geostationary hyperspectral imaging from 0.4 to 1 microns: a potent tool for convective analysis and...
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Geostationary Hyperspectral Imaging from 0.4 to 1 microns:A Potent Tool for Convective
Analysis and Nowcasting
James Purdom
&
Kenneth Eis
CIRA
Colorado State University, Fort Collins, CO 80523
Nowcasting convection requires frequent imaging and sounding that can only be provided by
geostationary satellites.
GOES-R: NOAA’s next generation geostationary satellite – “unique” in spectra, space and time (2012 timeframe)
The spatial and temporal variability of the phenomena being nowcast drive the observational needs as a function of its spectral, spatial and temporal domains, as well as signal to noise.
GOES-R’s Primary Earth Viewing Sensors: All play a role in nowcasting
• Advanced Baseline Imager
• Hyperspectral Environmental Suite– Hyperspectral IR
Sounder• Global mode• Mesoscale mode
– Hyperspectral visible to near IR imager
• Lightning detection sensor
• The spatial and temporal variability of the phenomena being nowcast drive the observational needs as a function of its spectral, spatial and temporal domains, as well as signal to noise.
Anticipated Highlights
• Advanced Baseline Imager
• Hyperspectral Environmental Suite– Hyperspectral IR
Sounder• Global mode• Mesoscale mode
– Hyperspectral visible to near IR imager
• Lightning detection sensor
• 16 or more channels
• 5 minute full disk capability with rapid scan capability
• ½, 1 and 2 km resolution depending on channel
Anticipated Highlights
• Advanced Baseline Imager
• Hyperspectral Environmental Suite– Hyperspectral IR
Sounder• Global mode• Mesoscale mode
– Hyperspectral visible to near IR imager
• Lightning detection sensor
• Hyperspectral regions from about 3.9 to 15 microns
• Hourly global at 10 km spatial resolution with capability of adaptive observing with more frequent limited areas (mesoscale) at 4 km resolution
Anticipated Highlights
• Advanced Baseline Imager
• Hyperspectral Environmental Suite– Hyperspectral IR Sounder
• Global mode• Mesoscale mode
– Hyperspectral visible to near IR imager (HES-VNIR)
• Lightning detection sensor
• Possible attributes– Hyperspectral from
about 0.4 to 1.0 microns with 10 or 20 nanometer spectral resolution
– 150 to 300 meters spatial resolution
– 6 second views of around 4000 to 5000 sq km
Anticipated Highlights
• Advanced Baseline Imager
• Hyperspectral Environmental Suite– Hyperspectral IR
Sounder• Global mode• Mesoscale mode
– Hyperspectral visible to near IR imager
• Lightning detection sensor
• 10 km resolution over most of earth disk (basically within 62 degree zenith angle)
• Near instantaneous refresh
In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution
– temporal (how often)
– spatial (what size)
– spectral (what wavelengths and their width)
– radiometric (signal-to-noise)
Compare cloud field evolution at different time intervals –GOES-R’s ABI with 5 minute full disk imagery (along with rapid scan capability and HES-VNIR) will provide unparalleled monitoring capability for nowcasting convection.
In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution
– temporal (how often)
– spatial (what size)
– spectral (what wavelengths and their width)
– radiometric (signal-to-noise)
The cold thunderstorm overshooting top region more accurately depicted using higher resolution data: this is important because the overshooting and coldness reflects storm updraft intensity - GOES-R’s ABI will provide unparalleled capability for assessing thunderstorm development, evolution and intensity.
* GOES-R’s hyperspectral sounder, in the mesoscale mode, will have a spatial resolution similar to the 4 km GOES-8 image (bottom left)
1 Km (today’s GOES) to 250 m (GOES-R HES-VNIR)
GOES-8: ~1 km Hurricane Erin09/09/01 ~1530 Z
MODIS: ~250 m
Note the detail in the eye wall (you can see up its side), improving the resolution of visible imagery (ABI and HES-VNIR) provides enhanced ability to analyze its cloud field
In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution
– temporal (how often)
– spatial (what size)
– spectral (what wavelengths and their width)
– radiometric (signal-to-noise)
Each spatial element has a continuous spectrum that may be used to analyze the surface and atmosphere
In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution
– temporal (how often)
– spatial (what size)
– spectral (what wavelengths and their width)
– radiometric (signal-to-noise)
•Next slide will show - Spectral animation from AIRS covering much of the mid-wavelength infrared portion of the spectrum
•With the hyperspectral sounder operating in the mesoscale mode this type data will be available at 4 km resolution (AIRS is 10x20 km res.)
