CLIVAR MJO WORKING GROUP -> WCRP/WWRP MJO Task Force

Transcription

1 CLIVAR MJO WORKING GROUP -> WCRP/WWRP MJO Task Force D. Waliser, K. Sperber, J. Gottschalck, H. Hendon, W. Higgins, I. Kang, D. Kim, E. Maloney, M. Moncrieff, K. Pegion, N. Savage, S. Schubert, W. Stern, A. Vintzileos, F. Vitart, B. Wang, W. Wang, K. Weickmann, M. Wheeler, S. Woolnough, C. Zhang VAMOS Panel Meeting 12 San Juan, Puerto Rico; 2009

2 Motivation The MJO is the dominant form of intraseasonal variability in the Tropics. The MJO impacts a wide range of weather & climate phenomena. o Monsoon Onset & Breaks o ENSO+IOD IInteractions o Tropical Cyclone Modulation o o Midlatitude Weather Impacts Organization of Chl, Aerosols, Ozone, etc variability. Our weather & climate models have a poor representation of the MJO. Figures: Maloney, PMEL/TAO, Nakazwa, MJO WG, Lin, Waliser Great benefit could be derived from better predictions of the MJO - Helps to bridge the gap between weather and seasonal predictions.

3 Considerations of Remaining Predictability Considerations of Remaining Predictability 100% 50% Normalized Useful Predictability (%) Weather MJO ENSO Clients, Applications & Services Theory, Mechanisms, Models & Forecasts PDO ACC 1 Day 1 Year 1 Season 1 Month 1 Week 1 Century 1 Decade 2 week time scale will repeat itself 260 times during lead time for one decadal prediction and 2600 times for 1 century projection.

4 US CLIVAR MJO Working Group Summary of Accomplishments 1) Develop MJO WG Web Site. Diagnostics Link, Meeting & Telecon Updates, Theme Pages 2) Diagnostics for Asessing Model Simulations. On Website. J. Climate Article ~ In Press. Also adopted by NCAR/NCL. 3) Application of Diagnostics to Models. CAM3.5, CAM-3Z, spcam, ECHAM4/OPYC, CFS, SNU, GFDL, GEOS5 J. Climate Article REVISION JUST SUBMITTED. 4) Operational MJO Forecasts & Metrics. Designed, Implemented at Several Opertional Centers, w/ WGNE Help and NCEP/CPC leading, BAMS Article drafted by J. Gottschalck 5) Workshop/Experimentation Planning November 2007, Irvine, CA. BAMS meeting summary published.

5 Model Simulation Diagnostics Need systemmatic ways of assessing quality, progress, model changes. J. Climate Article ~ In Press. Also adopted by NCAR/NCL.

6 Model Simulation Diagnostics Application to Contemporary Models

7 MJO Simulation Diagnostics: W-F Precip & U850 J. Climate Article ~ In Press. Also adopted by NCAR/NCL.

8 Developing an MJO Forecast Metric US CLIVAR MJO WG Based on Wheeler & Hendon 2004 Mode 1 Mode 2 Mode 2 Mode 1

9 Examples Display Format Observational RMM1 / RMM2 values for the past 40 days 15-day model forecasts --Green line: Ensemble mean week 1 (thick), week 2 (thin) --Ensemble members light gray shading: 90% of forecasts dark gray shading: 50% of forecasts

10 (a) (b) (c) (d) (e) Figure 2: Wheeler and Hendon (2004) RMM phase plots for five different ensemble forecasting systems (a) NCPE, (b) CANM, (c) UKME, (d) ECMF and (e) BOME (10days). The Realtime Multivariate MJO index 1 and 2 are the x-axis and y-axis respectively and range from -4 to 4. The numbers and text within the box represent MJO phase. The red and blue lines show the last 40 days of observations (red--january 2009, blue--december 2008). The green line is the model ensemble mean (thick--first 7 days, thin second 8 days) and yellow lines are individual ensemble member forecasts. The light (dark) gray shading indicates that 90% (50%) of the members fell within highlighted region respectively. The larger dot is the last observation point.

