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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

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Presentation on theme: "METR155: Using Satellite Remote Sensing in Climate Model – focus on Urban Menglin Jin, Professor Department of Meteorology San Jose State University"— Presentation transcript:

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

2 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

3 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” questions for 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?

4 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

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

6 An example Urban – an example

7 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

8 Night Light of Tokyo data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS)

9 Night Light of Paris

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

11 Importance of land surface skin temperature (T skin ) 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↑ = εσT skin 4 Eq. (1) SH = C DH U(T aero -T a )Eq. (2) LE =C DE U(q Tskin *-q a )Eq. (3) (1-α)Sd +LW d -εσT skin 4 +SH+LE + G= 0

12 We use NASA EOS and NCAR Climate Model to examine the urbanization effects, in particular, urban pollution urban heat island effect (UHI)

13 50km Urban heat island effect Daytime Nighttime 50km MODIS (Jin, Dickinson and Zhang. 2005, J. of Climate)

14 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

15 MODIS Observation Beijing

16

17 (Jin, Dickinson, et al. 2005) MODIS Observed Global urban heat island effect

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

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

20 Urbanization changes surface emissivity (MODIS)

21 Use MODIS observed surface properties into model

22 MODIS11_L2 Emissivity_BAND 32 over Houston regions Note: emissivity is missing over Houston urban regions, but available from monthly regions

23 MODIS15_A2 Leaf Area Index (LAI) over Houston regions Note: on daily product, LAI over Houston regions is missing, but available from monthly data

24 Physical Processes for UHI: (1-α)Sd +LW d -εσT skin 4 +SH+LE + G= 0 On Urban system: (1-α)Sd +LW d -εσT skin 4 +SH+LE + G= 0 All underlined terms are changed! The Land Surface Energy Balance

25 Urban Aerosol Effects Change atmosphere conditions to form clouds and rainfall Change surface insolation -> reduce urban surface temperature

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

27 Aerosol Distributions over Land and Ocean have evident differences July 2005 Satellite observations

28 NASA Aeronet Sites http://aeronet.gsfc.nasa.gov/ Ames has on of this site!

29 Aerosol effect on UHI

30 AERONET, New York EPA Scale, Scale, Scale!!Jin, Shepherd, King 2005 JGR

31 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

32 4.3 Jin and Shepherd, 2008, JGR

33 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?

34 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

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

36 Use satellite data to represent urban

37 Existing Coupled Land-Atmosphere Models: Coarse Resolution, Biogeophysics Focus e.g., CLM: (NCAR, DAO) NOAH: (NCEP) Turbulence production Urban thermal properties Radiation trapping Radiation attenuation Canopy heating & cooling

38 Conceptual UMD-NASA CLM-Urban Model Bare soil Road Building roofs Suburban Human-grass Original trees Urban-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)

39 Physical Processes for UHI: (1-α)Sd +LW d -εσT skin 4 +SH+LE + G= 0 On Urban system: (1-α)Sd +LW d -εσT skin 4 +SH+LE + G= 0 All underlined terms are changed! The Land Surface Energy Balance

40 CAM3/CLM3-Urban Model Results

41 Model results

42 Net longwave radiation

43 Model results

44 3 Km 5/9/2011, 8 PM MODIS land cover WRF-urban

45 WRF 1km 5/5/2011 5 PM

46 6 PM, 5/5/2011

47 7 PM, 5/5/2011

48 5 PM, 5/6/2011

49 7 PM, 5/6/2011

50 9 PM, 5/6/2011

51 11 PM, 5/6/2011

52 1 AM, 5/7/2011

53 3 AM, 5/7/2011

54 5 AM, 5/7/2011

55 8 AM, 5/7/2011

56 10 AM, 5/7/2011

57 Evaluation of WRF-urban, MODIS

58 Class participation Why urban albedo is reduced? What is uncertainty of remotely sensed albedo over urban regions?

59 NASA “Mission to measurements”

60 Nadir UV/vis Satellite instruments GOME-2 similar to GOME launched 10.06 80 x 40 km 2 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 km 2 ground pixel sun-synchronous orbit, 10:30 global coverage in 3 days SCIAMACHY 08.02 – today 8 channels 240 – 1700 nm and 2 – 2.4 μm 0.2 – 04 nm (1.5 nm) FWHM nadir viewing + limb + solar / lunar occultation 60 x 30 km 2 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 km 2 ground pixel global coverage in 1 day

61 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 O 3, NO 2, BrO, OClO O 3 profile ~ 5-10 km vert resolution Tracers: Column SO 2, 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 CCD wavelength ~ 580 pixels ~ 780 pixels

62 SO 2 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 SO 2 emissions in the planetary boundary layer (PBL) over China on a daily basis and is able to track individual pollution plumes outflow to Pacific

63 Average (2005-2006) SO 2 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

64 OMI NO 2 December 2006 Average

65 OMI NO 2 Western US

66 OMI NO 2 Western US + Cities

67 OMI NO 2 Western US + Cities + Power Plants

68 OMI NO 2 Eastern US

69 OMI NO 2 Asia

70 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 map carbon dioxide concentrations

71 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


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