Entekhabi, D.

Njoku, E.

ONeill, P.

NASA Technical Reports Server

Anticipated Impacts of Soil 
Moisture Active Passive 
(SMAP) Mission 
Measurements on 
Hydrologic Applications
The SMAP Science Definition 
Team (SDT)
Remote Sensing and Hydrology 
2010 Symposium (IAHS)
September 2010
https://ntrs.nasa.gov/search.jsp?R=20110011778 2019-08-30T15:46:52+00:00Z
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Talk Outline
1. SMAP mission and the Earth Science Decadal Survey 
2. Traceability of measurement requirements to hydrologic applications
3. Pathways of soil moisture influence on weather and climate
4. Applications to:
 Drought monitoring and seasonal climate prediction
 Water availability from snowmelt outlooks
 Flood monitoring and forecasting
5. Data products and latencies
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
US National Research 
Council Report: “Earth 
Science and Applications 
from Space: National 
Imperatives for the next 
Decade and Beyond”
(National Research Council, 
2007) http://www.nap.edu
SMAP is one of four missions 
recommended by the NRC “Decadal 
Survey” for launch in the 2010–2013 
time frame
Tier 1: 2010–2013 Launch
Soil Moisture Active Passive (SMAP)
ICESAT II
DESDynI
CLARREO
Tier 2: 2013–2016 Launch
SWOT
HYSPIRI
ASCENDS
GEO-CAFE
ACE
Tier 3: 2016–2020 Launch
LIST
PATH
GRACE-II
SCLP
GACM
3D-WINDS
Project/Mission Overview—Mission Context
• Feb 2008: NASA announces start of SMAP project
• SMAP is a directed-mission with heritage from Hydros 
• Hydros risk-reduction performed during Phase A 
(instrument, spacecraft dynamics, science, ground system)
Cancelled 2005 due to NASA budgetary constraints
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Requirement Hydro-Meteorology
Hydro-
Climatology
Carbon 
Cycle
Baseline Mission
Soil 
Moisture Freeze/Thaw
Resolution 4–15 km 50–100 km 1–10 km 10 km 3 km
Refresh Rate 2–3 days 3–4 days 2–3 days(1) 3 days 2 days(1)
Accuracy 4–6% ** 4–6%** 80–70%* 4%** 80%*
(*) % classification accuracy (binary Freeze/Thaw) 
(**) [cm3 cm-3] volumetric water content, 1-sigma
Science Requirements 
(1)North of 45N latitude
DS Objective Application Science Requirement
Weather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology
Climate Prediction
Boundary and Initial Conditions for Seasonal Climate Prediction 
Models Hydroclimatology
Testing Land Surface Models in General Circulation Models
Drought and 
Agriculture 
Monitoring
Seasonal Precipitation Prediction
HydroclimatologyRegional Drought Monitoring
Crop Outlook
Flood Forecast 
Improvements
River Forecast Model Initialization HydrometeorologyFlash Flood Guidance (FFG)
NWP Initialization for Precipitation Forecast
Human Health
Seasonal Heat Stress Outlook Hydroclimatology
Near-Term Air Temperature and Heat Stress Forecast Hydrometeorology
Disease Vector Seasonal Outlook Hydroclimatology
Disease Vector Near-Term Forecast (NWP) Hydrometeorology
Boreal Carbon Freeze/Thaw Date Freeze/Thaw State
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
5
Global mapping of Soil Moisture and Freeze/Thaw state to:
− Understand processes that link the terrestrial water, energy & carbon cycles
− Estimate global water and energy fluxes at the land surface
− Quantify net carbon flux in boreal landscapes
− Enhance weather and climate forecast skill
− Develop improved flood prediction and drought monitoring capability
Mission Science Objective
Primary Controls on Land 
Evaporation and Biosphere 
Primary Productivity
Freeze/
Thaw
Radiation
Soil 
Moisture
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Dry Soil
Moist Soil
5°C
Dry 
Surface
Moist  
Surface
Deep 
Mixing up 
to 1.5 Km 
Altitude
Shallow 
Mixing to 
1.0 Km
May 10 Dry soil, clear, mild winds. (LE≈H) 
May 18 90 mm Rain
May 20 Moist soil, clear, mild winds. (LE>H) 
Pathways of Land Surface Influence 
on Weather and Climate
CASES’97 Field Experiment, 
BAMS, 81(4), 2000.
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Source: Cahill et al., J. Appl. Met., 38
Key Determinants of Land Evaporation
Latent heat flux 
(evaporation) links the 
water, energy, and carbon
cycles at the surface. 
Closure relationship, yet 
virtually unknown.
Lack of knowledge of soil 
moisture control on 
evaporation causes 
uncertainty in land surface 
and atmospheric models.
pE
E
=β
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
NOAH
CLM
What Do We Do Today?
Dirmeyer et al., J. Hydromet., 7, 
1177-1198, 2006
Atmospheric model 
representations of this 
function are 
essentially “guesses”, 
