Paper 1: UHI from Beijing

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Paper 1: UHI from Beijing Jin, S. M. 2012: Developing an Index to Measure Urban Heat Island Effect Using Satellite Land Skin Temperature and Land Cover Observations. J. of Climate, vol 25, 6193-6201. Research Method

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Paper 1: UHI from Beijing. Research Method. Jin, S. M. 2012: Developing an Index to Measure Urban Heat Island Effect Using Satellite Land Skin Temperature and Land Cover Observations. J. of Climate, vol 25, 6193-6201. Urban Heat Island Effect (UHI). - PowerPoint PPT Presentation

Transcript of Paper 1: UHI from Beijing

Page 1: Paper 1: UHI from Beijing

Paper 1: UHI from Beijing

• Jin, S. M. 2012: Developing an Index to Measure Urban Heat Island Effect Using Satellite Land Skin Temperature and Land Cover Observations. J. of Climate, vol 25, 6193-6201.

Research Method

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Urban Heat Island Effect (UHI)

This phenomenon describes urban and suburban temperatures that are 2 to 10°F (1 to 6°C) hotter than nearby rural areas.

(1-α)Sd +LWd-εσTskin4 –SH-LE - G= 0

Because all the terms in the surface energy balance are changed in urban regions.

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What is the problem?

• What is the Approach• What is the New Finding’s contribution to UHI

research?

INTRODUCTION Section:

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MODIS Observation

Beijing

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Urbanization changes surface albedo (MODIS)

(Jin, Dickinson, and Zhang 2005, J. of Climate)

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Urbanization changes surface emissivity (MODIS)

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a. b.

c. d.

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Figure 3: Monthly mean skin temperature in July 2008 for Beijing observed by Terra daytime (10:30AM), Aqua Daytime (1:30 PM), Terra nighttime (10:30 AM) and Aqua nighttime (10:30 PM), respectively.

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a.

Aa

Figure 4a: Monthly mean skin temperature from January, April, July, and October 2008 together with July 2007 for Beijing. Land cover type (defined in Table 1) is also presented along the longitude 116°E-118°E. Data is from Terra MODIS.

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a.

b.

Figure 5: Box-plot based on April 2000 to December 2008 skin temperature observations over the 0.6°x0.6° selected box of (a) Beijing and surrounding land cover regions and (b) New York City (NYC). Total 105 monthly values are examined.The top of the box represents the 75th percentile, the bottom of the box represents the 25th percentile, and the line in the middle represents the 50th percentile (i.e., median). The whiskers (the lines that extend out the top and bottom of the box) represent the highest and lowest values that are not outliers or extreme values (Wilks 1995).

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2. Urban Aerosol Effects

• Jin, M., J. M. Shepherd, and W. Zheng, 2010: Urban Surface Temperature Reduction via the Urban Aerosol Direct Effect ------A Remote Sensing and WRF Model Sensitivity Study. Advances in MeteorologyVolume 2010 (2010), Article ID 681587, 14 pagesdoi:10.1155/2010/681587

• Jin, M. and J. M. Shepherd, 2008: Aerosol Relationships to Warm Season Clouds and Rainfall at Monthly Scales Over East China: Urban-land vs. Ocean– JGR, vol 113, D24S90, doi:10:1029/2008JD010276.

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Indirect Effect: serve as CCN

Cloud dropRain dropIce crystalIce precipitation

Aerosol Direct Effect: Scattering

0oC

surface

Aerosol reduce surface insolation

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Aerosol Distributions over Land and Ocean have evident differences

July 2005

Satellite observations Fig. 1, Jin and Shepherd 2008

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3.3 Result: Diurnal Cycle of Urban Aerosols

(Jin et al, 2005, JGR)

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Figure 2. Interannual variations of urban aerosols over land (25N–35N, 110E–120E) and the sea off China (25N–35N, 120E–130E).

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Figure 4. Scatter-plot between aerosol optical thickness and ice cloud effective radius. The data are sampled for July 2000, over the China Sea.

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3.3

(Jin and Shepherd 2008, JGR)

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Figure 5. Scatterplot between aerosol optical thickness and water cloud effective radius. The data are sampled for Julys 2000–2004, east China urban regions (20N–40N, 115E–120E).

