Transcript Functional Block Diagram - California Institute of Technology

The Orbiting Carbon Observatory (OCO)
Mission
Vijay Natraj
Ge152
Wednesday, 1 March 2006
Orbiting Carbon Observatory (OCO)
Atmospheric CO2: the Primary
Anthropogenic Driver of Climate Change
“Keeling Plot”
Since 1860, global mean surface temperature
has risen ~1.0 °C with a very abrupt increase
since 1980.
Atmospheric levels of CO2 have risen from
~ 270 ppm in 1860 to ~370 ppm today.
Accumulation of atmospheric CO2 has
fluctuated from 1 – 6 GtC/yr despite nearly
constant anthropogenic emissions. WHY?
Orbiting Carbon Observatory (OCO)
An Uncertain Future:
Where are the Missing Carbon Sinks?
• Only half of CO2 produced by human activities over the past 30 years
has remained in the atmosphere.
• What are the relative roles of the oceans and land ecosystems in
absorbing CO2?
• Is there a northern hemisphere land sink?
• What are the relative roles of North America/ Eurasia?
• What controls carbon sinks?
• Why does the atmospheric buildup vary with uniform emission rates?
• How will the sinks respond to climate change?
• Climate prediction requires an improved understanding of natural CO2
sinks.
• Future atmospheric CO2 increases
• Their contributions to global change
Orbiting Carbon Observatory (OCO)
The Global Carbon Cycle: Many Questions
• Atmospheric CO2 has been monitored systematically from a network
of ~100 surface stations since 1957.
The ~100 GLOBALVIEW-CO2 flask network
stations and the 26 continental sized zones used
for CO2 flux inversions.
This network is designed to measure background CO2. It cannot retrieve accurate source
and sink locations or magnitudes!
Bousquet et al., Science 290, 1342 (2000).
Orbiting Carbon Observatory (OCO)
Why Measure CO2 from Space?
Improved CO2 Flux Inversion Capabilities
•
Studies using data from the 56 GV-CO2 stations
• Flux residuals exceed 1 GtC/yr in some zones
• Network is too sparse
Inversion tests
• Global XCO2 pseudo-data with 1 ppm accuracy
• Flux errors reduced to <0.5 GtC/yr/zone for all zones
• Global flux error reduced by a factor of ~3.
OCO
Flux Retrieval Errors
GtC/year/Zone
•
Fig. F.1.3: Carbon flux errors from simulations including data from (A) the existing surface flask network, and
(B) satellite measurements of XCO2 with accuracies of 1 ppm on regional scales on monthly time scales
Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001)
Orbiting Carbon Observatory (OCO)
1.2
0.6
0.0
Why Measure CO2 from Space? Dramatically
Improved Spatiotemporal Coverage
45
45
The O=C=O orbit pattern
(16-day repeat cycle)
Orbiting Carbon Observatory (OCO)
The Orbiting Carbon Observatory (OCO)
Mission
• Make the first, global, space-based observations of the column
integrated dry air mole fraction, XCO2, with 1 ppm precision.
• Combine satellite data with ground-based measurements to
characterize CO2 sources and sinks on regional scales on monthly to
interannual time scales
• Fly in formation with the A-Train to facilitate coordinated observations
and validation plans
Orbiting Carbon Observatory (OCO)
XCO2 Retrieved from Bore-Sited CO2 and
O2 Spectra Taken Simultaneously
•
High resolution spectroscopic measurements
of reflected sunlight in near IR CO2 and O2
bands provide the data needed to retrieve XCO2
•
•
•
Column-integrated CO2 abundance
• Maximum contribution from surface
Other data needed (provided by OCO)
• Surface
pressure,
albedo,
atmospheric
temperature, water vapor, clouds, aerosols
Why high spectral resolution?
•
Lines must be resolved from the continuum to
minimize systematic errors
Clouds/Aerosols, Surface Pressure
Orbiting Carbon Observatory (OCO)
Column CO2
Clouds/Aerosols, H2O, Temperature
Spatial Sampling Strategy
• OCO is designed provide an
accurate description of XCO2 on
regional scales
• Atmospheric motions mix CO2 over
large areas as it is distributed
through the column
• Source/Sink model resolution limited
to 1o x 1o
• High spatial resolution
• 1 km x 1.5 km footprints
• Isolates cloud-free scenes
• Provides thousands of samples on
regional scales
• 16-day repeat cycle
• Provides large numbers of samples
on monthly time scales
Orbiting Carbon Observatory (OCO)
Spatial sampling
along ground track
810
45
Ground tracks
over the tip of
South America
Operational Strategy Maximizes
Information Content and Measurement
Validation Opportunities
• 1:15 PM near polar (98.2o) orbit
Nadir Mode
• 15 minutes ahead of EOS A-Train
• Same ground track as AQUA
Glint Mode
• Global coverage every 16 days
• Science data taken on day side
• Nadir mode
• Highest spatial resolution
• Glint mode
• Highest SNR over ocean
• Target mode
• Validation
• Airmass dependence
• Comparison with surface
stations
Target
Mode
FTS
• Calibration data taken on night side
• Solar, limb, dark, lamp
Orbiting Carbon Observatory (OCO)
Q20
Sampling Biases
• Atmospheric transport desensitizes
OCO measurements to the clear-sky
bias
• Air passes through clouds on a time-scale
short compared to the time needed to affect
significant changes in XCO2
• Mixing greatly reduces the influence of local
events & point sources on XCO2
Orbiting Carbon Observatory (OCO)
XCO2 (ppm)
• Production of CO2 by respiration is offset by
photosynthetic uptake
• Instantaneous XCO2 measurement is within
0.3 ppm of the diurnal average (see figure)
MAY
DXCO2 (ppm)
• 1:15 PM local sampling time chosen
because
Fig. F.2.4: a) Calculated monthly mean, 24 hour
average XCO2 (ppm) during May using the
NCAR Match model driven by biosphere and
fossil fuel sources of CO2. b) XCO2 differences
(ppm) between the monthly mean, 24 hour
average and the 1:15 PM value
Will it Work?
