1 glacio-hydrological projections with downscaled climate data · 2018. 12. 7. · research flow...
TRANSCRIPT
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Glacio-hydrological projections
with downscaled climate data
Megumi Watanabe and Shinjiro Kanae
Tokyo Institute of Technology
2018/02/08
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Current assessmentsand
our objective
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Current assessmentsfor impact of climate change
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(NATIONAL INTEGRATED WATER RESOURCES MANAGEMENT PLAN 2016)
Projected changes in precipitation for RCP4.5
Rainfall
River
discharg
e
Basin outflows and their return periods
To estimate of river discharge taking into
account glacier melt with a regional climate
projection
OBJECTIVE
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Research flow
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
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6
Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
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8
Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
-
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Past period• Uncertainty
• Data
- Air temperature
- Precipitation
Future period (GCMs)• Uncertainty
• Bias correction
• Multi-model
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Uncertainty of climate datafor the past period
The number of gauge (APHRODITE)
The scarcity of in-situ observations
(for temperature and precipitation)
at high elevations
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Temperature data for the past TA1 TA2
(Hirabayashi et al., 2008)
ERA-Interim
Thermometer
Reanalysis
It could be applied to
sparsely observed regionsRennie et al. (2014)
Sparse
stations
at
elevations
H08
Hybrid of observations and model
(Dee et al., 2012)
https://serc.carleton.edu/eet/envisioningcli
matechange/part_2.html
http://www.ushistory.org/franklin/fun/thermometer.htm
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Precipitation data for the pastPR1 PR2
PR3 PR4
©JAXA
APHRODITE Sakai
MSWEP MSWEP+PR
©JAXA
Gauge Gauge
Gauge Satellite Reanalysis Gauge Satellite Reanalysis
(This study)
http://www.stuffintheair.com/rain-gauge.html
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Precipitation data for the pastPR1 PR2
PR3 PR4
©JAXA
APHRODITE Sakai
MSWEP MSWEP+PR
©JAXA
©NASA
GaugeGauge
Gauge Satellite Reanalysis Gauge Satellite Reanalysis
(This study)
Inverse
estimation
using
discharge
Inverse
estimation
using
glacier
elevation
Directly
detect rain
drop using
satellite radar
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Precipitation data for the pastPR1 PR2
PR3 PR4
©JAXA
APHRODITE Sakai
MSWEP MSWEP+PR
©JAXA
GaugeGauge
Gauge Satellite Reanalysis Gauge Satellite Reanalysis
(This study)
Inverse
estimation
using
discharge
Inverse
estimation
using
glacier
elevation
Directly
detect rain
drop using
satellite radar
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15PR2 Sakai et al. (2015)
Gauge
Satellite
derived
glacier
elevation
Correct
(Nuimura et al., 2015)
Inversely estimate
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𝑷 = 𝑬 +𝑸 + ∆𝑺
P: Precipitation; Q: Observed discharge; E:Evaporation;
∆S: changes in water storage
PR3 MSWEP (Beck et al., 2015)
©JAXA
Multi
CorrectGauged
discharge
http://www.bafg.de/GRDC/E
N/02_srvcs/21_tmsrs/riverdis
charge_node.html
Global Runoff Data Centre
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Precipitation data for the pastPR1 PR2
PR3 PR4
©JAXA
APHRODITE Sakai
MSWEP MSWEP+PR
©JAXA
GaugeGauge
Gauge Satellite Reanalysis Gauge Satellite Reanalysis
(This study)
Inverse
estimation
using
discharge
Inverse
estimation
using
glacier
elevation
Directly
detect rain
drop using
satellite radar
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MicrowaveInfrared Radar (PR)
High emissivity
from the ground
Relationship between
the cloud height and
precipitation
More sensitive
over land as
well as ocean
Yamamoto et al. (2011)
The peak local-time distribution of precipitation showed a
relationship with the topography in the order of precipitation
radar (strongest relationship), microwave radiometer, and
infrared products.