given scarcity of soil 
moisture and 
evaporation data.  
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Identification of Drought
American Meteorological Society (AMS) 
Statement
Drought is often grouped into four basic types: 1) 
meteorological, 2) agricultural, 3) hydrological, and 
4) socioeconomic. 
Meteorological drought … magnitude [and 
duration] of a precipitation shortfall
Agricultural drought is largely the result of a deficit 
of soil moisture…
Hydrological droughts are concerned with shortfall 
on surface or subsurface water supply…Rootzone, 
vegetation and streams response
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
The Standardized 
Precipitation Index (SPI) 
for July 2010.
Palmer Drought Severity 
Index (PDSI)  
for July 2010.
Drought and Soil Moisture
Agricultural drought (deficit of soil moisture) cannot necessarily be inferred 
from precipitation deficit.
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
“Compared with the WWII drought, multi-year 
averages of rainfall and subsurface soil moisture 
during the Big Dry are not as low, but the 
sensitivity of soil moisture to rainfall decline is 
over 80% higher. 
We show that a relationship exists between 
subsurface soil moisture variations and 
fluctuations of temperature not associated with 
rainfall over eastern Australia in all seasons, and 
over SEA in austral spring and summer. “
Root-zone soil moisture dynamics may contribute 
to prolonged drought conditions.
Conditions are similar to those expected under 
global change.
Cai et al., 2009: Rising temperatures depletes soil moisture and exacerbates severe 
drought  conditions across southeast Australia, Geophy. Res. Letters, 36.
Role of Root-Zone Soil Moisture in 
Drought Duration and Climate Change Impacts
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Multi-model consensus view 
of land contribution to air 
temperature forecasts.
JJA Skill contribution at the 
30-day lead (days 31-45).  
From: Final Report of GLACE-2: 
Quantifying the Effects of Land 
Moisture Initialization on Precipitation 
Forecasts (PI: Randal Koster, 2010)
All 15-day averaging periods
Periods with soil moisture in 
top and bottom quartiles
Seasonal Climate Prediction
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Seasonal Climate Prediction  
Fischer et al. (2007), J. of Climate, 20.
European heatwave cause 
35,000 deaths, 
New Scientist, Oct. 2003.
Seasonal Climate Prediction:
50 km Resolution
Initialize rootzone moisture
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Notaro, M., 2008: Statistical identification of global hot spots in soil moisture 
feedback among IPCC AR4 models, J. Geophys. Res., 113.
Mean Summer (JJA) soil 
moisture feedback parameter on 
precipitation among 19 IPCC 
models [cm/month]
Same for Winter (DJF) 
Future Climate and Water Cycle: Soil moisture influence on precipitation intensifies the regional 
water cycle response to global change. 
Global average monthly 
precipitation over land is 
~8 cm/month 
Global Change and Water Cycle
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Water Availability from Snowmelt
Linear regression analysis examining observed 
streamflow, snow, climate and soil moisture:
“This study demonstrates that 
available macroscale estimates 
of soil moisture have the 
potential to enhance 
streamflow prediction...”
(Berg and Mulroy, Hydro. Sci., 
51, 642-654, 2006) 
\
Synthetic analysis showing where soil 
moisture initialization may improve 
streamflow prediction at seasonal 
timescales.  Results are supported by 
available streamflow observations.  
(Mahanama et al., in preparation)
Soil moisture information can contribute skill to streamflow forecasts
\
Contribution (r2) of Jan. 1 
soil moisture initialization to 
MAM streamflow prediction. 
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Koster et al., 2010: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and 
snow”, Nature-Geoscience, in press.
May-July 
streamflow 
forecasts
Soil Moisture Information Enhances Water 
Resource Availability Predictions
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Flood Applications: The Forecast 
and Monitoring Chain
1) Characterization of pre-storm soil moisture
2) Accurate real-time rainfall monitoring (in large basins)
3) Numerical weather prediction of extreme rainfall
4) Monitoring inundation
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Characterization of Pre-Storm Soil Moisture
Current: Empirical soil moisture indices based on filtering precipitation time-