11 CLIVAR+WGNE -> CPC/NCEP MJO Prediction Project Common Metric -> Compare/Validate ----> MM Ensemble IMD and KMA planned Courtesy J. Gottschalck

12 MJO Workshop New Approaches to Understanding, Simulating, and Forecasting the Madden- Julian Oscillation BAMS Meeting Summary

13 CLIVAR MJO Workshop Recommendations Follow on activities & foci of collaborations Renewing/Continuing MJOWG as WCRP/WWRP Task Force Further development of process-oriented diagnostics/metrics that improve our insight into the physical mechanisms for robust simulation of the MJO and that facilitate improvements in convective and other physical parameterizations relevant to the MJO. (e.g., GEWEX/GCSS, WGNE, YOTC) Continue to explore multi-scale interactions within the context of convectively-coupled equatorial waves, both in observations and by exploiting recent advances in high-resolution modeling frameworks, with particular emphasis on vertical structure and diabatic processes. (e.g,. YOTC, CMMAP, CASCADE, AMY) Expand efforts to develop and implement MJO forecast metrics under operational conditions, with additional focus on boreal summer and ensemble development. Includes the development of a multi-model hindcast to assess MJO predictability & forecast skill and development of ensemble methods. (e.g., pan-monsoon, Thorpex, WGNE, WGSIP, TFSIP, APCC, AMY).

14 Year of Tropical Convection (YOTC) A Scientific Framework for Addressing the Multi-scale Organization of Tropical Convection and its Interaction with the Global Circulation Duane Waliser, JPL/Caltech Mitch Moncrieff, NCAR Co-chairs, Science Planning Group A Contribution to Seamless Weather-Climate Prediction

15 Assessments Prediction Observations Service Delivery WWRP JSC 2008 Capacity Building

16 MJO & CCEWs MODELING in IPCC Models Difficult to get all Parts of the Variability Right Lin et al., 2005

17 MJO Simulation Diagnostics: Mean Precip & U850 Figure 1: November April mean precipitation (shaded) and 850hPa zonal wind (contoured) of a) CMAP/NCEP1, b) CAM3.5, c) CAM3z, d) CFS, e) CM2.1, f) ECHAM4/OPYC, g) GEOS5 h) SNU and i) SPCAM. Contours of mean 850hPa zonal wind are plotted every 3 ms 1, zero line is represented by thick solid line. Unit is mmday 1 for precipitation and

18 Nakazawa 1988 MJO Multi-Scale Structure How Important is This Finer Structure To The Phase Speed, Eastward Propagation, etc

19 Results from the Aqua-Planet Experiment (APE) NICAM Model Looks promising e.g., Matsuno talk Courtesy, Dave Williamson, NCAR

20 How to address this problem? Winter Kelvin Waves Rossby Waves MJOs Dominant Convectively-Coupled Tropical Waves Projected onto OLR Anomalies. Wheeler and Weickmann, 2001

21 Build a robust satellite Observing system TOPEX: sea surface height QuickScat: ocean surface winds TRMM: precipitation TMI: sea surface temperature w/clouds AIRS: temperature and water vapor profiles CloudSat: cloud profiles Calipso: aerosol/thin-cloud profiles AMSRE: ocean precip, water vapor, liquid water MLS: upper tropospheric water vapor, cloud ice, temperature CERES: TOA and surface radiative fluxes MODIS: cloud characteristics, ocean color, land characteristics AURA platform: atmospheric composition/chemistry MISR: aerosol and cloud structure

22 Invest in In-Situ Measurements for Diagnostic/process studies and data assimilation T-PARC AMY

23 Add In-situ measurements over tropical oceans for Diagnostic/process studies and data assimilation PIRATA

24 Develop high-resolution Regional & Global Modeling (& Analysis) Capabilities Global CSRM MMF; superparameterization A CRM A CRM A GCM cell (CSU, LLNL, GSFC, PNNL) Frontier Research Center for Global Change Courtesy Satoh NCAR Tropical Chanel Momdel

25 Climate Biases Start with a Time Step Forecast Bias NCAR Climate Bias Forecast Bias GFDL Climate Bias mm/day

26 The Tropical Atmosphere-Ocean-Land Systems Have Never Been So Well Observed YOTC Programmtic Hypothesis: We can better exploit the observation infrastructure and modeling capabilities that we already have to achieve better understanding, simulations and predictions of tropical convection. New/Improved Resources Satellite Observations (e.g., EOS) In-Situ Networks (ARM, CEOP) GOOS (e.g., TAO, PRADA, drifters) IOPs (e.g., VOCALS, T-PARC, AMY) High-Resolution Deterministic Forecast Models & Global Analyses Research Models [e.g., Regional and Global Cloud(-System) Resolving Models] Conceptual Framing + FGGE, GATE, TOGA COARE = YoTC Focus Year Virtual IOP