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Figure 8. (a) Scatterplot of aerosol optical thickness and rainfall efficiency for rainfall events less than0.5 mm/d, over the China Sea. The data are sampled for July (2000–2004). The red line is a linearregression based on original 5 July observations (blue dots); and the green line is the linear regressionbased on median. Median is calculated for each 10 optical thickness data. (b) Histogram of number ofpixels as function of aerosol optical thickness.

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Conclusion

• Results from this study suggest that urban aerosols may have stronger effects on clouds than on rainfall. We found a detectable negative aerosol-cloud droplet size relation, especially over the ocean.

• Aerosols may have different effects over ocean and over land. Over ocean, aerosols show significant effects on

effective radius of liquid water clouds. There is less evidence

for effects on ice clouds. On the other hand, over land

(namely, continental areas with a large fraction of urban

surfaces), no significant aerosol effects can be detectable in

either water clouds or ice clouds.

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Uncertainty Analysis

• Using various satellite platforms to conduct research will, as always, raise concerns about the correspondence among the measurements.

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3.3 Aerosol effect on UHI

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45.5

105.5

29.2

52.8

0

20

40

60

80

100

120

January July

So

lar

Rad

iati

on

(W

m-2

)NYC

BJ

Aerosol reduction on Surface Insolation

Using Chou and Suarez’s radiative transfer model

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3.4 WRF-urban model to examine relative contributions of different physical processes

Aerosol Experiment 48-hours sensitivity study July 26-27-2810-day sensitivity study

Albedo ExperimentEmissivity Experiment Soil moistre experiment

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Aerosol Experiment for July 2008

WRF: Version 3

Domains: D1=18km; D2=6km

Case: 00Z July 26, 2008; 48-h integration

Domain Centre: 40.0N, 116.0E

Beijing City: 39”56’N, 116”20’

Aerosol Domain: 39.7 - 40.1 N; 116.1 - 116.7 E

SW reduced by 100 Wm-2

April 16, 2009

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Domains: D1=18km; D2=6km

D1

D2

Domain 2: 6km Grid spacing

Beijing City

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Soil moisture at the first soil layer (10cm)

Green Vegetation Fraction: Beijing

City Domain 2

Finer Domain

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Case: 00Z July 26, 2008; 48-h integration

Plots: from 00Z July 27 to 00Z July 28

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Cloud Water (Qc) and Water Vapor (Qv) at 850 hPa & 700 hPa

700 hPa

850 hPa

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Tsfc / T2m Diurnal change: Surface insolation reduced by 100 Wm-2

Tsfc T2m

Tsfc decreases about 2-3 degrees

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Control Run Sensitivity 00 UTC

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SensitivityControl Run 06 UTC

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12 UTCControl Run Sensitivity

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18 UTC SensitivityControl Run

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Surface flux / PBL change: Surface insolation reduced by 100 Wm-2

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Winds at 950 hPa and 850 hPa

850 hPa

950 hPa

Control Run Sensitivity

Beijing City

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WRF-urban simulated urban aerosol effects10-day simulation

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3.4 Albedo Experiment for July 2008

WRF: Version 3

Domains: D1=18km; D2=6km

Case: (1) 00Z July 25, 2008; 48-h integration

(2) 00Z July 26, 2008; 48-h integration

Domain Centre: 40.0N, 116.0E

Beijing City: 39”56’N, 116”20’

Urban Domain: 39.7 - 40.1 N; 116.1 - 116.7 E

Albedo: change from 0.15 to 0.10

April 26, 2009

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Albedo Distribution:

Albedo in Beijing city decreases from 0.15 to 0.10

06 Z, 2008-07-26

Difference of Tsfc because Albedo change

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Tsfc increases about 1 degree at mid-day

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4. Future Directions

• Simulate SF Urban System in WRF-CLM4-urban

• Study urban impacts on local agriculture, for example, wine

• Use WRF model to assess the relative importance of snow cover change over the Sierra Nevada and urbanization to the regional water resources.

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Summary

• Urbanization has significant impacts on natural climate system, and thus shall be accurately simulated to predict such impacts.

• Satellite remote sensing and regional climate model are extremely useful for understanding regional climate change.

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Thank you.