Remote Sensing Satellite Systems

Satellite Remote Sensing Lasted just 78 days but proved the theory… TIROS-1 was an aluminum-and-stainless-steel drum measuring 42 inches in diameter, 19 inches high and weighing 270 pounds. An array of 9,200 solar cells powered its two TV cameras: one high-res, one low-res. One antenna received control signals from ground stations, and another four transmitted TV images back to Earth. Two video recorders stored images when the satellite was out of range of ground stations. The polar-orbiting craft was not constantly pointed at earth and could only operate in daylight, so coverage was not continuous. It functioned for just 78 days, but it sent back thousands of pictures of cloud patterns forming and moving across the face of the planet. And it proved the theory that satellites could effectively survey global weather from space. The April 1st launch was no joke… Cartooning Images at the start of my career in 1976…

How is satellite data used? To monitor cloud systems in real time To infer atmospheric structure from cloud types As a tool in short range forecasting Some satellite data is assimilated into model fields Numerous derived products precipitation estimates sea surface temperature atmospheric motion vectors Moisture Icing Turbulence etc The Analysis and Diagnosis of the Satellite Atmosphere is the next best things to real atmosphere

Objectives Satellite systems Radiation principles Sensing channels Image enhancement Sounding output NWP ingesting satellite data

Satellite Systems Geostationary and Polar Orbiting Imaging and sounding instruments Characteristics Advantages Limitations http://www.oso.noaa.gov/goesstatus/

Geostationary Polar Animation of Orbits Current GOES Status Parked over the equator Eclipses in spring and fall Orbit is earth synchronous (24 hour orbit) Orbit roughly over the poles Sun synchronous – no eclipse 14 orbits/day Animation of Orbits Current GOES Status Current NOAA POES Status

Geostationary Met Satellites around the world Examples other geostationary met satellites Europe (Meteosat) India (KALPANA formerly INSAT) Japan (MTSAT) China (FY2C-Feng Yun 2)

MetOp-A European Space Agency Click Here

Earth Observing Systems - EOS MODIS – NPOES

GOES Scanning Strategy Back and forth sweeps 15 minute global scan

POES – NOAA Series Orbital and sensor characteristics

Imaging and vertical sounders GOES GOES imager- 5 channels, VIS – IR GOES sounder – 18 thermal channels, one low-res visible channel ~ 50 km POES POES imager (AVHRR) - 6 channels POES sounder (ATOVS) HIRS (IR) – similar to GOES IR sounder AMSU (microwave), AMSU-A 15 channels, AMSU-B 5 channels – in-cloud soundings possible

GOES and POES Communication Paths GOES Satellite -> Wallops Island, West Virginia for some data processing ->then back to satellite -> ground stations POES Satellite directly to ground station Line of sight reception for 2-16 minutes

Image Resolution GOES: Wavelength and latitude dependant At equator: VIS=1km, Shortwave and IR=4km, WV=8km POES: 1.09 km at all wavelengths and latitudes

Factors affecting image interpretation Sensor resolution Coarser resolution of GOES sensors can lead to cloud image “merging” relative to a higher resolution image from POES Curvature of earth Except near the equator, slant angle of GOES scans can lead to parallax views, an effect absent from POES

RESOLUTION The smallest area that the satellite sensor (radiometer) can distinguish from the surrounding area

Image size and image resolution The smallest area that the satellite sensor (radiometer) can distinguish from the surrounding area Enlarging an image only makes larger pixels

GOES Resolution from subpoint 4

Image resolution depends on: closeness of satellite to earth distance of pixel from satellite subpoint satellite optics satellite sensor resolution image processing techniques quality of final display device

Image resolution (km)

GOES vs POES Advantages and Disadvantages One Sensor – preserves relativity Multiple Sensors – relativity is less certain GOES vs POES Advantages and Disadvantages

Radiation Principles

Radiation Principles 50% of incoming solar reaches the surface

Atmospheric Absorption Window with Nil Absorption 4u Window

Weighting Functions Pick and Choose wavelengths to take advantage of atmospheric components and absorption bands and windows - complex Distribution Dominate Source of Radiation to Satellite Transmittance is the fraction of incident light at a specified wavelength that passes through a sample Absorbance is the fraction of incident light that neither transmits nor reflects and is proportional to the concentration of a substance in a solution

Imager Channels Type Ident Satellite Wavelength

Limitations and errors Earth and clouds are not perfect black bodies – thin clouds may allow considerable radiation to pass through (upwelling), so satellite-derived brightness temperatures may be in error Other atmospheric constituents are not black bodies, but absorb/emit radiation at preferred wavelengths (e.g. water vapour at ~ 6 microns) Must use “window channel” radiation for Tb determinations (e.g. 11-12 microns)

Limitation - Subpixel Effect Cloud elements smaller that the resolution cannot be resolved but still contribute to the radiation Different wavelengths are also affected differently due to “dirty” vs clean windows and emissivity Cities as subpixel hot spots

Subpixel Example

The Satellite Channels

Colour-enhanced visible GOES 12 image: T.S. Gustav 29 August 2008 Visible Imagery Colour-enhanced visible GOES 12 image: T.S. Gustav 29 August 2008

