Evaluation of NHRCM highresolution climate simulations
over the Philippines
Faye Abigail T. Cruz1
Hidetaka Sasaki2
1 Manila Observatory, Quezon City, Philippines
2 Meteorological Research InsFtute, Tsukuba, Japan

InternaFonal Workshop on Climate Downscaling Studies
2-4 October 2017, InternaFonal Congress Center EPOCHAL Tsukuba, Japan

Philippines : a hotspot for climate risk
• High climate risk: high exposure, high vulnerability, lack of coping and adapFve capaciFes (WorldRisk Report, 2016)• High-resoluFon climate projecFons criFcal for appropriate adaptaFon measures, especially forareas along the coast, with complex topography• Currently available projecFons from single GCM, RCM, emission scenario• ProjecFons from mulFple GCMs, RCMs and RCPs recommended to address uncertainFes
World Risk Report, 2016

Source: hZp://weltrisikobericht.de/wp-content/uploads/2016/08/WorldRiskReport2016.pdf

Tropical Cyclone Tracks (1945-2010)

Figure source: Manila Observatory
Data: JTWC

The Southeast Asia Regional Climate Downscaling(SEACLID) / CORDEX Southeast Asia Project

2nd SEACLID/CORDEX Southeast Asia Manuscript WriFng Workshop
RU-CORE, Bangkok, Thailand, 3-10 July 2017

Participating members: 20 insFtuFons from
14 countries within and outside
Southeast Asia
• Aims to produce high-resoluFon climate projecFons over SE Asia from mulFple GCMs,RCMs and RCP scenarios (to be distributed via ESGF), and to enhance climate researchand capacity in the region• Website: hZp://www.ukm.my/seaclid-cordex

Climate simulations conducted under SEACLID /CORDEX Southeast Asia Project• SensiFvity tests using RegCM4 for present climate done (Juneng et al. 2016,Ngo-Duc et al. 2017, Cruz et al. 2017)• Ongoing analysis of projecFon simulaFons
Country

GCM

RCPRCM

Vietnam

CNRM-CM5

RCP8.5, 4.5

RegCM4

Philippines

HadGEM2

RCP8.5, 4.5

RegCM4RegCM4

Country

GCM

RCP

RCM

Australia

CNRM-CM5

RCP8.5CCAM

Australia

CCSM4

RCP8.5CCAM

Australia

ACCESS1.3

RCP8.5

CCAM

Thailand

MPI-ESM-MR

RCP8.5, 4.5

Thailand

EC-Earth

RCP8.5, 4.5

RegCM4

Hong Kong SAR

CCSM or CESM

RCP8.5, 4.5

WRF

Indonesia

CSIRO MK3.6

RCP8.5, 4.5

RegCM4

United Kingdom

HadGEM2-ES

RCP8.5, 4.5

PRECIS

Malaysia

CanESM2

RCP8.5, 4.5

RegCM4South Korea

HadGEM2-AO

RCP8.5, 4.5

WRF

Malaysia

IPSL-CM5A-LR

RCP8.5, 4.5

RegCM4

Sweden

CNRM-CM5

RCP8.5, 4.5

RCA3

Malaysia

GFDL-ESM2M

RCP8.5, 4.5

RegCM4Sweden

HadGEM2-ES

RCP8.5, 4.5

RCA3

Germany

MPI-ESM-LR

RCP8.5, 4.5

ROM

Japan

MRI-AGCM60

RCP8.5, 4.5

NHRCM

Model Domain at 25 km resolu>on

Application of NHRCM
over Southeast Asia andthe Philippines

CORDEX-SE Asia
domainPhilippine
domain (5 km)

ObjecFve : To generate highresoluFon mulF-scenario climate
projecFons for Southeast Asia (25km) and the Philippines (5 km) using
NHRCM (Sasaki et al. 2008)
Table 1. List of experiments

Methodology :• Boundary condiFons• ERA-Interim• MRI AGCM3.2• 14-month runs (from April toMay of the following year) inparallel, discarding iniFal 2
months as model spin-up• Spectral nudging used

