOPscience The influence of spectral nudging on typhoon formation in regional climate models This article has been downloaded from IOPscience. Please scroll down to see the full text article. 2012 Environ. Res. Lett. 7 014024 (http://iopscience.iop.org/1748-9326/7/1/014024) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 82.82.156.222 The article was downloaded on 27/02/2012 at 13:13 Please note that terms and conditions apply. IOP PUBLISHING ENVIRONMENTAL RESEARCH LETTERS Environ. Res. Lett. 7 (2012) 014024 (10pp) doi:10.1088/1748-9326/7/1/014024 The influence of spectral nudging on typhoon formation in regional climate models Frauke Feser1 and Monika Barcikowska Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany and Cluster of Excellence ‘Integrated Climate System Analysis and Prediction’ (CliSAP) of the University of Hamburg, Germany E-mail: [email protected] Received 8 December 2011 Accepted for publication 2 February 2012 Published 22 February 2012 Online at stacks.iop.org/ERL/7/014024 Abstract Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden–Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model, with results slightly closer to reanalysis data for the spectral nudged simulations. On the basis of this regional climate model hindcast study of a single typhoon season, spectral nudging seems to be favourable since it has mostly positive effects on typhoon formation, location and general circulation patterns in the generation areas of TCs. Keywords: regional climate modelling, spectral nudging, typhoons 1 Address for correspondence: Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Straße 1, 21502 Geesthacht, Germany. C10$33.00 11748-9326/12/014024 c 2012 IOP Publishing Ltd Printed in the UK Environ. Res. Lett. 7 (2012) 014024 F Feser and M Barcikowska 1. Introduction horizontal resolution of T62 (∼210 km)) as boundary and initial conditions. Homogeneous long-term climate data is essential for the In CCLM, spectral nudging after von Storch et al (2000) assessment of changes in extreme events like typhoons, which is implemented. Practically, the regional model solution is are known to be associated with heavy precipitation and altered after the model computed a time step by adding wind speeds. Such data are provided by global reanalyses, an additional spectral nudging term. For this purpose, the which often are too coarse to depict regional phenomena regional model solution is transferred into spectral space realistically. One way to achieve more regional detail is the via a Fourier transformation and the large spatial scales are dynamical regionalization using a regional climate model selected by their wavenumbers; the same is done for the global (RCM). Many RCM studies simulating tropical cyclones (TC) reanalysis input data. Then the nudging term is determined, were conducted (see e.g. Cha et al 2011, Kanamitsu et al it depends on the difference for large spatial scales between 2010, Feser and von Storch 2008b, Camargo et al 2007, the regional and global result. This term can be positive or Knutson et al 2007, Walsh and Watterson 1997), showing negative and ‘nudges’ the regional model solution so that the ability of RCMs in reconstructing TC numbers, tracks, it becomes more similar to the large-scale input field. The or intensities. Also many RCM studies exist for SE Asia nudging term is then added to the RCM result and the whole (among others Zhong 2006, Kang et al 2005, Lee et al 2004, solution is transferred back to physical space. In this analysis Suh and Lee 2004). But it was also shown that RCMs may the spectral nudging terms were added every third time step. deteriorate the large spatial scales when large-scale forcing The results are comparable to those when spectral nudging is only supplied from global climate model data via the is used at every time step, but less computation time is lateral boundaries (von Storch et al 2000, Miguez-Macho et al needed. The regional spatial scales are left unchanged; the 2004, Waldron et al 1996). Therefore, many RCM simulations nudging is adopted only for large spatial scales and for higher nowadays use a spectral nudging technique which prevents model layers (above 850 hPa and with increasing strength the RCM from altering the global spatial scales too much towards higher levels as in figure 3 of von Storch et al (2000) in comparison to the input data (e.g. Kanamitsu et al 2010, so that the regional processes close to the surface are not Knutson et al 2007, Castro et al 2005). Spectral nudging has disturbed. In this study, the spectral nudging was applied also been applied successfully to RCM studies for Southeast only for the horizontal wind components. The wavenumbers D D Asia (Cha et al 2011, Song et al 2011, Yhang and Hong 2011, chosen for nudging were i 12 and j 9 which correspond Tang et al 2010, Cha and Lee 2009, Feser and von Storch to spatial scales of about 500–660 km; all weather phenomena 2008a, 2008b). larger than this were nudged. Standard parameterizations were What remains to be shown is the effect that spectral selected and the Tiedtke convection scheme (Tiedtke 1989) nudging has on typhoon formation and associated large-scale was used. The CCLM uses the SST from the NCEP reanalyses circulation patterns. Some sensitivity experiments for a single after interpolation to the high-resolution grid. typhoon case were shown in Feser and von Storch (2008a), but Ten regional ensemble simulations were computed, 5 with (SN) and 5 without (NN) nudging. The only difference this case study cannot give answers for longer time periods. between the simulations is their starting date (consecutive Additionally the impact of spectral nudging on meteorological days at the beginning of March 2004, see table1). The model fields both in the vicinity of TC generation and a larger-scale domain is presented in figure1. It was chosen to include the circulation is of particular interest. For this letter, in addition main typhoon generation regions in the Northwestern Pacific. to typhoon numbers and tracks, also large-scale circulation Therefore, TCs should mainly develop inside of the model patterns and vertical atmospheric profiles were analysed domain and not enter the domain via its lateral boundaries. in order to identify the effect on the middle and upper Due to the large domain, the internal model variability should troposphere. Therefore, we simulated the typhoon season be large as well (Alexandru et al 2007). It describes the 2004 for several realizations both with and without spectral model’s ability to generate several possible atmospheric states nudging and compared them to satellite data as well as to for the same lateral boundary conditions. Spectral nudging different reanalyses. reduces this internal model variability (Weisse and Feser 2003) and thus leads to less differences between individual 2. Model, data, and methods ensemble members and a smaller ensemble spread. The period analysed in this letter is April–December 2004, which was The regional climate model used for this study is the quite an active typhoon season with 29 typhoons observed in COSMO–CLM (CCLM, www.clm-community.eu; Rockel the Western North Pacific. et al 2008, Steppeler et al 2003). Since 2005 it is the To assess the distance between typhoons, both for community model of the German climate research. So far simulated RCM and reference best track data (BTD) tracks, this non-hydrostatic RCM has been used for simulations on a great circle distance was computed with relaxed conditions. terms of up to several hundred years with spatial resolutions Both tracks had to be nearer than 500 km or less at least for between 1 and 60 km. In this study, 0.5◦ (∼55 km) was 10% of the longest track’s length (defined as ‘overlapping’). selected, which corresponds to about 55 km. The model If several CCLM tracks corresponded to the same BTD was run using the global NCEP–NCAR reanalyses I (Kalnay track, then only one track was counted to be overlapping.
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