Motivation Investigation of predictability using ensemble forecasts Courtesy: D.Anwender ET of Tropical Cyclones Reduction in forecast skill ET of Maemi Investigation of predictability using ensemble forecasts Ensemble Spread ≈ Measure of predictability Different possible development scenarios Examine physical properties, reducing forecast skill Recent studies with ECMWF & NCEP EPS (Anwender et al. 2008, Harr et al., 2008)

New studies using TIGGE Up to ten EPS instead of one Compare predictability of different EPS Are there other development scenarios? Statistically reliable in applied analysis method due to more ensemble members First approach: Can we learn more about ET-related processes by using TIGGE instead of the ECMWF-EPS?

Basics of the applied technique Calculating Empirical Orthogonal Functions (EOFs) Regions of largest variability Determining Principal Components (PC) Contribution of each ensemble member Fuzzy Clustering of members with related contributions Overview of possible development scenarios an their probability

Case Study: Tropical Storm Bavi (2008) TS: 06 UTC, 19 October – 09 UTC, 20 October ET: 12 UTC, 20 October – 00 UTC, 25 October ECMWF Analysis: gph of 200 hPa (shading) and mslp (contour) Strong intensification as ET-System Rather zonal flow before interaction strong T-R-pattern thereafter

Case Study: Tropical Storm Bavi (2008) Rather zonal before interaction Strong T-R pattern thereafter

Uncertainties in the different EPS stdev of gph at 200 hPa, averaged over 40-60°N Forecast initiated 18 Oct 2008 12 UTC =Surface Position of Bavi (out of cf)

Uncertainty in TIGGE-EPS stdev of gph at 200 hPa, averaged over 40-60°N Forecast initiated 18 Oct 2008 12 UTC TIGGE =Surface Position of Bavi (EC cf)

Differences in Standard Deviation Regions of increased uncertainty differ between EPS, e.g.: MSC:Vicinity of Bavi ECMWF:Upstream of Bavi Overall decreased stdev Pattern related to ECMWF

Scope of the investigations Comparison of TIGGE and ECMWF forecasts fcst 1 initialized: 17 Oct 2008, 12 UTC fcst 2 initialized: 18 Oct 2008, 12 UTC clustering time: 21 Oct 2008, 12 UTC Variable for clustering: gph at 200 hPa Based on TIGGE without Korea and France EPS France: Only 2.5 day forecast available Korea: Outlier in PC phase space Lower gph at 200 hPa after +48h south of ~30° N different development Korea

Distribution of uncertainty EOF 1 & 2 and 200 hPa gph ensemble mean 27% 27% 26% 18% 19% 22% ECMWF fcst 2 TIGGE fcst 1(2 similar) ECMWF fcst 1 ECMWF fcst 2

Different development scenarios Case 1: Mainly TIGGE fcst 1 Weak Bavi, less amplitude in ridge,moderate downstream dev 12 UTC, 21 Oct 12 UTC, 23 Oct geop. height at 200 hPa mslp pot. temp & rel. vort. at 850 hPa . Bavi Clustering time 48 h later

Different development scenarios Case 2: Only TIGGE fcst 1 Strong Bavi, high amplitude in ridge, moderate downstream dev 12 UTC, 21 Oct 12 UTC, 23 Oct geop. height at 200 hPa mslp pot. temp & rel. vort. at 850 hPa Bavi Clustering time 48 h later

Different development scenarios Case 3: TIGGE and ECMWF fcst 1&2 Moderate Bavi and amplitude in ridge, weaker downstream dev 12 UTC, 21 Oct 12 UTC, 23 Oct geop. height at 200 hPa mslp pot. temp & rel. vort. at 850 hPa Bavi Clustering time 48 h later

Result of qualitative comparison between TIGGE and ECMWF TIGGE fcsts show weak, strong and moderate pattern ECMWF fcsts have less differences, rather strong pattern Capture none of the both extremes found in TIGGE A pattern resembling analysis can be found in each fcst Conclusion Using TIGGE instead of ECMWF EPS new development scenarios offer possibility to study processes during ET

Outlook Other case studies (i.e. Hurricanes 2008) Selection of interesting development scenarios Investigation of ET related processes, using Eddy-Kinetic-Energy-Analysis (Orlanski&Sheldon, 1995, presented by B. Sanabia on Monday) PV-Inversion (Davis, 1992) New insights in processes during ET leading to reduction of predictability