Soil MoistureActive Passive (SMAP)Mission: a NASA Opportunity

Robert Gurney University of Reading

WIF Workshop17th October 2012

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

L-band Active/Passive Soil Moisture Mapping

• Soil moisture retrieval algorithms are derived from a long heritage of microwave modeling and field experiments

MacHydro’90, Monsoon’91, Washita92, Washita94, SGP97, SGP99, SMEX02, SMEX03, SMEX04, SMEX05, CLASIC, SMAPVEX08, CanEx10, SMAP-Ex3

• Radiometer - High accuracy (less influenced by roughness and vegetation) but coarser spatial resolution (40 km)

• Radar - High spatial resolution (1-3 km) but more sensitive to surface roughness and vegetation

• Combined Radar-Radiometer product provides intermediate resolution and intermediate accuracy to meet science objectives

The synthetic antenna measures the passive L- band emission of the Earth’s surface every three days at a resolution of 40km, allowing the system to focus on different points on the Earth’s surface and, as the satellite moves, examine areas at a range of angles. The emission is then used to estimate soil moisture and ocean salinity.

ESA’s SMOS (Soil Moisture and Ocean Salinity) missionlaunched on November 2nd, 2009

2011 US drought as measured by SMOS and USDA

Mean soil moisture estimates from SMOS over the period January – July 2011

The US Department of Agriculture combines a number of data sources to produce the Drought Monitor, indicating drought severity.

Mississippi Floods, April/May 2011

Levees demolished, causing a muddy torrent surge into the Illinois plains.

Cumulative precipitation for April 2011

26th April 8th May3rd May

Illinois flooded over 200 sq. miles, 100 homes affected

SMOS soil moisture

The increased nutrient pollution is likely to substantially enlarge The Gulf of Mexico’s hypoxic “dead zone”.

The effect of lower rainfall on the UK

…a 3.7% absolute reduction in mean April soil moisture between 2010 and 2011, compared to a 2010 mean of around 15%

An unusually dry March and April in 2011 caused…

Projected launch November 1st, 2014

The SMAP system is similarly specified to SMOS in most respects, but uses a simpler fixed passive microwave antenna allowing only one angle of the ground to be viewed, but it has an additional active radar antenna which will enable higher resolution measurements down to 1-3km.

NASA Soil Moisture Active/Passive mission

SMAP

SMAP Science Applications

SMAP measurements of soil moisture and freeze/thaw state address a wide range of Earth science applications

SMAP will provide high-resolution and frequent-revisit global observations of soil moisture and freeze/thaw state

Soil moisture is defined in terms of volume of water per unit volume of soil.

Freeze/thaw state is defined as the phase of the water contained within the landscape including soil and vegetation.

Surface soil moisture [cm3 /cm3 ]

NRC Earth Science Decadal Survey Report, 2007

3-day mapping coverage

Frozen Landscape

SMAP Science Requirements

Requirement Hydro-Meteorology

Hydro-Climatology

Carbon Cycle

Baseline Mission Minimum MissionSoil

MoistureFreeze/Thaw

Soil Moisture

Freeze/Thaw

Resolution 4–15 km 50–100 km 1–10 km 10 km 3 km 10 km 10 km

Refresh Rate 2–3 days 3–4 days 2–3 days(a) 3 days 2 days 3 days 3 days

Accuracy 0.04-0.06 (c) 0.04-0.06 80–70% (b) 0.04 80% 0.06 70%(a) North of 45N latitude (b) Percent classification accuracy (binary freeze/thaw) (c) Volumetric water content, 1-σ in [cm3/cm3] units

Key Level 1 Requirements (Derived from science objectives)

Decadal Survey Objective Application Science RequirementWeather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology

Climate PredictionBoundary and Initial Conditions for Seasonal Climate Prediction Models

HydroclimatologyTesting Land Surface Models in General Circulation Models

Drought and Agriculture Monitoring

Seasonal Precipitation PredictionHydroclimatologyRegional Drought Monitoring

Crop Outlook

Flood Forecast ImprovementsRiver Forecast Model Initialization HydrometeorologyFlash Flood Guidance (FFG)NWP Initialization for Precipitation Forecast

