SMAP Cal/Val
T. J. Jackson
USDA ARS Hydrology and Remote Sensing Lab
December 11, 2012
Outline
• Soil Moisture Satellite Missions: Past, Present and
Future
• SMAP
– Mission
– Cal/Val
• Sparse Networks in Cal/Val
• Challenges to using COSMOS
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
Climate Applications
Weather Applications
Week
Passive
Historic Perspective on Remote Sensing
Carbon Cycle
Applications
Active
Month
Scale ranges are based on the NRC Decadal Survey
100 km
10 km
Resolved Spatial Scales
1 km
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
ASCAT
AMSR-E
GCOM-W
ASCAT
Climate Applications
Weather Applications
Week
2012 GCOM-W
2002-2011
Soil moisture product is the
AMSR-E
X-band 40 km
same
as AMSR-E
Month
Scale ranges are based on the NRC Decadal Survey
100 km
10 km
Resolved Spatial Scales
Carbon Cycle
Applications
ALOS
ALOS-2
SAR
1 km
Soil Moisture and Ocean Salinity
Mission (SMOS)
• European Space
Agency (ESA)
• 1.4 GHz
Microwave
Radiometer
• 40 km footprint,
three day global
coverage
• Launch November
2009
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
AMSR-E
ASCAT
SMOS
Climate Applications
Weather Applications
Week
1.4 GHz
6.0 GHz
10.0 GHz
Month
100 km
• Same resolution
but a better
product
• Technology demo
10 km
Resolved Spatial Scales
Carbon Cycle
Applications
1 km
Aquarius/SAC-D
• Mission (NASA and CONAE)
– Sun-synch orbit
– 6 am (Des.)/6 pm (Asc.)
– Night time look direction
– 657 km Alt; 7 day revisit
– Launch: June 2011
• Aquarius Instrument
– L-band Polarimetric
– Radiometer and Scatterometer
– 3 Beam Pushbroom
– Incidence angles of
29.36°, 38.49°, and 46.29°
• SAC-D
– MWR
– Other
Middle beam
84×120 km
Outer beam
96×156
km
Inner beam
76×94 km
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
AMSR-E
ASCAT
SMOS
Climate Applications
Week
Month
Aquarius
Weather Applications
Active and passive Lband but coarser
spatial resolution and
temporal repeat
Carbon Cycle
Applications
Scale ranges are based on the NRC Decadal Survey
100 km
10 km
Resolved Spatial Scales
1 km
SAOCOM: SAtélite Argentino de
Observación COn Microondas
• Comisión Nacional de Actividades
•
•
•
•
•
Espaciales (CONAE)-Argentina Space
Agency
Constellation of two identical satellites
SAOCOM 1A and SAOCOM 1B
carrying an L-band polarimetric SAR
instrument
SAOCOM will be in a sun-synchronous
nearly circular frozen polar orbit (06:12
am LTAN/619.6 km)
Repeat cycle of 16 days (8 days with full
constellation of 2 satellites)
Launch of SAOCOM 1A in 2015.
Challenge: Infer surface soil moisture
values from SAR measurements with
varying incidence angles.
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
GCOM-W
ASCAT
SMOS
Climate Applications
Week
Aquarius
Weather Applications
Commitment to a soil
moisture product
Month
Scale ranges are based on the NRC Decadal Survey
100 km
10 km
Resolved Spatial Scales
SAOCOM
Carbon Cycle
Applications
ALOS-2
1 km
Outline
• Soil Moisture Satellite Missions: Past, Present and
Future
• SMAP
– Mission
– Cal/Val
• Sparse Networks in Cal/Val
• Challenges to using COSMOS
SMAP Level 1 Science Requirements
• The NRC Decadal Survey identified numerous potential applications for SM/FT
observations.
• These were grouped into three categories with a spatial resolution, refresh rate, and
accuracy.
Requirement
Resolution
Refresh Rate
Accuracy
Mission Duration
(a) North
HydroMeteorology
HydroClimatology
Carbon
Cycle
4–15 km
2–3 days
0.04-0.06 (c)
50–100 km
3–4 days
0.04-0.06 (c)
1–10 km
2–3 days(a)
80–70% (b)
Baseline Mission
Soil
Freeze/
Moisture
Thaw
10 km
3 km
3 days
2 days
0.04 (c)
80%(b)
36 months
Threshold Mission
Soil
Freeze/
Moisture
Thaw
10 km
10 km
3 days
3 days
0.06 (c)
70%(b)
18 months
of 45N latitude, (b) Percent classification accuracy (binary freeze/thaw), (c) Volumetric water content, 1-σ in [cm3/cm3] units
• These are the L1 priority products and requirements. Other product accuracies derive
from L2 requirements. Defines the baseline mission.
