Subseasonal Variability CLIVAR SUMMIT Keystone, CO August 2005

1. Subseasonal VariabilityCLIVAR SUMMITKeystone, CO August 2005 Duane WaliserWater & Carbon CycleSciences DivisionJPL

2. Principal Mechanisms of SS Variability • Madden-Julian Oscillation (MJO) - emphasized here. • Pacific/North American pattern (PNA) • Arctic / North Atlantic Oscillation (AO / NAO) • Mid-latitude blocking • Equatorial wave activity (e.g., TIW, Kelvin) • Soil Moisture Overarching Relevance • These phenomena have influence on basin/global scales and interact with phenomena at both shorter time scales (e.g., mid-latitude weather, tropical cyclones) as well as longer time scales time scales (e.g., ENSO, monsoons). • However in most cases, the important mechanisms involved, their mutual interactions, their predictability, and the ability of current models to simulate them are still in question. • Improvements in predicting these time scales are an important step in making progress in weather (e.g., modulation of background flows, statistics) and climate simulation/prediction (e.g., important component of “noise”).

3. MJO Impacts/Interactions • Monsoon active and break periods • Clustering of Monsoon Tropical Depressions • Tropical Storm/Hurricane Modulation - including W. Hemisphere • Mid-Latitude Circulation Anomalies • US West Coast Extreme Precipitation • ENSO state modulation • Weather In High Latitudes e.g. Alaska • Tropical Ocean Chl • Tropical Ocean Diurnal Cycle ~8 Empirical Models ~4 Dynamical Studies Predictability Fu et al. 2005

4. CLIVAR/Monsoongcm intercomparison projectN.H. Summer SubseasonalRainfallVariability Modeling • Variable Strength • Too little C. IO variability • N.H. peaks often okay • Often split about equator • Spurious S. IO peak Waliser et al. 2003

5. Equatorial Waves & MJOMODELINGinIPCC Models Difficult to get all Parts of the Variability Right Lin et al., 2005

6. Fundamental Components Important Feedbacks Annual/Seasonal Modulation Theory & Physical Processes • Basic State: • Summer: Easterly • vertical Shear • Winter: low-level westerlies • Vertical Resolution • Cloud Radiative Feedbacks Wang, 2005

7. Coupled SST Feedback Fu and Wang, 2004 Zheng, Waliser, Stern, Jones, 2004

8. Coupled SST Feedback • Phase Errors in Tropical Heating ~ 7 days or ~2000km • Subseasonal Predictions MUST Include SST Coupling • Two-Tier Approach Inadequate For Subseasonal Problem Zheng, Waliser, Stern, Jones, 2004 Fu and Wang, 2004

9. New Horizons - Data • BOBMEX, JASMINE , GAME-GEWEX, SCSMEX , CEOP • CLIVAR/AGCM Intercomparison Project, AMIP, CMIP • Indian Ocean moored array and drifter program • TRMM, NASA A-Train (e.g., AIRS, MODIS, CloudSat) • New Horizons - Modeling • Super-parameterization • Global Cloud Resolving: Earth Simulator • Not enough/practical…..

10. http://www.cdc.noaa.gov/MJO/ Recent “Programmatic” History • Apr 2002 - 1st Subseasonal Meeting (NASA) • Prospects For Improved Forecasts Of Weather And Short-Term Climate • Variability On Sub-Seasonal Time Scales • Compelling evidence for predictability at leads substantially longer than 2 weeks. • Predictability linked to low-frequency high latitude annular modes, PNA, MJO. • Tropical diabatic heating and soil wetness particularly important at these time scales. • June 2003 - 2st Subseasonal Meeting (USCLIVAR IAG/NOAA,NASA,NSF) • Modeling, Simulation and Forecasting of Subseasonal Variability • Framework for conducting a systematic evaluation of current subseasonal forecast skill. • Assess current state of MJO modeling capabilities. (Poor->Marginal; w/ Optimism) • Implementation plan for an experimental MJO prediction program.

11. Other Relevant Activities • Subseasonal Hindcasts: NCEP/CFS, NASA/GOES5 • NOAA, NASA, NSF - Modest size portfolios of subseasonal research • NOAA-CPC/EMC - “Seamless Suite”, “weather-climate” links. • NOAA-CDC - LIM, Experimental MJO Prediction Project Host • International CLIVAR AAMP • Asian Pacific Climate Center (APCC): Proposed Case Studies (IS-SI) Challenging Issues • Multi-scale interactions (cumulus<->planetary, weather <-> SI) • Mean state Simulation (IO, double ITCZ, eq. westerlies, v. shear). • Data - mainly lack data on microphysics, latent heating profiles, boundary layer processes/structure & cloud-radiative interactions. • Subseasonal Forecasting Methodology???: coupling, ICs vs BCs, super-ensemble, data assimilation issues. • Coordinating Mechanism(s).

12. Recommendation Based on the discussion above, as well as: • the cross-cutting nature of the MJO as well as other subseasonal variability (e.g., annular modes, PNA, soil moisture) in terms of • time scale (weather-climate link; modulates low-frequency variability) • global reach (Indian Ocean to Americas, Tropics to high latitudes) • phenomenological interaction (monsoons, ENSO, trop cyclones, extra-trop weather) • the importance of having this component of variability represented in our weather and S-I models • the breadth of activity occurring in this area • the overall enthusiasm for this area of research and development (e.g., over 100 participants at 1st subseasonal meeting and over 80 at 2nd subseasonal meeting - mostly US in each case) • the need for coordinated subseasonal follow-on activities • SS variability is the means fill the present-day weather-SI prediction gap that a Working Group on Subseasonal Variability be established in order to coordinate and best leverage ongoing activities in this area and plan future directions.