• Accuracies of 1 ppm needed to
identify CO2 sources and sinks
• Realistic, end-to-end, Observational
System Simulation Experiments
• Reflected radiances for a range of
atmospheric/surface conditions
• line-by-line multiple scattering
models
• Comprehensive description of
• mission scenario
• instrument characteristics
• Results
• Retrieve XCO2 from single clear sky
nadir sounding to 0.3-2.5 ppm
precision
• Rigorous
constraints
on
the
distribution and optical properties of
clouds and aerosols
Orbiting Carbon Observatory (OCO)
End-to-end retrievals of XCO2 from individual
simulated nadir soundings at SZAs of 35o
and 75o. The model atmospheres include
sub-visual cirrus clouds (0.02c 0.05),
light to moderate aerosol loadings (0.05a
0.15), over ocean and land surfaces. INSET:
Distribution of XCO2 errors (ppm) for each
case
Cloud, Aerosol and Cirrus Interference
Clouds, aerosols and sub-visible cirrus
(high altitude ice clouds) prevent
measurement of the entire atmospheric
column.
Sub-visible cirrus clouds are effective at
scattering near infrared light because the
light wavelengths and particle sizes are
both ~ 1 – 2 µm.
An analysis of available global data
suggests that a space-based instrument
will see “cloud-free” scenes only ~ 10%
of the time.
Geographically persistent cloud cover
will be especially problematic and will
induce biases in the data.
Orbiting Carbon Observatory (OCO)
Number of cloud-free scenes per month
anticipated for space-based sampling
averaged into 36 (LatLon) bins based on
AVHRR cloud data (O’Brien, 2001).
O=C=O Performance Improves with Spatial
Averaging
Accuracy
of
OCO
XCO2
retrievals as a function of the
number of soundings for
optimal (red) and degraded
performance (blue) for a
typical case (37.5 solar zenith
angle,
albedo=0.05,
and
moderate
aerosol
optical
depth, a{0.76 m} = 0.15).
Results
from
end-to-end
sensitivity tests (solid lines)
are
shown
with
shaded
envelopes indicating the range
expected for statistics driven
by SNR (N1/2) and small-scale
biases (N1/4).
Orbiting Carbon Observatory (OCO)
Validation Program Ensures Accuracy
and Minimizes Spatially Coherent Biases
•
Ground-based in-situ measurements
•
•
•
Uplooking FTS measurements of XCO2
•
•
•
•
NOAA CMDL Flask Network + Tower Data
TAO/Taurus Buoy Array
3 funded by OCO
4 upgraded NDSC
Aircraft measurements of CO2 profile
Complemented by Laboratory and on-orbit calibration
Buoy Network
Orbiting Carbon Observatory (OCO)
CMDL
The Pushbroom Spectrometer Concept
It is possible to obtain many ground-track
spectra
simultaneously
if
the
instantaneous field of view (IFOV) is
imaged onto a 2D detector array.
In this case, wavelength information is
dispersed across one dimension and crosstrack scenes are dispersed along the other
dimension.
The
instrument
acquires
spectra
continuously along the ground track at a
rate of 4.5 Hz.
This results in 70 spectra/sec and 9000
spectra per 45 region every 16 days.
Orbiting Carbon Observatory (OCO)
Wavelength
Crosstrack
OCO Data Product Pipeline
• The OCO data flow from space
through an automated pipeline
which yields Level 1 and 2 data
products.
• Level 3 and Level 4 products are
produced by individual Science
Team members.
• Preliminary tests of the retrieval
algorithm demonstrate the OCO
mission concept
• (Kuang et al., Geophys. Res.
Lett., 29 (15) 2001GL014298,
2002).
Orbiting Carbon Observatory (OCO)
Space-borne
Data
Acquisition
Level 2
Calibration &
Validation
Data
Spectral
Radiances
Level 3
Global 1
ppm XCO2
Maps
AIRS: T, P, H2O
Ancillary Data
FTIR: XCO2
GVCO2: [CO2]
MODIS: Aerosol
NCEP Fields
Data
Assimilation
Models
Inversion
Models
Level 4
Temporally
Varying CO2
Source/Sink
Maps
JAN
JUL
APR
OCT
Retrieval Algorithm
Retrieval Process
Incoming Spectra
Global CO2 Maps
Adjustment To The Atmospheric /Surface State x
Inversion Model
O2 A Band
Calculated Spectrum
f(x) and Jacobians
df/dx
yes
Convergence ?
no
Forward Model
Instrument Simulator
Radiative Transfer Model
CO2
Monochromatic RT Calculation
Frequency
Loop
Calculate Input Parameter
CO2
Orbiting Carbon Observatory (OCO)
XCO2
Summary
OCO will provide critical data for
•
•
•
Understanding the carbon cycle
• Essential for developing carbon
management strategies
Predicting weather and climate
• Understanding sources/sinks essential
for predicting CO2 buildup
• O2 A Band will provide global surface
pressure measurements
OCO validates technologies critically
needed for future operational CO2
monitoring missions
•
Satisfies a measurement need that has
been identified by NPOESS, for example
Orbiting Carbon Observatory (OCO)
Climate Forcing/Response
•T/H2O/O3
AIRS/TES/MLS
•Clouds
CloudSat
•Aerosols
CALIPSO
•CO2
OCO
XCO2 (ppm)
•