High SpectralResolution
(AIRS)resolves
H2Ospectral
Features (right)
GOES-I/M era sounder H20
Channels (above)
Hyperspectral IR sounders: the potential for very accurate surface temperatures and detection of temperature inversions
Detection of inversions is critical for severe weather forecasting. Combined with improved low-level moisture
depiction, key ingredients for night-time severe storm development can be monitored.
Spikes down - cooling with height
Spikes up -warming with height
Texas
Ontario
Bri
ghtn
ess
Tem
pera
ture
(K
)
(low-level inversion)
(No inversion)
Wavenumber (cm-1)
In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution
• They all deal with resolution: – temporal (how often) – spatial (what size)– spectral (what wavelengths
and their width)
– radiometric (signal-to-noise)
AVIRIS Loop - Linden CA 20-Aug-1992224 Spectral Bands: 0.4 - 2.5 m
Pixel: 20m x 20m Scene: 10km x 10km
Smoke - large part.
CloudHot Area
Smoke -small part.
Fire
Shadow
Grass
Lake
Soil
Example of AVIRIS Spectral Information from a Scene Depicting Cloud, Smoke and Active Burn Areas
AVIRIS Image - Linden CA 20-Aug-1992 Spectral Signatures of Selected Pixels
The unique characteristics of the spectral signatures provide a way to identify and characterize each feature and to derive other useful information about the scene. HES-VNIR has the potential for numerous atmospheric, ocean, land applications – for some we need to filter atmospheric effects and use that information
Water Vapor: a filtered atmospheric effectnote water vapor change every 15 minutes
HES VNIR at high resolutions will be able to monitor pre-cumulus cloud moisture and moisture convergence – this will be enhanced by HES-IR
Water vapor exhibits remarkable variability in space and time (as above!); it serves as the key energy source for deep convective development. For example, releasing latent heat: a gram of water vapor condensed into a kilogram of air (about 1 cu meter) will raise that air’s temperature about 2.5 ºK. Water vapor is important on scales ranging from climate to convection.
EO-1’s hyperion: a glimpse to the future
Hyperion (IHOP Day 173, 1650 UTC)Hyperion is hyperspectral sensor on NASA’s EO-1
Derived Water Vapor Image
Mean CWV: 35.1 mm
37.4 mm (no clds)
Raob @ 18 UTC: 34.5 mm
WV Image Histogram
CWV (cm)
•This case is being investigated with Mike Griffin of MIT/LL
Spatial Simulations (7.5 km x 30 km)
256 x 1000 51 x 210 16 x 65 4 x 16 1 x 4
HSI 30m HES-VNIR 150m ABI VIS 480m ABI IR 2km ABS 7.5km
Notice how readily cloud free fields of view can be detected at higher resolutions, allowing for detailed column water vapor retrievals – in synergy with HES-IR, this will provide powerful information for nowcasting convection
Great Plains severe thunderstorm viewed by GOES-West and GOES-East
From geostationary altitude we see the side of the base, side and top of clouds. Different viewing perspectives allow for stereo height determination of various features.
The development and evolution of deep convection
Unique in space and time
•To the right is the first ever one minute interval imagery taken by a geostationary satellite. It covers 6 minutes, and illustrates the dynamic nature of a strong (large hail) thunderstorm. The area covered is approximately 160 x 160 km.
