H33J-01
Understanding Spatial Variabilities in Clouds, Precipitation, Land/Surface Properties at the Southern Great Plains at Different Time Scales

Wednesday, 16 December 2015: 13:40
3020 (Moscone West)
Qi Tang1, Shaocheng Xie1, Karl E. Taylor1, Yunyan Zhang1, Thomas J Phillips1, Laura Riihimaki2 and Krista Gaustad2, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)Pacific Northwest National Laboratory, Richland, WA, United States
Abstract:
Spatial variability is of critical importance to many scientific studies, especially those involving high-frequency quantities (e.g., precipitation, clouds, surface turbulence fluxes, and soil properties). Spatially dense atmospheric radiation measurement (ARM) sites deployed at the U.S. Southern Great Plains (SGP) allow us to observe the spatial patterns of such variables. The upcoming "super site" at SGP will facilitate these studies at even finer scales. While many previous studies have focused only on the observations from the central facility (CF) site, in the current work we examine the robustness of many key surface and land observations at extended sites around the CF site, and on multiple time scales (hourly, diurnal, and seasonal). The correlations and variances at the CF and extended sites are analyzed at different frequencies extracted by the Kolmogorov-Zurbenko Fourier transform. We further exploit the possibilities of attributing the heterogeneity at SGP to dominant drivers (i.e., vegetation, land type, etc). These observation-based findings are likely to help interpret and improve model simulations, especially at the process level.


This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-675378