DomainResolu>on

Boundary Condi>on

Time Period

Scenario

SE Asia

25 km

ERA-Interim (~75 km)

1989-2008

SE Asia

25 km

MRI-AGCM60

1981-2000

Philippines

5 km

NHRCM (25 km)

1981-2000

SE Asia

25 km

MRI-AGCM60

2020-2039

RCP 8.5

SE Asia

25 kmMRI-AGCM60

2080-2099

RCP 8.5

Philippines

5 km

NHRCM (25 km)

2080-2099

RCP 8.5

SE Asia

25 km

MRI-AGCM60

2080-2099

RCP 2.6

SE Asia

25 km

MRI-AGCM60

2080-2099

RCP 4.5

SE Asia

25 km

MRI-AGCM60

2080-2099

RCP 6.0

Analysis• ObservaFon data
• APHRODITE (Yasutomiet al. 2011, Yatagai etal. 2012)• PAGASA staFons (46)
• Focus over the Philippines• SpaFal paZerns• Seasonal variability• Regional means basedon climate types
Source: Cinco et al. (2014)

Philippine Climate Classification(Modified Coronas Atlas)
Type I climate (two pronounced season withdry period from November to April and wet
period from May to October)Type II climate (no dry season with a very
pronounced maximum rainfall during themonths of November–December);Type III climate (seasons not very pronouncedwith a relatively dry period from November toApril, as in Type I);

Monthly Total Rainfall (mm/month)Type IV climate with rainfall more or less evenly
distributed along the year
600
500
400
300
200
100
0024

Type1Type26MonthType381012Type4

Data source: PAGASA

http://kidlat.pagasa.dost.gov.ph/cab/climate_change/images/ClimateMap.JPG

Evaluation of model performance
NHRCM captures the seasonal spaFal paZerns in rainfall and winds, especially along
coastlines and high topography but overesFmates rainfall in the windward side of mountains.

Cruz and Sasaki (2017)

Evaluation of model performance :Comparison with ERA-Interim(a)
DJF MAMJJASON

DJF MAM

20SON

20JJA(b)(% diff)

Correlation

100

1.00

80

0.75
0.50

151560
40

0.00

−20

−0.25

−40

10

−60
−80

−0.50

10Regions0−0.75−1.00

5−1005Regions

NHRCM reduces theoveresFmated rainfall
in ERA-Interim (overeastern Philippines
and the MariFmeConFnent) resulFng inhigher spaFal
correlaFon.

0.25

20PH
246810212468Cruz
10 and Sasaki
12 (2017)

Evaluation of model performanceDiﬀerence in Average Wet Days (days)

20(a)100-10-20-30-40
1

2

34

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

Diﬀerence in Average Rainfall Intensity(mm day-1)

Regions

JJA

15DJF(b)10Tendency tounderesFmate thenumber of wet days,
especially during thewet season, butoveresFmate thedaily rainfall
intensity

50-512345678

9 10 11 12 13 14 15 16 17 18 19 20

Regions

JJA

DJF

Cruz and Sasaki (2017)

Evaluation of model performance :Comparison with ERA-Interim(a)DJF MAM

10DJF MAM
Correlation

30.75

20.50

151.00

10.25

00.00

−1−0.25−3−0.50
−0.75
−1.00

5−4PH

SON

41015(°C)−25Regions

20JJA

Regions

SON20JJA(b)NHRCM has an overall
cold bias, which
reduces the warm bias
in ERA-Interim
Cruz, F. T., and H. Sasaki, 2017.
SimulaFon of present climate overSoutheast Asia using the NonhydrostaFc Regional Climate Model.
SOLA, 13, 13-18, doi:10.2151/sola.
2017-003.

