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, Research Method

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-εσTskin 4 –SH-LE - G= 0 Because all the terms in the surface energy balance are changed in urban regions.

What is the problem? What is the Approach What is the New Finding’s contribution to UHI research? INTRODUCTION Section:

MODIS Observation Beijing

Urbanization changes surface albedo (MODIS) (Jin, Dickinson, and Zhang 2005, J. of Climate)

Urbanization changes surface emissivity (MODIS)

a.b. c.d.

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.

A a 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.

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).

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 , 14 pagesdoi: /2010/ 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:10:1029/2008JD

Indirect Effect: serve as CCN Cloud drop Rain drop Ice crystal Ice precipitation Aerosol Direct Effect: Scattering surface Aerosol reduce surface insolation

Aerosol Distributions over Land and Ocean have evident differences July 2005 Satellite observations Fig. 1, Jin and Shepherd 2008

3.3 Result: Diurnal Cycle of Urban Aerosols (Jin et al, 2005, JGR)

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

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

3.3 (Jin and Shepherd 2008, JGR)

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).

Figure 8. (a) Scatterplot of aerosol optical thickness and rainfall efficiency for rainfall events less than 0.5 mm/d, over the China Sea. The data are sampled for July (2000–2004). The red line is a linear regression based on original 5 July observations (blue dots); and the green line is the linear regression based on median. Median is calculated for each 10 optical thickness data. (b) Histogram of number of pixels as function of aerosol optical thickness.

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.

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

3.3 Aerosol effect on UHI

Aerosol reduction on Surface Insolation Using Chou and Suarez’s radiative transfer model

3.4 WRF-urban model to examine relative contributions of different physical processes Aerosol Experiment 48-hours sensitivity study July day sensitivity study Albedo Experiment Emissivity Experiment Soil moistre experiment

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: N; E SW reduced by 100 Wm-2 April 16, 2009

Domains: D1=18km; D2=6km D1 D2 Domain 2: 6km Grid spacing Beijing City

Soil moisture at the first soil layer (10cm) Green Vegetation Fraction: Beijing City Domain 2 Finer Domain

Case: 00Z July 26, 2008; 48-h integration Plots: from 00Z July 27 to 00Z July 28

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

Tsfc / T2m Diurnal change: Surface insolation reduced by 100 Wm-2 TsfcT2m Tsfc decreases about 2-3 degrees

Control RunSensitivity 00 UTC

SensitivityControl Run 06 UTC

12 UTC Control RunSensitivity

18 UTC SensitivityControl Run

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

Winds at 950 hPa and 850 hPa 850 hPa 950 hPa Control RunSensitivity Beijing City

WRF-urban simulated urban aerosol effects 10-day simulation

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: N; E Albedo: change from 0.15 to 0.10 April 26, 2009

Albedo Distribution: Albedo in Beijing city decreases from 0.15 to Z, Difference of Tsfc because Albedo change

Tsfc increases about 1 degree at mid-day

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.

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.

Thank you.