Global Biophysical Datasets from NASA Missions Steven W
Global Biophysical Datasets from NASA Missions Steven W. Running Univ. Of Montana / USA IPCC – GEOSS Workshop Feb 2, 2011
CEOS ECV (Essential Climate Variables) from GCOS – 138, Aug 2010 • • Albedo Landcover FAPAR LAI Biomass (is NPP better? ) Soil Carbon (from satellite? ) Fire Disturbance Soil Moisture
Thematic standards Common classifiers (Terminology standard) Generic classes (Thematic standard) Mapping Categories (Cartographic standard) LANDCOVER INTERCOMPARISON • Classifiers commonly used to characterize land cover worldwide • i. e. life form & surface type, leaf type & Reference database (GLC 2000) phenology, terrestrial/aquatic • Basic set of standardized classes based on combination of common classifiers and independent of any cartographic standard • i. e. broadleaved evergreen trees, herbaceous crops, built up area • Application of cartographic generalization (MMU) to generic classes Comparative validation & assessment • Definition of mixed categories or using density thresholds • i. e. Closed to open (>15%) broadleaved evergreen forest (> 5 m) Probability
Global Fires for 10 Days 6
MODIS Annual Disturbance Index Mildrexler et al 2009
Global Net Primary Production trend (2000 -2009) Zhao & Running 2010, Science
NPP Anomaly compared to Inverted Atm CO 2 Anomaly R = 0. 81
Global Trend in NPP (1982 – 2009) AVHRR + MODIS with EOS algorithm
Consistency between MODIS NDVI and NPP (1982 -2009) Zhao and Running 2010
Non-Frozen Season Trend (1979 -2008) (SSM/I) Days yr-1 Mean Northern Hemisphere trend
Multi-Year Trend in Estimated Mean Annual ET and P-ET (1983 -2006 ) ET Ø ~73% of the global domain shows a positive ET trend; BUT P-ET Ø ~51% of the domain shows a negative water balance (P-ET) trend.
Global Annual Maximum MODIS Radiometric Surface Temp
Global Flux Tower Network
Aerosol Robotic Network AERONET • • Aerosol Optical Properties Research & Enabling Project • Program of long term systematic network measurements Mission Objectives • Validation of Satellite Aerosol Retrievals • Characterization of aerosol optical properties • Synergism with Satellite obs. , Climate Models Expanding to in situ Ocean Color & possibly total column CO 2
Missions in Formulation and Implementation – 12/2010 OCO-2 2/2013 Global CO 2 ICESat-II 10/2015 Ice Dynamics GLORY 2/2011 Aerosols, TSI SMAP 11/2014 w/CSA Soil Moist. , Frz/Thaw AQUARIUS 6/2011 w/CONAE; SSS GPM 7/2013, 11/2014 w/ JAXA; Precip NPP 10/2011 w/NOAA, Do. D EOS cont. , Op Met. LDCM 12/2012 18 w/USGS; TIRS
Unsustainable groundwater withdrawal Depletion rate 4 cm/yr Groundwater withdrawals as % of recharge, 2002 -2008. Rodell et al Nature 2009
SMAP Science Objectives Soil moisture and freeze/thaw state are primary environmental controls on water mobility and associated constraints to evaporation and Net Primary Productivity Dry Spring Soil Moisture Wet Spring Soil Moisture Mean Thaw Date (SSM/I, 1988 -2001) Summer Air Temperature Anomaly [ºC] Julian Day SMAP measurements of soil moisture and freeze-thaw cycles will provide an integrated measure of critical controls on surface water mobility and associated constraints to ecosystem processes. 20
OCO Measuring CO 2 from Space • Collect NIR spectra of CO 2 and O 2 absorption in reflected sunlight • Retrieve variations in the column averaged CO 2 dry air mole fraction, XCO 2 over sunlit hemisphere Initial Surf/Atm State New State (inc. XCO 2) Generate Synthetic Spectrum • Validate measurements to ensure XCO 2 accuracy of 1 - 2 ppm (0. 3 - 0. 5%) OCO/AIRS/GOSAT Instrument Model Difference Spectra FTS Tower Inverse Model Aircraft XCO 2 Flask
DESDyn. I Radar and Lidar Capabilities for Biomass and Aboveground Carbon Storage L-band Radar – high resolution mapping of low forest biomass and disturbance, extend sensitivity with lidar Multi-beam Lidar – accurate biomass and canopy profiles (along-track) at 25 m resolution, extend spatially with radar Vegetation 3 D Structure & Biomass: Radar and Lidar Vegetation Type Upland conifer Lowland conifer Northern hardwoods Aspen/lowland deciduous Grassland Agriculture Wetlands Open water Urban/barren Terrestrial Carbon Storage and Changes High: 30 kg/m 2 Biomass Low: 0 kg/m 2 22
