Simulate Urban-induced Climate Change Via EOS Observations and Land Surface Model Dr. Menglin Jin, Meteorology Dept, U University of Maryland, College.

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Presentation transcript:

Simulate Urban-induced Climate Change Via EOS Observations and Land Surface Model Dr. Menglin Jin, Meteorology Dept, U University of Maryland, College Park Dr. Christa D. Peters-Lidard NASA GSFC Acknowledgements – Funded by NASA EOSIDS and NASA GSFC DDF December 2003

Outline: 1.Rationale and Objectives 2.How to simulate urban 3.Observed Modifications of Urbanization Regions 4.Model Results for urban physical processes 5.Summary and future direction Dr. Menglin Jin Univ. of Maryland, College Park

1. Rationale and Objectives Dr. Menglin Jin Univ. of Maryland, College Park Basic idea: Optimally combine satellite data into urban model. Satellite observations can help (a) better identify urban features and (b) improve model’s surface parameters Problem: Land surface models coupled for GCM or regional models, do not simulate urban. For example, NCAR Community Land Model (CLM), NASA land model, GSFC land surface model, etc Needs: Need to know what is urban how to simulate urban Simulating urbanization in GCM/RCM is important to understand, project, and predict urban impacts on climate change Objectives: Develop urban scheme in land surface model

Dr. Menglin Jin Univ. of Maryland, College Park Question 1: Is urban region important enough for us to simulate in a GCM? (a) Is urban region big/significant enough? (b) Are urban physical processes unique enough? Question 2: How to simulate urbanization?

Dr. Menglin Jin Univ. of Maryland, College Park Human Density of 1998 (Source: Ame. Association for the Advancement of Science)

1000 household can make T air higher about 2ºC than surround regions (Oke, 1976, Torok et al. 2002) MODIS Observed Urban and Built-up

Dr. Menglin Jin Univ. of Maryland, College Park (1-α)S d +LW d -εσT skin 4 +SH+LE + G= 0 2. How to Simulate Urban? Land Surface Energy Budget:

Dr. Menglin Jin Univ. of Maryland, College Park (1-α)S d +LW d -εσT skin 4 +SH+LE + G= 0 2. How to Simulate Urban? Urbanization Modifies Surface Energy Budget:

Dr. Menglin Jin Univ. of Maryland, College Park (1-α)S d +LW d -εσT skin 4 +SH+LE + G= 0 2. How to Simulate Urban? Urbanization Modifies Surface Energy Budget: Urban add new physical processes

50km 3.1 Urbanization changes surface temperature (T skin ) Urban heat island effect Daytime Nighttime 50km MODIS

Dr. Menglin Jin Univ. of Maryland, College Park 3.2 MODIS Observed Global urban heat island effect

Comparison of skin temperature for urban and nearby forests MODIS Cities have higher T skin than forests

Dr. Menglin Jin Univ. of Maryland, College Park 3.3 Urbanization changes surface albedo (MODIS)

The decrease of urban albedo is mainly caused by the decrease of reflectance at NIR NIR VIS Albedo Urban region

3.4 Urbanization changes surface emissivity (MODIS) 50km

Zonal Averages from MODIS Urban albedo is lower than that of cropland Urban emissivity is lower than that of cropland

Dr. Menglin Jin Univ. of Maryland, College Park 3.5. Urbanization changes atmospheric conditions MODIS Aerosol Optical Depth

Total solar radiation decreased by aerosol = 20Wm-2 (Based on model of Ming-Dah Chou of NASA GSFC) Aerosol decreases surface insolation

Dr. Menglin Jin Univ. of Maryland, College Park (1-α)S d +LW d -εσT skin 4 +SH+LE + G= 0 SH, LE, and G cannot be directly observed from satellite. Need to use model framework to examine their changes.

Dr. Menglin Jin Univ. of Maryland, College Park Conceptual NCAR CLM-Urban Model Urban model type: water Bare soil Original trees Road/Building roofs Suburban Human-grass Urban-water body If land cover Is urban yn Existing CLMUrban scheme

Dr. Menglin Jin Univ. of Maryland, College Park Use MODIS observed surface properties into model

Dr. Menglin Jin Univ. of Maryland, College Park MODIS15_A2 Leaf Area Index (LAI) over Houston regions

Dr. Menglin Jin Univ. of Maryland, College Park MODIS11_L2 Emissivity_BAND 32 over Houston regions

Dr. Menglin Jin Univ. of Maryland, College Park Table for properties modified for Case 1 run variableControl runCase1 run LAI Albedo-shortwave Albedo-visible emissivity Heat capacity Soil moisture Control run – 0.25 Control run – *control run Set as zero at first layer

4. CLM-urban model results Urban increase ground temperature by 1-3ºC, with the largest increase occurring at local daytime Ground Temperature

4.2 CLM-urban model results Urban increases land surface 2m surface air temperature, at a lower rate than its effects on ground temperature/skin temperature maximum at nighttime! Surface air temperature

4.3 Urban Model Results Urban absorbs more Solar radiation Absorbed Solar Radiation

4.3 CLM-Urban Model Results Urban increase of SH can be as high as 15Wm -2, with maximum at local afternoon.

4.3 CLM-Urban Model Results Urban increase upward longwave radiation

4.3 CLM-Urban Model Results Urban reduces ground flux

Dr. Menglin Jin Univ. of Maryland, College Park Summary 1.Satellite observations are extremely useful for understanding and simulating urbanization in climate models. 2. Urbanization needs to be included in GCM’s land surface model, in order to accurately reflect human impacts on global land climate system. 3. We need more accurate urban land cover, building density, and population information for simulating urban in global and regional scales.