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Task: (ECSK06) Regional downscaling

UM collaboration meeting, 21-22 November 2011, KMA. Task: (ECSK06) Regional downscaling Regional modelling with HadGEM3-RA driven by HadGEM2-AO projections. National Institute of Meteorological Research (NIMR)/KMA. Outline. Introduction 50km-res CORDEX-East Asia experiment

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Task: (ECSK06) Regional downscaling

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  1. UM collaboration meeting, 21-22 November 2011, KMA Task: (ECSK06) Regional downscaling Regional modelling with HadGEM3-RA driven by HadGEM2-AO projections National Institute of Meteorological Research (NIMR)/KMA

  2. Outline • Introduction • 50km-res CORDEX-East Asia experiment • Evaluation of current climate simulation • Projection of future climate change • 12.5km-res Korea experiment • Evaluation of current climate simulation • Projection of future climate change • Summary and future plan

  3. Introduction • Task: (ECSK06) Regional downscaling • Objective: • Build UM-regional model over the East Asian region and perform experimental runs for simulation of regional climate. • Deliverables: • Report on the installation of the UM-regional model for the East Asian region and its evaluation using perfect boundary conditions on seasonal simulations of East Asian monsoon activity (2008-2010) • Report on evaluation of HadGEM3-RA with a focus on climate variability in long-term integrations using ECMWF interim reanalysis data, associated with CORDEX participation (Dec 2011) • Report on assessment of East Asian climate downscaled by HadGEM3-RA using global climate change projections, associated with CORDEX participation (Dec 2011)

  4. Introduction • Strategy for generating high resolution climate change scenarios under IPCC AR5 New IPCC Scenarios RCP 4.5/8.5/2.6/6.0 Anthropogenic forcing GCM projection HadGEM2-AO : ~135km CMIP5 Dynamical downscaling RCM projection HadGEM3-RA : ~12.5/50km CORDEX • HadGEM2-AO: Atmosphere-Ocean coupled model of Hadley Centre Global Environment Model version 2 • HadGEM3-RA: Atmospheric regional climate model of Hadley Centre Global Environment Model version 3

  5. Plan of generating regional climate change scenarios • Experiments and progress (GA3.0 version) • Simulations of Current Climate (to evaluate the performance of RCMs) - Experiments using reanalysis boundary conditions (1989-2008) - done • * Forcing: ERA-Interim atmospheric field & Daily Reynolds SST- Experiments using GCM boundary conditions (1950-2005) - done • * Forcing: HadGEM2-AO atmospheric field & daily SST • Simulations of Climate Change (to project future climate) - Experiment using GCM RCP 8.5/4.5 runs (2006-2100) - done • * Forcing: HadGEM2-AO atmospheric field & daily SST Korea 12.5km domain CORDEX 50km domain

  6. Evaluation of current climate simulation • in GCM forcing run (50km-res) • - surface climate

  7. Climatology (1971-200): Precipitation Observation GCM RCM CRU GCM RCM • RCM could resolve small-scale features related with topography and coastlines. Annual Summer Winter

  8. Climatology (1971-200): Temperature Observation GCM RCM CRU GCM RCM • RCM could resolve small-scale features related with topography and coastlines. Annual Summer Winter

  9. Bias: Precipitation and temperature • Precipitation • Temperature GCM RCM RCM GCM Annual Summer Winter

  10. Statistics: Precipitation & Temperature (Land) • Mean, bias, Root-mean-squared error (RMSE) and pattern correlation coefficient of precipitation and temperature. (Ref.CRU) • Overall, both GCM and RCM show similar performance and wet/cold biases.

  11. Annual cycle of Precipitation and temperature • 30-yr mean annual cycle of area-averaged precipitation and surface air temperature (1951~1980): East Asia monsoon region(100E-150E,20N-50N) Precip. Temp • Black: Observation (CRU) • Red: GCM • Blue: RCM

  12. Climate change projection (50km-res) • Change in surface air temperature and precipitation

  13. Climate change Projection: Temperature • Time series of annual mean surface air temperature averaged over model domain OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 Difference-Historical Difference –RCP4.5 Difference –RCP8.5 • RCM tends to underestimate warming trend

  14. Time series of CO2 concentration in RCP scenarios • RCM are using constant value of CO2 concentration with concentration for 1985 • Underestimation of warming trend is seems to be due to lack of increase of green house gases.

  15. Climate change Projection: Precipitation • Time series of annual mean precipitation averaged over model domain OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 Difference-Historical Difference –RCP4.5 Difference –RCP8.5 • Inter-annual variability of both GCM RCM is weak.

