Impact of the representation of the stratosphere on tropospheric weather forecasts Sana Mahmood © Crown copyright 07/0XXX Met Office and the Met Office.

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Impact of the representation of the stratosphere on tropospheric weather forecasts Sana Mahmood © Crown copyright 07/0XXX Met Office and the Met Office logo are registered trademarks Met Office FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom Tel: Fax: The mid-winter polar stratosphere has great potential as an additional source of predictability for medium and extended-range weather forecasts especially during particularly active periods in the stratosphere known as stratospheric sudden warmings (SSW). This study aims to explore this potential predictability. The key questions posed by the project are: Q1. How important is the representation of the stratosphere in a NWP forecast? Q2. Does the stratosphere couple to the troposphere by influencing tropospheric wave breaking? Increased stratospheric resolution improves the representation of the stratosphere and even the troposphere on the 5–30 day timescale. No additional improvement was seen in the L85 simulations compared to L70, suggesting that the L70 model has sufficient stratospheric resolution at these timescales to influence tropospheric behaviour. Surface differences between the high top and low top models following a SSW display a negative NAO pattern indicative of a dynamical interaction being captured in the high top models that the low top model is unable to simulate. This pattern can be seen as soon as 5 days into the forecast indicating the benefits of high top models in NWP. A new algorithm has been developed to identify wave breaking. Applying this to the ERA-I in months with and without a SSW reveals a change in the wave breaking profile. This change in wave breaking is also evident in the model simulations when comparing different initialisations but not in comparisons between model vertical resolutions. Figure 3: Skill score of total geopotential height (anomaly plus climatology) for L85 relative to L38 i.e. SS L85/L38. The contours are measured in percentage improvement. A positive percentage improvement indicates a forecast improvement relative to the reference forecast (L85 relative to L38 in this case). Figure 1: Comparison of the number of levels and their placement between model configurations. L38 (left), L70 (middle) and L85 (right). Ensemble experiments have been run using the Met Office Unified Model around the SSW in February 2010 at a range of vertical resolutions. The different vertical configurations employed are depicted in figure 1. In total, three cases were run; initialised on 15th, 21st and 28th February 2010 and run out to 30 days. The three dates captured different stratospheric conditions prior to the SSW. The ensemble forecasts initialised closer to the SSW (28th Feb 2010) better simulate the stratospheric evolution. The high top models capture the wind reversal in the stratosphere associated with the warming much better than the low top model which only shows weakening of the westerly wind. Averaged surface differences over the 30 day forecast show a negative NAO surface pattern in the 28th Feb case indicative of a stratosphere-troposphere dynamical interaction being captured in the high resolution that is non-existent in the L38 model. This same pattern is not reproduced in the other initalisations. The corresponding surface temperature differences between the high and low top models for 28 th Feb 2010 (figure 2-right) show a pattern similar to that seen in other studies (Thompson et al, 2002) with temperatures up to 2º K colder over Europe. Skill scores between the L85 and L38 model (figure 3) show a forecast improvement in the troposphere of % by day 5-this is also seen in skill scores computed for L70 relative to L38. Figure 2: Averaged differences (L85-L38) for case initialised on 28 th February 2010 for mean seal level pressure (left) and 1.5m temperature (right). Contours show MSLP for L85 averaged over the 30 day forecast, shading is the difference between L85 and L38 simulations and the stippling is the 95% confidence level calculated using the student t test. Figure 5: Frequency of wave breaking per five degree latitudinal band calculated from geopotential height on 200hPa for cyclonic wave breaking (blue); anti-cyclonic wave breaking (red) and all (black) for months without SSW (left) and months with a SSW (right) in ERA-Int. Barnes, E. A. and Hartmann, D. L. (2012). Detection of Rossby wave breaking and its response to shifts of the midlatitude jet with climate change. Journal of Geophysical Research, 117, D Thompson, D. W. J., Baldwin, M. P. and Wallace, J. M. (2002). Stratospheric connection to Northern Hemisphere wintertime weather: Implications for prediction. Journal of Climate, 15, Figure 4 Detection of a wave breaking event, taken from Barnes & Hartmann (2012). This figure shows overturning of contours on the 250hPa absolute vorticity surface. The dashed white line denotes a meridian line that intersects a contour at three overturning points which are denoted by the closed white circles. The solid white contours connect all such overturning points. The black crosses denotes each contour’s west-most and east-most overturning points used to determine breaking orientation, and the black star marks the centre of the event. Wave breaking in the UM: Results from the ensemble experiments corroborate the ERA-I results. Wave breaking profiles from different initialisations show a change in wave breaking like that seen in non-SSW months to SSW months (compare figures 5 and 6). No discernible differences in wave breaking between model vertical resolutions has been identified. Figure 6: Same as figure 6 but calculated for the ensemble experiments for the case initialised on the 15 th Feb 2010 (left) and the 28 th Feb 2010 (right) for the L85 simulations. 1. How important is the representation of the stratosphere in a NWP forecast? IntroductionExperimental design 2. Does the stratosphere couple to the troposphere by influencing tropospheric wave breaking? Observed wave breaking frequency: Figure 5 shows the frequency of wave breaking detected by this new algorithm, in months with and without a SSW calculated from ERA-I. During months with a SSW there is increased anti- cyclonic wave breaking polewards of the mean jet position (~50 degrees). Wave breaking detection: One of the proposed mechanisms of stratosphere- troposphere coupling describes the stratosphere influencing tropospheric baroclinic systems. To investigate this further an algorithm to identify wave breaking in the troposphere was developed by searching for contours that cross a meridian three times or more (see figure 4). Various checks ensure that an event is not counted twice spatially or temporally. The technique also allows identification of the direction in which the wave is breaking. Summary and Conclusions References