The Soil Moisture Active/Passive (SMAP) Mission: Monitoring Soil Moisture and Freeze/Thaw State

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The Soil Moisture Active/Passive (SMAP) Mission
Monitoring Soil Moisture and Freeze/Thaw State
John Kimball,
NTSG, The University of Montana
Global Vegetation Workshop, June 16-19 2009
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SMAP Science Objectives
SMAP is one of the four first-tier missions
recommended by the NRC Earth Science Decadal
Survey Report

• Primary Science Objectives
• Global, high-resolution mapping of soil moisture
  and its freeze/thaw state to
• Link terrestrial water, energy and carbon cycle
  processes
• Estimate global water and energy fluxes at the
  land surface
• Quantify net carbon flux in boreal landscapes
• Extend weather and climate forecast skill
• Develop improved flood and drought prediction
  capability

Soil moisture and freeze/thaw state are major
constraints to land-atmosphere energy, water
carbon exchange
Source Nemani et al. 2003. Science 300
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SMAP Instrument Mission Overview

• Science Measurements
• Soil moisture and freeze/thaw state
• Orbit
• Sun-synchronous, 6 am/6pm equatorial crossing
• 670 km altitude
• Instruments
• L-band (1.26 GHz) radar
• Polarization HH, VV, HV
• SAR mode 1-3 km resolution (degrades over center
  30 of swath)
• Real-aperture mode 30 x 6 km resolution
• L-band (1.4 GHz) radiometer
• Polarization V, H, U
• 40 km resolution
• Instrument antenna (shared by radar radiometer)
• 6-m diameter deployable mesh antenna
• Conical scan at 14.6 rpm
• incidence angle 40 degrees
• Creating Contiguous 1000 km swath
• Swath and orbit enable 2-3 day revisit

SMAP has significant heritage from Hydros ESSP
mission concept and Phase A studies
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Link Terrestrial Water, Energy and Carbon Cycle
Processes
Water and Energy Cycle
Carbon Cycle
Soil Moisture Controls the Rate of Continental
Water and Energy Cycles
Landscape Freeze/Thaw Dynamics Constrain the
Boreal Carbon Balance
Do Climate Models Correctly Represent the Land
surface Control on Water and Energy Fluxes?
What Are the Regional Water Cycle Impacts of
Climate Variability?
Are Northern Land Masses Sources or Sinks for
Atmospheric Carbon?
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Estimate Global Water and Energy Fluxes at the
Land Surface

• IPCC models currently exhibit large differences
  in soil moisture trends under simulated climate
  change scenarios
• Projections of summer soil moisture change (?SM)
  show disagreements in Sign among IPCC AR4 models

SMAP soil moisture observations will help
constrain model parameterizations of surface
fluxes and improve model performance
Relative soil moisture changes () in IPCC models
for scenario from 1960-1999 to 2060-2099
Li et al., (2007) Evaluation of IPCC AR4 soil
moisture simulations for the second half of the
twentieth century, Journal of Geophysical
Research, 112.
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Quantify Net Carbon Flux in Boreal Landscapes
SMAP will provide important information on
environmental constraints to land-atmosphere
carbon source/sink dynamics. It will provide
more than 8-fold increase in spatial resolution
over existing moderate resolution microwave
sensors.
Annual comparison of pan-Arctic thaw date and
high latitude growing season onset inferred from
atmospheric CO2 concentrations, 1988 2001
Mean growing season onset for 1988 2002 derived
from coarse resolution SSM/I data
McDonald et al. (2004) Variability in springtime
thaw in the terrestrial high latitudes
Monitoring a major control on the biospheric
assimilation of atmospheric CO2 with spaceborne
microwave remote sensing. Earth Interactions
8(20), 1-23.
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Extend Weather and Climate Forecast Skill
Predictability of seasonal climate is dependent
on boundary conditions such as sea surface
temperature (SST) and soil moisture Soil
moisture is particularly important over
continental interiors.
24-Hours Ahead High-Resolution Atmospheric Model
Forecasts
Prediction driven by SST
Difference in Summer Rainfall 1993 (flood) minus
1988 (drought) years
Without Realistic Soil Moisture
Observations
Prediction driven by SST and soil moisture
Buffalo Creek Basin
Observed Rainfall 0000Z to 0400Z 13/7/96 (Chen et
al., 2001)
(Schubert et al., 2002)
With Realistic Soil Moisture
High resolution soil moisture data will improve
numerical weather prediction (NWP) over
continents by accurately initializing land
surface states
-5 0 5
Rainfall Difference mm/day
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Develop Improved Flood and Drought Prediction
Capability
delivery of flash-flood guidance to weather
forecast offices are centrally dependent on the
availability of soil moisture estimates and
observations. SMAP will provide realistic and
reliable soil moisture observations that will
potentially open a new era in drought monitoring
and decision-support.
Decadal Survey
Operational Drought Indices Produced by NOAA and
National Drought Mitigation Center (NDMC)
NOAA National Weather Service Operational Flash
Flood Guidance (FFG)