• The SMAP Project proposed the active-passive approach for meeting these
requirements.
TJJ–12
SMAP Project Approach
• L-band unfocused SAR and radiometer system,
offset-fed 6 m light-weight deployable mesh
reflector. Shared feed for

1.26 GHz HH, VV, HV
Radar at 1-3 km (30% nadir gap)

1.4 GHz H, V, 3rd and 4th Stokes
Radiometer at 40 km
• Conical scan, fixed incidence angle (40o across
swath
• Contiguous 1000 km swath with 2-3 days revisit (8
day repeat)
• Sun-synchronous 6am/6pm orbit (680 km)
• Launch October 31, 2014 (now in Phase C/D)
• Mission duration 3 years
TJJ–13
SMAP Science Products
Product
Description
Gridding
(Resolution
)
Latency**
L1A_Radiometer
Radiometer Data in Time-Order
-
12 hrs
L1A_Radar
Radar Data in Time-Order
-
12 hrs
L1B_TB
Radiometer TB in Time-Order
(36x47 km)
12 hrs
L1B_S0_LoRes
Low Resolution Radar σo in Time-Order
(5x30 km)
12 hrs
L1C_S0_HiRes
High Resolution Radar σo in Half-Orbits
1 km (1-3
km)
12 hrs
L1C_TB
Radiometer TB in Half-Orbits
36 km
12 hrs
L2_SM_A
Soil Moisture (Radar)
3 km
24 hrs
L2_SM_P
Soil Moisture (Radiometer)
36 km
24 hrs
L2_SM_AP
Soil Moisture (Radar + Radiometer)
9 km
24 hrs
L3_FT_A
Freeze/Thaw State (Radar)
3 km
50 hrs
L3_SM_A
Soil Moisture (Radar)
3 km
50 hrs
L3_SM_P
Soil Moisture (Radiometer)
36 km
50 hrs
L3_SM_AP
Soil Moisture (Radar + Radiometer)
9 km
50 hrs
L4_SM
Soil Moisture (Surface and Root Zone )
9 km
7 days
L4_C
Carbon Net Ecosystem Exchange
(NEE)
9 km
14 days
Instrument
Data
Science Data
(Half-Orbit)
Science Data
(Daily
Composite)
Science
Value-Added
* Over outer 70% of swath.
** The SMAP project will make a best effort to reduce the data latencies beyond those shown in this table.
TJJ–14
Evolution of Microwave Remote Sensing (Land)
Resolved Temporal Scales
Day
GCOM-W
ASCAT
SMOS
SMAP Radar-Radiometer
Climate Applications
Aquarius
Week
Month
Weather Applications
SMAP will support established
climate and carbon cycle
applications and will open up
new applications in weather
and carbon cycle.
SAOCOM
Carbon Cycle
Applications
ALOS-2
Scale ranges are based on the NRC Decadal Survey
100 km
10 km
Resolved Spatial Scales
1 km
SMAP L1 Requirements Impacting Cal/Val
What the SMAP
Project and
NASA have
agreed to do.
Level 1 (Baseline) Science
Requirements and Mission
Success Criteria
Provide estimates of soil moisture in the top 5 cm of soil with an error of no
greater than 0.04 m3/m3 volumetric (one sigma) at 10 km spatial resolution and
3-day average intervals over non-excluded regions.
Provide estimates of surface binary freeze/thaw state in the region north of 45N
latitude, which includes the boreal forest zone, with a classification accuracy of
80% at 3 km spatial resolution and 2-day average intervals.
Conduct a calibration and validation program to verify data delivered meets the
requirements.
Threshold mission requirements are 0.06 m3/m3 and 70%
CEOS Validation Stages Adopted for SMAP
Validation: The process of assessing, by independent means, the quality of the
data products derived from the system outputs. The quality is determined with
respect to the specified requirements.
Validation
Stage
Stage 1
Stage 2
Stage 3
Stage 4
Description
Product accuracy is assessed from a small (typically < 30) set of locations and time periods by
comparison with in situ or other suitable reference data.
