Building Asian Climate Change Scenarios by Multi-Regional Climate Models Ensemble S. Wang, D. Lee, J. McGregor, W. Gutowski, K. Dairaku, X. Gao, S. Hong,

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Presentation transcript:

Building Asian Climate Change Scenarios by Multi-Regional Climate Models Ensemble S. Wang, D. Lee, J. McGregor, W. Gutowski, K. Dairaku, X. Gao, S. Hong, Y. Wang, K. Kurihara, J. Katzfey, Y. Lee RMIP and follow-up Project Teams Contact:

Outlines RMIP – Model evaluation and Asian regional climate projection Asian climate and changes Summer Monsoon Systems Follow-up project and future development

RMIP: Regional climate Model Intercomparison Project for Asia In April 2000, APN approved RMIP to support the further development of regional climate and environment models through inter-comparisons, and their applications for Temperate East Asia. History of Regional Collaboration – universities, research institutes, government sponsored research agencies; – scientists working on modelling, observation, and end users; CMA, IAP NJU HKCU SNU, YSU, KMA NIED, MRI CSIRO HU ISU

RMIP: I Seasonal cycle & Extremes RMIP: II Asian Climatology RMIP: III Asian Regional Climate Projection RMIP: Regional climate Model Intercomparison Project RMIP: Multi-RCM Ensemble System for Asian Climate and Change Emissions Regional Climate Models ECHAM

Activities for RMIP III Projecting high resolution regional climate change for for Asia by using the ensemble of nice regional climate models; Based on the RCM simulations, detecting and assessing the sources and magnitudes of uncertainty in Asian climate change projection; Calculating the change and variance of controlling climate factor of Asian climate, i.e., Asian monsoon system, and its impacts on Asian climate; Exploring and developing new methods and techniques for regional climate model outputs ensemble.

Domain , Time slices and Sub-regions Control climate Near future Projection Projected climate Region 8 India Region 6 Tibet Region 3 North China Region 4 Centre China Region 5 South China Region 1 Korea/Japan Region 2 Arid/semi arid area Region 7 Southeast Asia Region 9 North Maritime Continent Region 10 South Maritime Continent

Models and Data Availability ModelGroupCountry 1CCAMCSIROAustralia 2CCAM-60KMCSIROAustralia 3NIED-RAMSNIEDJapan 4MRI_RCMMRIJapan 5ReGCM3CMAChina 6GRIMsYSUKorea 7iRCMIUUSA 8WRFNJUChina 9WRF_SNNJUChina 10WRF_RRTMNJUChina 11SNU RCMSNUKorea 12ReGCM3NJUChina

Model outputs and Observation For surface climate: – Daily average MSLP, maximal/minimal temperature, surface wind speed – 3-hourly: 2m temperature, RH, convective precipitation, large scale precipitation, evaporation, 10m wind (U,V), surface radiation (up/downward shortwave radiation, up/downward longwave radiation), latent heat, sensible heat, column soil moisture, total runoff For upper level atmosphere – Daily average: U, V, T, H at 200, 500, 850 hPa – 3-hourly: radiation fluxes at TOA, cloud fraction, surface precipitable water Observation – CRU surface temperature, OISST SST – APHRODITE and GPCP Precipitation

-Surface climate -Climate variations -East Asian Monsoon -Indian Monsoon -Heat waves -Heavy rainfall and flood Regional Climate Change Asian Monsoon Systems Extremes Multi-model Ensemble with uncertainty addressed Ongoing Analyses for RMIP III Single model evaluation

Asian Climate and Changes Indian Subcontinent and Tibet

20-year ( ) Averaged Surface Air temperature (JJA, C)

20-year ( ) Averaged precipitation (JJA, mm/d)

1, Asia 2, Korea/Japan 3, Arid/Semi arid area 4, North China 5, Center China 6, South China 7, Tibet 8, Southeast Asia 9, India Subcontinent 10, North Maritime 11, South Maritime 12, Land 13, Ocean Summer surface climate BIASES in different sub-regions Δ T ( ℃ ) Δ P (%) Both driving GCM and RCMs are colder than observation; Smaller biases in temperature by RCMs than ECHAM5;

Biases in TAnnualJJAMAMSONDJF Asia Land Ocean Tibet Indian Subcontinent Biases in P (%)AnnualJJAMAMSONDJF Asia Land Ocean Tibet Indian Subcontinent

Projection of surface air Temperature Changes (JJA, C)

Projection of precipitation changes(JJA, %) (future-current) current *100 Purple lines mean the differences are significant at a 95% or greater confidence level

1, Asia 2, Korea/Japan 3, Arid/Semi arid area 4, North China 5, Center China 6, South China 7, Tibet 8, Southeast Asia 9, Indian Subcontinent 10, North Maritime 11, South Maritime 12, Land 13, Ocean T(C) Both driving GCM and RCMs project warmer and wetter climate for SA and India; Relative large difference between RCMs and GCM concerning Precipitation Sub-regional climate changes for JJA

Tibet Indian Subcontinent P (mm/d) Seasonal Cycle of Precipitation Change over Tibet and Indian Subcontinent

Seasonal Cycle of Temperature Change over Tibet and Indian Subcontinent Tibet Indian Subcontinent T (C)

For current climate, Tibet experiences more warming in both observation and simulation; the observed warming is actually more significant. Comparing to the rest of Asian subregions, Tibet will have more severe warming in the near future. Indian subcont. Asia Tibet Annual Temperature variation by multi-model Ensemble(C)

Changes in P (%)AnnualJJAMAMSONDJF Asia Land Ocean Tibet Indian Subcontinent Changes in TAnnualJJAMAMSONDJF Asia Land Ocean Tibet Indian Subcontinent Projected regional changes of T and P by multi-model Ensemble(C)

Projected changes of Interannual Variability of T(C, JJA)

Projected changes of Interannual Variability of Precipitation (mm/d, JJA)

Asian Monsoon Precipitation and Changes Indian Summer Monsoon

Present climate ( ) Future change ( ) under scenario A1B  Climatology  Interannual variability  Progresses  Climatology  Interannual variability  Monsoon index Multi model simulation of IM precipitation

Monsoon Precipitation (JJAS, mm/d) over Indian Subcontinent averaged over

Seasonal migration of the rainband (mm/d) zonally averaged between 70°and 90°E

Differences in 2-m temperature (°C) between the future ( ) and current for summer (JJAS)

(future-current) current *100 Purple circles indicate the differences are significant at a 95% or greater confidence level Projection of precipitation changes over Indian Subcontinent (JJAS, % )

Temporal Variation of Indian Summer monsoon index (ISMI)

ISMI: defined by the total rainfall amount from Jun. to Sep. over India, excluding four hilly meteorological subdivisions (Parthasarathy et al. 1992) ISMI ISMI Mean Projected changes in the Indian summer monsoon index (ISMI)

Summary RCMs can capture the climatology over Asian; For future climate, temperature will increase by up to 3C and show more warming in DJF and higher latitude; It is likely that Indian summer monsoon will be stronger in the future; Ensemble averages work well for mean climate;