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METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University [email protected]

METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University [email protected]

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Page 1: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban

Menglin Jin, Professor Department of Meteorology

San Jose State [email protected]

Page 2: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

http://www.usgcrp.gov/usgcrp/images/ocp2003/ocpfy2003-fig3-4.htm

The past, present and future of climate models

During the last 25 years, different components are added to the climate model to better represent our climate system

Page 3: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Climate Model:

Equations believed to represent the physical, chemical, and biological processes governing the climate system for the scale of interest

It can answer “What If” questionsfor example, what would the climate be if CO2 is doubled?

what would the climate be if Greenland ice is all melt?what………………………..if Amazon forest is gone?what…………………………if SF bay area

population is doubled?

Page 4: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Three Ways to Use Remote Sensing for Climate Model

• Satellite observed parameters, for example, albedo, vegetation, cloud droplet size

• Study climate process/feedback

• Evaluate Model Outputs

Page 5: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Climate Model (per NASA Earth Observatory Glossary http://earthobservatory.nasa.gov/Library/glossary.php3?mode=alpha&seg=b&segend=d )

A quantitative way of representing the interactions of the atmosphere, oceans, land surface, and ice.

Models can range from relatively simple to quite comprehensive.

Definition

Model components

Page 7: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

MODIS image for Chen Du, China –satellite provides high resolution information on land cover, temperature, albedo, vegetation, aerosol, etc

An application: Urbanization - the satellite view

Page 8: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Night Light of Tokyo

data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS)

Page 9: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Night Light of Paris

Page 10: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

pictures made by U.S. Defense Meteorological Satellites Program (DMSP)

Page 11: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Importance of land surface skin temperature (Tskin)

Land Skin Temperature is a good indicator of the energy balance at the Earth’s surface and the so-called greenhouse effect because it is one of the key parameters in land-surface processes at local, regional as well as global scales [Jin and Dickinson 2002].

The skin temperature used in calculating heat fluxes and radiation:F↑ = εσTskin

4 Eq. (1)SH = CDHU(Taero-Ta) Eq. (2)LE =CDEU(qTskin*-qa) Eq. (3)

(1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

Page 12: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

We use NASA EOS and NCAR Climate Model to examine the urbanization effects, in particular,

urban pollution

urban heat island effect (UHI)

Page 13: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

50km

Urban heat island effectDaytime Nighttime

50km 50km

MODIS

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

Page 14: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Table 1: MODIS land cover table

Land Cover Type (LC)

1 Evergreen Needleleaf Forest

2 Evergreen Broadleaf Forest

3 Deciduous Needleleaf Forest

4 Deciduous Broadleaf Forest

5 Mixed Forest

6 Closed Shrubland

7 Open Shrubland

8 Woody Savannas

9 Savannas

10 Grassland

11 Permanent Wetland

12 Croplands

13 Urban and Built-Up

14 Cropland/Narural Vegetation Mosaic

15 Snow and Ice

16 Barren or Sparsely Vegetated

Page 15: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

MODIS Observation

Beijing

Page 16: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu
Page 17: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

(Jin, Dickinson, et al. 2005)

MODIS Observed Global urban heat island effect

Page 18: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Comparison of skin temperaturefor urban and nearby forests

MODIS

Cities have higher Tskin

than forests

Page 19: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Urbanization changes surface albedo (MODIS)

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

Page 20: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Urbanization changes surface emissivity (MODIS)

Page 21: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Use MODIS observed surface properties into model

Page 22: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

MODIS11_L2 Emissivity_BAND 32 over Houston regions

Note: emissivity is missing over Houston urban regions, but available from monthly regions

Page 23: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

MODIS15_A2 Leaf Area Index (LAI) over Houston regions

Note: on daily product, LAI over Houston regions is missing, but available from monthly data

Page 24: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Physical Processes for UHI:

(1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

On Urban system:

(1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

All underlined terms are changed!

The Land Surface Energy Balance

Page 25: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Urban Aerosol Effects

•Change atmosphere conditions to form clouds and rainfall

•Change surface insolation -> reduce urban surface temperature

Page 26: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Indirect Effect: serve as CCN

Cloud dropRain dropIce crystalIce precipitation

Aerosol Direct Effect: Scattering

0oC

surface

Aerosol reduce surface insolation

Page 27: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Aerosol Distributions over Land and Ocean have evident differences

July 2005

Satellite observations

Page 28: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

NASA Aeronet Sites

http://aeronet.gsfc.nasa.gov/Ames has on of this site!

Page 29: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Aerosol effect on UHI

Page 30: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

AERONET, New York EPA

Scale, Scale, Scale!! Jin, Shepherd, King 2005 JGR

Page 31: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Total solar radiation decreased by aerosol= 20Wm-2

(Jin, Shepherd, and King, 2005, JGR)

Aerosol decreases surface insolation

Based on M-D. Chou’s radiative transfer model

Page 32: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

4.3

Jin and Shepherd, 2008, JGR

Page 33: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Urban system vs rainfall

• “Cities impact rainfall and can create their own rain and storms,” Marshall Shepherd explains.

• You need three basic ingredients for clouds and rainfall to develop, “

• air unstable - air lifting• CCN• moisture

Does urban have these?