  16. Climate change Projection: Anomalies • Reference period: 1971-2000 OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 • It is clear that RCM tends to underestimate warming trend.

  17. Climate change projection: Temperature Current Change (RCP4.5) Change (RCP8.5) GCM RCM

  18. Climate change projection: Precipitation Current Change (RCP4.5) Change (RCP8.5) GCM RCM

  19. Summary 1 • Overall, performance of HadGEM3-RA on current climate simulation is similar to HadGEM2-AO. • However, HadGEM3-RA could resolve small-scale features related with topography and coastline. • General patterns of regional climate change projection by HadGEM3-RA is similar to projection by HadGEM2-AO. • But, HadGEM3-RA tends to underestimate warming trend due to lack of increase of green house gases.

  20. Evaluation of current climate simulation • in GCM forcing run (12.5km res) • - surface climate

  21. Climatology (1971-200): Precipitation Observation GCM RCM • RCM could resolve small-scale features related with topography and coastlines. • RCM of 12.5km-res is better than not only GCM but also RCM of 50km-res. Annual Summer Winter

  22. Climatology (1971-200): Temperature Observation GCM RCM • RCM could resolve small-scale features related with topography and coastlines. • RCM of 12.5km-res is better than not only GCM but also RCM of 50km-res. Annual Summer Winter

  23. Bias: Precipitation and Temperature • Precipitation • Temperature GCM RCM GCM RCM Annual Summer Winter

  24. Statistics: Precipitation & Temperature (Land) • Mean, bias, Root-mean-squared error (RMSE) and pattern correlation coefficient of precipitation and temperature. (Ref. APHRO and CRU) • Overall, RCM show better performance than GCM. But, RCM shows wet/cold biases.

  25. Annual cycle of Precipitation and temperature • 30-yr mean annual cycle of area-averaged precipitation and surface air temperature (1971~2000) Precip. Temp • Black: OBS • Red: GCM • Blue: RCM

  26. Probability of daily precipitation • The probability of daily precipitation with thresholds up to 50 mm/day Probability (%) Thresholds (mm/day) • RCM simulated probability is much more realistic than GCM simulation. • RCM projections of changes in extremes in the future are likely to be very different to, and much more credible than, those from GCMs.

  27. Climate change projection (12.5km) • Change in surface air temperature and precipitation

  28. Climate change projection: Temperature • Time series of annual mean surface air temperature averaged over model domain OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 Difference-Historical Difference –RCP4.5 Difference –RCP8.5 • RCM tends to underestimate warming trend • Underestimation of warming trend is seems to be due to lack of increase of green house gases.

  29. Climate change projection: Precipitation • Time series of annual mean precipitation averaged over model domain OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 Difference-Historical Difference –RCP4.5 Difference –RCP8.5 • Inter-annual variability of RCM is similar to observation.

  30. Climate change Projection: Anomalies • Reference period: 1971-2000 OBS (CRU) GCM-Historical GCM –RCP4.5 GCM –RCP8.5 RCM -Historical RCM –RCP4.5 RCM – RCP8.5 • It is clear that RCM tends to underestimate warming trend.

  31. Climate change projection: Temperature Current Change (RCP4.5) Change (RCP8.5) GCM RCM

  32. Climate change projection: Precipation Current Change (RCP4.5) Change (RCP8.5) GCM RCM

  33. Summary 2 • Overall, performance of HadGEM3-RA on current climate simulation is better than HadGEM2-AO. • HadGEM3-RA could resolve small-scale features related with topography and coastline. • And, HadGEM3-RA reproduced climate extreme better than HadGEM2-AO. • General patterns of regional climate change projection by HadGEM3-RA is similar to projection by HadGEM2-AO. • But, HadGEM3-RA tends to underestimate warming trend due to lack of increase of green house gases.

  34. Future plan • New downscaling experiments will be performed with all RCP scenarios (RCP2.6/4.5/6.0/8.5) including prescribed green house gases.

  35. Thank you very much!

  36. Precipitation: Annual mean climatology • Climatology of annual precipitation GCM RCM Observation GCM bias RCM effect RCM bias

  37. Precipitation: JJA mean climatology • Climatology of summer precipitation Observation GCM RCM GCM bias RCM effect RCM bias

  38. Large-scale field: 500-hPa height (JJA) Observation GCM RCM GCM bias RCM effect RCM bias • Both GCM and RCM enhanced upper trough.

  39. Low level circulation: SLP, 850-hPa wind/humidity Observation GCM RCM GCM bias RCM effect RCM bias • Both GCM has cyclonic anomalies over East Asian monsoon region. • And, RCM enhanced cyclonic anomalies .

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