extension and application of an amsr global land parameter data record for ecosystem studies jinyang...

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 Meeting4-5 September 2013Oxnard, CA

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 (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

Temperature Algorithm

Tb 6.9 or 10.7 V & H pol. Tb 18.7, 23.8 V & H pol.

30-day running smoother

30-day running smoother

Estimate slope parameter:

Estimate emissivity

Invert for VOD(assume dry baseline soil conditions)

Invert for SM


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

Jan. 1, 2003 (Descending) July 15, 2003 (Descending)Flags

Jan. 1, 2003 (Descending) July 15, 2003 (Descending)Flags

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

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

AMSR-E / AMSRSwath 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

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

Tmax (May 29, 2010)

UMT (V7)

UMT (V6)

AMSR-E Tmax vs WMO Obs

Training sites

Validation sites


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

Comparisons between AMSR-E Retrieved Total Water Vapor and AIRS (V6) product (Left: using Training site

data; Right: using Validation sites).



2010; Right: RMSD (mm) of the two products)

Water Vapor– Comparison of the two version UMT products



2010; Right: RMSD of the two products)

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


AMSR2 --- Extended Land Surface Parameter Record


AMSR2: Extended Daily Maximum/Minimum Temperature Records – Validation

AMSR2 Tmax vs WMO ObsTmax (May 29, 2010 / May 30,2013)

UMT (V7)

UMT (AMSR2)


Water Vapor – Validation

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

UMT (V7)

UMT (AMSR2)

AMSR2 vs AIRS


Recent Ecological Application Studies

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., 2013. 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)

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 (r2=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


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


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