Page 34: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Urban vs. Rainfall

• New Paper “The Impact Of Urbanization On Current And Future Coastal Precipitation: A Case Study For Houston” By Shepherd Et Al 2010

http://www.envplan.com/abstract.cgi?id=b34102t

Page 35: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Video

• http://www.met.sjsu.edu/metr112-videos/MET%20112%20Video%20Library-MP4/urban%20system/

Page 36: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Use satellite data to represent urban

Page 37: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Existing Coupled Land-Atmosphere Models:Coarse Resolution, Biogeophysics Focus

BARE SOIL: 15%

10%

GRASSLAND:50%

SHRUBS:

NEEDLELEAFTREES: 25%

e.g., CLM: (NCAR, DAO) NOAH: (NCEP)

Turbulence production

Urban thermal properties

Radiation trapping

Radiation attenuation

Canopy heating & cooling

Page 38: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Conceptual UMD-NASA CLM-Urban Model

Bare soilRoadBuilding roofs SuburbanHuman-grassOriginal treesUrban-water body

CLM original type:

Vegetation covered regions

Bare soil regions

CLM-urban model:

Surface type structure

water

Bare soil

Urban modifies: LAI, albedo, emisisivity, heat capacity, soil moisture, roughness length, etc

(Jin et al. 2006)

Page 39: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Physical Processes for UHI:

(1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

On Urban system:

(1-α)Sd +LWd-εσTskin4 +SH+LE + G= 0

All underlined terms are changed!

The Land Surface Energy Balance

Page 40: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

CAM3/CLM3-Urban Model Results

Page 41: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Model results

Page 42: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Model results

Net longwave radiation

Page 43: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Model results

Page 44: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

3 Km5/9/2011, 8 PM

MODIS land cover

WRF-urban

Page 45: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

WRF 1km 5/5/20115 PM

Page 46: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

6 PM, 5/5/2011

Page 47: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

7 PM, 5/5/2011

Page 48: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

5 PM, 5/6/2011

Page 49: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

7 PM, 5/6/2011

Page 50: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

9 PM, 5/6/2011

Page 51: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

11 PM, 5/6/2011

Page 52: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

1 AM, 5/7/2011

Page 53: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

3 AM, 5/7/2011

Page 54: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

5 AM, 5/7/2011

Page 55: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

8 AM, 5/7/2011

Page 56: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

10 AM, 5/7/2011

Page 57: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Evaluation of WRF-urban, MODIS

Page 58: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Class participation

• Why urban albedo is reduced?

• What is uncertainty of remotely sensed albedo over urban regions?

Page 59: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

NASA “Mission to measurements”

Page 60: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Nadir UV/vis Satellite instruments

GOME-2• similar to GOME• launched 10.06• 80 x 40 km2 ground pixel• global coverage in 1.5 days

GOME

• 07.95 – 06.03 (full coverage)

• 4 channels 240 – 790 nm

• 0.2 – 04 nm FWHM

• nadir viewing

• 320 x 40 km2 ground pixel

• sun-synchronous orbit, 10:30

• global coverage in 3 days

SCIAMACHY

• 08.02 – today

• 8 channels 240 – 1700 nmand 2 – 2.4 μm

• 0.2 – 04 nm (1.5 nm) FWHM

• nadir viewing+ limb + solar / lunar occultation

• 60 x 30 km2 typical ground pixel

• sun-synchronous orbit, 10:00

• global coverage in 6 days

OMI• imaging spectrometer• launched 07.04• 13 x 24 -120 x 24 km2 ground pixel• global coverage in 1 day

Page 61: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Ozone Monitoring Instrument

• The NASA EOS Aura platform, launched on July 15, 2004, carries the Ozone Monitoring Instrument (OMI)

• Joint Dutch-Finnish Instrument with Duch/Finish/U.S. Science Team

• PI: P. Levelt, KNMI

• Hyperspectral wide FOV Radiometer

• 270-500 nm

• 13x24 km nadir footprint (highest resolution from space ! )

• Swath width 2600 km ( contiguous coverage )

• Radicals: Column O3, NO2, BrO, OClO

• O3 profile ~ 5-10 km vert resolution

• Tracers: Column SO2 , HCHO

• Aerosols (smoke, dust and sulfates)

• Cloud top press., cloud coverage

• Surface UVB

• Tropospheric ozone

13 km

(~2 sec flight))2600 km

12 km/24 km (binned & co-added)

flight direction» 7 km/sec

viewing angle± 57 deg

2-dimensional CCDwavelength

~ 580 pixels~ 780 pixels

Page 62: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

SO2 burdens increase over China

70% of China’s energy is derived from coal burning

SO2 emissions increased at a rate 35%/decade in 1979-2000. China’s sulfate aerosol loading has increased by 17%/decade in 1979-2000 [Massie, Torres and Smith 2004]

25.5 million tons of SO2 was emitted by Chinese factories in 2005 up 27% from 2000

OMI can observe SO2 emissions in the planetary boundary layer (PBL) over

China on a daily basis and is able to track individual pollution plumes outflow to Pacific

Page 63: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Average (2005-2006) SO2 burdens over

USA, Europe and China:

25.5 million tons of SO2 was emitted by Chinese factories in 2005

up 27% from 2000

East-Aire’05 experiment

Page 64: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 December 2006 Average

Page 65: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 Western US

Page 66: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 Western US + Cities

Page 67: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 Western US + Cities + Power Plants

Page 68: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 Eastern US

Page 69: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

OMI NO2 Asia

Page 70: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Nasa's CO2 satellite crashes into Antarctic ocean

• Nasa's pioneering satellite, designed to map carbon dioxide concentrations, has crashed into the ocean near Antarctica after running into technical difficulties during launch 24 February 2009

Page 71: METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University jin@met.sjsu.edu

Summary

• Urban System is an extreme land cover and land use example

• Satellite can provide a set of key parameters for urban system

• Satellite data can be used to• Detect urban features

• Improve urban parameter/parameterization in a land surface model, which shall elad to better ability to simulate/predict weather and climate of urban regions