PR4 MSWEP + PR (This study)
©JAXA
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Past period• Uncertainty
• Data
- Air temperature
- Precipitation
Future period (GCMs)• Uncertainty
• Bias correction
• Multi-model
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Projected change in
temperature for RCP4.5
(NIWRNP 2016)
Projected annual total
precipitation from CMIP5
GCMs (RCP8.5)
Spread
of
climate
models
Uncertainty of climate datafor the future
Climate models
Coarse spatial resolution & bias
Spread among models
Bias correction
Multi-model
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“Original”
Projected air temperature in 2080-2010 by INM-CM4, RCP8.5
correctionBias
℃“Downscaled”Bias correction
1950 2000 2050 2100Year
Climate
model
Observation
Compare
statics
【Baseline period】 【Projection period】
Correct
statics
!! Can be different
depending on data
for the past !!
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Eastern Himalaya
Various
climate
models
GHG emission levelScenarios
High
MidLow
ΔTemperature(℃) ΔSnowfall(%)(2070-2099 to 1950-1979)RCP2.6-8.5
CMIP5 GCMs
Multi-scenario, Multi-model
GCM1
GCM3
GCM2
High temperature
Median temperature & snowfall
More snowfall
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
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Initial glacier data
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The latest glacier inventory“Randolph Glacier Inventory”• A globally complete inventory of
glacier outlines using modern satellite (such as Landsat or ASTER) imagery
• Version 6.0: released July 28, 2017.
• Information • Glacier shape• Location (latitude & longitude)• Glacier area• Altitude• Length
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…
Glacier shape by RGI 6.0
Legend
glacier_BH
TM_WORLD_BORDERS-0.3
n25e090_dem.tif
-12.17773819 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 7,557.027832
n25e085_dem.tif
-5.14632225 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 8,839.171875
Legend
glacier_BH
TM_WORLD_BORDERS-0.3
n25e090_dem.tif
-12.17773819 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 7,557.027832
n25e085_dem.tif
-5.14632225 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 8,839.171875
Legend
glacier_BH
TM_WORLD_BORDERS-0.3
n25e090_dem.tif
-12.17773819 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 7,557.027832
n25e085_dem.tif
-5.14632225 - 1,000
1,000.000001 - 2,000
2,000.000001 - 3,000
3,000.000001 - 3,500
3,500.000001 - 4,000
4,000.000001 - 4,500
4,500.000001 - 5,000
5,000.000001 - 5,500
5,500.000001 - 6,000
6,000.000001 - 8,839.171875
< 1,000
1,000-2,000
2,000-3,000
3,000-3,500
3,500-4,000
4,000-4,500
4,500-5,000
5,000-5,500
5,500-6,000
> 6,000
Altitude (m)
ⒸNASALandsat
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Hydrological model
Research flow
Energy balance glacier
model with debris effect
Temperature index
glacier model
River discharge
Case1 Case2
Runoff from glaciers (Case1,2)
(Case1,2)
Initial glacier data
Multiple climate data at high elevations
Precipitation, air temperature and etc.
-
Temperature index glacier model
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Melt factor
[mm/℃/day]
Surface-air
temperature [℃] 0 [℃]
Snow pack is transformed into glacier ice
MeltingSnowfall
Accumulation Ablation
𝑻𝒊 + 𝒅𝑻 − 𝑻𝟎 𝑫𝑫𝑭
Surface air
temperaturePrecipitation
Glacier model –mass balance-Glacier
Snowfall = Precipitation*Cp
(if 𝑻𝒊 + dT 2)
(Hirabayashi et al., 2013)
Adjustment
factor
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Summary
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Today’s summary
• Multiple climate data for the past period• Air temperature (In-situ / Reanalysis)
• Precipitation (In-situ / Reanalysis / Inverse estimations)
• Climate data for the future period • Bias correction of GCMs
• Multi-GCMs
• Initial glacier data from the inventory
• Temperature index glacier model
• Uncertainty range of climate data
• Uncertainty range of glacier projections
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