Presentation is loading. Please wait.

Presentation is loading. Please wait.

Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,

Similar presentations


Presentation on theme: "Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,"— Presentation transcript:

1 Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim, Matt Jones, Jennifer Watts (UMT); Numerical Terradynamic Simulation Group, College of Forestry and Conservation and Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana Collaborators: Kyle McDonald, Eni Njoku & Steven Chan (JPL); Rolf Reichle (GSFC); Rama Nemani (NASA Ames). AMSR Joint Science Team Meeting 4-5 September 2013 Oxnard, CA

2 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA OVERVIEW The global satellite microwave record from the AMSR sensors has strong utility for ecosystem studies, including retrievals of vegetation optical depth, surface temperature & moisture, landscape freeze/thaw dynamics, open water inundation & Atm. water vapor changes. Synergistic satellite observations include AMSR-E ( ), AMSR2 (from Jun-2012) & similar sensor data (e.g. WindSat) Calibration & extension of the global land parameter record is desirable for Ecological studies & applications, including land-atmosphere carbon, water, and energy fluxes; In this study, recalibration of the University of Montana Global Land algorithms has been carried out using reprocessed (V7) AMSR-E & L1R AMSR2 swath data.

3 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Algorithm Flowchart Temperature Algorithm Tb 6.9 or 10.7 V & H pol.Tb 18.7, 23.8 V & H pol. 30-day running smoother Estimate slope parameter: Estimate emissivity Invert for VOD (assume dry baseline soil conditions) Invert for SM

4 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Pre-Screening Input Tb. (4) Precipitation (8) 6.9 GHz RFI only (7) 10.7 GHz RFI only (2) Snow & Frozen Soil (3) Coastal/Mountain Snow & Ice (0) Good Tb; Do retrieval! (1) Tb not collected by instrument (6) 6.9 and 10.7 GHz RFI (5) 18.7 GHz RFI  Hierarchy of conditional flags (those with lower numbers displace higher)  Derived from Tb ratios & differences (will require re-tuning for new datasets)

5 AMSR-E / AMSR Swath Brightness Temperature Gridded brightness Temperature Data Preparation Algorithm Parameters Calibration WMO Stations Temp. AIRS Water Vapor MODIS Land Cover DEM Land Surface Products Subset Brightness Temperature and AIRS products for WMO Stations Screening Datasets for RFI, Snow, Precipitation and High DEM variations Adjust Algorithm Parameters based on WMO measurements and AIRS products ALGORITHM RE-CALIBRATION

6 Daily Maximum/Minimum Temperature – Selection of the WMO stations Training (red dots) and Validation (green dots) Datasets from WMO Summary-of- the-Day weather stations

7 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Daily Max/Min Temperature Retrievals Tmax (May 29, 2010) UMT (V7) UMT (V6) AMSR-E Tmax vs WMO Obs Training sites Validation sites

8 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Daily Maximum/Minimum Temperature – Comparison of the two UMT product versions Comparisons between Recalibrated Products and the previous products (Left: Correlation between the retrievals of year ; Right: RMSD (K) of the two products)

9 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Retrieval of Total Water Vapor – Validation Comparisons between AMSR-E Retrieved Total Water Vapor and AIRS (V6) product (Left: using Training site data; Right: using Validation sites).

10 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Comparisons between Recalibrated Products and the previous products (Left: Correlation between the retrievals of year ; Right: RMSD (mm) of the two products) Water Vapor– Comparison of the two version UMT products

11 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Comparisons between Recalibrated Products and the previous products (Left: Correlation between the retrievals of year ; Right: RMSD of the two products) Vegetation Optical Depth (X-band)– Comparison of the two UMT product versions

12 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA AMSR2 --- Extended Land Surface Parameter Record

13 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA AMSR2: Extended Daily Maximum/Minimum Temperature Records – Validation AMSR2 Tmax vs WMO Obs Tmax (May 29, 2010 / May 30,2013) UMT (V7) UMT (AMSR2)

14 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Water Vapor – Validation Water vapor (May 29, 2010 / May 30, 2013) UMT (V7) UMT (AMSR2) AMSR2 vs AIRS

15 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Recent Ecological Application Studies

16 Documenting Alaska Boreal Forest Wildfire Recovery using AMSR-E VOD record VOD (10.7 GHz) recovery from Large Boreal Fires in 2004 Source: Jones, M.O. et al., Global Change Biology. VOD results show 3-7 year post fire recovery determined by burn severity; VOD recovery proportional to fire severity indicated by relative tree cover loss (MOD44B)

17 Comparing Land Surface Phenology between AMSR-E Vegetation Optical Depth (VOD) and GPS Normalized Microwave Reflectance Index (NMRI) network VOD and NMRI are responsive to changes in vegetation water content Significant correlations (p<0.05) were found at 276 of 305 sites (90.5%). VOD and NMRI Start of Season metrics (r 2 =0.73, P<0.001, RMSE=36.8 days) were also in agreement. VOD and NMRI Correspondence Jones MO, Kimball JS, et al. (2013) International Journal of Biometerology

18 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Summary Initial re-calibration of UMT Global Land Parameter algorithms using reprocessed (V7) AMSR-E & AMSR2 L1R 1 swath T b data records. Both UMT AMSR-E product versions are generally well correlated, but large differences occur in some areas. –Water vapor retrievals highly correlated except over dense vegetation; V7 results show higher water vapor over rainforest; – Temperature retrievals show larger differences for dense vegetation areas and southern- hemisphere; –VOD retrievals well correlated, though V7 results show higher VOD levels for dense vegetation; –Soil moisture retrievals show lower correspondence and need further evaluation. Algorithm calibration also carried out using AMSR2 data. Results similar to AMSR-E, but AMSR2 temperature and water vapor accuracy is slightly lower. Continuing calibration & extension of UMT record planned in support of several global ecosystem studies. 1 AMSR-E V7 reprocessed T b record provided by Remote Sensing Systems; AMSR2 L1R data are from JAXA

19 AMSR Joint Science Team Meeting 4-5 September 2013, Oxnard, CA Thanks! 1

20 Related Equations 1


Download ppt "Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,"

Similar presentations


Ads by Google