7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada National Aeronautics and Space Administration http:// smap.jpl.nasa.gov Utilization of Ancillary Data Sets for SMAP Algorithm Development and Product Generation IGARSS’11, Vancouver, BC July 27, 2011 Peggy E. O’Neill, NASA GSFC Erika Podest, JPL Eni G. Njoku, JPL
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7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada National Aeronautics and Space Administration Utilization of.
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7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
National Aeronautics and Space Administration http://smap.jpl.nasa.gov
Utilization of Ancillary Data Sets for SMAP
Algorithm Development and
Product Generation
IGARSS’11, Vancouver, BCJuly 27, 2011
Peggy E. O’Neill, NASA GSFCErika Podest, JPLEni G. Njoku, JPL
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
BACKGROUND
• SMAP is a planned NASA Earth Science Decadal Survey Mission
• Launch currently scheduled for October 2014 into a 6 am / 6 pm sun-synchronous orbit
• Will use an L-band radar & radiometer to measure global soil moisture & freeze/thaw every 2-3 days
• Baseline SMAP data products include:
-- radar-derived F/T at 3 km resolution
-- radiometer-only SM at 40 km resolution
-- combined radar/radiometer SM at 9 km resolution
-- value-added products (root zone SM, carbon NEE) at 9 km
• All SMAP products output on nested 1, 3, 9, 36 km EASE grids
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Product Short Description Resolution/Grid
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) [research product] 3 km 24 hoursScience 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_SM_A Soil moisture (radar) [research product] 3 km 50 hours
Science Data (Daily Composite)
L3_F/T_A Freeze/thaw state (radar) 3 km 50 hours
L3_SM_P Soil moisture (radiometer) 36 km 50 hours
L3_SM_A/P Soil moisture (radar/radiometer) 9 km 50 hours
L4_SM Soil moisture (surface & root zone) 9 km 7 days ScienceValue-AddedL4_C Carbon net ecosystem exchange (NEE) 9 km 14 days
SMAP Data Products
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Algorithm Needs
• All baseline SMAP products have associated algorithm(s) which require a variety of ancillary data to meet retrieval accuracies:
-- 0.04 cm3/cm3 for soil moisture within SMAP land mask
-- 80% classification accuracy for binary F/T in boreal latitudes
• Areas of snow/ice, frozen ground, mountainous topography, open water, urban areas, and dense vegetation (> 5 kg/m2) are excluded from SM accuracy statistics • Static ancillary data do not change during mission
• Dynamic ancillary data require periodic updates ranging from daily
to seasonally
-- soil T, precipitation, vegetation, surface roughness, land cover
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Ancillary Parameters
1 Soil Temperature2 Surface Air Temperature3 Vegetation Water Content
(VWC)
4 Sand & Clay Fraction5 Urban Area6 % Permanent Open Water7 Crop Type8 Land Cover Class9 Precipitation
10 Snow11 Mountainous Area [DEM]12 Permanent Ice13 b, ω, & τ Vegetation Parameters14 h Roughness Parameter
Table 1. Ancillary Parameters • 14 ancillary data parameters identified as needed by one or more SMAP algorithms
• choice of source of each parameter driven by:
-- availability
-- ease of use
-- inherent error
-- latency
-- temporal & spatial resolution
-- global coverage
-- positive impact on SMAP retrieval accuracies
-- compatibility with SMOS choices
• choices documented in a SMAP Ancillary Data Report for each parameter
• data from each primary source will be used now in pre-launch simulations
• choices will be revisited as new information becomes available
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Soil Temperature
Accuracy of synchronized NWP forecast surface soil temperature compared against in situ temperatures for the Oklahoma Mesonet for 2004 and 2009.
SMAP 6 am descending orbit • SMAP soil moisture products will be retrieved using data from the 6 am descending orbits
• the 6 am 0-5 cm TS is the most dynamic
ancillary parameter needed -- it is updated every orbit for each location
• SMAP error budgets currently carry 2 K as the error in ancillary TS
• data from the Oklahoma Mesonet indicates
that at the 6 am overpass time, all NWP TS products have errors just below 2 K
• initial global estimates of NWP TS error
against in situ point measurements are less optimistic, more in the range of 2.5 – 3.0 K; analysis on global TS error is continuing
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Vegetation Water Content
Annual climatology of NDVI for Walnut Creek, IA
snow
• a new 10-year (2000-2010) MODIS NDVI climatology has been created at 1 km resolution
globally
• VWC calculated using NDVI-based water contributions from both foliage and stem components, adjusted for IGBP land cover classes
VWC (kg/m2) over the continental U.S. for the month of July on a 1-km EASE grid as constructed from a 10-year MODIS NDVI climatology and land cover products.
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Soil Texture
• soil sand & clay fraction needed by dielectric models used in SM retrieval
• best available source used for any given region
• resulting global map a combination of different data sets
• potential for discontinuities at data set boundaries (e.g., US / Canada)
Global sand fraction at 0.01 degree resolution based on a composite of FAO, HWSD, STATSGO, NSDC, and ASRIS datasets using best available source for a given region.
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Urban Areas
• GRUMP urban data (Columbia U.) gridded to SMAP 9 km EASE grid
• better delineation between urban & rural areas
• urban fraction > 0.5 shown
• however, urban flag likely to be set much lower since TB cannot be
corrected for presence of urban areas
Global Rural-Urban Mapping Project
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Open Water Fraction
• use SMAP HiRes radar to determine open water fraction
• a 3 dB threshold is applied to HH to VV ratio to distinguish water from land
• this SMAP parameter can be supplemented by static permanent water body data sets like MODIS MOD44W and JERS-1/PALSAR (for boreal latitudes)
• the water fraction is then used to correct TB for a mix of land & water in the
grid cell
Partial UAVSAR ratio image of Mono Lake. ~7% detection error
Open water (both permanent & transient)
in a SMAP footprint is a potential large
error source for SMAP retrieval algorithms if
its presence is not detected & corrected for
7/27/11 Peggy O’Neill, NASA GSFC IGARSS’11, Vancouver, BC, Canada
Topography / DEM
JPL Global DEM
-- compiled from different sources
-- 1 arc-secondresolution
-- GMTED2010 will eventually replace GTOPO30
-- above will be useful in assessing any discontinuities between existing data sets
-- elevation and slope variance (TBC) could be used to set topography flag
Input Data Set: US SRTM SRTM GTOPO Alaska DEM Canada DEM
Coverage: United States 56 °S to 60 °N Global Alaska Canada