Research Needs for AMY 2008-2009: CLIVAR/AAMP perspective

Bin Wang

Second AMY08 International Workshop 9-3-4 2007, Bali

Acknowledgements : CLIVAR/AAMP

CLIVAR/A-AMP

Co-Chair: Bin Wang and Harry Hendon Cobin Fu, In-Sik Kang, Jay McCreary, Rajeevan, Satomura, Julia Slingo, Peter Webster Holger Meinke, Takehiko Andrews Schiller, Ken Sperber,

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Gaps: First Pan-WCRP workshop

Global Phenomena: diurnal cycle

annual cycle,

intraseasonal oscillation, atmospheric moisture distribution and transport aerosol-monsoon-cloud interaction

Model processes: surface fluxes, planetary boundary layer and cloud.

Land surface: better observations of land surface conditions, roles of atmosphere-land coupling in developing monsoon precipitation, Ocean: improve (and sustain) observations; importance of air-sea interaction and ocean processes in modeling of ISO and ENSO-monsoon relationship Regional foci: processes over the Maritime Continent, Pacific cold tongue and western boundary currents, and Indonesian through flow.

Year of coordinated Observing, modeling and Forecasting: Addressing the Challenge of Organized Tropical Convection This proposed activity arose out of a recommendation by the THORPEX/WCRP/ICTP Workshop on Organisation and Maintenance of Tropical Convection and the MJO, held in Trieste in March 2006. It was presented at the WCRP/CLIVAR SSG Meeting in Buenos Aires in April 2006. Based on positive feedback from the WCRP Director and the SSG, the SSG asked that the proposal be developed in cooperation with THORPEX, GEWEX, CEOP, AAMP, WOAP, WMP, etc. If implemented in 2008, this initiative could be a WCRP contribution to the UN Year of Planet Earth * and compliment IPY.

Key Issues AAMP is addressing

      What determines the structure and dynamics annual cycle (AC) and diurnal cycle (DC) of the of the coupled atmosphere-ocean-land system AC and DC? ? How to remedy the major weaknesses of climate models in simulation of the How predictable (IAV)? How to improve the predictions ? is the monsoon interannual variability dynamic monsoon seasonal What cause monsoon Intraseasonal Variability (ISV)? How to overcome the major challenges to modeling and predict monsoon ISV ? What are the major modes of interdecadal variation of the monsoon system ? How and why will monsoon system change in a global warming environment ? What is priority for future field and modeling studies for improving observing and modeling monsoon system ? and strategy of the

Modeling/prediction of Global Monsoon Domain

Number of Model The monsoon precipitation index (shaded) and monsoon domain (contoured) captured by (a) CMAP and (b) the one-month lead MME prediction. (c) The number of model which simulates MPI over than 0.5 at each grid point.

Performance of MMEs in Hindcast Global Precipitation

Temporal Correlation Skill of Precipitation Precipitation Wet Dry Dry Wet Dry Dry Dry Wet Wet Dry Dry Dry Wet Wet Dry Wet * Impact of El-Nino on Global Climate from NOAA (based on Ropelewski and Halpert (1987), Halpert and Ropelewski (1992), and Rasmusson and Carpenter (1982)

Asian-Australian Monsoon Predictability

S-EOF of Seasonal Mean Precipitation Anomalies The First Mode: 30% The Second Mode: 13% Forecast Skills of the Leading Modes of AA-M

CliPAS

Hot places of land surface feedback Koster et al. 2004

Need to understand Multi-Scale Interrelation In Monsoon ISO Slingo 2006:

LASG/IAP

Global Monsoon Changes (1948-2004)

Wang and Ding 2006, GRL

Annual Mean Precipitation

In the last 56 years global land monsoon shows a weakening trend. However, in the last 25 years, Oceanic unchanged.

monsoon rainfall increases while land monsoon LASG/IAP

Monsoon Research Needs

• Observation • Modeling • Prediction • Future changes

Observation

• Field campaign for observing specific phenomena : e.g., organization of convection, multi-scale structure of ISV. (Monsoon trough and Maritime Continent) • Supper station for validating and improving models • Provide ground truth for calibrating Satellite measurements • Improve . • Promote integrated usage of satellite observations to study , e.g., 3-D structure and multi-scale interaction in ISV. long-term monitoring network in tropical IO-WP and maritime Asia. • Improve and develop new reanalysis datasets that use new satellite observations, e.g., land data assimilation, ocean data assimilation.

Modeling

• Design monsoon metrics for assessing model performance and identify key modeling issues . Provide one-stop data source for cross-panel use. • Develop effective strategy for improving model Physics .

• Determine directions for developing next generation climate models. High resolution modeling • Encouraging use of forecast type experiments to evaluate models and study climate sensitivities. • Use large-domain CR or CSR simulation to provide surrogate data for studying convective organization, and mulit-scale interaction.

Prediction

• Better understand physical basis for seasonal prediction and ways to predict uncertainties of the prediction. • Improve representation of slow coupled physics .

• Improve initialization scheme and initial conditions in ocean and land surface.

• Develop new strategy and methodology for sub seasonal monsoon prediction .

• Design metrics for objective, quantitative assessing predictability and prediction skill. Improve MME prediction system.

Assess Future Changes

• Coordinate IPCC AR4 monsoon assessment to address how and why AA-M system will change in a global climate change environment.

• Role of the monsoon-aerosol interaction and land use future monsoon change. in • Use MME approach to study the sensitivity of the monsoon to external and anthropogenic climate forcing.

• Coordinate MME experiments to investigate sub-seasonal to interannual factors that influence extreme events , such as TC.

• Determine coherent structure and dynamics of the global monsoon system on Dec/Cen time scales and their linkage to ocean.

Modeling/Prediction (AAMP)

 Coordinate CGCM/RCM Process study on MJO/ MISO (MC-SEA): AAMP/MAHASRI, CIMS  Develop Multi-model ensemble Regional Climate prediction experiment with CGCM, RCM, GLACE i n collaboration with MAHASRI, APCC, and MAIRS to determine impacts of the land surface data assimilation, land surface processes, and land atmosphere interaction on monsoon seasonal prediction  C oordinated experiment on high resolution climate model simulation of hurricane/Typhoon activity . (NASA/GMAO: Sieg Schubert)

Thanks

AAMP-MAHASRI :

Coordinated GCM/RCM Process study on Monsoon ISO and onset (SEA+MC)      Integration of observation and modelling, Meteorology and Hydrology Domain: MC+SEA (70-150, 15S-40N)—a critical region for monsoon ISO influence Phenomenon and Issues: ISO, and its interaction with diurnal cycle, meso-scale and synoptic scale regulation. Onset of monsoon (summer and winter); impacts of Tibetan Plateau land surface processes Design: Driving field, Output, validation strategy and Data,… Participating model groups: both AGCM and RCM, each 4-5

MME Downscaling Seasonal Prediction Experiment

Develop effective strategy and methodology for RCM downscaling Assess the added values of RCM MME downscaling Determine the predictability of monsoon precipitation Large scale driving: 10 CGCM from DEMETER and APCC/CliPAS models