Assessing future heatwave risk change
considering climate change scenarios
Chae Yeon Park*, Dong Kun Lee*Research Institute of Agriculture and Life Science, Seoul National University

Global convection current

interaction between
local land surface & global current

Surface physical & socio-economic aspects
Adaptive capacity

Sensitivity

Extreme climate risk

Limitation of previous studies① limited considering of surface characteristics
Mora et al. 2017 (risk using climate drivers)② Index based③ hard to quantify & compare risk
spatially and temporally !
 Combine exposure and vulnerability
using not an index based method
Hoque et al. 2019 (Index based analysis)

How to assess the risks for extreme climate events Spatially & Temporally ?
RCPSSPs

𝑒𝑥𝑝𝑜𝑠𝑢𝑟𝑒 ∗ 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦
𝒓𝒊𝒔𝒌 =
𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦
land cover Connected with climate change scenario(RCP, SSPs, land cover change)
 Case study for Seoul, Korea

𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒 ∗ 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐴

𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦

Critical region

𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦

Future=Current =𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒 ∗ 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦

𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒= the number of extreme
event for sensitivity
populations per year

𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒

Climatic Impact
Low𝐴High

Area in the critical region
Current=2  Future=12

𝑬𝒙𝒑𝒐𝒔𝒖𝒓𝒆 = the day of extreme heat event per year
Extreme heat event = daily mean temperature > 98 % for 2011-2018 temp (=29.5 ℃ for Seoul)𝒔𝒆𝒏𝒔𝒊𝒕𝒊𝒗𝒊𝒕𝒚 = the sensitivity population (old and isolation)
𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒 ∗ 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦

Old: over 65 years old= the number of extreme
event for sensitivity
populations per year

Isolation: single person housing𝑨𝒅𝒂𝒑𝒕𝒊𝒗𝒆 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 : spatial capacity to reduce heat flux

Variables
1. Albedo
2. Building shadow area
3. Green area
4. Water area

Albedo, shadow

Net radiationGreen, water area

Storage heat

Latent heat
Sensible heat

𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 = ෍ 𝐸𝑓𝑓𝑒𝑐𝑡 𝑜𝑓 𝑟𝑒𝑑𝑢𝑐𝑖𝑛𝑔 ℎ𝑒𝑎𝑡 𝑓𝑙𝑢𝑥

Equation reference: Kwon et al., 2019𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦

𝐵 (𝑎𝑑𝑎𝑝𝑡𝑎𝑡𝑖𝑜𝑛 𝑝𝑜𝑖𝑛𝑡)

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝑖𝑚𝑝𝑎𝑐𝑡
𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦= Risk considering
adaptive capacity(=how much the spatial
characteristics canreduce urban heat)

Low impact
High adaptive

High impact
High adaptive

Low impact
Low adaptive

High impact
Low adaptive

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝑖𝑚𝑝𝑎𝑐𝑡
𝐴 (𝑐𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑝𝑜𝑖𝑛𝑡)

High risk areas

Current

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝑖𝑚𝑝𝑎𝑐𝑡
𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦= Risk considering
adaptive capacity

Future𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦𝑎𝑑𝑎𝑝𝑡𝑖𝑣𝑒𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦

𝐵𝐵

𝐴

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝑖𝑚𝑝𝑎𝑐𝑡

High Risk areas = 1

Case study  𝐴 ∶ 2,000 people ∗ days/yearB ∶ 50 % of adaptive capacity values

𝐴𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝑖𝑚𝑝𝑎𝑐𝑡

High Risk areas = 5

Case study Seoul 1km resolution
 RCP 4.5 & 8.5
 SSP 3 & 5

Base: RCP 4.5 & SSP 3
Assess spatial exposure, sensitivity, and adaptive capacity of Seoul

Spatial exposure & risk variation by RCPs
2040s
2090s

Spatial sensitivity & risk variation by SSPs

Spatial adaptive capacity & risk variation bySample land cover change

Case study
Results
 Base scenario
 RCP 4.5 & SSP 3

2041-2050

Exposure(day/year/㎢)

Sensitivity(people/㎢)

Adaptive capacity(W/㎡)

2091-2100

legendCase study
Results
 Base scenario

2041-2050

2091-2100

Exposure*sensitivity

 RCP 4.5 & SSP 3

Exposure*sensitivity/ adaptive capacity

N=66
High risk area
(red)

N=152

Case study
Results

2041-2050

 High exposure
scenario(change exposure) RCP 8.5 & SSP 3

Exposure(day/year/㎢)

2091-2100

legendCase study
Results

2041-2050
N=66

 High exposure
scenario(change exposure)2091-2100

legend

N=152
H-H
L-H

 RCP 8.5 & SSP 3

L-L

H-L

High riskarea(red)

impactadaptation

N=188

N=238

Case study
Results

2041-2050

 High population
scenario(change sensitivity)
 RCP 4.5 & SSP 5

Sensitivity(people/㎢)

2091-2100

legendCase study
Results

2041-2050
N=66

 High population
scenario(change sensitivity)

2091-2100

legend

N=152
H-H
L-H

 RCP 4.5 & SSP 5

L-L

H-L

High riskarea(red)

impactadaptation

N=83

N=206

Case study
Results
 Land cover changescenario(change adaptivecapacity)“MOTIVE (impact model)”land cover change scenario

 RCP 4.5 & SSP 3( prediction for 2050s, regarding minimizing future disasters & maximizing economical efficiency)

Case study
Results

2041-2050
N=66

2091-2100

legendN=152

 Land cover changescenario(change adaptivecapacity)

H-H
L-H
L-L

 RCP 4.5 & SSP 3

H-LHigh riskarea(red)impactadaptation

N=54

N=106

Conclusions① RCP 8.5 and SSP 5 increase exposure and sensitive population
 increase high risk area
② Predicted land cover (in the impact model) increase adaptive capacity of outskirt area
 decrease high risk area
③ The model finds out spatial and temporal variations of risk
 help consider equity, develop adaptation plan when the large increase of exposure is expected, we need to increase adaptive capacity④ Integrate other sectors (land cover change) with heat wave risk

Limitations and future works① Selecting threshold needs more scientific evidence (heat death data …)② Climate drivers: air temperature + humidity③ Applying this model to other climate risks (drought risk, flood risk …): explore adaptive capacity variables for each risk in the regional ~ national scale

Thank you
Chae yeon park: chaeyeon528@snu.ac.kr