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Spring Thaw Trend (Days yr -1 , 1988-2007). 0.22. -0.64. An Earth System Data Record for Land Surface Freeze/Thaw State. John Kimball 1 , Kyle McDonald 2 , Youngwook Kim 1 John Lucotch 1 & Joseph Glassy 1 1 The University of Montana 2 Jet Propulsion Laboratory, CalTech.

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  1. Spring Thaw Trend (Days yr-1, 1988-2007) 0.22 -0.64 An Earth System Data Record for Land Surface Freeze/Thaw State John Kimball1, Kyle McDonald2, Youngwook Kim1 John Lucotch1 & Joseph Glassy1 1The University of Montana 2Jet Propulsion Laboratory, CalTech NASA MEaSUREs/PoDAG meeting, Oct 15, 2010

  2. Project Goals and Objectives • Provide a consistent, long-term global record of landscape freeze/thaw (F/T) state dynamics for vegetated regions where frozen temperatures are a major constraint to ecosystem processes: • Distinguish F/T heterogeneity in accordance with mesoscale climate, terrain & land cover features; • Quantify F/T linkages to vegetation productivity and carbon fluxes; • Distinguish “natural” variability from climate change signal; • Establish baseline conditions for future missions (SMAP). Over half of the global land area is affected by F/T cycles that constrain land-atmosphere water, energy & carbon fluxes Freeze-Thaw Affected Regions Frozen Period (Days/yr) Source: Kim et al. 2010. TGARS

  3. Current Results and Output Products Daily Freeze-Thaw Status SSM/I (37GHz, 25km Res.) 2004 • Daily F/T state maps: • - 4 discrimination levels: Frozen (AM & PM), Thawed (AM & PM), Transitional (AM frozen, PM thaw), Inverse-Transitional (AM thaw, PM frozen); • Global domain encompassing F/T affected areas: • - 66 million km2 or 52% of global vegetated area); • Initial 20 year record (Final >30 years) • Detailed metadata on product QA/QC: • - Online documentation; • - Quantitative accuracy metrics (daily); • - Qualitative QA/QC maps (annual); • Quick-Visuals (thumbnails, animations); • Software support (HDFView, Panoply); • 2 data formats (binary, HDF-5) Apr 10 Jul 19 Dec 26 Source: http://freezethaw.ntsg.umt.edu

  4. Global F/T Climatology (1988-2007) Annual Variation Frozen Example FT-ESDR Research Applications Annual Non-Frozen Period Trend (1988-2007) Source: Kim et al. 2010. TGARS

  5. FT-ESDR Development Status • First ATBD release (Jun-09): • Available online: http://freezethaw.ntsg.umt.edu/publications.htm • Baseline seasonal threshold algorithm & single Tb data series; • Planned updates for error budget, data integration and validation; • Recent FT-ESDR releases (Mar/Oct-10 at NSIDC): • AMSR-E global land parameter bundle (2002-2008); • SSM/I based F/T record (1988-2007); • Two more releases planned (FY11/12); • 2 online data archives (NSIDC DAAC, NTSG-ESIP) • Baseline (Tier-1) documentation of FT-ESDR accuracy: • Daily comparisons against global WMO air temperature records (~3700 stations) over homogeneous land areas; • Spatial QA/QC using ancillary data (e.g. DEM, Land cover heterogeneity); • Current product characteristics: • - Global EASE-grid projection; 25-km Res; Daily repeat (AM, PM, CO); 20-yr record (1988-07); derived from SSM/I 37V GHz Tb series; HDF-5 & binary formats. • Product quality: Good(i.e. Validated Stage II based on EOS product maturity guidelines) • -Mean annual F/T classification accuracy >80% relative to WMO station observations (Tair).

  6. FT-ESDR Algorithm Baseline Pixel-wise Calibration using Tmx/Tmn from Global Reanalysis Seasonal Threshold Approach: Annual Definition of SSM/I (37V GHz) Tb F/T Reference States Frozen Non-Frozen Source: Kim et al. 2010. Developing a global record of daily landscape freeze/thaw status using satellite passive microwave remote sensing. IEEETGARS, DOI: 10.1109/TGRS.2010.2070515.

  7. Baseline (Tier-1) FT-ESDR Validation & QA/QC Spatially Explicit Quality Assessment Global Comparisons with WMO Daily Air Temperature Observations Cross-channel F/T classification assessment Source: Kim et al. 2010. TGARS

  8. Secondary (Tier-2) FT-ESDR Validation • Focused studies over intensive sub-regions: • Sub-grid scale terrain & land cover heterogeneity effects; • F/T sensitivity to individual landscape elements (snow, soil, vegetation); • Leverage planned NASA field campaigns involving synergistic measurements (CARVE, SMAP). • Comparisons with other synergistic datasets: • Atm. CO2 anomalies, Satellite based snow cover extent, GPP/NPP, NDVI & LST. FT-ESDR Spring Thaw & 1Snow Cover Extent Anomalies over Northern (>50ºN) Domain r = 0.64, p<0.001 1Source: D.A. Robinson (http://climate.rutgers.edu/snowcover)

