1Glacio-hydrologicalprojections
with downscaled
climate data
Megumi Watanabe and Shinjiro Kanae
Tokyo Institute of Technology
2018/02/08

2

Current assessments
andour objective

Current assessments
for impact of climate change(NATIONAL INTEGRATED WATER RESOURCES MANAGEMENT PLAN 2016)

Rainfall

Projected changes in precipitation for RCP4.5
Riverdischarge
OBJECTIVE

To estimate of river discharge taking into
account glacier melt with a regional climate
projection Basin outflows and their return periods

34Research flow

5Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

6Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

7Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

8Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

9Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.

Past periodInitial glacierdata period (GCMs)
Future• Uncertainty
Case1• Data-Temperature
Air temperatureindex- Precipitation
glacier model• Uncertainty
Case2• Bias correction•Energy
Multi-model
balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

Uncertainty of climate data
for the past period

The number of gauge (APHRODITE)

The scarcity of in-situ observations(for temperature and precipitation)
at high elevations

10Temperature data for the past
TA1 H08

ERA-Interim(Dee et al., 2012)TA2(Hirabayashi et al., 2008)

Thermometer
http://www.ushistory.org/franklin/fun/thermometer.htm

Sparsestations
atelevations
Rennie et al. (2014)

https://serc.carleton.edu/eet/envisioningcli
matechange/part_2.html

Reanalysis

Hybrid of observations and model

It could be applied tosparsely observed regions

Precipitation data for the past
PR1 APHRODITE

Gauge
PR3 MSWEPPR2 Sakai

Gauge
PR4 MSWEP+PR (This study)

©JAXA

©JAXA

Gauge Satellite Reanalysis

Gauge Satellite Reanalysis

http://www.stuffintheair.com/rain-gauge.html

Precipitation data for the past
PR1 APHRODITE

Gauge
PR3 MSWEPPR2 Sakai

Inverseestimation
usingglacierelevation

Gauge

PR4 MSWEP+PR (This study)

©JAXA

©JAXA

Gauge Satellite Reanalysis

Gauge Satellite Reanalysis
Directlydetect rain
drop using©NASAsatellite radar

Inverseestimation
usingdischarge

Precipitation data for the past
PR1 APHRODITE

Gauge
PR3 MSWEPPR2 Sakai

Inverseestimation
using
glacierelevation

Gauge

PR4 MSWEP+PR (This study)

©JAXA

©JAXA

Gauge Satellite Reanalysis

Gauge Satellite Reanalysis
Directlydetect rain
drop using
satellite radar

Inverseestimation
usingdischarge

15

PR2 Sakai et al. (2015)
Satellite
derivedglacierelevation

Correct
Gauge

Inversely estimate(Nuimura et al., 2015)

16

PR3 MSWEP (Beck et al., 2015)
Gaugeddischarge

Correct

©JAXA

Multi
𝑷 = 𝑬 + 𝑸 + ∆𝑺
P: Precipitation; Q: Observed
discharge; E：Evaporation;∆S: changes in water storage
Global Runoff Data Centre
http://www.bafg.de/GRDC/E
N/02_srvcs/21_tmsrs/riverdis
charge_node.html

Precipitation data for the past
PR1 APHRODITE

Gauge
PR3 MSWEPPR2 Sakai

Inverseestimation
usingglacierelevation

Gauge

PR4 MSWEP+PR (This study)

©JAXA

©JAXA

Gauge Satellite Reanalysis

Gauge Satellite Reanalysis
Directlydetect rain
drop using
satellite radarInverse
estimation
usingdischarge

18

PR4 MSWEP + PR (This study)
Infrared

Microwave

Radar (PR)

©JAXA

Relationship between
the cloud height andprecipitation

High emissivity
from the ground

More sensitive
over land as
well as ocean

Yamamoto et al. (2011)
The peak local-time distribution of precipitation showed arelationship with the topography in the order of precipitation
radar (strongest relationship), microwave radiometer, andinfrared products.

19

Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.

Past period

Initial glacierdata period (GCMs)
Future• Uncertainty
Case1• Data-Temperature
Air temperature
index- Precipitation
glacier model• Uncertainty
Case2• Bias correction•Energy
Multi-model
balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)

Uncertainty of climate datafor the future

20Spreadofclimatemodels

Projected change intemperature for RCP4.5(NIWRNP 2016)

Projected annual total
precipitation from CMIP5
GCMs (RCP8.5)

Climate models
 Coarse spatial resolution & bias Bias correction
 Spread among models
Multi-modelBias correction“Original”

21“Downscaled”℃

Biascorrection
Projected air temperature in 2080-2010 by INM-CM4, RCP8.5【Baseline period】 【Projection period】

Correctstatics

2000

Climatemodel!! Can be different
depending on data
for the past !!

Comparestatics
1950

Observation

2050

2100

Year

Multi-scenario, Multi-model
Eastern Himalaya

Scenarios
GHG emission levelHighMid
Low
RCP2.6-8.522

ΔTemperature(℃) ΔSnowfall(%)(2070-2099 to 1950-1979)

Variousclimatemodels
CMIP5 GCMs

GCM1 High temperature
GCM2 Median temperature & snowfall
GCM3 More snowfall

23

Research flow
Multiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)24Initial glacier data

The latest glacier inventory“Randolph Glacier Inventory”

Landsat

25ⒸNASA• A globally complete inventory of
glacier outlines using modern
satellite (such as Landsat or ASTER)
imagery• Version 6.0: released July 28, 2017.
• Information
LegendLegend• Glacier shapeglacier_BH
Glacier shape by RGI glacier_BH
6.0• Location
TM_WORLD_BORDERS-0.3 TM_WORLD_BOR
n25e090_dem.tif(latitude & longitude) n25e090_dem.tif<セル値>• Glacier area
Legend-12.17773819 - 1<セル値>
glacier_BH
1,000.000001 - 2• Altitude-12.17773819 - TM_WORLD_BORDERS-0.3
1,000
2,000.000001 - 3• Length
3,000.000001 - 3
1,000.000001 n25e090_dem.tif- 2,000…

Altitude (m) 3,500.000001 - 4
2,000.000001 - 3,000< 1,000
4,000-4,500 - 4-12.17773819- 1,000 4,000.000001
1,000-2,000
4,500-5,000 - 5
3,000.000001 - 3,500
1,000.000001 - 2,000 4,500.000001
2,000-3,000
5,000-5,500
2,000.000001 - 3,000 5,000.000001 - 5
3,000-3,500
5,500-6,000
3,500.000001 - 4,000
3,000.000001-63,500-4,000 - 3,500 5,500.000001> 6,000
4,000.000001 - 4,500
3,500.000001 - 4,000 6,000.000001 - 7<セル値>

26Research flowMultiple climate data at high elevations
Precipitation, air temperature and etc.
Initial glacier data
Case2

Case1

Temperature index
glacier model

Energy balance glaciermodel with debris effect

Runoff from glaciers (Case1,2)Hydrological modelRiver discharge (Case1,2)27Temperature index
glacier modelGlacier model –mass balance-28(Hirabayashi et al., 2013)

Glacier

Precipitation

SnowfallAccumulation

Snow pack is transformed
into glacier ice
Snowfall = Precipitation*Cp(if 𝑻𝒊 + dT<= 2)0 (if 𝑻𝒊 + dT > 2)

Surface airtemperature

MeltingAblation

𝑻𝒊 + 𝒅𝑻 − 𝑻𝟎 𝑫𝑫𝑭
Surface-airtemperature [℃] 0 [℃]
Adjustment Melt factor[mm/℃/day]factor29Summary

Today’s summary30• 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