1) Global Coefficients: Derived from all available cloud-free ASTER scenes for a given network...
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All Scenes 2.75 2.78 3.66 3.41 2.74 34683Daytime Only 2.87 2.63 3.21 3.17 2.63 15858Nighttime Only 2.48 2.69 2.34 2.97 2.63 18825Spring 2.81 2.86 3.60 3.40 2.82 8619Summer 2.71 2.98 3.77 3.90 3.06 8719Fall 2.74 2.43 3.73 3.11 2.41 11400Winter 2.73 2.53 3.37 2.57 2.47 5945
Group to Which Regression was Applied
UnscaledCoefficient Type Number of in
situ and MODIS LST Comparisons
GlobalDay/Night-
SpecificSeason-Specific
Site-Specific
All Scenes 2.75 2.66 2.68 2.67 2.69 34855Daytime Only 2.87 2.97 2.96 3.00 3.05 15958Nighttime Only 2.48 2.34 2.41 2.37 2.29 18897Spring 2.81 2.74 2.79 2.84 2.74 8696Summer 2.71 2.67 2.79 2.73 2.76 8723Fall 2.74 2.57 2.57 2.57 2.52 11418Winter 2.73 2.48 2.50 2.50 2.72 6018
Number of in situ and MODIS LST Comparisons
UnscaledCoefficient TypeGroup to Which
Regression was Applied
GlobalDay/Night-
SpecificSeason-Specific
Site-Specific
1) Global Coefficients: Derived from all available cloud-free ASTER scenes for a given networkSURFRAD: 246 scenes USCRN: 371 scenes
2) Day/Night-Specific Coefficients: ASTER scenes grouped by network and daytime or nighttime overpass
Upscaling of in situ Land Surface Temperature for Satellite ValidationRobert Hale (CIRA/Colorado St. Univ.), Yunyue Yu (NOAA/NESDIS STAR), and Dan Tarpley (Short & Assoc.)
Conclusions and Future Activities At USCRN sites, regression-based upscaling of in situ LSTs can
reduce scale-induced errors, thereby rendering in situ LSTs more appropriate for use in validating coarse-resolution satellite LSTs
While statistically significant reduction of error is observed in many USCRN cases, the absolute reduction is typically fairly small (~0.2 K), and SURFRAD sites generally realize little benefit from upscaling
Scale-induced error reduction is highly variable between models and coefficient groups, as well as between individual sites (not shown)
Better performance from more generalized coefficients versus site-specific coefficients suggests lack of ASTER scenes for coefficient determination may be limiting model performance
To address the above, Landsat data are being acquired and utilized for improved model development
2 km x 2 km average LSTavg = 318.59 K
Central pixel LSTpixel = 318.80 K
LSTin situ = 312.76 K
Validation of satellite-derived Land Surface Temperature (LST) poses challenges due both to the paucity of in situ measures against which the satellite-derived LSTs may be compared and because of the mismatch in spatial scale between the two. In an effort to address these issues, multiple linear regression models were derived using high-resolution LSTs from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to characterize the relationship between “point” measurements at ground validation sites and the average LST over a larger area representing a coarse-resolution satellite pixel. The derived models were then used to upscale in situ LSTs from Surface Radiation (SURFRAD) and U.S. Climate Reference Network (USCRN) sites. Unscaled and scaled LSTs were subsequently compared with LSTs from the Moderate Resolution Imaging Spectroradiometer (MODIS).
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USCRN (Newton 11SW, GA)Field of View of IRT: 1.3 m
http://www.esrl.noaa.gov/gmd/grad/surfrad/bonpics/tower01c.jpghttp://www1.ncdc.noaa.gov/pub/data/uscrn/documentation/site/photos/stationsbystate_hires.pdf
SURFRAD (Bondville, IL)FOV of Radiometer: ~30 m
1 km 1 km
ASTER LST(Stillwater 5WNW, OK; 7/23/2005)Resolution: 90 m
MODIS LST(Stillwater 5WNW, OK; 7/23/2005)Resolution: 1000 m
Upscaling Model Coefficients
Group SURFRAD USCRNDaytime Scenes 186 193Nighttime Scenes 60 178
3) Season-Specific Coefficients: ASTER scenes grouped by network and climatological season
4) Site-Specific Coefficients: ASTER scenes grouped by individual siteSURFRAD: 13-70 scenes, depending on siteUSCRN: 4-68 scenes, depending on site
Group SURFRAD USCRNSpring (MAM) 53 96Summer (JJA) 72 96Fall (SON) 80 115Winter (DJF) 41 64
One-Predictor Regression ModelSingle ASTER pixel encompassing the ground station used as predictor of large-area average LST
Once the and coefficients are determined using ASTER scenes, the formula is applied to in situ LSTs to determine scaled values
Scaled values then are compared with MODIS coarse-resolution LSTs to determine efficacy of model – reduced standard deviation of differences for scaled vs. unscaled LSTs used as indicator of model performance
Standard deviation of differences of MODIS – unscaled or scaled in situ LSTs (K)
USCRN Sites (22 sites)
All Scenes 2.37 2.36 2.37 2.35 2.48 12714Daytime Only 2.59 2.59 2.59 2.59 2.53 5596Nighttime Only 2.18 2.16 2.18 2.15 2.44 7118Spring 2.53 2.53 2.55 2.53 2.65 3041Summer 2.39 2.39 2.40 2.39 2.46 3931Fall 2.36 2.36 2.33 2.32 2.47 4164Winter 1.94 1.92 1.92 1.87 2.18 1578
Group to Which Regression was Applied
Coefficient TypeUnscaled
Number of in situ and MODIS LST Comparisons
GlobalDay/Night-
SpecificSeason-Specific
Site-Specific
Significantly different from unscaled at: = 0.05 = 0.01
No significant difference for any coefficient type
SURFRAD Sites (7 sites)
Two-Predictor Regression Model
0.00.10.20.30.40.50.60.70.8
ND
VI
Day of Year
Asheville 13S (NC) 2003-2010 Mean NDVI
Multi-year average of MODIS NDVI used as additional predictor to better capture seasonal changes in vegetation amount that strongly influence LST
Two-Predictor Regression Model (Continued)
All Scenes 2.75 2.67 2.52 2.73 2.91 34683Daytime Only 2.87 2.93 2.78 2.86 2.98 15858Nighttime Only 2.48 2.40 2.29 2.62 2.84 18825Spring 2.81 2.76 2.62 2.94 2.90 8619Summer 2.71 2.66 2.59 2.80 3.07 8719Fall 2.74 2.58 2.38 2.62 2.83 11400Winter 2.73 2.50 2.51 2.46 2.79 5945
Group to Which Regression was Applied
UnscaledCoefficient Type Number of in
situ and MODIS LST Comparisons
GlobalDay/Night-
SpecificSeason-Specific
Site-Specific
Significantly different from unscaled at: = 0.05 = 0.01
USCRN Sites (22 sites)
Results at SURFRAD sites similar to those for 1-predictor model – No significant reduction in scale-induced error with any of the coefficient types
Air Temperature-Based Regression ModelNewton 8W, GA
http://www1.ncdc.noaa.gov/pub/data/uscrn/documentation/site/photos/stationsbystate_hires.pdf
Air temperature used as a proxy for canopy temperature
ASTER single-pixel or in situ LST used as indicator of soil surface temperature
NDVI used to weight the two temperatures
USCRN Sites (22 sites)
Significantly different from unscaled at: = 0.05 = 0.01