High Priority Science Passive Instrument Heritage Spacecraft Cost Resiliency All NASA Flight System...

High Priority Science • Passive Instrument • Heritage Spacecraft • Cost Resiliency • All NASA Flight System

Orbiting Carbon Observatory (OCO)

Science -1

Why CO2?

O OCISSUES: Carbon dioxide (CO2) is the

• Principal atmospheric component of the global carbon cycle

• Primary anthropogenic driver of climate change

• Only half of CO2 produced by human activities over the past 30 years has remained in the atmosphere.

• Where are the sinks?

• Will this continue?

Atmosphere

Human Activity

LandOcean

? ?



Science -3

The Global Carbon CycleNatural carbon fluxes account for 300 GtC/yr and exist in near equilibrium.

The ~6 GtC/yr produced by human activity represents only 2% of the carbon flux, but it may tip the balance

6 G

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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?

Since 1860, global mean surface temperature has risen ~1.0 °C with a very abrupt increase since 1980.

“Keeling Plot”

Does increasing atmospheric CO2 drive increases in global temperature?Do increasing temperatures increase atmospheric CO2 levels?

Atmospheric CO2: the Primary Anthropogenic Driver of Climate Change



Science -5

• What are the relative roles of the oceans and land ecosystems in absorbing CO2?

• Is there a Northern hemisphere land sink?– Relative roles of North America/ Eurasia

• What controls carbon sinks?– Why does the atmospheric buildup vary

substantially with uniform emission rates?– How will sinks respond to climate change

• Climate prediction requires an improved understanding of natural CO2 sinks

– Future atmospheric CO2 increases

– Their contributions to global change

An Uncertain FutureWhere are the Missing Carbon Sinks?

Atmospheric CO2

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Global Mean Temperature

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OCO will dramatically reduce these uncertainties



Science -6

An Uncertain Future:Where are the Missing Carbon Sinks?

• Only half of the CO2 released into the atmosphere since 1970 years has remained there. The rest has been absorbed by land ecosystems and oceans

• 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

and Eurasia• What controls carbon sinks?

• Why does the atmospheric buildup vary with uniform emission rates?

• How will sinks respond to climate change?• Reliable climate predictions require an improved

understanding of CO2 sinks

• Future atmospheric CO2 increases

• Their contributions to global change

• Atmospheric CO2 has been monitored systematically from a network of ~100 surface stations since 1957

• Over the past 20 years– only ~1/2 of the CO2 associated with fossil

and biomass fuel combustion has remained in the atmosphere

– the remainder has been absorbed by the ocean and land ecosystems

• Carbon sinks are not well understood– Is there a Northern hemisphere land sink?

• Relative roles of North America/ Eurasia– What controls sources and sinks?

• Why does the atmospheric buildup vary from 1 - 6 GtC/year in the presence of roughly constant emission rates?

• How will the efficiency of these sinks evolve as the climate changes?

• An Integrated, global strategy needed to answer these questions.

– The US Carbon Cycle Science Program• USGCRP, NSF, DoE, USDA, NOAA,

NASA, USGS

The ~100 GLOBALVIEW-CO2 flask network stations and the 26 continental sized zones used for CO2 flux inversions.

This network is designed to measure back-ground CO2. It can not retrieve accurate source and sink locations or magnitudes!

Bousquet et al., Science 290, 1342 (2000).

The Global Carbon Cycle: Many Questions



Science -8

Measurements Needed to Revolutionize Our Understanding of the Global Carbon Cycle

• Accurate, spatially resolved global measurements of XCO2 will revolutionize our understanding of the carbon cycle if measurement can be acquired

– With accuracies of 1 ppm

– On regional scales (8o X 10o)

– On monthly time scales

1.2

0.6

0.0Fig. 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 1ppm on regional scales on monthly time scales

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FLASK SATELLITE

Flux Errors

Fig. F.1.2 Flux Errors vs Measurement Accuracy



Science -9

Why Measure CO2 from Space?Improved CO2 Flux Inversion Capabilities

Rayner & O’Brien, Geophys. Res. Lett. 28, 175 (2001)

Current State of Knowledge• Global maps of carbon flux errors for 26

continent/ocean-basin-sized zones retrieved from inversion studies

• 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.