NRC Decadal Survey Hysp. IRI Visible Short. Wave Infra. Red (VSWIR) Imaging Spectrometer + Multispectral Thermal Infra. Red (TIR) Scanner VSWIR: Plant Physiology and Function Types (PPFT) Map of dominant tree species, Bartlett Forest, NH Red tide algal bloom in Monterey Bay, CA Multispectral TIR Scanner
Linkages between International Programs concerned with Terrestrial Earth Observation 24
LPV Objective & Goals To foster and coordinate quantitative validation of higher level global land products derived from remotely sensed data, in a traceable way, and to relay results so they are relevant to users • To increase the quality and efficiency of global satellite product validation by developing and promoting international standards and protocols for: – – Field sampling Scaling techniques Accuracy reporting Data / information exchange • To provide feedback to international structures (GEOSS) for: – Requirements on product accuracy and quality assurance (QA 4 EO) – Terrestrial ECV measurement standards – Definitions for future missions 25
Focus Groups Focus Group North America Europe / Other Land Cover * Mark Friedl Martin Herold (Boston University) (Wageningen University, NL) Fire* Luigi Boschetti Kevin Tansey (Active/Burned Area) (University of Maryland) (University of Leicester, UK) Biophysical Richard Fernandes Stephen Plummer (LAI*, APAR*) (NR Canada) (Harwell, UK) Crystal Schaaf Gabriela Schaepman (Boston University) (University of Zurich, SW) Land Surface Temperature Simon Hook Jose Sobrino (NASA JPL) (University of Valencia, SP) Soil Moisture* Tom Jackson Wolfgang Wagner (USDA) (Vienna Uni of Technology, AT) Land Surface Phenology Jeff Morisette Jadu Dash (USGS) (University of Southampton, UK) Surface Radiation (Reflectance, BRDF, Albedo*, Snow/Ice*) * ECV Listserv 137 73 72 41 65 48 76 26
KEY FINDINGS • Many global datasets now exist • Need validation and intercomparison amongst sensors • Need to unify formats, gridding, units • Coordinate data distribution • Continuity to new sensors
EXTRA SLIDES
IPCC WORKING GROUP II IMPACTS SUMMARY 2007
CO 2 emissions (Pg. CO 2 y-1) CO 2 emissions (Pg. C y-1) CO 2 Emissions from Land Use Change 1990 s Emissions: 1. 5± 0. 7 Pg. C 2000 -2005 Emissions: 1. 3± 0. 7 Pg. C 2006 -2010: Emissions: 0. 9± 0. 7 Pg. C Friedlingstein et al. 2010, Nature Geoscience; Data: RA Houghton, GFRA 2010
Fire Emissions from deforestation zones (Tg C y-1) Fire Emissions from Deforestation Zones 1400 Global Fire Emissions Database (GFED) version 3. 1 America Africa Asia Pan-tropics 1200 1000 800 600 400 200 0 1997 99 01 200 3 Year 05 07 van der Werf et al. 2010, Atmospheric Chemistry and Physics Discussions 2009
Modelled Natural CO 2 Sinks 0 5 models Land sink (Pg. Cy-1) 2 -2 -4 -6 1960 1970 1980 1990 2000 2010 2 4 models Ocean sink (Pg. Cy-1) 0 -2 -4 -6 1960 Time (y) Updated from Le Quéré et al. 2009, Nature Geoscience
NASA Operating Missions (International Collaboration) 34
Future Orbital Flight Missions – 2010 – 2022 (International contributions) 35
Gravity Recovery & Climate Experiment 500 km orbit 220 km separation Distance accuracy 0. 001 mm
Focus Group Responsibilities • Engage community members (via listserv/website) • Update on progress, relevant meetings • Report back to LPV group on activities, meetings, new products, potential funding mechanisms • Organize at least 1 topical workshop within leadership term • Expand LPV activities, field sites, collaboration globally • Lead product inter-comparison activities • Lead the development and writing of “best practice” land product validation protocols • Define product error definitions for ECV’s, LTDR’s for the climate modeling community 37
Global Water Availability Risk Vorasmairty et al Nature 2010
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