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Multi-Layer RT Modeling� �: Clear-Sky, Wildfire, Geo-Engineering Methods를 중심으로

오유신, 이윤성, 변형준, 강동원

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1. Modeling

- Assumptions

- RT Equations

- Temperature Change Rate Differential Equations

- Finite Difference Method (FDM | 유한차분법)

2. Scenario

- Two-layer

- Clear Sky

- Black Carbon from Wildfires

- Artificial Emission of Black Carbon

3. Results

목차

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  1. Schwartzchild’s Equation (대기에서 지표에서의 SW 반사를 제외한 그 어떤 종류의 반사도 일어나지 않는다고 가정)
  2. 대기는 수평 운동하지 않음�→ 따라서 대기에서 잠열 과정은 일체 고려하지 않고 오직 복사만을 대기와 지표 온도를 바꾸는 유일 Forcing으로 고려�→ 대기의 수직 운동의 경우 ‘단열 과정’은 고려하되 속도는 충분히 느리다고 가정
  3. 기온이 변화하더라도 각 층에서의 대기 밀도는 변화하지 않는다고 가정
  4. Plane-Parallel Approximation

1. Modeling-Assumptions

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  •  

1. Modeling-Assumptions

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  •  

1. Modeling-Assumptions

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1. Modeling-RT Equations: Atmosphere

surface

(j)th layer

(j+1)th layer

(j-1)th layer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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1. Modeling-RT Equations: Atmosphere

surface

(j)th layer

(j+1)th layer

(j-1)th layer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

지표로부터 반사된 직후

지표에서 방출된 lw flux

 

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1. Modeling-RT Equations: Surface

surface

 

 

 

 

 

 

 

 

 

 

 

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1. Temperature Change Rate Differential Equations: Atmosphere

surface

(j)th layer

(j+1)th layer

(j-1)th layer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Thermodynamic Equation of Atmosphere �(Unit Mass)

 

 

 

 

… Ideal Gas Law

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1. Temperature Change Rate Differential Equations: Surface

 

 

 

 

 

surface

 

 

 

 

 

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Finite Difference Method (FDM, 유한차분법)

 

 

 

 

 

 

 

x

x

 

 

 

 

〈연속적인 미분방정식〉을 〈단순 산술 방정식〉으로 근사하여(=차분화하여) 초기 조건이 주어졌을 때 미분방정식의 근사해를 계산하는 방법

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Finite Difference Method (FDM, 유한차분법)

〈연속적인 미분방정식〉을 〈단순 산술 방정식〉으로 근사하여(=차분화하여) 초기 조건이 주어졌을 때 미분방정식의 근사해를 계산하는 방법

 

 

 

 

 

 

 

 

 

 

…

 

x

 

 

 

x

 

 

x

x

x

x

x

x

x

x

x

Forward Euler Method

Backward Euler Method, Trapezoidal Method, Runge-Kutta Method (4th order)

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SMART (Single-column Multi-layered Atmospheric Radiative Transfer) Model

https://github.com/stevenoh0908/SMART/tree/main

Open to the Public via Github

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Scenario(1) Clear Sky

Altitude(km)

Temperature(K)

Density(kg/m3)

Longwave

Absorptivity

Shortwave

Absorptivity

0~5

271.9

0.980558

0.68

0.1119

5~10

239.4

0.574412

0.43

0.0262

10~15

219.9

0.303191

0.2

0.00636

15~20

216.65

0.140854

0.1

0.00632

20~25

219.15

0.063750

0.06

0.00628

25~30

224.15

0.028739

0.03

0.00736

30~35

231.85

0.013113

0.02

0.00731

35~40

244.05

0.006032

0.01

0.00725

40~45

258.05

0.002866

0.005

0.00720

45~50

267.85

0.001429

0.0025

0.00715

Properties of the clear sky

Miskolczi, (2010)

Ollila, A. (2015)

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Scenario(2) Black Carbon from Wildfires

Altitude(km)

BC Concentration (No Fire)

(ng/m³)

BC Concentration (Post-Fire) (ng/m³)

Shortwave Absorptivity

(No Fire)

Shortwave Absorptivity

(Post-Fire)

0~5

200

400

0.123371

0.134693

5~10

117.1601

234.3203

0.033588

0.040919

10~15

61.8404

1236.808

0.010346

0.083115

15~20

28.72945

143.6472

0.008174

0.015555

20~25

13.00287

26.00574

0.00712

0.007958

25~30

5.861734

11.72347

0.007738

0.008116

30~35

2.674581

5.349162

0.007483

0.007655

35~40

1.230415

1.230415

0.007329

0.007329

40~45

0.584596

0.584596

0.007238

0.007238

45~50

0.29155

0.29155

0.007169

0.007169

Ohata, S., et al. (2021)

Popovicheva, O. B., et al. (2022).