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45

Why Measure CO2 from Space?Dramatically Improved Spatiotemporal Coverage

The O=C=O orbit pattern (16-day repeat cycle)

O=C=O Measurement Objectives

Objective:

Characterize the geographic distribution of CO2 sources and sinks on regional to continental scales over seasonal to interannual time scales

Approach:• Space-based atmospheric carbon monitoring

system– Global coverage (land and ocean)

• high spatial resolution (4o x 5o)• weekly to monthly time scales

– High measurement precision

• Column CO2 measurement precision

– ~1ppm (0.3% of 370 ppm)• Resolve East-West gradients as well as

interhemispheric gradients in CO2

• Advanced Modeling tools used to retrieve

– CO2 column amounts from observations

– Sources and sinks from global CO2 maps

• Correlative Measurement Program– Validation, bias removal, diurnal cycles– Laboratory Measurements Coverage in Each 16-Day Repeat Cycle

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Science -12

Proposed Sampling Strategy Addresses All Science Objectives

B) Satellite

• OCO will 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 – Isolates cloud-free scenes– Provides thousands of samples on

regional scales• 16 Day Repeat Cycle

– Provides large numbers of samples on monthly time scales

45

810Ground tracksover the tip of South America

Spatial samplingalong ground track



Science -13

Measurement Strategy Maximizes Information Content and Measurement Validation Opportunities

Nadir Mode

TargetMode

Glint Mode

• 1:15 PM near polar orbit – 15 minutes ahead of the A-Train

• Same ground track as AQUA

– 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• Same path as FTIR

• Calibration data taken on night side



Science -14

OCO 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 1ox1o

• OCO flies in the A-train, 15 minutes ahead of the Aqua platform

• 1:15 PM equator crossing time yields same ground track as AQUA

• Global coverage every 16 days

• OCO samples at high spatial resolution • Nadir mode: 1 km x 1.5 km footprints

• Isolates cloud-free scenes• Provides thousands of samples on regional

scales• Glint Mode: High SNR over oceans• Target modes: Calibration



Science -15

Will it Work?

• Accuracies of 1ppm 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: The OCO payload will• meet or exceed the requirements for

measuring CO2

• provide rigorous constraints on the distribution and optical properties of clouds and aerosols

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 (0.02c 0.05), light to moderate aerosol loadings (0.05a 0.15), over ocean and land surfaces. INSET: Distribution of XCO2 errors (ppm) for each case



Science -16

Validation Program Ensures Accuracy and Minimizes Spatially Coherent

Biases

• Ground-based in-situ measurements

– NOAA CMDL Flask Network + Tower Data

– TAO/Taurus Buoy Array

• Uplooking FTIR measurements of XCO2

– 3 OCO

– 4 NDSC

• Aircraft measurements of CO2 profile

• Complemented by Laboratory and on-orbit calibration

Buoy Network CMDL



Science -17

Rigorous Physics Based Retrieval Algorithms

Level 1

Level 2

Level 3

XCO2 Retrieval

Calibration

Source/SinkRetrieval

• Inverse Models• Assimilation Models Level 4

The Pushbroom Spectrometer Concept

Crosstrack

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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 cross-track scenes are dispersed along the other dimension.

The instrument acquires spectra continuously along the ground track at a rate of 4 Hz.

This results in 24 spectra/sec and 3000 spectra per 45 region every 16 days.

2D 1024 1024 arrays are available in Si (visible) and HgCdTe (NIR) from Rockwell Sciences.

Cloud and Aerosol Interference

Clouds, aerosols and sub-visible cirrus (high altitude ice clouds) prevent measurement of the entire atmospheric column.

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.

Number of cloud-free scenes per month anticipated for space-based sampling averaged into 36 (LatLon) bins based on AVHRR cloud data.D. O’Brien (2001).

Sub-visible Cirrus Clouds

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 m.