Human Health

Seasonal Heat Stress Outlook HydroclimatologyNear-Term Air Temperature and Heat Stress Forecast HydrometeorologyDisease Vector Seasonal Outlook HydroclimatologyDisease Vector Near-Term Forecast (NWP) Hydrometeorology

Boreal Carbon Freeze/Thaw Date Freeze/Thaw State

SMAP data will improve numerical weather prediction (NWP) over continents by more accurately initializing land surface states

Major operational weather centers linked to SMAP:

ECMWF

EnvironmentCanada

NOAAClimateAir Force

Weather

NOAAWeather

SMAP Soil Moisture Applications

SMAP will provide 10 km soil moisture data product to help meet operational user needs

Radar-Observed Rainfall (Caused Flash-Flood)0000Z to 0400Z 13/7/96 Without Realistic Soil Moisture

With Realistic Soil Moisture24-Hours Ahead Atmospheric Model Forecasts Buffalo

Creek, CO

SMAP Mission Concept• Contiguous 1000 km swath with 2-3 days

revisit (8 day repeat)

• Sun-synchronous 6am/6pm orbit (680 km)

• Launch November 2014

• Mission duration 3 years

Nadir gap in high res radar data (~300 km)

• 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 across swath

SMAP Science Data Products

* Over outer 70% of swath.** The SMAP Project will make a best effort to reduce the data latencies beyond those shown in this table.

Product Description Gridding (Resolution)

Latency**

L1A_Radiometer Radiometer Data in Time-Order - 12 hrs

Instrument Data

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 hrsScience Data (Half-Orbit)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

Science Data (Daily

Composite)

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 Science Value-AddedL4_C Carbon Net Ecosystem Exchange (NEE) 9 km 14 days

Latency of SMAP Instrument Data

Proactive Engagement on Applications

SMAP leading the way and deeply engaged in realizing the applied science potential of the missionActions:• Developed an Applications Plan • Formed Applications Working Group (AppWG) to engage

community• Appointed a SMAP Applications Coordinator• Formed three levels of engagement with applications

partners (1. Workshops, 2. Tutorials and 3. Focus Groups)• So far two SMAP Applications workshops hosted by

applications partners (NOAA and USDA)• Released calls for Early-Adopters (total of 50 applied) to

engage with SDT and project to demonstrate value of SMAP data to their decision support systems early on

• Co-organize two workshops on applications across Decadal Survey missions (SMAP-ICESat2-AirMOSS and SMAP-GPM-GRACE/FO-SWOT-CARVE)

SMAP’s Proactive Applications Approach Deemed a “Best Practice” in Recent NRC Mid-Term Report

“BOX 2.2 SMAP Mission Applications Engagement: A Best Practice”

“SMAP is implementing a strategy that promotes applications researchand engages a broad community of users in SMAP applications.”

“The [Applications Workshops] make itclear that the project is reaching out to its identified end users and looking for ways to entrain even more of them.”

Science Definition Team (SDT) (ROSES)

K. McDonald (JPL)J. van Zyl (JPL)R. Koster (GSFC)R. Reichle (GSFC)W. Crow (USDA)S. Moran (USDA)T. Jackson (USDA)J. Johnson (Ohio St U)J. Kimball (U Mont)M. Moghaddam (U So Cal)J. Shi (UCSB)L. Tsang (U Wash)

S. Belair (Canada)P. de Rosnay (UK)R. J. Gurney (UK)Y. Kerr (France)S. Paloscia (Italy)J. Walker (Australia)

Project ScientistE. Njoku (JPL)

Deputy Project ScientistP. E. O’Neill (GSFC)

Science Team LeaderD. Entekhabi (MIT)

Working Groups:1. Applications2. Algorithms3. Cal/Val 4. RFI

Inte

rnat

iona

l

Applications Coordinator

Molly Brown and Vanessa Escobar

(GSFC)

Science Organization