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0.22 Spring Thaw Trend (Days yr -1, 1988-2007) -0.64 An Earth System Data Record for Land Surface Freeze/Thaw State John Kimball 1, Kyle McDonald 2, Youngwook.

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Presentation on theme: "0.22 Spring Thaw Trend (Days yr -1, 1988-2007) -0.64 An Earth System Data Record for Land Surface Freeze/Thaw State John Kimball 1, Kyle McDonald 2, Youngwook."— Presentation transcript:

1 0.22 Spring Thaw Trend (Days yr -1, 1988-2007) -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 NASA MEaSUREs/PoDAG meeting, Oct 15, 2010

2 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 Source: Kim et al. 2010. TGARS Freeze-Thaw Affected Regions Frozen Period (Days/yr) Project Goals and Objectives

3 Apr 10 Jul 19 Dec 26 Daily Freeze-Thaw Status SSM/I (37GHz, 25km Res.) 2004 Source: 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 km 2 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) Current Results and Output Products

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

5 FT-ESDR Development Status First ATBD release (Jun-09): - Available online: - Baseline seasonal threshold algorithm & single T b 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 T b 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 (T air ).

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

7 Source: Kim et al. 2010. TGARS 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

8 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. CO 2 anomalies, Satellite based snow cover extent, GPP/NPP, NDVI & LST. Secondary (Tier-2) FT-ESDR Validation FT-ESDR Spring Thaw & 1 Snow Cover Extent Anomalies over Northern (>50ºN) Domain r = 0.64, p<0.001 1 Source: D.A. Robinson (

9 Enhanced FT-ESDR Development & Validation Mean annual F/T Classification Accuracy 2007 frozen period difference between SSM/I and AMSR-E 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. ≥ 39 SMMR/SSM/I: 37V GHz AMSR-E: 36V GHz SeaWinds: 13 GHz

10 Human Health climate sensitive infectious disease distribution and change, vector habitat change Agriculture Frost status/potential, growing season and potential yield 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 Forests phenology, productivity, carbon source/sink activity, cold hardiness, vegetation stress & forest ecoregions Species and Habitats Shift in ecological zones, habitat change Potential FT-ESDR Research Applications Climate Change Monitoring of extent, seasonal- annual variation & trends in frozen/non-frozen period

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

12 Potential FT-ESDR User Community Example Agriculture Application: 2007 Spring Frost Index Source: 1 2 2 Soybean Harvested Acres 2007 1

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

14 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 1 Metrics Reporting 1 Preliminary results based on NTSG-ESIP statistics from Jun-Aug, 2010.

16 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; FT-ESDR User Community 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. IEEE TGARS); 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;


19 Source: Product Maturity Definitions

20 Data for FT-ESDR Production and Validation

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

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

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

24 Example Agriculture Application: 2007 Spring Frost Index Source: 1 2 2 Corn Harvested Acres 2007 1

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