  9. ≥ 39 Enhanced FT-ESDR Development & Validation Mean annual F/T Classification Accuracy • Cross-sensor F/T comparisons: • Document F/T differences between overlapping sensor records: SSM/I, SMMR, AMSR-E, ASCAT, SeaWinds, SMOS; • Utilize multiple sensor records for FT-ESDR production (e.g. empirical & forward process models, data assimilation); • Goal: Document & exploit synergies among multiple satellite records/frequencies/polarizations to enhance FT-ESDR information, accuracy and QA/QC. SMMR/SSM/I: 37V GHz AMSR-E: 36V GHz SeaWinds: 13 GHz 2007 frozen period difference between SSM/I and AMSR-E

  10. Climate Change Monitoring of extent, seasonal-annual variation & trends in frozen/non-frozen period Human Health climate sensitive infectious disease distribution and change, vector habitat change Agriculture Frost status/potential, growing season and potential yield Potential FT-ESDR Research Applications Forests phenology, productivity, carbon source/sink activity, cold hardiness, vegetation stress & forest ecoregions Water Resources snow cover status and frozen soils monitoring, timing of ice breakup and formation in rivers and lakes Weather, Natural Hazards Weather forecasting, runoff and flood risk potential Species and Habitats Shift in ecological zones, habitat change

  11. Potential FT-ESDR User Community Primary Thaw Date vs Spring Flood Pulse, Yukon Basin, AK Example FT-ESDR Cryosphere & Hydrology Applications: Primary Spring Thaw Date vs Spring River Ice Breakup on Tanana River AK

  12. 1 Potential FT-ESDR User Community Example Agriculture Application: 2Soybean Harvested Acres 2007 2007 Spring Frost Index Source: 1http://www.nass.usda.gov/Statistics_by_Subject/index.php 2http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_Maps/Crops_and_Plants/index.asp

  13. Potential FT-ESDR User Community Example FT-ESDR Carbon Cycle & Ecosystems Application:

  14. http://freezethaw.ntsg.umt.edu Potential FT-ESDR User Community • Diverse User Community: • - Decadal Survey mission teams (SMAP) • - Cryosphere • - Ecosystems & Carbon Cycle • - Hydrology • - Global Change • - Atmosphere and Climate • Community ID & Interaction: • Literature search • Publications • “Dear Colleague” letters • - Workshop presentations • FT-ESDR user metrics • User “feedback” • SMAP SDT/WG activities

  15. User Identification Through FT-ESDR 1Metrics Reporting 1Preliminary results based on NTSG-ESIP statistics from Jun-Aug, 2010.

  16. FT-ESDR User Community Support • Project website with online data archives, documentation & metadata • - Embedded links to NSIDC archives & similar or synergistic data products; • Publication of methods, data & software • - Peer-review journal publications; • Public data archives (NSIDC DAAC, NTSG-ESIP); • Data links through existing community data portals (NACP); • “Dear Colleague” invitations for data download & feedback • SMAP SDT involvement: • - Baseline Info. for planned L3_F/T product development; • - F/T inputs for other product retrievals (L3/4_SM & L4_C); • - Cal/Val & Applications WGs; • Development, publication, distribution of synergistic data bundles (AMSR-E) • - FT-ESDR used as a frozen T constraint for production of higher-order AMSR-E product retrievals: Inundated area, Soil Moisture, Air Temperature, Water Vapor & VOD; • - AMSR-E science team support;

  17. FT-ESDR Project Summary • Three planned FT-ESDR data releases: • - Initial data release (FY10: 20 yr record [1988-07]) & transfer to NSIDC completed; • - Additional F/T data release with AMSR-E land product bundle (2002-08); • - Two more releases planned for FY11/12 (up to 33 yr record [1979-011]); • Metrics reporting initiated for both NSIDC & NTSG-ESIP archives; • Product Maturity: Good (i.e. validated, Stage 2 based on EOS product maturity guidelines) • - Mean annual F/T classification accuracy >80% relative to ~3700 WMO stations; • Accuracy adequate for broad set of science applications: climate change, cryosphere, hydrology, ecosystems & C cycle; • Methods publication (Kim et al. 2010. IEEETGARS); • Product readiness to support next wave of IPCC activity: Good • Work in progress: • Comparison & use of multiple sensor records for improved information & development of longer F/T record; • Detailed algorithm error budget development; • Validation (Stage 3) & QA/QC;

  18. BACKUP SLIDES

  19. Product Maturity Definitions Source: http://nsidc.org/data/docs/daac/ae_land3_l3_soil_moisture.gd.html

  20. Data for FT-ESDR Production and Validation

  21. Data Volume in GB (Jun-Aug 2010) 80 70 60 50 40 30 20 10 0 Total FT-ESDR AMSR-E FT-ESDR User Community Statistics Example user metrics from NTSG-ESIP archive Daily Users Distinct Users by Class

  22. Cross Sensor F/T Comparisons 2004 Non-Frozen Season from SSM/I, AMSR-E & SeaWinds

  23. Potential FT-ESDR User Community Example FT-ESDR Ecosystems Application: Annual NPP (MOD17) vs FT-ESDR Spring Thaw Timing Anomalies

  24. 1 Potential FT-ESDR User Community Example Agriculture Application: 2Corn Harvested Acres 2007 2007 Spring Frost Index Source: 1http://www.nass.usda.gov/Statistics_by_Subject/index.php 2http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_Maps/Crops_and_Plants/index.asp

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