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Radiative Transfer, MODIS and VIIRS, and the AERONET system North Larsen north.larsen@lmco.com. Todays Presentation.
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Radiative Transfer, MODIS and VIIRS, and the AERONET systemNorth Larsennorth.larsen@lmco.com
Todays Presentation The Radiative Transfer Equation has evolved into a powerful expression which is used by the community for understanding problems from global warming to the development of sensors and data products. Today an overview of the radiative transfer equation will be presented and a discussion into some of the NASA MODIS and NPOESS VIIRS sensors data products. There will also be a discussion of the AERONET data and the suite of sun photometers globally and how they are used by NASA. These topics are at the forefront and cutting edge of the remote sensing commmunity currently.
Understanding the Earth’s Atmosphere 20-30 km O3 (0-400 DU) stratosphere 8–20 km Clouds 78% N2 21% O2 0.8% Ar < 0.2% trace gases 99% of Atmosphere Aerosols troposphere Water vapor Temp
Radiative Transfer • Radiative Transfer is the study of the transport of radiant energy through a scattering, absorbing, and scattering medium. • The Atmosphere is divided into numerous homogeneous layers each possessing its own optical depth, single scattering albedo, temperature, and phase function. • The boundary conditions specified at the top of the atmosphere are solar input, thermal emissivity, solar zenith angle. And at the bottom of the atmosphere are surface albedo, surface temperature, and the surface emissive properties.
Radiative Transfer • The Radiative Transfer Equation has evolved into a powerful expression which is used by the community for understanding problems from global warming to the development of sensors and data products. dI/dt=Ioe-t IO I dt Earth’s Surface
The Plane Parallel Atmosphere for Radiative Transfer sensor m= cos(q) Q= (m,f;,m’,f’) Fs Z=100 t=0 a=a(t) T=T(t) P(Q)=P(Q,t) qo q T=T(t*) Z=0 t=t* Lambertian Surface A=Albedo fo f
Radiative Transfer Equation The Radiative Trnsfer Equation in Plane Parallel Atmospheres In Which: I Radiance being solved for (W/m2str-1) a Single Scattering Albedo (no units) P Phase Function (no units) t Optical Depth (no units) m Cosine of zenith angle (no units) B Planck function of temperature T (W/m2str-1) Fs Solar Flux input at the top of atmosphere (W/m2)
Then and Now First Image from TIROS-1 First Image from EOS-Terra New Brunskwick and Nova Scotia (40 Years ago) Mississippi Delta from MODIS Feb 24, 2000
MODIS Sensor (2000-2006) MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (0.4 – 15 microns). These data are improving our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.
MODIS Sensors Data Products Surface Reflectance Vegetation Cover Snow Cover Sea and Lake Ice Cover Normalized Water-leaving Radiance Pigment Concentration Chlorophyll Fluorescence Chlorophyll a Pigment Concentration Photosynthetically Available Radiation (PAR Suspended-Solids Concentration Organic Matter Concentration Coccolith Concentration Ocean Water Attenuation Coefficient Ocean Primary Productivity Sea Surface Temperature Phycoerythrin Concentration Total Absorption Coefficient Ocean Aerosol Properties Clear water Epsilon Radiance Aerosol Product Total Precipitable Water Atmospheric Profiles Gridded Atmospheric Product Cloud Mask and cover Surface Reflectance Land Surface Temperature and Emissivity Land Cover/Land Cover Change Gridded Vegetation Indices (Max NDVI and Integrated MVI) Thermal Anomalies, Fires, and Biomass Burning Leaf Area Index, and FPAR Evapotranspiration Net Photosynthesis and Primary Productivity
Forest Fires in Portugal (09/16/03) Hurricane Isabel 09/17/2003
AERONET Network The AERONET (Aerosol Robotic Network) is a global network of sun Photometers which measure local the atmospheric properties hourly.
AERONET Network Measurements are taken Of the AOT in 7 bands, and Total Column water vapor Is measured also. With this data validation of MODIS and future VIIRS Algorithms is performed and Data products are improved
The VIIRS Sensor (2008-2018) Description Collects visible/infrared imagery and radiometric data. Data types include atmospheric, clouds, earth radiation budget, clear-air land/water surfaces, sea surface temperature, ocean color, and low light visible imagery. Primary instrument for satisfying 26 EDRs. Visible/Infrared Imager Radiometer Suite VIIRS Specifications Multiple VIS and IR channels between 0.3 and 12 microns Imagery Spatial Resolution: 350m @ NADIR / 700m @ EOS Heritage and Risk Reduction POES - Advanced Very High Resolution Radiometer (AVHRR/3) DMSP - Operational Linescan System (OLS) - MOLS on F18-F20 EOS - Moderate Resolution Imaging Spectroradiometer (MODIS) NPP - Early validation of operational instrument and algorithms
VIIRS data products Cloud Top Height Cloud Top Pressure Cloud Top Temperature Albedo (Surface) Land Surface Temperature Vegetation Index Snow Cover/Depth Surface Type Currents Fresh Water Ice Ice Surface Temperature Littoral Sediment Transport Net Heat Flux Mass Loading Active Fires Precipitable Water Radiance Imagery Cloud Cover Imagery Cloud Type Imagery Ice Edge Location Imagery Ice Concentration Imagery Soil Moisture Aerosol Optical Thickness Aerosol Size Parameter Suspended Matter Cloud Base Height Cloud Cover/Layers Cloud Effective Particle Size Cloud Optical Thickness Ocean Color/Chlorophyll Sea Ice Age and Motion
Why? National Importance • Civilian Community • Timely, accurate, and cost-effective public warnings and forecasts of severe weather events, reduce the potential loss of human life and property and advance the national economy • Support of general aviation, agriculture, and maritime communities aimed at increasing U.S. productivity • Military Community • Shift tactical and strategic focus from “coping with weather” to anticipating and exploiting atmospheric and space environmental conditions
Why? Protect Safety of Life and PropertyImprove Accuracy of Severe Weather Warnings Increase in hurricane landfall forecast skill will save an estimated $1 million per mile of coastline that does not have to be evacuated Improved early warnings mitigate the devastating effects of floods through disaster planning and response
Why? Benefits to Industry Maritime industry - Ocean winds, waves, currents, and marine warnings and forecasts improve vessel routing for safety, fuel savings, and efficient operations Commercial fishing industry - knowledge of sea surface winds is critical to shrimp yields in the gulf Agricultural industry - Fire monitoring, vegetation index, frost, hail, and flood warnings critical to production
Why? Other Benefits to the World Community NPOESS will improve ability to predict El Niño. A 60% increase in El Niño forecast skill will save $183 million per year over 12 year period Ice monitoring for shipping and oil exploration Snow cover mapping - spring flood prediction
Thanks • MODIS Images and information presented is • from the NASA Goddard MODIS website • NPOESS information is from the NPOESS IPO • AERONET information is from the NASA Goddard • AERONET Sun Photometer website