Albedo by Wavelength VIS GOES Channel 1 VIS AVHRR Channel 1 520-720nm 1u The visible channel (channel 1) is a collection of reflected light in the 0.52-0.72 mm wavelength. These images are obtained only during daylight hours. They are used to show clouds, haze, severe storms, snow cover, volcanic activity, and other visible features. Many surface features are also apparent. The infrared (IR) imagery represents the measurement of energy emitted by the Earth in a variety of wavelengths, the above image is a channel 2 image from the 3.78-4.03 mm wavelength. This short wave IR is helpful in observing ground fog, fires, volcanoes, sea surface temperatures, and clouds. Scientists access other IR images depending upon their interest. A long wave IR, channel 4 (10.2-11.2 mm) is used to show jet stream features, surface temperatures and frost/freeze forecasts. Channel 5 (11.5-12.5 mm) is commonly used to observe daily temperature changes, cold cloud tops, dust, and ash. The water vapor imagery, channel 3, (6.47-7.02 mm) is an infrared image which allows meteorologists to observe upper-level moisture sources and the presence of humidity within the atmosphere. This will enhance their ability to forecast the development and motion of weather systems. Contrast VIS AVHRR Channel 2 725-1000nm

Near Infrared (1 micron) POES Similar to visible Most radiation is reflected solar with a small IR contribution Good for land/water differentiation since vegetation is a better scatterer of 1u radiation No use at night like visible Sun Glint What time of day is it?

4 Micron (4u) Thermal Radiation << than 11u Not much radiation – both solar and thermal at 4 micron Not much atmospheric absorption in 4 micron window though

Solar Dominates Thermal Solar Pollution

4 Micron (4u) GOES and POES Considered an IR channel low radiation mapped to white high mapped to black Contribution from both albedo and temperature Solar pollution Noisy signal at cold temperatures

4 Micron (4u) Daytime interpretation Water cloud is dark Cloud droplets are more reflective to solar portion of 4u signal – lots of radiation = dark thermal representation Ice cloud is bright – Why? Fog/stratus is dark over bright snow Mid cloud (ice/water mix) is mottled Nighttime interpretation Thermal channel Noisy at cold temperatures (cold cloud tops)

Water Vapour Imagery Water vapour is a strong absorber-emitter – upper 3 mm of water vapour Water vapour distribution varies greatly in the horizontal and vertical = weather! This is why Water Vapour imagery should be your new best friend…

Water Vapour (6.7 micron) Displays high and mid level moisture No need for cloud White = moist & cold = low flux Black =dry & warm = high flux Coarse 8 km resolution but signal very clean - not noisy Only on GOES Animation displays circulation patterns Hurricane Edouard

GOES Limb Darkening Limb NADIR The point is that one senses the 3 mm of water vapour at a higher and colder level.

Infrared (11 micron) Displays temperature White = low flux = cold Used day or night Thin cloud may be contaminated from upwelling radiation from below Stratus/fog poorly displayed Usually requires enhancement

Infrared (11 micron) In atmospheric absorption “window” Absorption/emissivity near 1 (except for thin cirrus) Radiative temperature is close to the effective blackbody temperature Thin Cirrus E<1 =.4 CB E=1 The point is that the thin cirrus is as cold as the thick cirrus (blue-green) but Upwelling radiation contaminates the observation (yellow)

Infrared (12 micron) The Dirty Window Looks almost like the 11u Displays temperature White = low flux = cold Used day or/and night More sensitive to low level water vapour than the 11u Used for SST’s Derived products like Tsfc and Precipitable Water Volcanic Ash

Infrared (12 micron) The Dirty Window More Sensitive to low level water vapour than the 11 micron

Image Enhancement The process whereby meteorologically significant parts of an image are made easier to discriminate. Enhancement involves reassigning new color or brightness values to a specific range of pixel elements.

Enhancement Curves Increased low light Linear

Visible image enhancement This is my work from the early 1980’s. The image on the left has been enhanced to increase its brightness

Enhanced Visible Imagery Correction to visible imagery to enhance areas with low sun angle Correction across image near terminator Correction both diurnally and seasonally “Black step” for high albedo clouds – possible precipitation Effort from 1980 … never published E series of visible enhancements

Chadwick family of enhancement curves named by seasons and purpose… IR image enhancement Chadwick family of enhancement curves named by seasons and purpose… the IR image on the right has been enhanced to bring out the high (cold) tops west of James Bay

Q6 Curve on IR Imagery White Black linear Uses a 'range' of temperature to discriminate features (e.g. low, mid, high, convective cloud etc.) linear Black

Color Enhancement In this 11 micron GOES-8 image of hurricane Fran, the coldest tops are colored in red so that they stand out more clearly.

More Satellite Data for NWP Temperature and moisture (Sounding data) Drift Winds – both direction and speed Southern hemisphere benefits!

Questions? Summary Satellite systems Radiation principles Future satellites will have even greater capabilities Spatial and temporal resolution will be amazing! Satellite systems Radiation principles Sensing channels Image enhancement Sounding output Questions?