Results:
Validation ofpresent-day
temperature

NHRCM is able torepresent the spaFal
paZerns oftemperature• Reduced cold bias
in the global
model (AGCM60)

APHRO25
DJF

JJA

AGCM60NHRCM25

NHRCM5

Results:
Validation ofpresent-day
temperature

Colder bias in
NHRCM5 in Luzon
and Mindanao
islands, comparedwith NHRCM25

AGCM60DJF

JJA

NHRCM25

NHRCM5Model evaluation : Temperature Annual CycleTemperature (°C)

30Type 12826•24••22

APHRODITE tends to belower than PAGASA
throughout the year
(Note: area average fromgrid vs point values)
Close values between
AGCM60 and NHRCM25
Cold bias in NHRCM5Also seen in other types

30

Temperature (°C)•282624
22Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Type 328262422

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

AGCM60_25km

112Rainfall (mm/day)

Temperature (°C)

30

APHRO25
NHRCM5_25km

230Temperature (°C)

PAGASA (12 stn)
NHRCM25

Type 484

PAGASA (13 stn)

APHRO25

NHRCM25

NHRCM5_25km

AGCM60_25km

Type 428262422

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
PAGASA (12 stn)
NHRCM25

Type 2

APHRO25
NHRCM5_25km

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

AGCM60_25km

40Jan
PAGASA

FebMarAPHRO25

AprMayJun

AGCM60_25km

JulAugSep

NHRCM25Oct

PAGASA (9 stn)

APHRO25

NHRCM25

NHRCM5_25km

Nov

Dec

NHRCM5_25km

AGCM60_25km

Results:
Validation ofpresent-day
rainfall

APHRO25

AGCM60DJF

NHRCM is able torepresent the spaFal
paZerns of rainfall• Captured the highrainfall over areas
with high terrain,
along coast

JJA
Annual Mean Daily Rainfall

NHRCM25

NHRCM5

Results:
Validation ofpresent-dayrainfall• Reduced the wet bias inLuzon from the globalmodel• Tendency tooveresFmate rainfall
over mountain areas• Dry bias on the eastern
secFon during thesouthwest monsoon
season (JJA)

AGCM60DJF

JJA

NHRCM25

NHRCM5

Results:
Validation ofpresent-day
850mb (zonal)
winds

ERAI25

AGCM60NHRCM25

DJF

JJA
Close representaFonof winds; stronger
southwesterlies inNHRCM25(m/s)

Model evaluation : Rainfall Annual Cycle• NHRCM captures
seasonality,
within variability• Reduces bias inglobal modelType 11812624Rainfall (mm/day)

Rainfall (mm/day)

2418
12600

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
PAGASA (12 stn)
NHRCM25

APHRO25
NHRCM5_25km

PAGASA (13 stn)
NHRCM25

AGCM60_25km

18401212Type 484

APHRO25
NHRCM5_25km
0

AGCM60_25km

JanPAGASAFebMarAPHRO25

Apr

AGCM60_25km

MayJunAGCM60_25km

Type 48404Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
PAGASA (12 stn)
NHRCM25

APHRO25
NHRCM5_25km

2Rainfall (mm/day)Type 3Rainfall (mm/day)

Rainfall (mm/day)

12Type 2

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
PAGASA (9 stn)
NHRCM25

JulAugSep

NHRCM25

OctNovDec

NHRCM5_25km

APHRO25
NHRCM5_25km

AGCM60_25km

Seasonal mean bias, correlation per type (relative to APHRODITE)

DJF

0.00

increased cold bias but improved spaFal correlaFon
more areas with dry bias, minimal improvement in correlaFon

JJA
Rainfall Bias (%)

-1.00
-1.50
-2.00

1.00

Type 2DJF

Type 3Rainfall Correla,on0.75

AGCM60 NHRCM25 NHRCM5 AGCM60 NHRCM25 NHRCM5-0.25

0.50Type 1

Type 2

AGCM60Type 30.00-25.00-50.00Type 4NHRCM25

AGCM60 NHRCM25 NHRCM5 AGCM60 NHRCM25 NHRCM5Type 1

1.00

1.00

0.75

0.25

25.00

Type 4

JJA

0.50
0.25
0.00

NHRCM5JJA

50.00-75.00

AGCM60 NHRCM25 NHRCM5 AGCM60 NHRCM25 NHRCM5Type 1

DJF

75.00-0.50-2.50

Temperature Correla-on••Rainfall Correla,onTemperature Bias (°C)

