Fine‐Scale Variability of Observed and Simulated Surface Albedo Over the Southern Great Plains

Author(s):  
Larry K. Berg ◽  
Charles N. Long ◽  
Evgueni I. Kassianov ◽  
Duli Chand ◽  
Sheng‐Lun Tai ◽  
...  
2006 ◽  
Vol 45 (1) ◽  
pp. 210-235 ◽  
Author(s):  
Claude E. Duchon ◽  
Kenneth G. Hamm

Abstract Time series of daily broadband surface albedo for 1998 and 1999 have been analyzed from six locations in the network of 22 Atmospheric Radiation Measurement Program Solar–Infrared Radiation Stations distributed from central Kansas to central Oklahoma. Two of the stations are in Kansas, and four are in Oklahoma; together they reasonably encompass the variation in geography in the southern Great Plains. Daily precipitation totals locally measured or obtained from nearby Oklahoma Mesonet stations and time series of biweekly maximum normalized difference vegetation index obtained from NOAA’s Advanced Very High Resolution Radiometer were used to determine linkages between surface albedo and amount of precipitation and degree of green vegetation. As part of this determination, daily albedo was categorized according to sky condition, that is, clear, partly cloudy, or overcast, with appropriate boundaries for each category. The more notable results are the following: 1) 2-yr mean annual albedos varied by more than 20% among the six sites, the lowest albedo being 0.18 and the highest albedo being 0.22; 2) the numerical difference was about 4 times the maximum interannual mean difference among the six stations, indicating the importance of geographic location; 3) for sites with a large amount of bare soil, a systematic decrease in albedo in response to rainfall events and a systematic increase in albedo as the soil dried were observed; 4) at the one site with total vegetation cover, that is, no bare soil, albedo response to precipitation events was suppressed; 5) no relation was found between mean annual albedo and annual precipitation; 6) whether days were classified as clear or partly cloudy had little influence on daily albedo, but overcast days typically reduced albedo, sometimes substantially; and 7) the main contributor to low albedos on overcast days with rain was the wet surface; the contribution by the overcast sky was secondary.


2011 ◽  
Vol 4 (3) ◽  
pp. 3097-3145
Author(s):  
S. A. McFarlane ◽  
K. L. Gaustad ◽  
E. J. Mlawer ◽  
C. N. Long ◽  
J. Delamere

Abstract. We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.


2011 ◽  
Vol 4 (9) ◽  
pp. 1713-1733 ◽  
Author(s):  
S. A. McFarlane ◽  
K. L. Gaustad ◽  
E. J. Mlawer ◽  
C. N. Long ◽  
J. Delamere

Abstract. We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.


Tellus B ◽  
2011 ◽  
Vol 63 (2) ◽  
Author(s):  
Margaret S. Torn ◽  
Sebastien C. Biraud ◽  
Christopher J. Still ◽  
William J. Riley ◽  
Joe A. Berry

2015 ◽  
Vol 213 ◽  
pp. 209-218 ◽  
Author(s):  
Naama Raz-Yaseef ◽  
Dave P. Billesbach ◽  
Marc L. Fischer ◽  
Sebastien C. Biraud ◽  
Stacey A. Gunter ◽  
...  

2021 ◽  
pp. 1-18
Author(s):  
J. Kelly Hoffman ◽  
R. Patrick Bixler ◽  
Morgan L. Treadwell ◽  
Lars G. Coleman ◽  
Thomas W. McDaniel ◽  
...  

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