Transcript Global Biophysical Datasets from NASA Missions Steven W. Running Univ. Of Montana / USA IPCC – GEOSS Workshop Feb 2, 2011

Global Biophysical Datasets
from NASA Missions
Steven W. Running
Univ. Of Montana / USA
IPCC – GEOSS Workshop
Feb 2, 2011
CEOS ECV (Essential Climate Variables)
from GCOS – 138, Aug 2010
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Albedo
Landcover
FAPAR
LAI
Biomass (is NPP better?)
Soil Carbon (from satellite?)
Fire Disturbance
Soil Moisture
Thematic standards
Common
classifiers
(Terminology
standard)
LANDCOVER INTERCOMPARISON
• Classifiers commonly used to characterize land
cover worldwide
• i.e. life form & surface type, leaf type &
phenology, terrestrial/aquatic
Generic
classes
(Thematic
standard)
• Basic set of standardized classes based on
combination of common classifiers and
independent of any cartographic standard
• i.e. broadleaved evergreen trees, herbaceous
crops, built up area
Mapping
Categories
(Cartographi
c standard)
• Application of cartographic generalization
(MMU) to generic classes
• Definition of mixed categories or using density
thresholds
• i.e. Closed to open (>15%) broadleaved
evergreen forest (> 5m)
Reference
database (GLC2000)
Comparative
validation & assessment
Probability
Global Fires for 10 Days
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MODIS Annual Disturbance Index
Mildrexler et al 2009
Global Net Primary Production trend (2000-2009)
Zhao & Running 2010, Science
NPP Anomaly compared to Inverted Atm CO2 Anomaly
R = 0.81
Global Trend in NPP (1982 – 2009)
AVHRR + MODIS with EOS algorithm
Consistency between MODIS NDVI and NPP (1982-2009)
Zhao and Running 2010
Non-Frozen Season Trend (1979-2008)
(SSM/I)
Days yr-1
Mean Northern Hemisphere trend
Multi-Year Trend in Estimated Mean Annual ET and P-ET (1983-2006)
 ~73% of the global
domain shows a
positive ET trend;
ET
BUT
P-ET
 ~51% of the
domain shows a
negative water
balance (P-ET) trend.
Global Annual Maximum
MODIS Radiometric Surface Temp
Global Flux Tower Network
Aerosol Robotic Network
AERONET
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Aerosol Optical Properties Research & Enabling Project
• Program of long term systematic network measurements
Mission Objectives
• Validation of Satellite Aerosol Retrievals
• Characterization of aerosol optical properties
• Synergism with Satellite obs., Climate Models
Expanding to in situ Ocean Color & possibly total column CO2
Missions in Formulation and Implementation – 12/2010
OCO-2
2/2013
Global CO2
ICESat-II
10/2015
Ice Dynamics
GLORY
2/2011
Aerosols, TSI
SMAP
11/2014
w/CSA
Soil Moist., Frz/Thaw
AQUARIUS
6/2011
w/CONAE; SSS
GPM
7/2013, 11/2014
w/ JAXA; Precip
NPP
10/2011
w/NOAA, DoD
EOS cont., Op Met.
LDCM
12/2012
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w/USGS; TIRS
Unsustainable groundwater withdrawal
Depletion rate 4cm/yr
Groundwater withdrawals as % of recharge, 2002-2008.
Rodell et al Nature 2009
SMAP Science Objectives
Soil moisture and freeze/thaw state are primary environmental controls on water
mobility and associated constraints to evaporation and Net Primary Productivity
Snow Accumulation
Frozen
High
Surface Resistance
Dry Spring Soil Moisture
Wet Spring Soil Moisture
Freeze - Thaw
cycles
Inc
rea
sin
gB
iol
Thawed
og
ica
lC
on
str
ain
ts
Low
Low
Landscape Water Content
High
Mean Thaw Date
(SSM/I, 1988-2001)
Summer Air Temperature Anomaly [ºC]
Julian Day
SMAP measurements of soil moisture and freeze-thaw cycles will provide an integrated measure of critical
controls on surface water mobility and associated constraints to ecosystem processes.
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OCO Measuring CO2 from Space
• Collect NIR spectra
of CO2 and O2
absorption in
reflected sunlight
• Retrieve variations in the
column averaged CO2 dry
air mole fraction, XCO2
over sunlit hemisphere
Initial
Surf/Atm
State
New
State
(inc.