• Current Status Indirect soil moisture indices
  are based on rainfall and air temperature
• (by county or 30
  km)
• SMAP Capability Direct soil moisture
  measurements global, 3-day, 10 km resolution

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Satellite Global Biospheric Monitoring The
Problem with Clouds
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SMAP Science, Instrument and Mission Requirements
SMAP requirements were developed under Hydros and
refined through extensive community interaction -
The July 07 NASA SMAP Science Workshop confirmed
that these requirements satisfy the SMAP mission
science objectives
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Baseline Science Data Products
Data Product Description
L1B_S0_LoRes Low Resolution Radar so in Time Order
L1C_S0_HiRes High Resolution Radar so on Earth Grid
L1B_TB Radiometer TB in Time Order
L1C_TB Radiometer TB on Earth Grid
L2/3_F/T_HiRes Freeze/Thaw State on Earth Grid
L2/3_SM_HiRes Radar-only Soil Moisture on Earth Grid
L2/3_SM_40km Radiometer-only Soil Moisture on Earth Grid
L2/3_SM_A/P Radar/Radiometer Soil Moisture on Earth Grid
L4_Carbon Carbon Model Assimilation on Earth Grid
L4_SM_profile Soil Moisture Model Assimilation on Earth Grid
Global Mapping L-Band Radar and Radiometer
High-Resolution and Frequent-Revisit Science
Data
Observations Models Value-Added Science Data
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SMAP L4_Carbon product Land-atmosphere CO2
exchange

• Motivation/Objectives Quantify net C flux in
  boreal landscapes reduce uncertainty regarding
  missing C sink on land
• Approach Apply a soil decomposition algorithm
  driven by SMAP L4_SM and GPP inputs to compute
  land-atmosphere CO2 exchange (NEE)
• Inputs Daily surface (lt5cm) soil moisture T
  (L4_SM) GPP (MODIS/NPP)
• Outputs NEE (primary/validated) Reco SOC
  (research/optional)
• Domain Vegetated areas encompassing
  boreal/arctic latitudes (45N)
• Resolution 10x10 km
• Temporal fidelity Daily (g C m-2 d-1)
• Latency Initial posting 12 months post-launch,
  followed by 14-day latency
• Accuracy Commensurate with tower based CO2 Obs.
  (RMSE 30 g C m-2 yr-1).

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Prototype L4_C Product Example
Mean Daily net CO2 Exchange (NEE)
NEE for NSA-OBS Ameriflux Site
C source ()
C sink (-)
L4_C application using MODIS GPP (MOD17) AMSR-E
(SM T) inputs. The graph (above) shows 2004
seasonal pattern of daily NEE for a mature boreal
conifer stand from L4_C, ecosystem model and
tower measurements. SMAP L4_C resolution/sampling
will allow characterization of surface processes
approaching scale accuracy of tower flux
measurements 10km resolution, daily repeat, NEE
30 g C m-2 yr-1 RMSE.
Source Kimball et al. 2009 TGARS 47.
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SMAP Calibration and Validation activities
Pre-launch L4_C Test using MODIS AMSR-E Inputs

• Pre-launch (2009-2013)
• - Development, testing selection of baseline
  algorithms
• - Development of algorithm software test-bed for
  algorithm testing sensitivity studies
• - Verify algorithm sensitivity accuracy
  requirements using available satellite, in situ
  and model based data targeted field campaigns
• - Initialization/calibration/optimization of
  algorithm parameters (e.g. BPLUT, SOC pools)
• Post-launch (2013-2015)
• - Verify product accuracy through focused field
  campaigns and global observation networks
• - Model assimilation based value assessment
  (GMAO, TOPS, CarbonTracker)

Kimball et al. TGARS 2009
Global Biophysical Station Networks
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• Opportunities for Community Involvement
• Community workshops (Events)
• SMAP SDT Working Groups (Team)
• - Algorithms
• - Calibration Validation
• - Applications

http//smap.jpl.nasa.gov/