Extension and application of an AMSR global land parameter data record for ecosystem studies
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 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);

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 Extension and application of an AMSR global land parameter data record for ecosystem studies

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Extension and application of an amsr global land parameter data record for ecosystem studies

 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


Overview

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 (2002-2011), 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.


Algorithm flowchart

Algorithm Flowchart

Tb 18.7, 23.8 V & H pol.

Tb 6.9 or 10.7 V & H pol.

Estimate emissivity

Temperature Algorithm

Estimate slope parameter:

30-day running smoother

30-day running smoother

Invert for VOD

(assume dry baseline soil conditions)

Invert for SM


Pre screening input tb

Pre-Screening Input Tb.

  • Hierarchy of conditional flags (those with lower numbers displace higher)

  • Derived from Tb ratios & differences (will require re-tuning for new datasets)

(0) Good Tb; Do retrieval!

(3) Coastal/Mountain Snow & Ice

(6) 6.9 and 10.7 GHz RFI

(5) 18.7 GHz RFI

(7) 10.7 GHz RFI only

(1) Tb not collected by instrument

(4) Precipitation

(8) 6.9 GHz RFI only

(2) Snow & Frozen Soil


Algorithm re calibration

Data Preparation

AMSR-E / AMSR

Swath Brightness Temperature

Gridded brightness Temperature

Algorithm Parameters Calibration

  • 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

  • WMO Stations Temp.

  • AIRS Water Vapor

  • MODIS Land Cover

  • DEM

Algorithm Re-Calibration

Land Surface Products


Daily maximum minimum temperature selection of the wmo stations

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


Daily max min temperature retrievals

Daily Max/Min Temperature Retrievals

AMSR-E Tmaxvs WMO Obs

Tmax (May 29, 2010)

Training sites

UMT (V7)

Validation sites

UMT (V6)


Daily maximum minimum temperature comparison of the two umt product versions

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 2009-2010; Right: RMSD (K) of the two products)


Retrieval of total water vapor validation

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).


Water vapor comparison of the two version umt products

Water Vapor– Comparison of the two version UMT products

Comparisons between Recalibrated Products and the previous products (Left: Correlation between the retrievals of year 2009-2010; Right: RMSD (mm) of the two products)


Vegetation optical depth x band comparison of the two umt product versions

Vegetation Optical Depth (X-band)– Comparison of the two UMT product versions

Comparisons between Recalibrated Products and the previous products (Left: Correlation between the retrievals of year 2009-2010; Right: RMSD of the two products)


Amsr2 extended land surface parameter record

AMSR2 --- Extended Land Surface Parameter Record


Amsr2 extended daily maximum minimum temperature records validation

AMSR2: Extended Daily Maximum/Minimum Temperature Records – Validation

AMSR2 Tmaxvs WMO Obs

Tmax (May 29, 2010 / May 30,2013)

UMT (V7)

UMT (AMSR2)


Water vapor validation

Water Vapor – Validation

AMSR2 vs AIRS

Water vapor (May 29, 2010 / May 30, 2013)

UMT (V7)

UMT (AMSR2)


Recent ecological application studies

Recent Ecological Application Studies


Extension and application of an amsr global land parameter data record for ecosystem studies

Documenting Alaska Boreal Forest Wildfire Recovery using AMSR-E VOD record

VOD results show 3-7 year post fire recovery determined by burn severity;

VOD (10.7 GHz) recovery from Large Boreal Fires in 2004

VOD recovery proportional to fire severity indicated by relative tree cover loss (MOD44B)

Source: Jones, M.O. et al., 2013. Global Change Biology.


Extension and application of an amsr global land parameter data record for ecosystem studies

Comparing Land Surface Phenology between AMSR-E Vegetation Optical Depth (VOD) and GPS Normalized Microwave Reflectance Index (NMRI) network

VOD and NMRI Correspondence

  • 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 (r2=0.73, P<0.001, RMSE=36.8 days) were also in agreement.

Jones MO, Kimball JS, et al. (2013) International Journal of Biometerology


Summary

Summary

  • Initial re-calibration of UMT Global Land Parameter algorithms using reprocessed (V7) AMSR-E & AMSR2 L1R 1swath Tb 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.

1AMSR-E V7 reprocessed Tb record provided by Remote Sensing Systems; AMSR2 L1R data are from JAXA


Thanks

Thanks!

1


Related equations

Related Equations

1


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