Downscaling activities to support the Impact of rice production under climate change
Ramkhamhaeng University
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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
Background Information
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• 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
Downscaling GCMs
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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
Statistical Downscaling
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• 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 ) .
Transfer function
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• D o w n s c a l e t h e C M I P 5 - G C M s b y u s i n g – 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 .
Activities
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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
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Station number by meteorological data
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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
Solar Radiation Data
• D a t a f r o m 3 2 s t a t i o n s • With compliment from
Assoc.Prof.Serm Janjai, Silpakorn University
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GFDL-ESM2M MPI-ESM-LR HadGEM2-ES Organization
Geophysical Fluid Dynamic Laboratory
Max Planck Institute for Meteorology
Met Office Hadley Centre
Base year 1961 – 2005 Future climate projection 2006 – 2100 Scenario RCP4.5
RCP6.0 RCP8.5
RCP4.5 -
RCP8.5
RCP4.5 RCP6.0 RCP8.5
G r i d r e s o l u t i o n L a t i t u d e L o n g i t u d e
2.02247o
2.50000o
1.86500o 1.87500o
1.25500o 1.87500o
No. of Predictor 7 7 7
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Selected GCMs
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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/m2/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
Predictors
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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 – 22oN
longitude 95 – 105oE 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
Downscaling Output
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 .
Downscaling Procedures
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Future Mean temperature : RCP8.5
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GFDL MPI HadG
Historical data 2006 2006 2025 2050 2075 2100
Future Max. Temperature : RCP8.5
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Historical data 2006 2006 2025 2050 2075 2100
GFDL MPI HadG
Future Precipitation : RCP8.5
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Historical data 2006 2006 2025 2050 2075 2100
GFDL MPI HadG
• 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
Ideas for future work
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Researchers
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Asst. Prof. Dr. Jerasorn Santisirisomboon : Ramkhamhaeng University Dr . Somkia t Ap ipa t t anav i s : Roya l I r r i ga t i on Depa r tmen t 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 . Pawanra t Agsorns ingcha i : Ramkhamhaeng Unive r s i ty M r . S o n g s a k C h u a i b u m r o o n g : R a m k h a m h a e n g U n i v e r s i t y
Thank You
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