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INSTITUTE OF METEOROLOGY , HYDROLOGY AND ENVIRONMENT (IMHEN). SIMULATIONS AND PROJECTIONS OF CLIMATE EXTREMES FOR VIETNAM USING AGCM/MRI MODEL. Mai Van KHIEM, Nguyen Van HIEP, Tran Dinh TRONG. Understand change in climate extremes is very impotant. Increased: • heatwaves • droughts
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INSTITUTE OF METEOROLOGY , HYDROLOGY AND ENVIRONMENT (IMHEN) SIMULATIONS AND PROJECTIONS OF CLIMATE EXTREMES FOR VIETNAM USING AGCM/MRI MODEL Mai Van KHIEM, Nguyen Van HIEP, Tran Dinh TRONG
Understand change in climate extremes is very impotant Increased: • heatwaves • droughts • strong typhoons • major rain storms • sea level Less: • frosts • sea ice • snow cover • glacier ice Climate change ICIA, 2004
Objective • To enhance the undersanding on climate change related climate extremes in Vietnam • Data used in this study: • - AGCM/MRI simulations • - Local observation • - CRU data Hoang sa island Truong sa island
Extreme event projection with very-high resolution atmospheric models MRI / JMA / AESTO High-resolution global atmospheric model Regional cloud resolving model by nesting CMIP3 CGCM Multi-model 110-180km mesh 5km & 1km mesh 20kmmesh Atmosphere Atmosphere Predicted SST Boundary condition SST SST Ocean Boundary condition Future 50-100km mesh Near Future Present SST SST=Sea Surface Temperature Year 1979-2003 2015-2039 2075-2099
CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) from ETCCDI: • Definition of 27 core extreme indices • Organization of regional workshop • WMO-guide on extremes, 2009, targeted at NMHSs around the world http://cccma.seos.uvic.ca/ETCCDI
Spatial patterns of annual temperature CCAM Res: 60km x60km RegCM Res: 20km x 0km MRI Res: 20km x 20km CRU • A tendency for winter temperatures to be lower than observations • MRI and RegCM have more detailed information and correct higher temperature in the south • The south part is better then northern part of Vietnam.
Spatial patterns of temperature Underestimate temperature DJF JJA CCAM RegCM MRI CRU
Spatial patterns of annual rainfall CCAM RegCM MRI CRU • Correct larger rainfall area in Central Vietnam at all models • CCAM underestimates rainfall in the north and RegCM underestimates rainfall southern part of Vietnam.
Spatial patterns of DJF rainfall DJF CCAM RegCM MRI CRU JJA
Annual cycle of temperature There is a tendency towards a cold bias in most part of domain, except R5, with the largest biases is found in regions R1. During the months Sep-Nov, values are closer to the observed in all sub-regions
Annual cycle of temperature - The model also can capture the seasonal cycle of precipitation well - Tend to be wetter than OBS during Jan-May
Climate extremes projection - present: 1979-2003 • near future: 2015-2039 • far future: 2075-2099
near future - present Annual Rainfall (%) Annual Temperature (oC)
far future - present Annual Rainfall (%) Annual Temperature (oC)
Mean. Tmin far future - present Present Temperature increase by 2-2,8°C. Far furture 3,4°C 2°C
Mean.Tmax far future - present Present Temperature increase by 2-2,4°C. Far furture 3,4°C 1,6°C
Present - Days with Tmax>35oC: increase by 1-15 days - Nights with Tmin>25oC: increase by 20-30 days far future - present
Greatest 5-day total rainfall far future - present Present Descrease over coastal area. Far furture 40 mm -70
Number days rainfall >= 10mm far future - present Present Increase most part of domain Far furture 35 day -20
Max number consecutive dry days far future - present Present More seriously drought over south? Far furture 21 day -9
Max number consecutive wet day far future - present Present Increase over most part of domain Far furture 30 day -50
95th percentile of rainfall Present far future - present mm/day Increase in heavy rainfall most part of domain, except in coastal central Vietnam
6 Jun 16 Aug Rainfall pentad Present Far furture Lon=100-120 far future - present Trong et al, 2010 -60 %
6 Dec 26 Feb Rainfall pentad Present Far furture Lon=100-120 far future - present Trong et al, 2010 -60 %
Summary • Model show good results in spatial and temporal distribution of rainfall and temperature. But, model underestimates temperature • Model results show more climate extremes in future: • - yearly mean daily maximum and minimum temperature increase. • - the number of very hot day and number of tropical night increase. • - increase in the intensity of heavy rainfall • - to have more seriously drought over south? • - decrease in rainfall associated with monsoon activities