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Scenario(2) Black Carbon from Wildfires

Phase 1. 산불 발생 직후

Phase 2. 산불 발생 후 오랜 시간 경과

Altitude(km)

Shortwave Absorptivity

(Post-Fire)

0~5

0.134693

5~10

0.040919

10~15

0.083115

15~20

0.015555

20~25

0.007958

25~30

0.008116

30~35

0.007655

35~40

0.007329

40~45

0.007238

45~50

0.007169

Altitude(km)

Shortwave Absorptivity

(Long After Fire)

0~5

0.12337

5~10

0.03359

10~15

0.083115

15~20

0.015555

20~25

0.007958

25~30

0.008116

30~35

0.007655

35~40

0.007329

40~45

0.007238

45~50

0.007169

Shortwave Absorptivity

(No Fire)

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Scenario(2) Black Carbon from Wildfires

(1) A = 0.3 (average albedo of Earth)

(2) A = 0.2 (concrete albedo)

(3) A = 0.12 (woodland albedo)

(4) A = 0.08 (oceans albedo)

(5) A = 0

Phase 1. 산불 발생 직후

(1) A = 0.3 (average albedo of Earth)

(2) A = 0.2 (concrete albedo)

(3) A = 0.12 (woodland albedo)

(4) A = 0.08 (oceans albedo)

(5) A = 0

Phase 2. 산불 발생 후 오랜 시간 경과

Albedo values of Different Surface Types

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Scenario(3) Artificial Emission of Black Carbon

0

10km

15km

61.84

ng/m3

309.202

ng/m3

618.404ng/m3

 

5배

10배

n배

?

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Conclusion(1) Model Verification-2 Layer Model

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Conclusion(1) 모델 검증-Clear Sky

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Conclusion(2) Black Carbon From Wildfires

1. 대류권 계면에서 온도가 20K 가량 크게 증가

-> 새로운 역전층

​

​

2. 지표 온도가 2K가량 감소

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Conclusion(2) Black Carbon From Wildfires

1. 역전층은 조건에 관계없이 형성

​

2. 알베도 감소에 따른 경향성의 차이

하부-온도 증가

상부-온도 감소

A. 지표 알베도 B. 산불 후 시간

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Conclusion(2) Black Carbon From Wildfires

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Conclusion(2) Black Carbon From Wildfires

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Conclusion(3) Artificial Emission of Black Carbon

 

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Conclusion(3) Artificial Emission of Black Carbon

2,236,800,000Kg

=

=

X 6500000

X 25000

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참고자료

Miskolczi, F. (2010). Greenhouse Effect and the IR Radiative Structure of the Earth's Atmosphere. *International Journal of Environmental Research and Public Health, 7*(1), 1-x. https://doi.org/10.3390/ijerph70x000x

​

Ollila, A. (2015). Clear sky absorption of solar radiation by the average global atmosphere. Journal of Earth Sciences and Geotechnical Engineering, 5(14), 19-34. ISSN: 1792-9040 (print), 1792-9660 (online). Scienpress Ltd.

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Popovicheva, O. B., Evangeliou, N., Kobelev, V. O., Chichaeva, M. A., Eleftheriadis, K., Gregorič, A., & Kasimov, N. S. (2022). Siberian Arctic black carbon: Gas flaring and wildfire impact. Atmospheric Chemistry and Physics, 22(10), 5983-6004. https://doi.org/10.5194/acp-22-5983-2022

​

Veira, A., G. Lasslop, and S. Kloster (2016), Wildfires in a warmer climate: Emission fluxes, emission heights, and black carbon concentrations in 2090–2099, J. Geophys. Res. Atmos., 121, 3195–3223, doi:10.1002/2015JD024142.

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