27 YOTC: Progress & Plans Science Plan Completed, Printed. Abridged version submitted to BAMS, Moncrieff et al., 1 of 5 coordinated papers on seamless weather-climate prediction YOTC Science Sessions Fall AGU 08, AMS 09, Spring AGU 09 Implementation Plan Being Prepared (HiRes) Analysis & (~15 day) Forecast Data Sets ECMWF ~25km, Available on-line; w/ extra diabatic fields. NASA/GEOS5 - ~25km, calculations in progress, w/ extra fields NCEP - ~50km, archiving occuring, extra diabatic fields needs ~O($100k)). Satellite Data Sets, Archive and Dissemination Approximately 15 key satellite-mission data sets have been identified for inclusion. NASA GES DISC Giovanni system is proposed for dissemination. Seeking support from NASA for the dissemination. Synoptic Event / Period of Interest Discussions Underway TC, MJO, CCEWs, Monsoon, Diurnal Cycle

28 IMPLEMENTATION PLAN

29 YoTC : Analyses & Forecasts ECMWF: T799 Analyses & 10-day Forecasts Weather Analyses High-Res ICs & BCs Weather/Satellite Comparison Special diabatic and other fields saved. $ Source: NSF + ONR

30 Satellite Data Analysis & Dissemination NASA Giovanni & A-Train Data Interfaces AIRS AMSR-E CALIPSO CERES CloudSat GPS ISCCP MLS MODIS PEHRRP QuikSCAT TRMM/TMI

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32 YOTC: A-Train A Data Co-Location Possibilities for Studying & Modeling Cloud/Convection P (hpa) CALIPSO Aerosol (p) Cloud (p) τ < ~3 CERES TOA and SFC radiative fluxes MLS UTLS T(p), q(p), q (p), CO (p), O (p), HNO i 3 3 (p) q (p) i AIRS q(p) T(p) ECMWF ω(p) u(p) du/dp(p) div (p) H q (p) l Aerosol Opt Depth Cloud Top - Temperature Temperature Pressure, Particle Size, etc AMSR MODIS Precipitation SST Prec Water LWP Surf. Wind Speed Light Precip CloudSat q (p) & IWP q i (p) & LWP Cloud l Type (p) ~ Particle Size (p) Light Precip

33 EXAMPLE: Synoptic Event of Interest June/July 2008 MJO/Kelvin Waves -> E.Pac ITCZ -> TCs -> Gulf Surge -> NA Monsoon -> Flash Floods AZ, NM Contributed by J. Gottschalck/NCEP & M. Wheeler/ABOM Developing MJO-like system: June 3

34 Northward and Eastward Propagating Components: June 6

35 Upstream Kelvin Wave Activity: June 19

36 Downstream Propagation -> ITCZ & TC Activity : June 29

37 Gulf Surge & Monsoon Activity : July 11

38 YOTC: Progress & Plans Research Modeling Framework A number of modeling team connections have been established and enthusiasm is significant: CMMAP and Tao/GMAO Superparameterization, Japanese NICAM effort, UK Cascade Project, DOE/ARM CAPT Transpose AMIP work, several CRM efforts, etc. Significant work remains in this aspect of implementation, including integration with GEWEX/GCSS, CLIVAR, WGNE, AMY, Pan- Monsoon, THORPEX, etc, and parameterization improvement plans. Coordination with Field Campaign e.g. AMY, VOCALS, T-PARC Expected leading up to and at IP Workshop. Implementation Plan and Workshop Implementation Plan being Drafted. Implementation Planning Workshop, Honolulu, July 13-15, 09. About 50 invited so far, 30 accepted, 5 declined, 15 maybe/waiting. Implementation Plan deliverable shortly after workshop. Project Support With WCRP + WWRP help/request: USTEC now provides ~1/2 FTE support for a specialist to help with Information and Communication Specialist/Support. (NSF+NASA+NOAA).