Landscape Temperature and Frozen/Thawed Condition over Alaska with Infrared and Passive Microwave Remote

SensingDetermination of Thermal Controls on Land-Atmosphere

Carbon Flux in Support of CARVE

N. Steiner1, K. McDonald1,2, R. Schröder1,2, S. Dinardo2 and C. Miller2

 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

Overview

• Carbon in the Arctic Vulnerability Experiment (CARVE)• Remote Sensing Datasets• Freeze/Thaw

• Passive Microwave• Land Surface Temperature

•Overview CARVE Flights• Conclusion/Future Work

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?

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

SciDB: Swath to Grid Processing

Time Dimension

Dense Grid Data

Lati

tude D

imensi

on

Longitude Dimension

Sparse Swath Data

Column Dimension

Row

Dim

en

sion

Moving Window Aggregation• Swath to grid

processing done in-storage

• Window size set to satellite footprint

brig

htn

ess te

mpera

ture

, vertica

l pol. [K

]Advanced Microwave Scanning Radiometer 2 (AMSR2)

Gri

dded a

t 3 k

m

Example: September 25, 2013 (6-day)M

OD

IS LS

T [

oK]

Day

Night

MO

DIS

LST [

oK]

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

AMSR2 Freeze/Thaw Algorithm

Coldfoot AWS

Snow DepthSoil Temp., 2 m depth

Tem

pera

ture

[C

]D

iurn

al Δ

TB

Seaso

nal Δ

TB

Snow

Depth

[in.]

Seasonal Scaling:

Diurnal Difference:

𝑀𝑒𝑙𝑡 (𝑡 )={𝐓𝐫𝐮𝐞 ; Δ𝑇 𝐵 (𝑡)>𝑇 𝑅

𝑭𝒂𝒍𝒔𝒆 }• Thresholds (TR) are determined using

surface temperatures

TR

MO

DIS

LST [

oK]

MO

DIS

LST [

oK]

• 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)

NightDay

Coldfoot Station Sagwon Station

Passive Microwave and Thermal IR - Freeze/Thaw

Coldfoot StationSoil te

mpera

ture

[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 te

mpera

ture

[C]

2005 2006

2007 2008

Thawed

Transitional

Frozen

ColdfootSagwon

Thermal LST / Passive Microwave Freeze Thaw Comparison

AMSR-E F/T and MODIS LST InSitu Soil F/T and MODIS LST

Station Agreement [%] N

MODIS Threshold

[deg.K]

Agreement [%] N

MODIS Threshold

[deg.K]

Toolik 91.31% 2419 265 91.82% 3168 278

Sagwon 92.48% 2275 263 86.47% 2751 275

Coldfoot (958) 92.77% 1952 266 85.47% 1977 270

Bonanza Creek (A01) 96.08% 1481 270 86.52% 1893 276

Forward Looking Infrared (FLIR) Imager

• Aircraft mounted• Nadir pointing• 40.4x40.5 FOV

• Measures infrared radiance at 3-5 microns

• 200 megapixels per second

CARVE Flight - 10/24/2013

AMSR2, 36GHz V-polarization

MODIS–LST, Day

(b)(a)

(a)

(b)

CARVE Flight 10/24/13

CARVE Flight 10/24/13

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 CO2 and CH4

Thank You