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.

VISIBLE

1.38 m

MODIS data

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).



Science -22

Q4Science Impacts of X-band Failure

• OCO will meet its 1 ppm relative accuracy requirement under both scenarios

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The Baseline Science Mission will be achieved

Based on Fig. F.1.10



Science -23

Response:

• OCO requires no ancillary data to measure XCO2

• XCO2 measurements are relatively insensitive to the details of the underlying terrain and surface characteristics

– Observations from the high resolution O2 A-band spectrometer will be used to characterize the topographic variability within each spatial footprint

– Effects of surface albedo are discussed in Question #18

Q15OCO Geolocation Requirements (cont.)

The claimed need for 5 km geolocation (F-18) is deemed inadequate for mapping CO2 retrievals onto terrain and surface characteristics



Science -24

Question #17Q17

Question 17: Due to the critical effect of changing surface albedo, it is essential that the entire spectra are collected simultaneously. Please clarify.

Response• OCO uses grating spectrometers

– All wavelength information for a given spatial sample is recorded simultaneously on array detectors

– Each spatial sample is read out almost simultaneously • 1.4 msec per spectrum



Science -25

Response:

The wavelength-dependent albedo is retrieved as an independent variable in each spectral channel.

Question18Q18

Question 18: Please quantify the error in the CO2 column measurement resulting from surface albedo variations and uncertainties. A formal, detailed error analysis is not required here. However, you do need to demonstrate that this error source, which is not explicitly considered in the proposal, is not important relative to the error budget and specified 1 ppm accuracy level.



Science -26

Albedo Is Retrieved Explicitly

• The wavelength dependent albedo is determined from the continuum level within each spectral band as part of the simultaneous retrieval– Surface albedo changes much more slowly with wavelength than

gas vibration-rotation features– The OCO spectral resolution has been chosen to resolve the

spectral lines from the continuum in each band• Because the entire spectrum is collected almost

simultaneously in each channel, the XCO2 retrieval depends only on the spatial average of the albedo within each footprint

Q18

2.06



Science -27

Albedo Is Retrieved Explicitly

• The end-to-end retrieval simulations included wavelength-dependent albedos, which were retrieved as part of the XCO2 retrieval process. – Albedo types considered: dark ocean, desert, snow,

conifer forests and snow • Errors associated with uncertainties in the albedo

retrieval are a small part of the total error budget– The XCO2 retrieval algorithm is only weakly dependent

on the absolute value of the surface albedo (through its effects on the SNR)

– Atmospheric O2 and CO2 columns depend on differences between the line core and continuum

Q18

Demonstrate that this error source, which is not explicitly considered in the proposal, is not important relative to the error budget and specified 1 ppm accuracy level.

Fig. F.1.9: End to end test of the OCO retrieval algorithm



Science -28

Q20OCO Sampling Biases: Level 3 ProductsGlobal XCO2 Maps (16-day average)

• 1:15 PM local sampling time chosen because

– Production of CO2 by respiration is offset by photosynthetic uptake

– Instantaneous XCO2 measurement is within 0.3 ppm of the diurnal average (see figure)

– Airborne measurements of CO2 profiles from COBRA and ABLE-2B substantiate this view

• 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 (no cloud bias evident in figure)

– Mixing greatly reduces the influence of local events & point sources on XCO2

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

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Science -29

Q20

• Level 4a: Inverted Sources and Sinks

• OCO measurements of XCO2 will not be evenly distributed in time and space.

• The inversion approaches incorporated into the OCO Mission Science strategy account for spatial and temporal inhomogeneity in observations.

– The power of OCO in constraining sources and sinks comes from the ~108 new observations over a two-year period and the relatively high density of XCO2 observations in the tropics (where constraints from contemporary surface networks are weak).

– Inversions of OCO data in combination with FTIR, aircraft, and flask observations, will revolutionize our understanding of the global carbon cycle.

