1. NSIDC DAAC UWG Meeting August 9-10 Boulder, CO
Developing An Extended Global Data Record on Daily Landscape Freeze-Thaw Status from Satellite Passive Microwave Remote Sensing
John Kimball, Youngwook Kim, Joe Glassy, Jinyang Du
NTSG, University of Montana
NSIDC DAAC UWG Meeting
August 9-10
Boulder, CO

2. Processing Overview
Science study area: All global land areas affected by seasonal freezing and thawing.
Types of data used:
37 GHz V-pol daily Tb retrievals; AM & PM orbit; swath and 25-km global (EASE v1) grids
Nimbus-7 SMMR Pathfinder (
SSM/I-SSMIS Pathfinder (
AMSR-E (
AMSR2 (

3. Processing Overview Cont.
Overview of processing steps
Calibration of overlapping 37 GHz, V-pol Tb records from SMMR and SSM/I
Calibration of AMSR-E/ GHz, V-pol Tb records using similar overlapping FY-3B MWRI Tb retrievals.
Per grid cell Modified Seasonal Threshold Algorithm (MSTA) Tb temporal change classification
Per grid cell annual MSTA calibration of Tb freeze-thaw threshold using ERA-Interim daily surface air temperature
Application of calibrated MSTA using daily AM and PM Tb inputs to classify FT status.
FT global accuracy assessment using collocated in-situ WMO daily temperatures
Production of annual QA maps and per grid cell daily QC flags
Production of final product formats (HDF5, GeoTIFF, Binary)
Challenges
Lack of EASE-grid version 2 (V2) format SSMR, SSM/I and AMSR-E/2 daily Tb records
Large file sizes and data processing loads required to process global Tb orbital swath data
For production of finer resolution FT retrievals closer to native (~12-km) 37-GHz Tb footprint rather than standard 25-km gridding.
Recommendations
Provide SMMR, SSM/I and AMSR Tb records in EASE v2 format

4. Scope of Research Science question(s) addressed:
Can similar 37 GHz Tb retrievals from different satellite microwave sensors be used to quantify consistent patterns and trends in landscape FT status?
What are the impacts of varying land cover, terrain and algorithm assumptions on the FT accuracy?
Does the research cross scientific domains?
Yes: global change, cryosphere, hydrology, ecosystems
Local (or Regional) versus global extent?
Global and polar regional
Long time series?
1979 – present enabled from similar overlapping satellite records and continuing operations for key sensors (SSM/I, AMSR2)
Is data latency/download time critical?
Not critical for research, but would be optimal to have at least annual updates.
Potential exists for similar FT retrievals at shorter latencies through LANCE for other operational applications

5. Types of data being used
Primary observational data used
SMMR, SSM/I(S), AMSR-E/2 daily (AM/PM) Tb
MODIS (MOD11C1) 8-day LST (used for Cal/Val)
ERA-Interim reanalysis (used for calibration)
WMO Summary of the Day (used for validation)
Data types & formats needed/desired
Primarily passive microwave; visible imagery used for calibration and secondary validation assessments
Global and Polar EASE-grid v2 desired, but still working with v1 format consistent with input Tb data
Combining data with other sources or models?
Modified seasonal threshold algorithm (MSTA) for Tb temporal change-based FT classification, where grid cell-wise Tb FT thresholds calibrated annually using ERA-Interim daily surface temperatures.
Data volumes
~8 GB and 31 GB for final FT-ESDR in hdf5 and binary formats
Much Larger data volumes involved in data processing

6. Data Workflow
Driven by research objectives & periodic requests from community for FT-ESDR updates
Periodic data pull to local server for processing, with periodic revisits to NSIDC for updating Tb records
Challenges:
Processing and formatting of AMSR Tb orbital swath data
Large AMSR L2a swath data volumes
Lack of standardized EASE-grid V2 format for gridded Tb products
Maintaining FT-ESDR results in multiple formats (HDF5, GeoTIFF, Binary) due to variable user needs.

7. Recommendations Improvements to DAAC tools/services
NSIDC Tb data posting to EASE-grid V2 format
Enhanced services for provision of data records in a variety of common formats
Shared software tools for viewing/translating/reformatting datasets