# Presentation: 889410

## Detect and Simulate Urban Climate Change

**Detect and Simulate Urban Climate Change**
**Via**
**    ****EOS Observations and Land Surface Model**

***Dr. Menglin Jin, ***
***Department of Meteorology***
***University of Maryland, College Park***
***Dr. Christa D. Peters-Lidard***
***NASA GSFC***

- Acknowledgements – Funded by NASA EOSIDS and NASA DDF

- April 20,  2004,

## Outline:

_***Outline:***_
**Rationale and Objectives**
**Observed Modifications of Urban Regions**
**Skin Temperature**
**Surface Albedo**
**Surface Emissivity**
**Aerosol and Clouds**
**Description of urban model**
**Model Results**
**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

_**Current Problem:**__** **_Land surface schemes in the leading GCM/regional
- 	     models do not include urban landscape. For example,
- 	    NCAR Community Land Model (CLM), NASA land model,
- 	    NCEP land surface model, etc

_** **__**Needs:**_ Need to know _*what is urban*_
- 			_*how to simulate urban*_

_**Objectives**_: **Develop urban scheme in land surface model**

## Question 2: How to simulate urbanization?

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- Question 1: Is urban region important enough for us to
- simulate it specifically in a land surface scheme?

- (a) Is urban region big enough?
- (b) Are urban physical processes unique enough?

## Human Density of 1700

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

**Human Density of 1700**

- (Source: Ame. Association for the Advancement of Science)

## Human Density of 1800

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

**Human Density of 1800**

- (Source: Ame. Association for the Advancement of Science)

## Human Density of 1900

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

**Human Density of 1900**

- (Source: Ame. Association for the Advancement of Science)

## Human Density of 1998

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

**Human Density of 1998**

- (Source: Ame. Association for the Advancement of Science)

## MODIS Observed Urban and Built-up

- 1000 household can make Tair higher about 2oC than surroundings
-                (Oke, 1976, Torok et al. 2002)

##        (1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

-        (1-_α_)_S__d_ +_LW__d_-_ε_σ_T__skin_4 +_SH_+_LE_ + _G_= 0

- Question 1. Is Urban region important enough for us to
- simulate it a GCM?

- Land Surface Energy Budget:

- As an extreme case of land cover and land use changes, urban region:

- modifies surface and atmospheric properties, and thus

-       changes heat, water, and momentum transports
- 2.   Adds new  surface physical processes into original existing,
-       natural physical processes

##        (1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

-        (1-_α_)_S__d_ +_LW_d-_ε_σ_T__skin_4 +_SH_+_LE_ + _G_= 0

- 2. How to Simulate Urban?

- Urbanization Modifies Surface Energy Budget:

***Urban adds new physical processes:***

- Storage term,
- Anthropogenic flux
- Modified roughness length
- Canyon effect

## Dr. Menglin Jin 			Univ. of Maryland, College Park

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- Canyon effect

- Radiation attenuation

- Turbulence production

- Radiation trapping

**Canopy heating & cooling**

- Urban thermal properties

## 50km

- Nighttime

**50km**

**50km**

***MODIS***

- Jin et al. 2004, submitted to J. of Climate

## 3.2 MODIS Observed Global urban heat island effect

***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 Tskin
- than forests

## 3.3 Urbanization changes surface albedo (MODIS)

***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 urban albedo is mainly caused by ***
***the decrease of reflectance at NIR***

- NIR

- VIS

- Albedo

- Urban region

## urban

- Spectral Albedo, January 2001, courtesy M. King

- Urban albedo lower than cropland

**urban**

## Evident seasonality is observed on urban albedo

- Seasonality of urban Albedo,
- 				*courtesy M. King*

- July

- January

## 3.4 Urbanization changes surface emissivity (MODIS)

- 3.4 Urbanization changes surface emissivity (MODIS)

**50km**

**50km**

## Zonal Averages from 	MODIS

- Zonal Averages from 	MODIS

***Urban albedo is lower than ***
***that of cropland***

***Urban emissivity is lower ***
***than that of cropland ***

## 3.5. Urbanization changes atmospheric conditions

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- MODIS Aerosol Optical Depth

## Interannual variation of 

- Interannual variation of
- Aerosol optical depth

## Diurnal variation of aerosol from EPA PM2.5

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

## MODIS Seasonal variation of urban aerosol							

- MODIS Seasonal variation of urban aerosol

- Houston

- Jin, Shepherd, and King 2004

## Houston

- Jin, Shepherd, and King 2004

##  Aerosol decreases surface insolation

- Total solar radiation decreased by aerosol
- = 20Wm-2

- (Based on model of Ming-Dah Chou of NASA GSFC)

** ****Aerosol decreases surface insolation**

## (1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- (1-_α_)_S__d_ +_LW_d-_ε_σ_T__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.