OCO Sampling Bias: Level 4a ProductsGeographic Distribution of CO2 Sources & Sinks



Science -30

Q20

• Level 4b: Carbon Cycle Data Assimilation

• Data assimilation will calculate the 3-D CO2 field by combining OCO XCO2 data with

– in situ CO2 observations

– Uplooking FTIR XCO2

– Atmospheric transport model

• Analogous to modern weather forecasting

– Spatially and temporally biased observations assimilated into a physical model to produce maps with continuous spatial and temporal information.

OCO Sampling Bias: Level 4b ProductsCarbon Cycle Data Assimilation

XCO2 Assimilation Strategy

Assimilation step

Transportmodel

CO2Forecast

(F)

4-D CO2Analyses (A)for science

System statsA - FO – F

for monitoring

CO2Assimilation

cycle

OCO XCO2obs. (O)

Meteorology Source/Sinkestimates

In-situ CO2 obs.

INPUT OUTPUT

MODELS

Assimilation step

Transportmodel

CO2Forecast

(F)



System statsA - FO – F

for monitoring

CO2Assimilation

cycle

OCO XCO2obs. (O)

Meteorology Source/Sinkestimates

In-situ CO2 obs.

INPUT OUTPUT

MODELS

INPUT OUTPUT

MODELS



Science -31

Q21Question # 21

Question 21:

Level 2 data consists of a constellation of point measurements obtained in clear sky conditions. What are the spatial and temporal statistics of these measurements as a function of latitude? In particular, how will the geographical sampling of the instrument be affected by the relatively larger amount of cloudiness which tends to occur in the tropics relative to other latitudes? How will this degrade the quality of the Level 3 and Level 4 data, and how will this affect your science?

Response:– OCO acquires 740 soundings per degree of latitude along the orbit track– With 14.65 orbits/day, and a 16 day repeat cycle,

• Ground tracks are separated by ~1.5o of longitude

• Over a 16 day period, each 4o x 5o sub-region is traversed 3.3 times, yielding ~10,000 XCO2 soundings (assuming no clouds)

– Only a small fraction of these samples are needed to meet the baseline science requirements



Science -32

• Response: – Observational System Simulation

Experiments (OSSE’s) using the OCO orbit and 8 km x 8 km footprint (based on ISCCP data)

– There is no strong tropical bias in the number of CO2 soundings

– High cirrus produce a sampling bias in the tropics, but their effects are compensated by the low solar zenith angle and high SNR

Effects of Clouds on Sampling

How will the geographical sampling of the instrument be affected by the relatively larger amount of cloudiness which tends to occur in the tropics relative to other latitudes?

Average number of cloud-free hits each month in each 4 x 5 degreelatitude bin, averaged over the year.

Q21

Rayner et al. (2002)



Science -33

Probability of Viewing Cloud-Free Scenes Increases with Spatial Resolution

July

8 km x 8 km

0.0 0.5 1.0

Probability of clear-sky scene

24 km x 24 km

40 km x 40 km

Rayner, Law and O’Brien III (2001)

• OSSE’s confirm that the probability of viewing cloud-free scenes increases as the sample footprint size decreases

• The high spatial resolution (1 km x 1.5 km) provided by OCO will yield more cloud free scenes

Q21



Science -34

Q22Airborne Demonstration of +0.1% Retrieval Precision for Column O2

• Retrieval of tropospheric column O2 to + 0.1% demonstrated using reflected near infrared sunlight with an airborne O2 A-band instrument

D. M. O’Brien et al., J. Atmos. Oceanic Tech. 15, 1272 (1998).



Science -35

Q22Flight Instrument Validation

• Prior to launch the OCO flight instrument will

• Measure the CO2 column looking up towards sun

• Be compared to the OCO FTIR spectrometers.