series at county resolution (~50 km)
Future: Direct observations: SMAP at 10 km
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Characterization of Pre-Storm Soil Moisture
( >302 km2 MOPEX Basins in Southern US)
Red – Remote 
Sensing Only 
(TRMM TMI)
Black – Model 
Only
Blue – Remote 
Sensing/ Model 
KF Combined
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Red – Remote 
Sensing Only 
(TRMM TMI)
Black – Model 
Only
Blue – Remote 
Sensing/ Model 
KF Combined
Characterization of Pre-Storm Soil Moisture
( >302 km2 MOPEX Basins in Southern US)
SMAP will:
• Lead to more added skill.
(Here: X-band, SMAP: L-band)
• Allow for implementation in finer-
scale basins. 
(Here: >1000 km2, SMAP: >100 km2)
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
TRMM 3B40RT
AMSRE USDA
Accurate Rainfall Monitoring
Kalman Filtering
Crow et al. (2009), JHM, 10(1), 199-212.
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Improvement in TRMM 3B40RT 3-day accumulation skill
Accurate Rainfall Monitoring
Crow et al. (2009), JHM, 10(1), 199-212.
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Improvement in TRMM 3B40RT 3-day accumulation skill
Crow et al. (2009), JHM, 10(1), 199-212.
Accurate Rainfall Monitoring
SMAP will:
• Enhance correction in vegetated areas. (Here: 
X-band, SMAP: L-band)
•Allow for implementation at finer space scales. 
(Here: ~10,000 km2, SMAP: 100 km2)
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Prediction of Extreme Rainfall
NEXRAD Observed Rainfall
0000Z to 0400Z 13/7/96
With Antecedent Soil Moisture24-Hours ahead 
atmospheric model 
forecastsBuffalo 
Creek
Basin
With Climatological Soil Moisture
Flash flood event near Fort Collins
July 13, 1996
Chen et al. (2001), JAS, 58, 3204-3223.
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Inundation detection 
using dual-polarization 
QuikSCAT backscatter 
data. Shades of blue on 
land represent 
inundation
[Form Son Nghiem, JPL]
hh
vv
σ
σ
γ =
SMAP provides 3 km resolution dual-polarization 
radar data with 2-3 days revisit (all-weather and 
regardless of illumination)
Monitoring Inundation
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
In situ Soil Moisture Network Coverage:Adequate?
Significant spatial variability between 
point measurements !
10 km Scale
An airborne campaign 
US SGP
SMAP Mission Concept
• L-band unfocused SAR and radiometer 
system, offset-fed   6 m light-weight 
deployable mesh reflector. Shared feed for
 1.26 GHz dual-pol Radar at 1-3 km (30% 
nadir gap) 
 1.4 GHz polarimetric Radiometer at 40 km
• Conical scan, fixed incidence angle across 
swath
• Contiguous 1000 km swath with 2-3 days 
revisit
• Sun-synchronous 6am/6pm orbit (680 km)
• Launch November 2014
• Mission duration 3 years 
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
L-band Active/Passive Assessment
• 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
• 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 optimal blend of 
resolution and accuracy to meet 
science objectives
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Product Short Description Resolution Latency
L1A_S0 Radar raw data in time order – 12 hours
Instrument Data
L1A_TB Radiometer raw data in time order – 12 hours
L1B_S0_LoRes Low resolution radar σo in time order 5x30 km 12 hours
L1B_TB Radiometer TB in time order 36x47 km 12 hours
L1C_S0_HiRes High resolution radar σo 1-3 km 12 hours
L1C_TB Radiometer TB 36 km 12 hours
L2_SM_A Soil moisture (radar) 3 km 24 hours
Science Data 
(Half-Orbit)
L2_SM_P Soil moisture (radiometer) 36 km 24 hours
L2_SM_A/P Soil moisture (radar/radiometer) 9 km 24 hours
L3_F/T_A Freeze/thaw state (radar) 3 km 36 hours
Science Data 
(Daily Composite)
L3_SM_P Soil moisture (radiometer) 36 km 36 hours
L3_SM_A/P Soil moisture (radar/radiometer) 9 km 36 hours
L4_SM Soil moisture (surface & root zone) 9 km 7 days Science
Value-AddedL4_C Carbon net ecosystem exchange (NEE) 9 km 14 days
SMAP Data Products
National Aeronautics and 
Space Administration
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California
Interested in joining the SMAP Working Group?
• Sign up at http://smap.jpl.nasa.gov/science/wgroups
1. Algorithms Working Group (AWG)
2. Calibration & Validation Working Group (CVWG)
3. Radio-Frequency Interference Working Group (RFIWG)
4. Applications Working Group (ApWG)


Anticipated Impacts of Soil Moisture Active Passive (SMAP) Mission Measurements on Hydrologic Applications

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