NHRCM5

Type 2DJF

Type 3

Type 4JJA

0.75
0.50
0.25
0.00
-0.25

Type 1

AGCM60 NHRCM25 NHRCM5 AGCM60 NHRCM25 NHRCM5Type 1
Type 2Type 3
Type 2Type 3
Type 4

Type 4

Results: Projected temperature changes in far-future (RCP8.5)• Comparable changes regardless of resoluFon but some areas warmer in NHRCM• At end of 21st century, the Philippines (SE Asia) signiﬁcantly warmer• Consistent warming across all seasons (relaFvely high warming in MAM (summer))

AGCM60

PH: 3.13°C
SEA: 3.36°C

NHRCM25

PH: 3.30°C
SEA: 3.38°C

Annual Mean Temperature Change

NHRCM5

PH: 3.26°C

Results: Projected rainfall changes in far-future (RCP8.5)• At the end of 21st century, more areas with signiﬁcantly weZer condiFons at higher resoluFon,
parFcularly over high terrain

AGCM60

PH: 8.21%
SEA: 8.46%

NHRCM25

PH: 10.61%
SEA: 13.3%

Annual Mean Rainfall Change

NHRCM5

PH: 13.36%

Results: Projectedseasonal rainfallchanges in farfuture (RCP8.5)••••

Highest rainfall change(weZer) in DJF (dryseason in Type1, wetseason in Type2)
More drier areas in
MAM, parFcularly
eastern Luzon and central
Mindanao
Enhanced wet condiFons
in JJA in NHRCM5ContrasFng changes inMindanao between
NHRCM25 and NHRCM5
in JJA and SON

DJF

AGCM60NHRCM25

NHRCM5MAM

JJASON

Results: Projected rainfall changes in far-future (RCP8.5)•10.00Daily Rainfall Intensity
AGCM60NHRCM25

5.00
0.00
-5.00

Change in Daily Rainfall
Intensity (mm/day)Number of Rainfall Days

-10.00Type 1 Type 2 Type 3 Type 4

3.00

AGCM60NHRCM25

2.00

1.00

0.00
Type 1 Type 2 Type 3 Type 4

PHPH

95th PercenFle Rainfall
AGCM60NHRCM25

Percentage change in95th percen/le rain (%)•

Increase in wet
days, daily
rainfallintensity in
AGCM60Decrease in
number of wetdays (esp.
Type4) but
increase in
rainfallintensity (esp.
Type1) in
NHRCM25
Higher increasein extreme
rainfall in
NHRCM,
occurring overmost ofPhilippines

Change in Rainfall Days
(days/year)

•

16.00

AGCM60NHRCM25

12.00
8.00
4.00
0.00
Type 1 Type 2 Type 3 Type 4PHSummary• Results indicate applicability of NHRCM in providing high-resoluFon climate informaFon
over the Philippines and Southeast Asia
• NHRCM can reduce the wet and warm biases in ERA-Interim, and may have higher
spaFal correlaFons in some regions (e.g. Philippines, MariFme ConFnent).
• In the Philippines, NHRCM projecFons indicate signiﬁcant warming (3.3 °C) and rainfall
increases (10.6 to 13.4 %) in the far-future under RCP 8.5 scenario• Projected increase in days with extreme rainfall found over most land areas• Look into more detail on the underlying mechanisms behind the inﬂuence of model
resoluFon on the simulated climate and changes• Results of this study will contribute to the ongoing eﬀorts to increase climate change
informaFon in the region, e.g. Southeast Asia Regional Climate Downscaling/CORDEXSoutheast Asia projectThank you for your attention.

Acknowledgments• Meteorological Research InsFtute• Japan Meteorological Agency• Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan• F. Cruz was an InternaFonal Research Fellow of the Japan Society for the PromoFon of Science(JSPS)• JSPS KAKENHI Grant Number 15F15028• SOUSEI Program of the Ministry of EducaFon, Culture, Sports, Science and Technology of Japan