1. Landscape Temperature and Frozen/Thawed Condition over Alaska with Infrared and Passive Microwave Remote Sensing Determination of Thermal Controls on Land-Atmosphere Carbon Flux in Support of CARVE N. Steiner 1, K. McDonald 1,2, R. Schröder 1,2, S. Dinardo 2 and C. Miller 2 1. Earth and Atmospheric Sciences, The City College of New York, CUNY, New York, NY, United States. 2. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States. CARVE

2. Overview Carbon in the Arctic Vulnerability Experiment (CARVE) Remote Sensing Datasets Freeze/Thaw Passive Microwave Land Surface Temperature Overview CARVE Flights Conclusion/Future Work

3. Carbon in the Arctic Vulnerability Experiment (CARVE) - Overview Key Science Questions: What are the sensitivities of the Alaskan Arctic carbon cycle and ecosystems to climate change? How does interannual variability in surface controls (e.g., soil moisture) affect landscape-scale atmospheric concentrations and surface-atmosphere fluxes of CO2 and CH4 in the Alaskan Arctic? What are the impacts of fire and thawing permafrost on the Alaskan Arctic carbon cycle and ecosystems?

4. Remote Sensing Data System Determine various surface controls Freeze/Thaw Surface Temperature Soil Moisture / Inundation Volume of daily data 21 Level Grids for Alaska (1 + 3 km gridding) Generated in near real-time (when possible) Support flight planning Identify of interest SciDB – An Array-Based Analytical DBMS Handles sparse (swath) and dense (grid) arrays Contains both Query (SQL-like) and Functional language Linear algebra on very large arrays Scalable scidb.org

5. SciDB: Swath to Grid Processing Time Dimension Dense Grid Data Latitude Dimension Longitude Dimension Sparse Swath Data Column Dimension Row Dimension Moving Window Aggregation Swath to grid processing done in-storage Window size set to satellite footprint

6. brightness temperature, vertical pol. [K] Advanced Microwave Scanning Radiometer 2 (AMSR2) Gridded at 3 km

7. Example: September 25, 2013 (6-day) MODIS LST [ o K] Day Night MODIS LST [ o K] MODIS Land Surface Temperature MODIS (MOD11) LST and Emissivity Product Standard split-window CARVE Generated Daily Grids 1 km grid centers Combined Aqua and Terra Separate Day, Night 6 Day forward-filling to replace missing observations Gridded using moving window aggregation

8. AMSR2 Freeze/Thaw Algorithm Coldfoot AWS Snow Depth Soil Temp., 2 m depth Temperature [C] Diurnal ΔT B Seasonal ΔT B Snow Depth [in.] Thresholds (T R ) are determined using surface temperatures TRTR

9. MODIS LST [ o K] Early Summer – Late stages of the freeze/thaw transition Evidence of North Slope Diurnal Melting Corresponds to near-freezing temperatures found in the nighttime MODIS LST Quick-Look Freeze/Thaw Product - Week of June 1, 2013 36 GHz Diurnal Product (AMSR2) Night Day

10. Coldfoot StationSagwon Station Passive Microwave and Thermal IR - Freeze/Thaw Coldfoot Station Soil temperature [C] Th Tr Fr Comparison of AMSRE freeze/thaw and MODIS surface temperatures Threshold on MODIS LST can be found to separate frozen from thawed state Sagwon Station Soil temperature [C] 2005 2006 2007 2008 Thawed Transitional Frozen Coldfoot Sagwon

11. Thermal LST / Passive Microwave Freeze Thaw Comparison AMSR-E F/T and MODIS LSTInSitu Soil F/T and MODIS LST Station Agreement [%]N MODIS Threshold [deg.K] Agreement [%] N MODIS Threshold [deg.K] Toolik91.31%241926591.82%3168278 Sagwon92.48%227526386.47%2751275 Coldfoot (958)92.77%195226685.47%1977270 Bonanza Creek (A01) 96.08%148127086.52%1893276

12. Forward Looking Infrared (FLIR) Imager Aircraft mounted Nadir pointing 40.4x40.5 FOV Measures infrared radiance at 3-5 microns 200 megapixels per second

13. CARVE Flight - 10/24/2013 AMSR2, 36GHz V-polarization MODIS–LST, Day (b)(a) (b)

14. CARVE Flight 10/24/13

16. Conclusions The use of SciDB is found to be well suited for the processing of satellite data for CARVE Successful implementation of an operational freeze/thaw product at near-real-time latency Thermal infrared and passive microwave instruments can be used to observe freeze thaw processes This will enable the use of high resolution monitoring of freeze/thaw processes using FLIR imager Future Work Combine remote sensing products with aircraft and in-situ carbon measurements and surface process modelling Use remote sensing measurements for the spatiotemporal distribution of carbon cycling of CO 2 and CH 4

17. Thank You