Product accuracy is estimated over a significant set of locations and time periods by comparison with
reference in situ or other suitable reference data. Spatial and temporal consistency of the product and
with similar products have been evaluated over globally representative locations and time periods.
Results are published in the peer-reviewed literature.
Uncertainties in the product and its associated structure are well quantified from comparison with
reference in situ or other suitable reference data. Uncertainties are characterized in a statistically
robust way over multiple locations and time periods representing global conditions. Spatial and
temporal consistency of the product and with similar products have been evaluated over globally
representative locations and periods. Results are published in the peer-reviewed literature.
Validation results for stage 3 are systematically updated when new product versions are released
and as the time-series expands.
TJJ–17
SMAP Validation Methodologies
Methodology
Role
Constraints
Resolution
Core Validation Sites
Accurate estimates of products • In situ sensor calibration • In Situ Testbed
at matching scales for a limited • Limited number of sites • Cal/Val Partners
set of conditions
Sparse Networks
One point in the grid cell for a
wide range of conditions
Satellite Products
Estimates over a very wide
• Validation
range of conditions at matching • Comparability
scales
• Continuity
• Validation studies
• Distribution
matching
Model Products
Estimates over a very wide
range of conditions at matching
scales
Detailed estimates for a very
limited set of conditions
• Validation studies
• Distribution
matching
• Airborne simulators
• Partnerships
Field Campaigns
• In situ sensor calibration • In Situ Testbed
• Up-scaling
• Scaling methods
• Limited number of sites • Cal/Val Partners
• Validation
• Comparability
• Resources
• Schedule conflicts
TJJ–18
SMAP Cal/Val Approach
Pre-launch
• Focus on insuring that there are means in place to fulfill the
mission objectives
– Acquire and process data with which to calibrate, test, and improve
models and algorithms used for retrieving SMAP science data products
– Develop and test the infrastructure and protocols for post-launch
validation
Post-launch
• Focus on validating that the products meet their quantified
requirements
– Calibrate, verify, and improve the performance of the science algorithms
– Validate accuracies of the science data products as specified in L1 science
requirements according to Cal/Val timeline
TJJ–19
Science Data Validation and Delivery
Timeline
Pre-launch
Preparation
Launch
In-Orbit Checkout (3 months)
Formal start of SMAP Science Mission
Beta release of L1 products
and start of routine delivery
Beta release of L2-L4 products
and start of routine delivery
L1 validation (6 months)
Delivery of validated L1 products to Data Center
L2-L4 validation (12 months)
Delivery of validated L2-L4 products
to Data Center
TJJ–20
Outline
• Soil Moisture Satellite Missions: Past, Present and
Future
• SMAP
– Mission
– Cal/Val
• Sparse Networks in Cal/Val
• Challenges to using COSMOS
SMAP Validation Methodologies
Methodology
Role
Constraints
Resolution
Core Validation Sites
Accurate estimates of products • In situ sensor calibration • In Situ Testbed
at matching scales for a limited • Limited number of sites • Cal/Val Partners
set of conditions
Sparse Networks
One point in the grid cell for a
wide range of conditions
Satellite Products
Estimates over a very wide
• Validation
range of conditions at matching • Comparability
scales
• Continuity
• Validation studies
• Distribution
matching
Model Products
Estimates over a very wide
range of conditions at matching
scales
Detailed estimates for a very
limited set of conditions
• Validation studies
• Distribution
matching
• Airborne simulators
• Partnerships
Field Campaigns
• In situ sensor calibration • In Situ Testbed
• Up-scaling
• Scaling methods
• Limited number of sites • Cal/Val Partners
• Validation
• Comparability
• Resources
• Schedule conflicts
TJJ–22
SMAP Cal/Val Partners Program
• In situ observations are essential to SMAP Cal/Val
• There were only a few high quality resources available
• Increasing the number was constrained by
– The time and effort to establish a site
– No $ to support these
• Action: ROSES DCL
– No cost collaboration
– Minimum standards
– In situ data in exchange for early access to SMAP products
• Based on responses
– Refined definitions
– Missed some important resources
TJJ–23
SMAP Cal/Val Partners: Site Types
• Core Validation Sites: In situ observing sites that provide wellcharacterized estimates of a L2-L4 product at a matching spatial
scale, a direct benchmark reference for the products. Additional
minimum criteria are:
–
–
–
–
Provides calibration of the in situ sensors
Up-scaling strategy provided (implemented by Project)
Provides data in a timely manner
Long term commitment by the sponsor/host
• Contributing Validation Sites: In situ observing sites that
provide estimates of a L2-L4 product but do not meet all of the
minimum criteria for a Core Validation Site. (i.e. sparse
networks)
– Contributing Validation Sites are a supplemental resource (In assessing
meeting mission requirements but important in Stage 2 Validation).
