TY - JOUR
T1 - Land-Surface Heterogeneity Effects in the Planetary Boundary Layer
AU - Reen, Brian P.
AU - Stauffer, David R.
AU - Davis, Kenneth J.
N1 - Funding Information:
Acknowledgments Cyrille Flamant of Laboratoire Atmosphère, Milieux, Observations Spatiales, CNRS, and Université Pierre et Marie Curie, Paris, France, and colleagues from there and the Technical Division of the Institut National des Sciences de l’Univers (Jacques Pelon, Didier Bruneau, Fredéric Blouzon, Abdel Abchiche, Patricia Delville, Nadir Amarouche) are acknowledged for provision of LEANDRE II lidar data, Gerhard Ehret, Christoph Kiemle, and colleagues for DLR Differential Absorption Lidar data, Ken Craig for lidar-derived PBL depth, Fei Chen and Kevin Manning for High Resolution Land Data Assimilation System output, and Ricardo Muñoz for the 1D Matlab GUI version of MM5 and the code used to create the skew-T diagram. In addition to the co-authors, Toby Carlson and Chris Duffy are acknowledged for participation on the PhD committee of the first author. George Young provided helpful guidance in interpreting results. Some data were obtained from the Atmospheric Radiation Measurement Program sponsored by the U.S. Department of Energy or from NCAR/EOL under sponsorship of the National Science Foundation. We acknowledge the efforts of three anonymous reviewers that led to improvements in this manuscript. This research was supported by National Science Foundation Grant ATM-0130349, the U.S. Defense Threat Reduction Agency through W911NF-06-1-0439 under the supervision of John Hannan, and the U.S. Defense Threat Reduction Agency through HDTRA1-10-1-0033 under the supervision of John Hannan and Anthony Esposito.
PY - 2014/1
Y1 - 2014/1
N2 - We investigate the cumulative added value of assimilating temperature, moisture, and wind observations in the three-dimensional non-hydrostatic Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model MM5 and use these forecasts to analyze the relationship between surface forcing and planetary boundary-layer (PBL) depth. A data assimilation methodology focused on the surface and the PBL, previously tested in a one-dimensional version of MM5, is applied to 29 May, 6 June, and 7 June 2002 during the International H2 Project over the Southern Great Plains. Model-predicted PBL depth is evaluated against PBL depth diagnosed from data across 4,800 km of airborne lidar data (flight tracks 100-300 km long). The forecast with data assimilation verifies better against observations and is thus used to investigate the environmental conditions that govern PBL depth. The spatial structure in PBL depth is found to be most affected by spatial variations in surface buoyancy flux and capping inversion strength. The spatial scales of surface flux forcing reflected in the PBL depth are found through Fourier analysis and multiresolution decomposition. Correlations are <0.05 at scales of 64 km or less and increase at larger scales for 29 May and 6 June, but on 7 June low correlations are found at all scales, possibly due to greater within-PBL wind speeds, a stronger capping inversion on this day, and clouds. The results suggest a minimum scale, a function of wind speed, below which heterogeneity in surface buoyancy fluxes is not reflected directly in PBL depth.
AB - We investigate the cumulative added value of assimilating temperature, moisture, and wind observations in the three-dimensional non-hydrostatic Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model MM5 and use these forecasts to analyze the relationship between surface forcing and planetary boundary-layer (PBL) depth. A data assimilation methodology focused on the surface and the PBL, previously tested in a one-dimensional version of MM5, is applied to 29 May, 6 June, and 7 June 2002 during the International H2 Project over the Southern Great Plains. Model-predicted PBL depth is evaluated against PBL depth diagnosed from data across 4,800 km of airborne lidar data (flight tracks 100-300 km long). The forecast with data assimilation verifies better against observations and is thus used to investigate the environmental conditions that govern PBL depth. The spatial structure in PBL depth is found to be most affected by spatial variations in surface buoyancy flux and capping inversion strength. The spatial scales of surface flux forcing reflected in the PBL depth are found through Fourier analysis and multiresolution decomposition. Correlations are <0.05 at scales of 64 km or less and increase at larger scales for 29 May and 6 June, but on 7 June low correlations are found at all scales, possibly due to greater within-PBL wind speeds, a stronger capping inversion on this day, and clouds. The results suggest a minimum scale, a function of wind speed, below which heterogeneity in surface buoyancy fluxes is not reflected directly in PBL depth.
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U2 - 10.1007/s10546-013-9860-8
DO - 10.1007/s10546-013-9860-8
M3 - Article
AN - SCOPUS:84891846775
SN - 0006-8314
VL - 150
SP - 1
EP - 31
JO - Boundary-Layer Meteorology
JF - Boundary-Layer Meteorology
IS - 1
ER -