impacts of bias correction over climate change projections ......impacts of bias correction over...
TRANSCRIPT
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Impacts of bias correction over climate
change projections applied to crop yield simulations
Santiago V. Cuadra, Rosmeri P. da Rocha, Marta Pereira
Llopart, Kenneth J.Boote, Daniel De Castro Victoria
e-mail: [email protected]
São Paulo, Brasil, June 25-27/2018.
CORDEX Central America and South America Training Workshop on Downscaling Techniques
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Climate Change Impacts
for BrazilAverage Air Temperature
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Climate Change Impacts
for BrazilPrecipitation Anomaly
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Climate Change Impacts
for BrazilWater Defict Anomaly
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Crop Development, Growth and Yield
Crop Cycle
Sow.| Emerg. | Vegetative Phase | Flowering Phase | Pod Formation and Maturation
Phase 4
-80
-60
-40
-20
0
20
40
60
80
100
120
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
sWater Balance
Phase 3
Phase 2
Phase 1
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Summary of projected changes in crop yield
(combines 1090 evaluations)
Source: IPCC/WG1AR5
Expect Impacts for food
production
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Goald
Present the climate simulations systematic errors and their impacts over climate change
scenarios for food production – soybean over south Brazil.
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RegCM4-HadGEM Bias
Minimum Temperature Bias Maximum Temperature Bias
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RegCM4-HadGEM Bias
Precipitation Bias Solar Radiation Bias
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Consequences of climate
model Bias
Soybean Simulated Yield
Observed Climate RegCM4-Original
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NOT Handling Bias - REGO
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Handling Bias -
REGDDELTA
DELTA
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Handling Bias - REGB
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Handling Bias -
REGQ
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Consequences of climate
model Bias
Soybean Simulated Yield
Observed Climate RegCM4-Original RegCM4-Bias Correct
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Bias correction of climate
model fieldsOriginal RegCM4 outputs
YIELD WITH OBS DATA
YIE
LD W
ITH
REG
O
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Bias correction of climate
model fieldsRemove Average Bias from RegCM4 outputs
YIELD WITH OBS DATA
YIE
LD W
ITH
REG
B
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Bias correction of climate
model fieldsQuantil-Quatil correction RegCM4 outputs
YIELD WITH OBS DATA
YIE
LD W
ITH
REG
Q
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Bias correction of climate
model fields
Original RegCM4 outputsObserved Climate Data
YIELD (kg/ha)
Fre
qu
en
cy
YIELD (kg/ha)
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Bias correction of climate
model fields
Remove Average Bias from RegCM4 Observed Climate Data
YIELD (kg/ha)
Fre
qu
en
cy
YIELD (kg/ha)
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Bias correction of climate
model fields
Quantil-Quatil correction RegCMObserved Climate Data
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Impacts of Bias correction for
climate change scenarios
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TMAX anomaly - DELTA (RegCM4)
TMAX anomaly - Bias correction TMAX anomaly - Quantil correction
TMAX anomaly - original RegCM4
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TMAX - DELTA (RegCM4) TMAX - original RegCM4
TMAX - Bias correction TMAX - Quantil correction
TMAX
Fre
qu
en
cy
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PRCP Anomaly - DELTA (RegCM4)
PRCP Anomaly - Bias correction PRCP Anomaly - Quantil correction
PRCP Anomaly - original RegCM4
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PREC - DELTA (RegCM4) PREC - original RegCM4
PREC - Bias correction PREC - Quantil correction
PREC
Fre
qu
en
cy
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SRAD Anomaly - DELTA (RegCM4)
SRAD Anomaly - Bias correction SRAD Anomaly - Quantil correction
SRAD Anomaly - original RegCM4
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SRAD - DELTA (RegCM4) SRAD - original RegCM4
SRAD - Bias correction SRAD - Quantil correction
Solar Radiation
Fre
qu
en
cy
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Impacts through DELTA (RegCM4)
Impacts with Bias correction Impacts with Quantil correction
Impacts with original RegCM4
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Impacts through DELTA (RegCM4)
Impacts with Bias correction Impacts with Quantil correction
Impacts with original RegCM4
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Impacts through DELTA (RegCM4) Impacts with original RegCM4
Impacts with Bias correction Impacts with Quantil correction
YIELD (kg/ha)
Fre
qu
en
cy
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• Yield anomalies with the original RegCM4 data presented differences in
relation to the simulations with bias correction, reaching up to 40%
differences;
• Simulations with all bias correction methods presented similar results for
average yield anomalies;
• Delta method underestimated the climate change impacts on the average
soybean yield and its interannual variability;
• The results shows the need to correct the systematic errors of the climate
models for impacts assessments applications.
Conclusions and
Recommendations