1.571.59 1.58

Wavelength (m)

CO2 1.58 m Band

Ground-based FTIR solar spectrum in the OCO 1.58 m CO2 band recorded at Table Mountain Facility, Wrightwood, CA

(May 2002, S. Sander)



Science -36

Question 8a

Question 8a:

Quantify the science impacts of the descope options

Response:The OCO Team has identified 5 descope options

1. Relax geolocation requirement from 5 km to ~10 km2. Leave A-Train3. Reduce sampling rate from 4.5 to 3.0 Hz4. Limit science observation to NADIR viewing5. Delete 2.06 m channel

Q8a



Science -37

Q8aThe Execution of All Descope Options Defines the Minimum Science Mission

Baseline Science Mission Minimum Science MissionProvide global XCO2 measurements from space with

• 1 ppm relative accuracy• 2.5 x 105 km2 scale (4 x 5)• 16 day interval• 2 year mission

Provide global XCO2 measurements from space with

• 1 ppm relative accuracy• 1.0 x 106 km2 scale (8 x 10)• 1 month interval• 2 year mission

Combine XCO2 measurements with ground-based data to retrieve the geographic distribution of CO2 sources & sinks on seasonal to interannual timescales.

Combine XCO2 measurements with ground-based data to retrieve the geographic distribution of CO2 sources & sinks on seasonal to interannual timescales.

Use NADIR, GLINT and TARGET modes to provide independent data validation approaches

Deleted

Formation fly with the A-Train to allow coordinated observations and enhance data value to the ESE community

Deleted

Section F.2.6, pp. F-17-18

Q8a



Science -38

Q8aOCO XCO2 Retrieval Performance Quantified for Baseline & Minimum Missions

Minimum Mission

Baseline Mission

After Fig. F.1.10, p. F-8

• OCO delivers global XCO2 measurements with 1 ppm relative accuracy in the Baseline Science Mission & Minimum Science Mission.

Simulations conducted with the end-to-end OCO retrieval algorithm

Q8a



Science -39

Response:

• Relaxing the geolocation requirement from 5 km to ~10 km complicates the validation of the OCO data but does not affect the data accuracy.– Detailed response provided in Question 15

• A relaxed geolocation requirement increases difficulty in collocating OCO validation measurements using TARGET mode.– FTIR’s located in spatially uniform areas

• The relaxed geolocation requirement will not affect the ability to correlate the OCO measurements with those from the A-Train– OCO swath is substantially smaller than that of A-Train

instruments.

Descope 1Relaxed Geolocation Requirements

Q8a



Science -40

Descope 3Reduced Sampling Rate

Response:• Reducing sampling rate from 4.5 Hz to 3.0 Hz will

– Reduce the number of samples in each 4 x 5 region by 33%– Increases footprint area by 50%

• Slightly increased cloud contamination• Results quantified in the response to Question 21

Q8a

33%

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Science -41

Descope 4Delete TARGET & GLINT Modes

Response:• Deleting GLINT mode will

reduce sensitivity over oceans and at high latitudes

– OCO still meets its 1 ppm XCO2 relative accuracy goal operating only in NADIR mode

• Deleting TARGET mode decreases the number of independent validation methods

Fig. F.1.9, p. F-7

OCO retrieval performance for several NADIR viewing scenarios

Q8a



Science -42

Descope 5Delete 2.06 m Channel

Response:• Deleting the 2.06 m channel requires significantly more soundings

to be averaged to meet the 1 ppm XCO2 relative accuracy goal

Fig. F.1.8 quantifies the RSS errors for retrievals with all three spectrometers (c) and without the 2.06 m channel (b).

Q8a



Science -43

Q8aDescope 5Delete 2.06 m Channel (con’t)

• The Baseline configuration reaches the 1 ppm accuracy goal in 10 – 50 soundings while it requires 50 – 10,000 soundings to achieve this goal without the 2.06 m channel.

• To achieve 1 ppm requires–Increasing sampling grid from

4 x 5 to 8 x 10 – Increasing interval from 16

days to 1 month

Fig. F.1.10 quantifies the simulated observatory performance as a function of the number of soundings for the baseline configuration (red) and the instrument with the 2.06 m channel deleted (blue).



Science -44

OCO Addresses the High Science Priorities

XC

O2 (

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• OCO provides 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

Climate Forcing/Response

•T/H2O/O3 AIRS/TES/MLS

•Clouds CloudSat•Aerosols CALIPSO

•CO2 OCO

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