Downscaling activities to support the Impact of rice production - PowerPoint PPT Presentation

Downscaling activities to support the Impact of rice production under climate change Ramkhamhaeng University www.ru.ac.th

Background Information Project title : Downscaling of GCMs for the impacts study of climate change on rice p r o d u c t i o n i n T h a i l a n d Funded by : Thailand Research Fund (TRF) D u r a t i o n : 2 y e a r s Collaboration : Ramkhamhaeng University D e p a r t m e n t o f R i c e D e p a r t m e n t o f I r r i g a t i o n www.ru.ac.th

Downscaling GCMs • General Circulation Model, GCM: Mathematical model use to simulate present and project future c l i m a t e . • G C M : c o a r s e r e s o l u t i o n : l o c a l d e t a i l s a r e l o s t • Downscaling activities are required • There are two general approaches : dynamical and statistical downscaling www.ru.ac.th

Statistical Downscaling Statistical downscaling comprises 3 broadly t e c h n i q u e s : • W e a t h e r g e n e r a t o r s • W e a t h e r t y p i n g a n d • T r a n s f e r f u n c t i o n www.ru.ac.th

Transfer function • Transfer function achieved from linear and non-linear r e g r e s s i o n a n a l y s e s . • Transfer function technique is to develop quantitative r e l a t i o n s h i p s b e t w e e n – large-scale atmospheric variables (predictors) and – l o c a l s u r f a c e v a r i a b l e s ( p r e d i c t a n d ) . www.ru.ac.th

Activities • Downscale the CMIP5-GCMs by using – S t a t i s t i c a l a p p r o a c h – Transfer function technique: Artificial Neural N e t w o r k ( A N N ) • To generate historical and future climate data with f i n e r g r i d r e s o l u t i o n . www.ru.ac.th

Meteorological Stations and Data • Data from 123 Meteorological s t a t i o n s • D a t a c o n s i d e r e d : – Mean, Max, Min Temp. – R H – S u n s h i n e d u r a t i o n – A t m o s p h e r i c p r e s s u r e – W i n d s p e e d – P r e c i p i t a t i o n www.ru.ac.th

Station number by meteorological data Data 1951-1980 1981-1990 1991-2000 2001-2011 Max. Temperature 85 103 116 120 Mean Temperature 75 90 101 120 Min. Temperature 85 103 116 119 Precipitation 85 103 116 119 Relative Humidity 84 103 118 120 Sunshine duration 8 15 17 60 Atmospheric pressure N/A 69 75 120 Wind speed N/A N/A 84 85 www.ru.ac.th

Solar Radiation Data • Data from 32 stations • With compliment from Assoc.Prof.Serm Janjai, Silpakorn University www.ru.ac.th

Selected GCMs GFDL-ESM2M MPI-ESM-LR HadGEM2-ES Organization Geophysical Max Planck Met Office Fluid Dynamic Institute for Hadley Centre Laboratory Meteorology Base year 1961 – 2005 Future climate projection 2006 – 2100 Scenario RCP4.5 RCP4.5 RCP4.5 RCP6.0 - RCP6.0 RCP8.5 RCP8.5 RCP8.5 G r i d r e s o l u t i o n L a t i t u d e 2.02247 o 1.86500 o 1.25500 o L o n g i t u d e 2.50000 o 1.87500 o 1.87500 o No. of Predictor 7 7 7 www.ru.ac.th

Predictors Predictors for GCMs Unit D a i l y - M e a n N e a r S u r f a c e W i n d S p e e d m/s S e a L e v e l P r e s s u r e Pa P r e c i p i t a t i o n kg/m 2 /s N e a r - S u r f a c e S p e c i f i c H u m i d i t y N e a r - S u r f a c e A i r T e m p e r a t u r e K Daily Maximum Near-Surface Air Temperature K Daily Minimum Near-Surface Air Temperature K www.ru.ac.th

Downscaling Output รายละเอียด B a s e y e a r 1961 - 2005 F u t u r e y e a r 2006 - 2100 S p a t i a l s c a l e 10 km × 10 km T e m p o r a l s c a l e Daily A r e a latitude 5 – 22 o N longitude 95 – 105 o E O u t p u t ( P r e d i c t a n d s ) Mean, Max., Min. Temperature Precipitation Relative humidity Sunshine duration Solar radiation Atmospheric pressure Wind speed www.ru.ac.th

Downscaling Procedures Statistical downscaling technique applied in this study has 4 m a i n s t e p s : 1) Develop quantitative functions between predictors (base year data from reanalysis) and predictands (statistical data from meteorological stations) by using ANN. 2) Apply the functions to project future point station data with future data from GCMs as predictors. 3) Generate grid data from future point station data 4 ) C a l i b r a t i o n o f g r i d d a t a . www.ru.ac.th

Future Mean temperature : RCP8.5 Historical data 2006 2006 2025 2050 2075 2100 GFDL MPI HadG www.ru.ac.th

Future Max. Temperature : RCP8.5 Historical data 2006 2006 2025 2050 2075 2100 GFDL MPI HadG www.ru.ac.th

Future Precipitation : RCP8.5 Historical data 2006 2006 2025 2050 2075 2100 GFDL MPI HadG www.ru.ac.th

Ideas for future work • Downscale CMIP4-GCM2 to 25 km × 25 km – S E A C L I D / C O R D E X S E A o u t p u t • F u r t h e r d o w n s c a l i n g – A p p l y t h e s t a t i s t i c a l d o w n s c a l i n g × 1 0 k m – 1 0 k m – Need high quality measurement data from the whole region www.ru.ac.th

Researchers Asst. Prof. Dr. Jerasorn Santisirisomboon : Ramkhamhaeng University Dr. Somkiat Apipattanavis : Royal Irrigation Department D r . C h i t n u c h a B u d d h a b o o n : R i c e D e p a r t m e n t Asst. Prof. Dr. Jaruthat Santisirisomboon : Ramkhamhaeng University Dr. Waranyu Wongseree : King Mongkut’s University of Technology North B a n g k o k D r . Y o d S u k h a m o n g k o l : R a m k h a m h a e n g U n i v e r s i t y M s . B e n j a m a s R o s o c h a : R i c e D e p a r t m e n t Ms. Pawanrat Agsornsingchai : Ramkhamhaeng University Mr. Songsak Chuaibumroong : Ramkhamhaeng University www.ru.ac.th

Thank You 19 www.ru.ac.th