– The baseline approach to using sparse networks is the triple-collocation
technique. Efforts to improve this approach are desirable.
TJJ–24
Outline
• Soil Moisture Satellite Missions: Past, Present and
Future
• SMAP
– Mission
– Cal/Val
• Sparse Networks in Cal/Val
• Challenges to using COSMOS
–
–
–
–
Up-scaling
Contributing depth
Integrating networks
Resolving “noise”
Challenge: Scaling Points to Footprints
Proposed best practices*:
θPOINT
Footprint-scale
First, apply temporal stability analysis (Cosh
et al., 2006; 2008) to select sampling
sites with temporal dynamics that best
mimic footprint scale variability.
F↑ (θPOINT)
Second, use land surface modeling (Crow
et al., 2005) and/or an intensive field
campaign (De Rosnay et al. 2009) to
refine understanding of the relationship
between point- and footprint-scale
variability (i.e., F↑ on left).
Up-scaling Challenge:
Using point-scale soil
moisture observations to
validate footprint-scale
SMAP retrievals.
Third, apply triple collocation (Mirrales et al.,
2010) to estimate impact of residual
sampling errors on RMSE validation
results.
*Based on: Crow et al., “Upscaling sparse ground-based soil moisture observations for
the validation of coarse-resolution satellite soil moisture products,” Reviews of
Geophysics, 50, RG2002, doi:10.1029/2011RG000372, 2012.
TJJ–26
Application of Triple Co-Location To Estimate Random
Sampling Error in Sparse Ground Observations
1) Obtain three independent (and uncertain) estimates of footprint-scale
soil moisture:
 RS
 LSM
 SPARSE
Remote Sensing (RS)-SMAP
Land Surface Model (LSM)
Sparse Ground Observation (SPARSE)
2) Assume independent errors and sample the following temporal average
to estimate random sampling error in SPARSE:
SPARSE RS SPARSE LSM   MSESPARSE,TRUE 
3) Use this estimate to correct soil moisture RMSE estimates derived
from RS versus SPARSE comparisons for sampling error in SPARSE.
TJJ–27
Challenge: Scaling Points to Footprints
• Intensive sampling of a limited number of sites?
• Exploit the Rover? How many conditions?
Challenge: Matching Depth to a SMAP
Product
• We all understand why the contributing depth varies with the
wetness and shape of the profile.
• SMAP is only concerned with soil moisture of two layers; 0-5
cm and the root-zone (1 m) (for validation).
• Can COSMOS produce standard depth products?
Challenge: Integrating Networks
• Lots of points that are currently not compatible.
• Still need to address the variable contributing depth issue but
there are more options for matching the depths of other
networks.
• First step: co-location of instruments (i.e MOISST)
USDA-NRCS-Soil Climate Analysis
Network – D. Harms
• Natural Resource Conservation Service
monitoring
• SMAP Soil Moisture (surface and
profile)
• CONUS - 181
• Telemetry and FTP
• Hourly
• Status – Operating and Developing
Measurement
Method
Depths
Soil Moisture
Hydra
5, 10, 20, 50, and 100
cm
Soil Temperature
Hydra
5, 10, 20, 50, and 100
cm
Precipitation
Tipping
Bucket
-
TJJ–31
U.S. Climate Reference Network
M. A. Palecki and J.E. Bell, NCDC
• USCRN observes climate change
• Soil Moisture/Temperature Product Validation
with sparse network
• 114 sites, 20 field calibrated in FY13
• Satellite to NCDC, Internet to SMAP
• 2-3 hours
• Instruments in place, communication in place,
gravimetric sampling of subset planned for
FY13
Measurement Type
Method
Depths (cm)
Soil Moisture
Coaxial Impedance
Dielectric
5,10,20,50,100
Soil Temperature
Thermistor
5,10,20,50,100
Meteorological
Variables (air T,
prec, surface T,
global solar
Platinum resistance
thermometer, weighing
bucket, IR, pyranometer
150
Above Ground
TJJ–32
Challenge: Resolving “Noise”
• Vegetation, atmosphere,….