## Conceptual Urban Model

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

**Conceptual Urban Model**

_**Urban model type:**_

- Urban Canyon
- Suburban
- Human-grass
- Roads

- Is land cover
- urban

- n

- y

- Existing CLM

- Urban scheme

## Model Design--- Two Steps:

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

_**Model Design--- Two Steps:**_
- Modify Physical Parameters which are changed for urban regions:
- 1). Albedo,
- 2). Emissivity
- 3). LAI,
- 4). Heat capacity
- 5). Thermal conductivity
- 6). Hydro-conductivity

- 2. Modify physical process:
- 	1). Anthropogenic heat flux (follow Voogt and Grimmond 2000)
- 	2). Storage heat flux
- 	3). Roughness length
- 	4). Momentum changes by buildings

## Model Design ---Two Steps:

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

_**Model Design ---Two Steps:**_
- Modify Physical Parameters which are changed for urban regions:
- 1). Albedo,
- 2). Emissivity
- 3). LAI,
- 4). Heat capacity
- 5). Thermal conductivity
- 6). Hydro-conductivity

- 2. Modify physical process:
- 	1). Anthropogenic heat flux (follow Voogt and Grimmond 2000)
- 	2). Storage heat flux
- 	3). Roughness length (Follow Grimmond and Oke 2002)
- 	4). Momentum changes by buildings (not implemented yet)

- MODIS

## Dr. Menglin Jin 			Univ. of Maryland, College Park

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- Use MODIS observed surface properties into model

## Dr. Menglin Jin 			Univ. of Maryland, College Park

***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

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- MODIS11_L2 Emissivity_BAND 32 over Houston regions

## Model Design Two steps:

_**Model Design Two steps:**_

- 2. Modified physical processes:
- 	1). Anthropogenic heat flux (Qf)

- 	Qf(hour) = Qf0 {1-0.6*cos(π*(hour-3)/12)}
- 		Qf0 = 62.5W/m2 in January
- 		Qf0 =37.5W/m2 in July

- 2.) Storage term (ΔQs)

- ΔQs = Σ(aiQ*+biQs+ci)Ai
- 	a,b,c are experical coefficients corresponding
- 	to surface type
- 	Ai – surface areas for each urban land surface type
- 	Q* - net radiation radiation
- 	Qs –absorbed surface solar radiation

- Following Voogt and Grimmond 2000

- Adopted from Arnfield and Grimmond 1998

## New Physical Processes (cont.)

_**New Physical Processes (cont.)**_

- 3). Roughness Length (rub), Building impact on momentum calculation

## Complex Surface Parameters -Some Background Literature

- Earliest study – U Wisc. MS thesis of John Kutzback, 1961– studies effect on surface roughness of density of objects that were bushel baskets placed on frozen Lake Mendota
- Mike Raupach1992,1994  formulates theoretically the issue of partitioning of stress between smooth and such roughness objects- relates roughness length and displacement height to fractional area of obstacles normal to wind direction
- Linroth, 1993, identifies LAI as contributing to tree effect
- MacDonald et al, 1998, formulates modified version for buildings

*(Copied from R. Dickinson Fall AGU 2003 urban session invited talk)*

## Key Elements

- Uh = wind at the top of the canopy
- Cd = drag coefficient ,such that the overlying atmosphere loses  = *** Cd U**h** **2* of momentum to the complex canopy
- where *** *= effective frontal area density
- But  sqrt(*** Cd )  =  *0.4* / log(( h – d)/ z**0 **) *from the simple relationship between logarithmic wind profile and momentum transfer, which is inverted to get *z**0 **/ (h –d )*

*(Copied from R. Dickinson Fall AGU 2003 urban session invited talk)*

## Resolution of  Roughness Issues

- McDonald scaling likely ok if modified to include reduction by leaf area factor for vegetation
- Raupach expression for d/h should be modified to allow for eddy sheltering (i.e. wake vortices of building only interact over the area not covered by building so that d should become h as structures become a single  building  - however for closed canopy, this is between 0.7 and 0.85 h depending on crown-aspect ratio

*(Copied from R. Dickinson Fall AGU 2003 urban session invited talk)*

## Table for properties modified  for Case 1 run

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- 1.5

- 0.5

- Control run – 0.25

- Control run – 0.15

- 0.92

- 0.96

- 1.5*control run

- Set as zero at first layer

## 4. CLM-urban model results

**Urban increase ground temperature**
**by 1-3****o****C, 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

## 4.4 Single Column NCAR SCAM-CLM-Urban Model

- Beijing

## 4.4 SCAM/CLM2/urban-scheme Results 	Beijing

- 4.4 SCAM/CLM2/urban-scheme Results 	_*Beijing*_

- Sep. 1998

**LE**

## 4.4 Single Column NCAR CAM-CLM-Urban Model

** ****Houston**

## 4.4 SCAM/CLM2/urban-scheme Results

**LE**

## Summary

***Dr. Menglin Jin ******	******	******	******Univ. of Maryland, College Park***

- Satellite observations are extremely useful for understanding and
- 	 simulating urbanization in climate models.

- 2.  Urbanization scheme is needed in GCM/RCM’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.