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1 Nicholas P. Klingaman | Steven J. Woolnough | Department of Meteorology, University of Reading E-mail: [email protected] Web: www.met.rdg.ac.uk/~ss901165 Twitter: @nick_klingaman Vertical structure and diabatic processes of the MJO intercomparison: Initial results from 20-day hindcasts 1. Introduction to the MJO 4. Initial assessments of model skill Summary References • An international model intercomparison project aims to understand the relationship between biases in model representations of the MJO and errors in vertical profiles of diabatic heating, moistening and momentum. • Preliminary analysis of the 20-day hindcast component of the intercomparison indicates that models exhibit a wide range of skill in predicting two strong MJO events during the Years of Tropical Convection (YoTC). • Models which display greater skill show less drift away from the initialised state towards the model climatology, and are thus able to maintain organised sub-seasonal anomalies in tropical convection for 15-20 days. 5. Drift from initial conditions The Madden-Julian oscillation(MJO; Fig. 1) is the leading mode of sub-seasonal (30-70 day) tropical variability. By modulating monsoon systems and influencing extra-tropical variability (e.g., the North Atlantic Oscillation; Cassou, 2008), the MJO provides a key source of weekly and monthly predictability globally. Despite the importance of the MJO, many models used for numerical weather prediction (NWP) and climate simulations fail to represent its amplitude, period and/or eastward propagation along the equator (Lin et al., 2006). 3. 20-day hindcast experiments Phase 2 Phase 4 Phase 6 Phase 8 Figure 1: Composite precipitation anomalies (mm day -1 ) associated with the Madden-Julian oscillation, using satellite data from the Tropical Rainfall Measuring Mission (TRMM) for 1999-2011. MJO phases defined as in Wheeler and Hendon (2004; WH04). 2. Objectives of the intercomparison project Biases in GCM vertical profiles of diabatic heating, as well as incorrect or weak feedbacks between heating and large-scale circulation, may be key sources of error in GCM representations of the MJO (e.g., Li et al. 2009; Fu and Wang 2009). Increasing the entrainment rate for deep convection in the Hadley Centre HadGEM3 model improved the MJO; the profiles of diabatic heating show a much clearer transition from shallow to deep convection (Fig. 2). HadGEM3 Default Entrainment HadGEM3 High (+50%) Entrainment Figure 2: Composites of non-radiative diabatic heating (Q 1 minus Q R ; K day -1 ) per unit of WH04 MJO amplitude, averaged over 10˚S-10˚N, 100-120˚E, for each WH04 MJO phase. Phases 3 and 4 (7 and 8) are the active (suppressed) phase. The lifecycle is shown twice. A major international model intercomparison project is underway, which aims to link errors in MJO simulation to errors in GCM vertical profiles of heat, moisture and momentum in the tropics. The goal is to develop a model-evaluation framework with which GCM developers can improve physical parameterisations. The “Vertical Structure and Diabatic Processes of the MJO” intercomparison project is endorsed by the GEWEX Atmospheric System Studies (GASS) panel and the CLIVAR MJO Task Force. It is led by scientists from the NASA Jet Propulsion Laboratory, the U.K. Met Office Hadley Centre and NCAS-Climate. Figure 3: The two MJO active events targeted by the 20- day (orange) hindcast components. Shown is TRMM precipitation (mm day -1 ), averaged 5˚S to 5˚N. 20-day hindcasts are initialised every day during the periods marked in blue. YoTC Case F YoTC Case E The 20-day hindcast component of the project focuses on: • The predictability of the MJO events (YoTC Cases E and F; Fig. 3). • The model drift away from its initial state (analysed in the 2-day hindcast component) and towards its attractor (analysed in the 20-year component). • How errors in vertical profiles of diabatic processes contribute to the drift and the lack of predictability. Figure 4: Bi-variate correlations (left) and RMS errors (right) of model RMM1 and RMM2 indices – computed as in Gottschalck et al. (2010) – against “observed” RMM indices from NOAA OLR and ECMWF YoTC analysis winds. All RMM indices computed from daily-mean fields. Case F: Start dates 2009/12/10 - 2010/01/25 Case E: Start dates 2009/10/10 - 2009/11/25 Among the eight models that have submitted results to date, there is a considerable spread in performance, with several models displaying more than 20 days’ predictability (at a threshold correlation value of 0.6) and several others not substantially different from a persistence forecast. Most models display greater skill for the first case (E). Correlations Correlations RMS Errors RMS Errors MRI-AGCM GISS ModelE2 CCCma CanCM4 Figure 5: (Top) RMM indices for observations (black) and the first 11 days of model forecasts (colours) for Case E. The Hovmoller plots for each model show (top left) total OLR at day+1, then OLR anomalies from the daily model climatology (from 20-year simulations) at days +4, +7, +10, +13 and +16. OLR is averaged 10˚S-10˚N. The corresponding plots from NOAA CIRES observations are shown at right. Cassou, C., 2008: Nature, 455, 523-527. Fu, X. and B. Wang, 2009: J. Climate, 22, 3939-3959. Gottschalck, J. et al., 2010: BAMS, 91, 1247-1258. Li, C. et al., 2009: Clim. Dynam., 32, 167-187. Lin, J.-L. et al., 2006: J. Climate, 19, 2665-2690. Wheeler and Hendon, 2004: MWR, 132, 1917-1932. Day +1 total Day +1 total Day +1 total Obs total OLR Day +4 anom Day +4 anom Day +4 anom Day +7 Day +10 Day +13 Day +16 Obs anom OLR Day +7 Day +10 Day +13 Day +16 Day +7 Day +10 Day +13 Day +16