XCO2)
Generate
Synthetic
Spectrum
• Validate measurements
to ensure XCO2 accuracy
of 1 - 2 ppm (0.3 - 0.5%)
OCO/AIRS/GOSAT
Instrument
Model
Difference
Spectra
FTS
Tower
Inverse
Model
Aircraft
XCO2
Flask
DESDynI Radar and Lidar Capabilities for
Biomass and Aboveground Carbon Storage
L-band Radar – high resolution
mapping of low forest biomass
and disturbance, extend
sensitivity with lidar
Multi-beam Lidar – accurate
biomass and canopy profiles
(along-track) at 25 m resolution,
extend spatially with radar
Vegetation 3D
Structure &
Biomass: Radar
and Lidar
Vegetation
Type
Upland conifer
Lowland conifer
Northern hardwoods
Aspen/lowland deciduous
Grassland
Agriculture
Wetlands
Open water
Urban/barren
Terrestrial Carbon
Storage and Changes
High: 30 kg/m2
Biomass
Low: 0 kg/m2
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NRC Decadal Survey HyspIRI
Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer
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Multispectral Thermal InfraRed (TIR) Scanner
VSWIR: Plant Physiology and
Function Types (PPFT)
Multispectral
TIR Scanner
Map of dominant tree species, Bartlett Forest, NH
Red tide algal bloom in Monterey Bay, CA
Linkages between International Programs concerned with
Terrestrial Earth Observation
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LPV Objective & Goals
To foster and coordinate quantitative validation of higher level
global land products derived from remotely sensed data, in a
traceable way, and to relay results so they are relevant to users
• To increase the quality and efficiency of global satellite product
validation by developing and promoting international standards and
protocols for:
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Field sampling
Scaling techniques
Accuracy reporting
Data / information exchange
• To provide feedback to international structures (GEOSS) for:
– Requirements on product accuracy and quality assurance (QA4EO)
– Terrestrial ECV measurement standards
– Definitions for future missions
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Focus Groups
Focus Group
North America
Europe / Other
Land Cover *
Mark Friedl
Martin Herold
(Boston University)
(Wageningen University, NL)
Fire*
Luigi Boschetti
Kevin Tansey
(Active/Burned Area)
(University of Maryland)
(University of Leicester, UK)
Biophysical
Richard Fernandes
Stephen Plummer
(LAI*, APAR*)
(NR Canada)
(Harwell, UK)
Crystal Schaaf
Gabriela Schaepman
(Boston University)
(University of Zurich, SW)
Land Surface
Temperature
Simon Hook
Jose Sobrino
(NASA JPL)
(University of Valencia, SP)
Soil Moisture*
Tom Jackson
Wolfgang Wagner
(USDA)
(Vienna Uni of Technology, AT)
Land Surface
Phenology
Jeff Morisette
Jadu Dash
(USGS)
(University of Southampton, UK)
Surface Radiation
(Reflectance, BRDF,
Albedo*, Snow/Ice*)
* ECV
Listserv
137
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72
41
65
48
76
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KEY FINDINGS
• Many global datasets now exist
• Need validation and intercomparison amongst
sensors
• Need to unify formats, gridding, units
• Coordinate data distribution
• Continuity to new sensors
EXTRA SLIDES
IPCC WORKING GROUP II IMPACTS SUMMARY 2007
CO2 Emissions from Land Use Change
CO2 emissions (PgC y-1)
CO2 emissions (PgCO2 y-1)
Friedlingstein et al. 2010, Nature Geoscience; Data: RA Houghton, GFRA 2010
1990s
Emissions: 1.5±0.7 PgC
2000-2005
Emissions: 1.3±0.7 PgC
2006-2010:
Emissions: 0.9±0.7 PgC
Fire Emissions from Deforestation Zones
Fire Emissions from
deforestation zones (Tg C y-1)
1400
Global Fire Emissions Database (GFED) version 3.1
America
Africa
Asia
Pan-tropics
1200
1000
800
600
400
200
0
1997
99
01
2003
Year
05
van der Werf et al. 2010, Atmospheric Chemistry and Physics Discussions
07
2009
Modelled Natural CO2 Sinks
2
5 models
Land sink
(PgCy-1)
0
-2
-4
-6
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
0
4 models
Ocean sink
(PgCy-1)
2
-2
-4
-6
Time (y)
Updated from Le Quéré et al. 2009, Nature Geoscience
NASA Operating Missions (International Collaboration)
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Future Orbital Flight Missions – 2010 – 2022
(International
contributions)
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Gravity Recovery &
Climate Experiment
500 km orbit
220 km separation
Distance accuracy 0.001 mm
Focus Group Responsibilities
• Engage community members (via listserv/website)
• Update on progress, relevant meetings
• Report back to LPV group on activities, meetings, new products,
potential funding mechanisms
• Organize at least 1 topical workshop within leadership term
• Expand LPV activities, field sites, collaboration globally
• Lead product inter-comparison activities
• Lead the development and writing of “best practice” land
product validation protocols
• Define product error definitions for ECV’s, LTDR’s for the climate
modeling community
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Global Water Availability Risk
Vorasmairty et al Nature 2010