•Notice the cloud field variability, differences in cloud motion, cloud top and anvil growth, cloud growth along a front at the top of the image
Viewing Perspective, t and , determine what we see
with HES-VNIR
• Differences in scattering as a function of sun-scatterer-detector geometry allow for a variety of atmospheric, land, costal zone and ocean applications (think of MISR)
• Stereo cloud height determinations: accuracy is in large part a function of spatial resolution (shadows can also provide exceptionally accurate cloud height depending on time of day and viewing geometries)
• Exceptional CMV’s (u, u', v, v', w') in complex situations: potential for nearly 50 times higher resolution than today (150m vs 1000m) and over 10 times higher than GOES-R’s ABI (150m vs 500m)
• Pre-cumulus moisture field and its changes in time
• Over land atmospheric instability can change dramatically due to surface heating, an increase in low level moisture due to advection and evaporation as well as precipitation effects
• For nowcasting, one question is how representative is a sounding the further one is displaced from it as a function of space and time
• Thermodynamic soundings at different locations in these images will provide different information. This is especially true in the boundary layer where the fuel for deep convection is found. GOES-R will provide greatly enhanced capabilities to monitor moisture with HES-IR and HES-VNIR, and surface temperature with HES-IR and ABI.
Photo of thunderstorm from manned s/c
Photo of convection from airplane
•GOES-8 loop from 1033 to 1615: this loop illustrates the changes that have occurred in the cloud field (and boundary layer) since the launch of a “representative” rawinsonde.
MODIS at 1 km resolution compared to same data at 250 meters (similar to HES-VNIR)
Notice how well the cloud field can be analyzed at 250 meters. Everywhere there isn’t a cloud you can compute moisture from HES-VIS/NIR, and where there are the bigger holes you can do the total job with HES-IR (some are representative of a modified boundary layer due to storm outflow air)
Severe Weather
31
GOES Visible Loop at 1 to 30 minute IntervalsGOES Visible Loop at 1 to 30 minute Intervals
July 24, 2000 severe weather July 24, 2000 severe weather outbreak across South Dakota outbreak across South Dakota and Nebraska produces hail, and Nebraska produces hail, tornadoes, flash flooding and tornadoes, flash flooding and damaging windsdamaging winds One minute interval visible One minute interval visible
imagery shows storm imagery shows storm evolution over 2 hr periodevolution over 2 hr period
Important for severe weather: Vertical wind shear, evolving instability field, updraft strength, anvil development and blocking, rotating cloud top
32
Vertical shear ABI (cloud motion) HES-IR (moisture motion) HES-VNIR (cloud and
moisture motion) Evolving instability field
ABI (surface heating) HES-IR (instability and
surface heating) HES-VNIR (detailed
moisture field) Updraft strength
ABI (IR top temperature) ABI and HES-VNIR
(overshooting top height) Above with HES-IR
(updraft efficiency)
33
Updraft strength ABI (IR top temperature) ABI and HES-VNIR
(overshooting top height) Above with HES-IR
(updraft efficiency) Anvil development and
blocking ABI (growth and detailed
upper level atmospheric motion and water vapor behavior)
HES-IR and VNIR (as ABI but with better spectral definition)
Rotating overshooting top ABI and HES-VNIR
Oklahoma City tornado of May 3, 1999 left damage easily detected by Landsat 5 several days later (30 meter resolution), with residual damage even evident almost one year later. There are other instances where Landsat imagery has been used to locate areas of storm damage from hail, wind and tornadoes. Frequent hyper-spectral views possible from HES-VNIR point to a new and exciting potential
High resolution Hyperspectral: We infer today, we will see and measure with GOES-R
– Very accurate cloud motion vectors with accurate cloud bases and cloud tops
– High resolution water vapor measurements in the presence of cumulus cloudiness
– A few implications (with ABI and HES-IR & VNIR)
• Monitor the growth and destabilization of the boundary layer over land
• Cloud growth rate and cloud top behavior
• Smoke, haze, dust, aerosols, visibility in cloud free areas
• Damage paths for large storms• Areas of flooding (wet ground)
Shear, cold air production, evolving instability field, updraft strength, anvil development, blocking, cloud motion, rotating cloud top, rain area, hail swath and tornado damage path –
High resolution Hyperspectral: And we haven’t even talked about hurricanes and other phenomena – like
moisture, aerosols and plume tracking for “local disasters”